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| I0525 00:09:25.737826 5272 solver.cpp:280] Solving mixed_lstm | |
| I0525 00:09:25.737840 5272 solver.cpp:281] Learning Rate Policy: fixed | |
| I0525 00:09:26.273970 5272 solver.cpp:229] Iteration 0, loss = 27.9836 | |
| I0525 00:09:26.274058 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0 | |
| I0525 00:09:26.274077 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0 | |
| I0525 00:09:26.274091 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0525 00:09:26.274102 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0525 00:09:26.274114 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0 | |
| I0525 00:09:26.274126 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.125 | |
| I0525 00:09:26.274138 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0 | |
| I0525 00:09:26.274149 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0 | |
| I0525 00:09:26.274161 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0 | |
| I0525 00:09:26.274173 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 0 | |
| I0525 00:09:26.274184 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 0 | |
| I0525 00:09:26.274195 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 0 | |
| I0525 00:09:26.274207 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 0 | |
| I0525 00:09:26.274219 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 0.125 | |
| I0525 00:09:26.274231 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 0.25 | |
| I0525 00:09:26.274243 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 0 | |
| I0525 00:09:26.274255 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 0 | |
| I0525 00:09:26.274266 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 0 | |
| I0525 00:09:26.274277 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 0.125 | |
| I0525 00:09:26.274289 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 0 | |
| I0525 00:09:26.274301 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 0 | |
| I0525 00:09:26.274312 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 0 | |
| I0525 00:09:26.274323 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 0 | |
| I0525 00:09:26.274334 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0 | |
| I0525 00:09:26.274346 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.0416667 | |
| I0525 00:09:26.274363 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 4.42599 (* 0.3 = 1.3278 loss) | |
| I0525 00:09:26.274379 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 4.31819 (* 0.3 = 1.29546 loss) | |
| I0525 00:09:26.274392 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 4.69454 (* 0.0272727 = 0.128033 loss) | |
| I0525 00:09:26.274406 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 4.82997 (* 0.0272727 = 0.131726 loss) | |
| I0525 00:09:26.274420 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 4.90334 (* 0.0272727 = 0.133728 loss) | |
| I0525 00:09:26.274435 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 4.79926 (* 0.0272727 = 0.130889 loss) | |
| I0525 00:09:26.274448 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 4.85635 (* 0.0272727 = 0.132446 loss) | |
| I0525 00:09:26.274462 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 4.47805 (* 0.0272727 = 0.122129 loss) | |
| I0525 00:09:26.274477 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 4.62066 (* 0.0272727 = 0.126018 loss) | |
| I0525 00:09:26.274490 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 5.0867 (* 0.0272727 = 0.138728 loss) | |
| I0525 00:09:26.274504 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 4.28531 (* 0.0272727 = 0.116872 loss) | |
| I0525 00:09:26.274518 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 4.00745 (* 0.0272727 = 0.109294 loss) | |
| I0525 00:09:26.274533 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 5.00466 (* 0.0272727 = 0.136491 loss) | |
| I0525 00:09:26.274546 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 5.06219 (* 0.0272727 = 0.13806 loss) | |
| I0525 00:09:26.274559 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 3.84701 (* 0.0272727 = 0.104918 loss) | |
| I0525 00:09:26.274585 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 3.85242 (* 0.0272727 = 0.105066 loss) | |
| I0525 00:09:26.274600 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 4.94109 (* 0.0272727 = 0.134757 loss) | |
| I0525 00:09:26.274615 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 3.75635 (* 0.0272727 = 0.102446 loss) | |
| I0525 00:09:26.274627 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 3.97544 (* 0.0272727 = 0.108421 loss) | |
| I0525 00:09:26.274641 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 3.81998 (* 0.0272727 = 0.104181 loss) | |
| I0525 00:09:26.274655 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 4.77268 (* 0.0272727 = 0.130164 loss) | |
| I0525 00:09:26.274668 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 5.3693 (* 0.0272727 = 0.146435 loss) | |
| I0525 00:09:26.274682 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 4.20823 (* 0.0272727 = 0.11477 loss) | |
| I0525 00:09:26.274696 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 4.75394 (* 0.0272727 = 0.129653 loss) | |
| I0525 00:09:26.274708 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0 | |
| I0525 00:09:26.274719 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0 | |
| I0525 00:09:26.274731 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0 | |
| I0525 00:09:26.274742 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0 | |
| I0525 00:09:26.274757 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0 | |
| I0525 00:09:26.274770 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0 | |
| I0525 00:09:26.274780 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.125 | |
| I0525 00:09:26.274792 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0 | |
| I0525 00:09:26.274803 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0 | |
| I0525 00:09:26.274814 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 0 | |
| I0525 00:09:26.274826 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 0 | |
| I0525 00:09:26.274837 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 0 | |
| I0525 00:09:26.274848 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 0 | |
| I0525 00:09:26.274859 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 0 | |
| I0525 00:09:26.274870 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 0 | |
| I0525 00:09:26.274883 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 0 | |
| I0525 00:09:26.274893 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 0.125 | |
| I0525 00:09:26.274904 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 0 | |
| I0525 00:09:26.274916 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 0 | |
| I0525 00:09:26.274927 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 0 | |
| I0525 00:09:26.274938 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 0 | |
| I0525 00:09:26.274950 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 0 | |
| I0525 00:09:26.274960 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 0 | |
| I0525 00:09:26.274971 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0 | |
| I0525 00:09:26.274982 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.0208333 | |
| I0525 00:09:26.274999 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 4.37339 (* 0.3 = 1.31202 loss) | |
| I0525 00:09:26.275013 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 4.56156 (* 0.3 = 1.36847 loss) | |
| I0525 00:09:26.275027 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 4.76261 (* 0.0272727 = 0.129889 loss) | |
| I0525 00:09:26.275041 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 4.69128 (* 0.0272727 = 0.127944 loss) | |
| I0525 00:09:26.275054 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 4.42595 (* 0.0272727 = 0.120708 loss) | |
| I0525 00:09:26.275079 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 5.29859 (* 0.0272727 = 0.144507 loss) | |
| I0525 00:09:26.275094 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 4.47793 (* 0.0272727 = 0.122125 loss) | |
| I0525 00:09:26.275109 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 3.95786 (* 0.0272727 = 0.107942 loss) | |
| I0525 00:09:26.275122 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 4.44144 (* 0.0272727 = 0.12113 loss) | |
| I0525 00:09:26.275136 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 4.40003 (* 0.0272727 = 0.120001 loss) | |
| I0525 00:09:26.275151 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 4.63225 (* 0.0272727 = 0.126334 loss) | |
| I0525 00:09:26.275163 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 4.60923 (* 0.0272727 = 0.125706 loss) | |
| I0525 00:09:26.275177 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 4.29059 (* 0.0272727 = 0.117016 loss) | |
| I0525 00:09:26.275192 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 4.41449 (* 0.0272727 = 0.120395 loss) | |
| I0525 00:09:26.275205 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 4.69665 (* 0.0272727 = 0.12809 loss) | |
| I0525 00:09:26.275219 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 3.86432 (* 0.0272727 = 0.105391 loss) | |
| I0525 00:09:26.275233 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 5.36989 (* 0.0272727 = 0.146452 loss) | |
| I0525 00:09:26.275248 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 3.81105 (* 0.0272727 = 0.103938 loss) | |
| I0525 00:09:26.275261 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 4.28254 (* 0.0272727 = 0.116797 loss) | |
| I0525 00:09:26.275274 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 5.43854 (* 0.0272727 = 0.148324 loss) | |
| I0525 00:09:26.275288 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 4.31123 (* 0.0272727 = 0.117579 loss) | |
| I0525 00:09:26.275302 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 4.3938 (* 0.0272727 = 0.119831 loss) | |
| I0525 00:09:26.275316 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 3.84154 (* 0.0272727 = 0.104769 loss) | |
| I0525 00:09:26.275331 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 4.09996 (* 0.0272727 = 0.111817 loss) | |
| I0525 00:09:26.275341 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0 | |
| I0525 00:09:26.275353 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0 | |
| I0525 00:09:26.275364 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0 | |
| I0525 00:09:26.275377 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0 | |
| I0525 00:09:26.275388 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0 | |
| I0525 00:09:26.275399 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0 | |
| I0525 00:09:26.275411 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0 | |
| I0525 00:09:26.275423 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0 | |
| I0525 00:09:26.275434 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0 | |
| I0525 00:09:26.275445 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 0 | |
| I0525 00:09:26.275457 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 0 | |
| I0525 00:09:26.275472 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 0 | |
| I0525 00:09:26.275485 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 0 | |
| I0525 00:09:26.275496 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 0 | |
| I0525 00:09:26.275506 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 0 | |
| I0525 00:09:26.275517 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 0 | |
| I0525 00:09:26.275529 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 0 | |
| I0525 00:09:26.275540 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 0 | |
| I0525 00:09:26.275552 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 0 | |
| I0525 00:09:26.275573 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 0 | |
| I0525 00:09:26.275585 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 0 | |
| I0525 00:09:26.275598 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 0 | |
| I0525 00:09:26.275609 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 0 | |
| I0525 00:09:26.275620 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.0909091 | |
| I0525 00:09:26.275631 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.0416667 | |
| I0525 00:09:26.275645 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 4.32039 (* 1 = 4.32039 loss) | |
| I0525 00:09:26.275658 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 4.11144 (* 1 = 4.11144 loss) | |
| I0525 00:09:26.275672 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 4.43148 (* 0.0909091 = 0.402862 loss) | |
| I0525 00:09:26.275687 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 4.33167 (* 0.0909091 = 0.393788 loss) | |
| I0525 00:09:26.275701 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 4.46903 (* 0.0909091 = 0.406276 loss) | |
| I0525 00:09:26.275714 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 4.53691 (* 0.0909091 = 0.412446 loss) | |
| I0525 00:09:26.275728 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 4.21558 (* 0.0909091 = 0.383234 loss) | |
| I0525 00:09:26.275741 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 4.92885 (* 0.0909091 = 0.448077 loss) | |
| I0525 00:09:26.275755 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 4.38094 (* 0.0909091 = 0.398267 loss) | |
| I0525 00:09:26.275769 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 4.81857 (* 0.0909091 = 0.438052 loss) | |
| I0525 00:09:26.275782 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 4.51415 (* 0.0909091 = 0.410377 loss) | |
| I0525 00:09:26.275799 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 4.28006 (* 0.0909091 = 0.389096 loss) | |
| I0525 00:09:26.275813 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 4.03323 (* 0.0909091 = 0.366658 loss) | |
| I0525 00:09:26.275827 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 4.22007 (* 0.0909091 = 0.383643 loss) | |
| I0525 00:09:26.275841 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 4.62234 (* 0.0909091 = 0.420213 loss) | |
| I0525 00:09:26.275854 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 4.29994 (* 0.0909091 = 0.390904 loss) | |
| I0525 00:09:26.275868 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 4.21356 (* 0.0909091 = 0.383051 loss) | |
| I0525 00:09:26.275882 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 4.16724 (* 0.0909091 = 0.37884 loss) | |
| I0525 00:09:26.275895 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 4.42567 (* 0.0909091 = 0.402334 loss) | |
| I0525 00:09:26.275909 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 4.65742 (* 0.0909091 = 0.423402 loss) | |
| I0525 00:09:26.275923 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 4.20004 (* 0.0909091 = 0.381822 loss) | |
| I0525 00:09:26.275938 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 4.21463 (* 0.0909091 = 0.383148 loss) | |
| I0525 00:09:26.275951 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 4.89986 (* 0.0909091 = 0.445442 loss) | |
| I0525 00:09:26.275965 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 4.33633 (* 0.0909091 = 0.394212 loss) | |
| I0525 00:09:26.275977 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 00:09:26.275988 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 00:09:26.276000 5272 solver.cpp:245] Train net output #149: total_confidence = 7.11833e-36 | |
| I0525 00:09:26.276011 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 1.88933e-31 | |
| I0525 00:09:26.276033 5272 sgd_solver.cpp:106] Iteration 0, lr = 0.001 | |
| I0525 00:15:51.341509 5272 solver.cpp:229] Iteration 500, loss = 14.5273 | |
| I0525 00:15:51.341969 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0 | |
| I0525 00:15:51.341990 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0 | |
| I0525 00:15:51.342003 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0.125 | |
| I0525 00:15:51.342015 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0.125 | |
| I0525 00:15:51.342028 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0 | |
| I0525 00:15:51.342041 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.125 | |
| I0525 00:15:51.342051 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.5 | |
| I0525 00:15:51.342064 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.5 | |
| I0525 00:15:51.342077 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 1 | |
| I0525 00:15:51.342088 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 1 | |
| I0525 00:15:51.342099 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 1 | |
| I0525 00:15:51.342111 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 00:15:51.342123 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 00:15:51.342134 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 00:15:51.342145 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 00:15:51.342157 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 00:15:51.342170 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 00:15:51.342180 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 00:15:51.342191 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 00:15:51.342203 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 00:15:51.342216 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 00:15:51.342226 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 00:15:51.342238 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 00:15:51.342249 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.744318 | |
| I0525 00:15:51.342262 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.155556 | |
| I0525 00:15:51.342278 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 4.16698 (* 0.3 = 1.25009 loss) | |
| I0525 00:15:51.342293 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.60984 (* 0.3 = 0.482952 loss) | |
| I0525 00:15:51.342308 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.93111 (* 0.0272727 = 0.107212 loss) | |
| I0525 00:15:51.342321 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.95271 (* 0.0272727 = 0.107801 loss) | |
| I0525 00:15:51.342335 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 4.36032 (* 0.0272727 = 0.118918 loss) | |
| I0525 00:15:51.342350 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.9613 (* 0.0272727 = 0.108035 loss) | |
| I0525 00:15:51.342363 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 3.75937 (* 0.0272727 = 0.102528 loss) | |
| I0525 00:15:51.342377 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 2.70828 (* 0.0272727 = 0.0738621 loss) | |
| I0525 00:15:51.342391 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 3.32993 (* 0.0272727 = 0.0908162 loss) | |
| I0525 00:15:51.342406 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 0.267894 (* 0.0272727 = 0.00730621 loss) | |
| I0525 00:15:51.342419 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.11113 (* 0.0272727 = 0.00303082 loss) | |
| I0525 00:15:51.342433 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.11995 (* 0.0272727 = 0.00327138 loss) | |
| I0525 00:15:51.342447 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.114153 (* 0.0272727 = 0.00311326 loss) | |
| I0525 00:15:51.342461 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.0895019 (* 0.0272727 = 0.00244096 loss) | |
| I0525 00:15:51.342475 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.0595278 (* 0.0272727 = 0.00162348 loss) | |
| I0525 00:15:51.342504 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.0851157 (* 0.0272727 = 0.00232134 loss) | |
| I0525 00:15:51.342519 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0755571 (* 0.0272727 = 0.00206065 loss) | |
| I0525 00:15:51.342533 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.0347603 (* 0.0272727 = 0.000948009 loss) | |
| I0525 00:15:51.342547 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.0213723 (* 0.0272727 = 0.00058288 loss) | |
| I0525 00:15:51.342562 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0390867 (* 0.0272727 = 0.001066 loss) | |
| I0525 00:15:51.342576 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.0495933 (* 0.0272727 = 0.00135255 loss) | |
| I0525 00:15:51.342591 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.0303031 (* 0.0272727 = 0.000826448 loss) | |
| I0525 00:15:51.342604 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.0191478 (* 0.0272727 = 0.000522212 loss) | |
| I0525 00:15:51.342618 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.0457332 (* 0.0272727 = 0.00124727 loss) | |
| I0525 00:15:51.342631 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0 | |
| I0525 00:15:51.342643 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0 | |
| I0525 00:15:51.342654 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0.125 | |
| I0525 00:15:51.342666 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0 | |
| I0525 00:15:51.342677 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0 | |
| I0525 00:15:51.342689 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.25 | |
| I0525 00:15:51.342701 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.5 | |
| I0525 00:15:51.342713 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.5 | |
| I0525 00:15:51.342721 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 1 | |
| I0525 00:15:51.342730 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 1 | |
| I0525 00:15:51.342741 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 1 | |
| I0525 00:15:51.342752 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 00:15:51.342764 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 00:15:51.342775 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 00:15:51.342787 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 00:15:51.342797 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 00:15:51.342809 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 00:15:51.342820 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 00:15:51.342831 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 00:15:51.342842 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 00:15:51.342854 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 00:15:51.342864 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 00:15:51.342878 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 00:15:51.342890 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.744318 | |
| I0525 00:15:51.342902 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.0444444 | |
| I0525 00:15:51.342916 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 4.27844 (* 0.3 = 1.28353 loss) | |
| I0525 00:15:51.342929 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.67829 (* 0.3 = 0.503488 loss) | |
| I0525 00:15:51.342943 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.85101 (* 0.0272727 = 0.105028 loss) | |
| I0525 00:15:51.342957 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 4.11976 (* 0.0272727 = 0.112357 loss) | |
| I0525 00:15:51.342970 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 4.15074 (* 0.0272727 = 0.113202 loss) | |
| I0525 00:15:51.343000 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 4.0261 (* 0.0272727 = 0.109803 loss) | |
| I0525 00:15:51.343016 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 4.13462 (* 0.0272727 = 0.112762 loss) | |
| I0525 00:15:51.343029 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 2.86264 (* 0.0272727 = 0.0780721 loss) | |
| I0525 00:15:51.343044 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 2.97172 (* 0.0272727 = 0.081047 loss) | |
| I0525 00:15:51.343057 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 0.361772 (* 0.0272727 = 0.00986651 loss) | |
| I0525 00:15:51.343071 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.240554 (* 0.0272727 = 0.00656058 loss) | |
| I0525 00:15:51.343086 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.362438 (* 0.0272727 = 0.00988467 loss) | |
| I0525 00:15:51.343099 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.148349 (* 0.0272727 = 0.00404588 loss) | |
| I0525 00:15:51.343113 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.0827182 (* 0.0272727 = 0.00225595 loss) | |
| I0525 00:15:51.343127 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.12439 (* 0.0272727 = 0.00339247 loss) | |
| I0525 00:15:51.343142 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.116527 (* 0.0272727 = 0.003178 loss) | |
| I0525 00:15:51.343154 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.105147 (* 0.0272727 = 0.00286766 loss) | |
| I0525 00:15:51.343168 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.059241 (* 0.0272727 = 0.00161566 loss) | |
| I0525 00:15:51.343183 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.0836293 (* 0.0272727 = 0.0022808 loss) | |
| I0525 00:15:51.343196 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.0844754 (* 0.0272727 = 0.00230387 loss) | |
| I0525 00:15:51.343210 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.03367 (* 0.0272727 = 0.000918272 loss) | |
| I0525 00:15:51.343225 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.052629 (* 0.0272727 = 0.00143534 loss) | |
| I0525 00:15:51.343237 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.0451705 (* 0.0272727 = 0.00123192 loss) | |
| I0525 00:15:51.343252 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.0656845 (* 0.0272727 = 0.0017914 loss) | |
| I0525 00:15:51.343264 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0 | |
| I0525 00:15:51.343276 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0 | |
| I0525 00:15:51.343287 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0 | |
| I0525 00:15:51.343298 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0 | |
| I0525 00:15:51.343309 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.125 | |
| I0525 00:15:51.343322 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.25 | |
| I0525 00:15:51.343333 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.5 | |
| I0525 00:15:51.343344 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.5 | |
| I0525 00:15:51.343355 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 1 | |
| I0525 00:15:51.343366 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 1 | |
| I0525 00:15:51.343379 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 1 | |
| I0525 00:15:51.343389 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 00:15:51.343400 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 00:15:51.343411 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 00:15:51.343422 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 00:15:51.343433 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 00:15:51.343446 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 00:15:51.343456 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 00:15:51.343487 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 00:15:51.343510 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 00:15:51.343524 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 00:15:51.343536 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 00:15:51.343547 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 00:15:51.343559 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.738636 | |
| I0525 00:15:51.343570 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.133333 | |
| I0525 00:15:51.343585 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.75694 (* 1 = 3.75694 loss) | |
| I0525 00:15:51.343598 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.20916 (* 1 = 1.20916 loss) | |
| I0525 00:15:51.343612 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 3.76891 (* 0.0909091 = 0.342629 loss) | |
| I0525 00:15:51.343626 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.48806 (* 0.0909091 = 0.317096 loss) | |
| I0525 00:15:51.343639 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 4.05613 (* 0.0909091 = 0.368739 loss) | |
| I0525 00:15:51.343653 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.34506 (* 0.0909091 = 0.304096 loss) | |
| I0525 00:15:51.343667 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 3.1946 (* 0.0909091 = 0.290418 loss) | |
| I0525 00:15:51.343682 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 2.23188 (* 0.0909091 = 0.202898 loss) | |
| I0525 00:15:51.343695 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 3.04774 (* 0.0909091 = 0.277067 loss) | |
| I0525 00:15:51.343709 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.201753 (* 0.0909091 = 0.0183412 loss) | |
| I0525 00:15:51.343722 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.122778 (* 0.0909091 = 0.0111616 loss) | |
| I0525 00:15:51.343736 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.08909 (* 0.0909091 = 0.00809909 loss) | |
| I0525 00:15:51.343750 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.0940597 (* 0.0909091 = 0.00855088 loss) | |
| I0525 00:15:51.343765 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.0746214 (* 0.0909091 = 0.00678376 loss) | |
| I0525 00:15:51.343778 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.0745911 (* 0.0909091 = 0.00678101 loss) | |
| I0525 00:15:51.343792 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.0355917 (* 0.0909091 = 0.00323561 loss) | |
| I0525 00:15:51.343806 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.0508557 (* 0.0909091 = 0.00462325 loss) | |
| I0525 00:15:51.343819 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.0291794 (* 0.0909091 = 0.00265267 loss) | |
| I0525 00:15:51.343833 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.012849 (* 0.0909091 = 0.00116809 loss) | |
| I0525 00:15:51.343847 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.0118228 (* 0.0909091 = 0.0010748 loss) | |
| I0525 00:15:51.343861 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00941348 (* 0.0909091 = 0.00085577 loss) | |
| I0525 00:15:51.343875 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.0074061 (* 0.0909091 = 0.000673282 loss) | |
| I0525 00:15:51.343889 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00801268 (* 0.0909091 = 0.000728426 loss) | |
| I0525 00:15:51.343904 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.00776598 (* 0.0909091 = 0.000705999 loss) | |
| I0525 00:15:51.343915 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 00:15:51.343930 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 00:15:51.343941 5272 solver.cpp:245] Train net output #149: total_confidence = 1.41157e-08 | |
| I0525 00:15:51.343953 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 1.65183e-06 | |
| I0525 00:15:51.343976 5272 sgd_solver.cpp:106] Iteration 500, lr = 0.001 | |
| I0525 00:22:16.113615 5272 solver.cpp:229] Iteration 1000, loss = 13.4113 | |
| I0525 00:22:16.113762 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0 | |
| I0525 00:22:16.113782 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.125 | |
| I0525 00:22:16.113796 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0.25 | |
| I0525 00:22:16.113808 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0525 00:22:16.113821 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0 | |
| I0525 00:22:16.113832 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.625 | |
| I0525 00:22:16.113845 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.625 | |
| I0525 00:22:16.113857 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.75 | |
| I0525 00:22:16.113868 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 1 | |
| I0525 00:22:16.113883 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 1 | |
| I0525 00:22:16.113895 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 1 | |
| I0525 00:22:16.113906 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 00:22:16.113919 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 00:22:16.113930 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 00:22:16.113941 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 00:22:16.113953 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 00:22:16.113965 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 00:22:16.113976 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 00:22:16.113988 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 00:22:16.113999 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 00:22:16.114012 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 00:22:16.114022 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 00:22:16.114034 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 00:22:16.114045 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.784091 | |
| I0525 00:22:16.114058 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.0526316 | |
| I0525 00:22:16.114074 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.98246 (* 0.3 = 1.19474 loss) | |
| I0525 00:22:16.114089 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.40073 (* 0.3 = 0.420219 loss) | |
| I0525 00:22:16.114104 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 4.16377 (* 0.0272727 = 0.113557 loss) | |
| I0525 00:22:16.114117 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.42226 (* 0.0272727 = 0.0933343 loss) | |
| I0525 00:22:16.114131 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.70956 (* 0.0272727 = 0.10117 loss) | |
| I0525 00:22:16.114145 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.75778 (* 0.0272727 = 0.102485 loss) | |
| I0525 00:22:16.114159 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 2.78501 (* 0.0272727 = 0.0759548 loss) | |
| I0525 00:22:16.114173 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 2.49968 (* 0.0272727 = 0.0681731 loss) | |
| I0525 00:22:16.114187 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 1.87425 (* 0.0272727 = 0.0511159 loss) | |
| I0525 00:22:16.114200 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 0.371593 (* 0.0272727 = 0.0101343 loss) | |
| I0525 00:22:16.114214 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.147338 (* 0.0272727 = 0.0040183 loss) | |
| I0525 00:22:16.114228 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.260484 (* 0.0272727 = 0.0071041 loss) | |
| I0525 00:22:16.114243 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.101823 (* 0.0272727 = 0.002777 loss) | |
| I0525 00:22:16.114258 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.101002 (* 0.0272727 = 0.00275459 loss) | |
| I0525 00:22:16.114271 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.081603 (* 0.0272727 = 0.00222554 loss) | |
| I0525 00:22:16.114305 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.05648 (* 0.0272727 = 0.00154036 loss) | |
| I0525 00:22:16.114320 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0845832 (* 0.0272727 = 0.00230682 loss) | |
| I0525 00:22:16.114333 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.0476369 (* 0.0272727 = 0.00129919 loss) | |
| I0525 00:22:16.114347 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.0586945 (* 0.0272727 = 0.00160076 loss) | |
| I0525 00:22:16.114362 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.021597 (* 0.0272727 = 0.000589008 loss) | |
| I0525 00:22:16.114375 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.0494823 (* 0.0272727 = 0.00134952 loss) | |
| I0525 00:22:16.114389 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.0448972 (* 0.0272727 = 0.00122447 loss) | |
| I0525 00:22:16.114403 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.0443787 (* 0.0272727 = 0.00121033 loss) | |
| I0525 00:22:16.114416 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.0291346 (* 0.0272727 = 0.00079458 loss) | |
| I0525 00:22:16.114429 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0 | |
| I0525 00:22:16.114441 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0.25 | |
| I0525 00:22:16.114452 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0 | |
| I0525 00:22:16.114464 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0 | |
| I0525 00:22:16.114475 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0.25 | |
| I0525 00:22:16.114486 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.625 | |
| I0525 00:22:16.114498 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.625 | |
| I0525 00:22:16.114509 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.75 | |
| I0525 00:22:16.114521 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 1 | |
| I0525 00:22:16.114532 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 1 | |
| I0525 00:22:16.114543 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 1 | |
| I0525 00:22:16.114555 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 00:22:16.114567 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 00:22:16.114578 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 00:22:16.114589 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 00:22:16.114598 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 00:22:16.114604 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 00:22:16.114617 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 00:22:16.114629 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 00:22:16.114639 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 00:22:16.114650 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 00:22:16.114662 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 00:22:16.114673 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 00:22:16.114684 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.784091 | |
| I0525 00:22:16.114696 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.0263158 | |
| I0525 00:22:16.114709 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 4.00513 (* 0.3 = 1.20154 loss) | |
| I0525 00:22:16.114722 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.33065 (* 0.3 = 0.399195 loss) | |
| I0525 00:22:16.114737 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.86058 (* 0.0272727 = 0.105288 loss) | |
| I0525 00:22:16.114750 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 4.13858 (* 0.0272727 = 0.11287 loss) | |
| I0525 00:22:16.114763 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 4.37234 (* 0.0272727 = 0.119246 loss) | |
| I0525 00:22:16.114792 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.73512 (* 0.0272727 = 0.101867 loss) | |
| I0525 00:22:16.114807 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 2.40307 (* 0.0272727 = 0.0655383 loss) | |
| I0525 00:22:16.114821 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 1.99799 (* 0.0272727 = 0.0544907 loss) | |
| I0525 00:22:16.114835 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 1.57227 (* 0.0272727 = 0.04288 loss) | |
| I0525 00:22:16.114850 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 0.199847 (* 0.0272727 = 0.00545038 loss) | |
| I0525 00:22:16.114863 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.0967752 (* 0.0272727 = 0.00263932 loss) | |
| I0525 00:22:16.114877 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.104619 (* 0.0272727 = 0.00285325 loss) | |
| I0525 00:22:16.114891 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.0818492 (* 0.0272727 = 0.00223225 loss) | |
| I0525 00:22:16.114904 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.10203 (* 0.0272727 = 0.00278264 loss) | |
| I0525 00:22:16.114918 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.172598 (* 0.0272727 = 0.00470721 loss) | |
| I0525 00:22:16.114935 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.0475379 (* 0.0272727 = 0.00129649 loss) | |
| I0525 00:22:16.114948 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.0649334 (* 0.0272727 = 0.00177091 loss) | |
| I0525 00:22:16.114962 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.0437856 (* 0.0272727 = 0.00119415 loss) | |
| I0525 00:22:16.114976 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.027479 (* 0.0272727 = 0.000749428 loss) | |
| I0525 00:22:16.114990 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.035191 (* 0.0272727 = 0.000959754 loss) | |
| I0525 00:22:16.115003 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.034326 (* 0.0272727 = 0.000936163 loss) | |
| I0525 00:22:16.115017 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.0263038 (* 0.0272727 = 0.000717375 loss) | |
| I0525 00:22:16.115031 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.0461519 (* 0.0272727 = 0.00125869 loss) | |
| I0525 00:22:16.115044 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.0367581 (* 0.0272727 = 0.00100249 loss) | |
| I0525 00:22:16.115056 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.0789474 | |
| I0525 00:22:16.115068 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.125 | |
| I0525 00:22:16.115079 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0.125 | |
| I0525 00:22:16.115092 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0.125 | |
| I0525 00:22:16.115103 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.25 | |
| I0525 00:22:16.115114 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.625 | |
| I0525 00:22:16.115125 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.625 | |
| I0525 00:22:16.115137 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.75 | |
| I0525 00:22:16.115149 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 1 | |
| I0525 00:22:16.115160 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 1 | |
| I0525 00:22:16.115171 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 1 | |
| I0525 00:22:16.115182 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 00:22:16.115195 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 00:22:16.115206 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 00:22:16.115216 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 00:22:16.115228 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 00:22:16.115239 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 00:22:16.115250 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 00:22:16.115270 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 00:22:16.115283 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 00:22:16.115295 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 00:22:16.115306 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 00:22:16.115317 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 00:22:16.115329 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.789773 | |
| I0525 00:22:16.115340 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.105263 | |
| I0525 00:22:16.115355 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.60232 (* 1 = 3.60232 loss) | |
| I0525 00:22:16.115367 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.08289 (* 1 = 1.08289 loss) | |
| I0525 00:22:16.115383 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 3.58339 (* 0.0909091 = 0.325763 loss) | |
| I0525 00:22:16.115411 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.46167 (* 0.0909091 = 0.314697 loss) | |
| I0525 00:22:16.115434 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.69659 (* 0.0909091 = 0.336054 loss) | |
| I0525 00:22:16.115449 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.08156 (* 0.0909091 = 0.280142 loss) | |
| I0525 00:22:16.115463 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 2.60997 (* 0.0909091 = 0.23727 loss) | |
| I0525 00:22:16.115476 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 1.99255 (* 0.0909091 = 0.181141 loss) | |
| I0525 00:22:16.115490 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 1.61895 (* 0.0909091 = 0.147177 loss) | |
| I0525 00:22:16.115504 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.243698 (* 0.0909091 = 0.0221543 loss) | |
| I0525 00:22:16.115517 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.114596 (* 0.0909091 = 0.0104178 loss) | |
| I0525 00:22:16.115531 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.14765 (* 0.0909091 = 0.0134228 loss) | |
| I0525 00:22:16.115545 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.122678 (* 0.0909091 = 0.0111525 loss) | |
| I0525 00:22:16.115559 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.132164 (* 0.0909091 = 0.0120149 loss) | |
| I0525 00:22:16.115573 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.0639484 (* 0.0909091 = 0.00581349 loss) | |
| I0525 00:22:16.115586 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.0459391 (* 0.0909091 = 0.00417628 loss) | |
| I0525 00:22:16.115602 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.0406054 (* 0.0909091 = 0.0036914 loss) | |
| I0525 00:22:16.115615 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.0210758 (* 0.0909091 = 0.00191599 loss) | |
| I0525 00:22:16.115628 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.0137746 (* 0.0909091 = 0.00125223 loss) | |
| I0525 00:22:16.115643 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.0102468 (* 0.0909091 = 0.000931525 loss) | |
| I0525 00:22:16.115656 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00757501 (* 0.0909091 = 0.000688637 loss) | |
| I0525 00:22:16.115670 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00679802 (* 0.0909091 = 0.000618002 loss) | |
| I0525 00:22:16.115684 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00615695 (* 0.0909091 = 0.000559722 loss) | |
| I0525 00:22:16.115697 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.00554393 (* 0.0909091 = 0.000503994 loss) | |
| I0525 00:22:16.115710 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 00:22:16.115720 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 00:22:16.115731 5272 solver.cpp:245] Train net output #149: total_confidence = 4.67072e-09 | |
| I0525 00:22:16.115743 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 1.42419e-06 | |
| I0525 00:22:16.115767 5272 sgd_solver.cpp:106] Iteration 1000, lr = 0.001 | |
| I0525 00:28:40.750103 5272 solver.cpp:229] Iteration 1500, loss = 13.1165 | |
| I0525 00:28:40.750239 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0 | |
| I0525 00:28:40.750264 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.25 | |
| I0525 00:28:40.750279 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0525 00:28:40.750291 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0.125 | |
| I0525 00:28:40.750303 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0 | |
| I0525 00:28:40.750315 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.25 | |
| I0525 00:28:40.750327 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.375 | |
| I0525 00:28:40.750339 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.375 | |
| I0525 00:28:40.750351 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.625 | |
| I0525 00:28:40.750368 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 0.75 | |
| I0525 00:28:40.750380 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 0.75 | |
| I0525 00:28:40.750392 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 0.75 | |
| I0525 00:28:40.750404 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 0.875 | |
| I0525 00:28:40.750416 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 0.875 | |
| I0525 00:28:40.750429 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 0.875 | |
| I0525 00:28:40.750440 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 0.875 | |
| I0525 00:28:40.750452 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 00:28:40.750463 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 00:28:40.750483 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 00:28:40.750496 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 00:28:40.750507 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 00:28:40.750519 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 00:28:40.750530 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 00:28:40.750541 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.659091 | |
| I0525 00:28:40.750553 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.0666667 | |
| I0525 00:28:40.750569 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 4.05514 (* 0.3 = 1.21654 loss) | |
| I0525 00:28:40.750584 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.68482 (* 0.3 = 0.505445 loss) | |
| I0525 00:28:40.750598 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.79241 (* 0.0272727 = 0.103429 loss) | |
| I0525 00:28:40.750612 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.68147 (* 0.0272727 = 0.100404 loss) | |
| I0525 00:28:40.750627 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 4.17152 (* 0.0272727 = 0.113769 loss) | |
| I0525 00:28:40.750639 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.5854 (* 0.0272727 = 0.0977836 loss) | |
| I0525 00:28:40.750653 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 3.68295 (* 0.0272727 = 0.100444 loss) | |
| I0525 00:28:40.750668 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 3.15246 (* 0.0272727 = 0.0859761 loss) | |
| I0525 00:28:40.750680 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 2.92764 (* 0.0272727 = 0.0798448 loss) | |
| I0525 00:28:40.750694 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 2.29493 (* 0.0272727 = 0.062589 loss) | |
| I0525 00:28:40.750708 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 1.80476 (* 0.0272727 = 0.0492208 loss) | |
| I0525 00:28:40.750722 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 1.66005 (* 0.0272727 = 0.0452742 loss) | |
| I0525 00:28:40.750736 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 1.78289 (* 0.0272727 = 0.0486242 loss) | |
| I0525 00:28:40.750757 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.888369 (* 0.0272727 = 0.0242282 loss) | |
| I0525 00:28:40.750772 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.828803 (* 0.0272727 = 0.0226037 loss) | |
| I0525 00:28:40.750805 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.820904 (* 0.0272727 = 0.0223883 loss) | |
| I0525 00:28:40.750820 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 1.08018 (* 0.0272727 = 0.0294596 loss) | |
| I0525 00:28:40.750834 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.0363395 (* 0.0272727 = 0.000991077 loss) | |
| I0525 00:28:40.750849 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.0233024 (* 0.0272727 = 0.00063552 loss) | |
| I0525 00:28:40.750862 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0220617 (* 0.0272727 = 0.000601682 loss) | |
| I0525 00:28:40.750876 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.020704 (* 0.0272727 = 0.000564653 loss) | |
| I0525 00:28:40.750890 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.0165594 (* 0.0272727 = 0.000451619 loss) | |
| I0525 00:28:40.750905 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.0203279 (* 0.0272727 = 0.000554397 loss) | |
| I0525 00:28:40.750917 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.0282538 (* 0.0272727 = 0.000770559 loss) | |
| I0525 00:28:40.750929 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0 | |
| I0525 00:28:40.750941 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0 | |
| I0525 00:28:40.750952 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0 | |
| I0525 00:28:40.750963 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0 | |
| I0525 00:28:40.750974 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0.125 | |
| I0525 00:28:40.750987 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.25 | |
| I0525 00:28:40.750998 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.375 | |
| I0525 00:28:40.751009 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.375 | |
| I0525 00:28:40.751020 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.625 | |
| I0525 00:28:40.751031 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 0.75 | |
| I0525 00:28:40.751044 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 0.75 | |
| I0525 00:28:40.751055 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 0.75 | |
| I0525 00:28:40.751065 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 0.875 | |
| I0525 00:28:40.751077 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 0.875 | |
| I0525 00:28:40.751088 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 0.875 | |
| I0525 00:28:40.751101 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 0.875 | |
| I0525 00:28:40.751111 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 00:28:40.751122 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 00:28:40.751133 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 00:28:40.751144 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 00:28:40.751155 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 00:28:40.751166 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 00:28:40.751178 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 00:28:40.751188 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.659091 | |
| I0525 00:28:40.751200 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.0833333 | |
| I0525 00:28:40.751214 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 4.1402 (* 0.3 = 1.24206 loss) | |
| I0525 00:28:40.751226 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.74291 (* 0.3 = 0.522874 loss) | |
| I0525 00:28:40.751240 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 4.22948 (* 0.0272727 = 0.115349 loss) | |
| I0525 00:28:40.751255 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 4.16168 (* 0.0272727 = 0.1135 loss) | |
| I0525 00:28:40.751278 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 4.19356 (* 0.0272727 = 0.11437 loss) | |
| I0525 00:28:40.751292 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.67371 (* 0.0272727 = 0.100192 loss) | |
| I0525 00:28:40.751307 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 3.78463 (* 0.0272727 = 0.103217 loss) | |
| I0525 00:28:40.751320 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 3.42423 (* 0.0272727 = 0.0933881 loss) | |
| I0525 00:28:40.751333 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 3.3034 (* 0.0272727 = 0.0900927 loss) | |
| I0525 00:28:40.751346 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 2.48196 (* 0.0272727 = 0.0676897 loss) | |
| I0525 00:28:40.751360 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 1.81997 (* 0.0272727 = 0.0496355 loss) | |
| I0525 00:28:40.751374 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 2.00737 (* 0.0272727 = 0.0547465 loss) | |
| I0525 00:28:40.751387 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 1.77121 (* 0.0272727 = 0.0483058 loss) | |
| I0525 00:28:40.751400 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.753922 (* 0.0272727 = 0.0205615 loss) | |
| I0525 00:28:40.751420 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.710852 (* 0.0272727 = 0.0193869 loss) | |
| I0525 00:28:40.751435 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.854343 (* 0.0272727 = 0.0233003 loss) | |
| I0525 00:28:40.751447 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.851088 (* 0.0272727 = 0.0232115 loss) | |
| I0525 00:28:40.751462 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.038494 (* 0.0272727 = 0.00104984 loss) | |
| I0525 00:28:40.751476 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.0161986 (* 0.0272727 = 0.000441781 loss) | |
| I0525 00:28:40.751489 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.0204036 (* 0.0272727 = 0.000556463 loss) | |
| I0525 00:28:40.751503 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.0299059 (* 0.0272727 = 0.000815615 loss) | |
| I0525 00:28:40.751516 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.0284334 (* 0.0272727 = 0.000775455 loss) | |
| I0525 00:28:40.751530 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.013689 (* 0.0272727 = 0.000373336 loss) | |
| I0525 00:28:40.751544 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.0209422 (* 0.0272727 = 0.000571152 loss) | |
| I0525 00:28:40.751555 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.0166667 | |
| I0525 00:28:40.751567 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0 | |
| I0525 00:28:40.751579 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0 | |
| I0525 00:28:40.751590 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0 | |
| I0525 00:28:40.751601 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.125 | |
| I0525 00:28:40.751612 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.25 | |
| I0525 00:28:40.751624 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.375 | |
| I0525 00:28:40.751636 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.375 | |
| I0525 00:28:40.751646 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.625 | |
| I0525 00:28:40.751658 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 0.75 | |
| I0525 00:28:40.751669 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 0.75 | |
| I0525 00:28:40.751682 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 0.75 | |
| I0525 00:28:40.751693 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 0.875 | |
| I0525 00:28:40.751703 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 0.875 | |
| I0525 00:28:40.751714 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 0.875 | |
| I0525 00:28:40.751725 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 0.875 | |
| I0525 00:28:40.751737 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 00:28:40.751759 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 00:28:40.751771 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 00:28:40.751782 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 00:28:40.751793 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 00:28:40.751807 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 00:28:40.751819 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 00:28:40.751832 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.664773 | |
| I0525 00:28:40.751847 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.116667 | |
| I0525 00:28:40.751858 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 4.13008 (* 1 = 4.13008 loss) | |
| I0525 00:28:40.751873 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.52206 (* 1 = 1.52206 loss) | |
| I0525 00:28:40.751885 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 4.16205 (* 0.0909091 = 0.378368 loss) | |
| I0525 00:28:40.751904 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.62899 (* 0.0909091 = 0.329908 loss) | |
| I0525 00:28:40.751919 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.92432 (* 0.0909091 = 0.356756 loss) | |
| I0525 00:28:40.751938 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.63787 (* 0.0909091 = 0.330716 loss) | |
| I0525 00:28:40.751952 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 3.51613 (* 0.0909091 = 0.319648 loss) | |
| I0525 00:28:40.751965 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 3.24685 (* 0.0909091 = 0.295169 loss) | |
| I0525 00:28:40.751979 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 2.84856 (* 0.0909091 = 0.25896 loss) | |
| I0525 00:28:40.751992 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 1.95696 (* 0.0909091 = 0.177905 loss) | |
| I0525 00:28:40.752005 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 1.51142 (* 0.0909091 = 0.137402 loss) | |
| I0525 00:28:40.752019 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 1.74986 (* 0.0909091 = 0.159078 loss) | |
| I0525 00:28:40.752032 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 1.61079 (* 0.0909091 = 0.146436 loss) | |
| I0525 00:28:40.752046 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.854904 (* 0.0909091 = 0.0777185 loss) | |
| I0525 00:28:40.752059 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 1.04248 (* 0.0909091 = 0.0947705 loss) | |
| I0525 00:28:40.752073 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.913568 (* 0.0909091 = 0.0830517 loss) | |
| I0525 00:28:40.752086 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.958453 (* 0.0909091 = 0.0871321 loss) | |
| I0525 00:28:40.752100 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.0385833 (* 0.0909091 = 0.00350757 loss) | |
| I0525 00:28:40.752113 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.0195122 (* 0.0909091 = 0.00177383 loss) | |
| I0525 00:28:40.752127 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.021645 (* 0.0909091 = 0.00196773 loss) | |
| I0525 00:28:40.752140 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00805381 (* 0.0909091 = 0.000732164 loss) | |
| I0525 00:28:40.752154 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.0074033 (* 0.0909091 = 0.000673027 loss) | |
| I0525 00:28:40.752167 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00841593 (* 0.0909091 = 0.000765084 loss) | |
| I0525 00:28:40.752182 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.00512228 (* 0.0909091 = 0.000465662 loss) | |
| I0525 00:28:40.752192 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 00:28:40.752203 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 00:28:40.752214 5272 solver.cpp:245] Train net output #149: total_confidence = 3.96097e-08 | |
| I0525 00:28:40.752235 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 1.2685e-06 | |
| I0525 00:28:40.752249 5272 sgd_solver.cpp:106] Iteration 1500, lr = 0.001 | |
| I0525 00:35:05.272518 5272 solver.cpp:229] Iteration 2000, loss = 12.7829 | |
| I0525 00:35:05.272686 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0227273 | |
| I0525 00:35:05.272707 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.25 | |
| I0525 00:35:05.272722 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0.25 | |
| I0525 00:35:05.272733 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0525 00:35:05.272747 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0 | |
| I0525 00:35:05.272759 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.25 | |
| I0525 00:35:05.272771 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.625 | |
| I0525 00:35:05.272783 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.75 | |
| I0525 00:35:05.272795 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.875 | |
| I0525 00:35:05.272807 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 1 | |
| I0525 00:35:05.272820 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 1 | |
| I0525 00:35:05.272831 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 00:35:05.272843 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 00:35:05.272855 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 00:35:05.272867 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 00:35:05.272881 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 00:35:05.272894 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 00:35:05.272907 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 00:35:05.272918 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 00:35:05.272929 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 00:35:05.272941 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 00:35:05.272953 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 00:35:05.272965 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 00:35:05.272976 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.755682 | |
| I0525 00:35:05.272989 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.159091 | |
| I0525 00:35:05.273005 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.92125 (* 0.3 = 1.17637 loss) | |
| I0525 00:35:05.273020 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.27123 (* 0.3 = 0.381368 loss) | |
| I0525 00:35:05.273035 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.53988 (* 0.0272727 = 0.0965421 loss) | |
| I0525 00:35:05.273048 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.48922 (* 0.0272727 = 0.0951607 loss) | |
| I0525 00:35:05.273062 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.59355 (* 0.0272727 = 0.0980059 loss) | |
| I0525 00:35:05.273077 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 4.47588 (* 0.0272727 = 0.122069 loss) | |
| I0525 00:35:05.273090 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 4.01635 (* 0.0272727 = 0.109537 loss) | |
| I0525 00:35:05.273104 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 1.89373 (* 0.0272727 = 0.0516471 loss) | |
| I0525 00:35:05.273133 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 2.07407 (* 0.0272727 = 0.0565656 loss) | |
| I0525 00:35:05.273150 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 1.04755 (* 0.0272727 = 0.0285696 loss) | |
| I0525 00:35:05.273164 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.126235 (* 0.0272727 = 0.00344278 loss) | |
| I0525 00:35:05.273180 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.0787587 (* 0.0272727 = 0.00214796 loss) | |
| I0525 00:35:05.273193 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.0573684 (* 0.0272727 = 0.00156459 loss) | |
| I0525 00:35:05.273208 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.0460874 (* 0.0272727 = 0.00125693 loss) | |
| I0525 00:35:05.273222 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.0604106 (* 0.0272727 = 0.00164756 loss) | |
| I0525 00:35:05.273257 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.0426749 (* 0.0272727 = 0.00116386 loss) | |
| I0525 00:35:05.273273 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0395692 (* 0.0272727 = 0.00107916 loss) | |
| I0525 00:35:05.273288 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.0445833 (* 0.0272727 = 0.00121591 loss) | |
| I0525 00:35:05.273301 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.0271112 (* 0.0272727 = 0.000739395 loss) | |
| I0525 00:35:05.273315 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0140552 (* 0.0272727 = 0.000383324 loss) | |
| I0525 00:35:05.273329 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.0313113 (* 0.0272727 = 0.000853944 loss) | |
| I0525 00:35:05.273344 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.0358698 (* 0.0272727 = 0.000978267 loss) | |
| I0525 00:35:05.273357 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.014232 (* 0.0272727 = 0.000388146 loss) | |
| I0525 00:35:05.273371 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.0281452 (* 0.0272727 = 0.000767597 loss) | |
| I0525 00:35:05.273385 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0 | |
| I0525 00:35:05.273396 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0.25 | |
| I0525 00:35:05.273408 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0.25 | |
| I0525 00:35:05.273419 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0.125 | |
| I0525 00:35:05.273432 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0 | |
| I0525 00:35:05.273443 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.25 | |
| I0525 00:35:05.273455 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.625 | |
| I0525 00:35:05.273466 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.75 | |
| I0525 00:35:05.273478 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.875 | |
| I0525 00:35:05.273490 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 1 | |
| I0525 00:35:05.273501 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 1 | |
| I0525 00:35:05.273514 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 00:35:05.273524 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 00:35:05.273536 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 00:35:05.273547 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 00:35:05.273558 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 00:35:05.273571 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 00:35:05.273581 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 00:35:05.273593 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 00:35:05.273604 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 00:35:05.273617 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 00:35:05.273627 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 00:35:05.273639 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 00:35:05.273650 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.75 | |
| I0525 00:35:05.273663 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.181818 | |
| I0525 00:35:05.273676 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.93224 (* 0.3 = 1.17967 loss) | |
| I0525 00:35:05.273689 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.22689 (* 0.3 = 0.368068 loss) | |
| I0525 00:35:05.273707 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.7261 (* 0.0272727 = 0.101621 loss) | |
| I0525 00:35:05.273721 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 3.5749 (* 0.0272727 = 0.0974973 loss) | |
| I0525 00:35:05.273736 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.46198 (* 0.0272727 = 0.0944177 loss) | |
| I0525 00:35:05.273761 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 4.00962 (* 0.0272727 = 0.109353 loss) | |
| I0525 00:35:05.273775 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 4.0617 (* 0.0272727 = 0.110774 loss) | |
| I0525 00:35:05.273789 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 2.15543 (* 0.0272727 = 0.0587845 loss) | |
| I0525 00:35:05.273803 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 1.90413 (* 0.0272727 = 0.0519308 loss) | |
| I0525 00:35:05.273816 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 0.927545 (* 0.0272727 = 0.0252967 loss) | |
| I0525 00:35:05.273831 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.125155 (* 0.0272727 = 0.00341331 loss) | |
| I0525 00:35:05.273850 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.0804279 (* 0.0272727 = 0.00219349 loss) | |
| I0525 00:35:05.273865 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.0828219 (* 0.0272727 = 0.00225878 loss) | |
| I0525 00:35:05.273880 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.0812313 (* 0.0272727 = 0.0022154 loss) | |
| I0525 00:35:05.273895 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.0752477 (* 0.0272727 = 0.00205221 loss) | |
| I0525 00:35:05.273908 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.075886 (* 0.0272727 = 0.00206962 loss) | |
| I0525 00:35:05.273922 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.0441645 (* 0.0272727 = 0.00120449 loss) | |
| I0525 00:35:05.273939 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.043339 (* 0.0272727 = 0.00118197 loss) | |
| I0525 00:35:05.273953 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.0305005 (* 0.0272727 = 0.000831833 loss) | |
| I0525 00:35:05.273967 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.0332818 (* 0.0272727 = 0.000907687 loss) | |
| I0525 00:35:05.273982 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.0287694 (* 0.0272727 = 0.00078462 loss) | |
| I0525 00:35:05.273995 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.0178319 (* 0.0272727 = 0.000486324 loss) | |
| I0525 00:35:05.274010 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.0399262 (* 0.0272727 = 0.0010889 loss) | |
| I0525 00:35:05.274024 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.0279846 (* 0.0272727 = 0.000763216 loss) | |
| I0525 00:35:05.274036 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.0454545 | |
| I0525 00:35:05.274049 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0 | |
| I0525 00:35:05.274060 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0 | |
| I0525 00:35:05.274071 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0.125 | |
| I0525 00:35:05.274083 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0 | |
| I0525 00:35:05.274094 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.25 | |
| I0525 00:35:05.274106 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.625 | |
| I0525 00:35:05.274118 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.75 | |
| I0525 00:35:05.274130 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.875 | |
| I0525 00:35:05.274142 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 1 | |
| I0525 00:35:05.274153 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 1 | |
| I0525 00:35:05.274165 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 00:35:05.274176 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 00:35:05.274188 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 00:35:05.274199 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 00:35:05.274210 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 00:35:05.274222 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 00:35:05.274245 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 00:35:05.274257 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 00:35:05.274268 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 00:35:05.274281 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 00:35:05.274292 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 00:35:05.274304 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 00:35:05.274315 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.75 | |
| I0525 00:35:05.274327 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.159091 | |
| I0525 00:35:05.274341 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.75894 (* 1 = 3.75894 loss) | |
| I0525 00:35:05.274355 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.19701 (* 1 = 1.19701 loss) | |
| I0525 00:35:05.274369 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 3.54954 (* 0.0909091 = 0.322686 loss) | |
| I0525 00:35:05.274382 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.75869 (* 0.0909091 = 0.341699 loss) | |
| I0525 00:35:05.274396 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.3944 (* 0.0909091 = 0.308582 loss) | |
| I0525 00:35:05.274410 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.8402 (* 0.0909091 = 0.349109 loss) | |
| I0525 00:35:05.274425 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 3.65981 (* 0.0909091 = 0.33271 loss) | |
| I0525 00:35:05.274437 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 2.05177 (* 0.0909091 = 0.186524 loss) | |
| I0525 00:35:05.274451 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 1.69134 (* 0.0909091 = 0.153758 loss) | |
| I0525 00:35:05.274466 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.904634 (* 0.0909091 = 0.0822395 loss) | |
| I0525 00:35:05.274478 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.120506 (* 0.0909091 = 0.0109551 loss) | |
| I0525 00:35:05.274492 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.0811063 (* 0.0909091 = 0.0073733 loss) | |
| I0525 00:35:05.274507 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.0766133 (* 0.0909091 = 0.00696485 loss) | |
| I0525 00:35:05.274520 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.0584315 (* 0.0909091 = 0.00531196 loss) | |
| I0525 00:35:05.274534 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.0580073 (* 0.0909091 = 0.00527339 loss) | |
| I0525 00:35:05.274549 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.0332099 (* 0.0909091 = 0.00301908 loss) | |
| I0525 00:35:05.274562 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.0254822 (* 0.0909091 = 0.00231657 loss) | |
| I0525 00:35:05.274576 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.0171924 (* 0.0909091 = 0.00156295 loss) | |
| I0525 00:35:05.274590 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.00972325 (* 0.0909091 = 0.000883932 loss) | |
| I0525 00:35:05.274603 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.00888911 (* 0.0909091 = 0.000808101 loss) | |
| I0525 00:35:05.274617 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.0058786 (* 0.0909091 = 0.000534418 loss) | |
| I0525 00:35:05.274631 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.0072391 (* 0.0909091 = 0.0006581 loss) | |
| I0525 00:35:05.274646 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00436002 (* 0.0909091 = 0.000396366 loss) | |
| I0525 00:35:05.274659 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.00509385 (* 0.0909091 = 0.000463077 loss) | |
| I0525 00:35:05.274672 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 00:35:05.274683 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 00:35:05.274691 5272 solver.cpp:245] Train net output #149: total_confidence = 2.32681e-09 | |
| I0525 00:35:05.274713 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 2.42269e-06 | |
| I0525 00:35:05.274729 5272 sgd_solver.cpp:106] Iteration 2000, lr = 0.001 | |
| I0525 00:41:29.941377 5272 solver.cpp:229] Iteration 2500, loss = 12.789 | |
| I0525 00:41:29.941529 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0232558 | |
| I0525 00:41:29.941550 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0 | |
| I0525 00:41:29.941563 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0525 00:41:29.941576 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0525 00:41:29.941587 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0 | |
| I0525 00:41:29.941598 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.125 | |
| I0525 00:41:29.941612 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.625 | |
| I0525 00:41:29.941623 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.875 | |
| I0525 00:41:29.941637 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 1 | |
| I0525 00:41:29.941648 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 1 | |
| I0525 00:41:29.941659 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 1 | |
| I0525 00:41:29.941671 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 00:41:29.941684 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 00:41:29.941695 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 00:41:29.941707 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 00:41:29.941720 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 00:41:29.941732 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 00:41:29.941745 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 00:41:29.941756 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 00:41:29.941767 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 00:41:29.941781 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 00:41:29.941792 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 00:41:29.941803 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 00:41:29.941815 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.761364 | |
| I0525 00:41:29.941828 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.0930233 | |
| I0525 00:41:29.941843 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 4.09851 (* 0.3 = 1.22955 loss) | |
| I0525 00:41:29.941859 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.19809 (* 0.3 = 0.359426 loss) | |
| I0525 00:41:29.941872 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.88507 (* 0.0272727 = 0.105956 loss) | |
| I0525 00:41:29.941890 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.89771 (* 0.0272727 = 0.106301 loss) | |
| I0525 00:41:29.941905 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 4.68213 (* 0.0272727 = 0.127695 loss) | |
| I0525 00:41:29.941917 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.99585 (* 0.0272727 = 0.108978 loss) | |
| I0525 00:41:29.941931 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 3.90896 (* 0.0272727 = 0.106608 loss) | |
| I0525 00:41:29.941946 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 2.34393 (* 0.0272727 = 0.0639254 loss) | |
| I0525 00:41:29.941958 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 1.00309 (* 0.0272727 = 0.0273569 loss) | |
| I0525 00:41:29.941973 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 0.309577 (* 0.0272727 = 0.008443 loss) | |
| I0525 00:41:29.941987 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.145605 (* 0.0272727 = 0.00397103 loss) | |
| I0525 00:41:29.942001 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.158907 (* 0.0272727 = 0.00433383 loss) | |
| I0525 00:41:29.942016 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.0976243 (* 0.0272727 = 0.00266248 loss) | |
| I0525 00:41:29.942030 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.139111 (* 0.0272727 = 0.00379393 loss) | |
| I0525 00:41:29.942044 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.0755138 (* 0.0272727 = 0.00205947 loss) | |
| I0525 00:41:29.942078 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.0851903 (* 0.0272727 = 0.00232337 loss) | |
| I0525 00:41:29.942093 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0767541 (* 0.0272727 = 0.00209329 loss) | |
| I0525 00:41:29.942108 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.0435614 (* 0.0272727 = 0.00118804 loss) | |
| I0525 00:41:29.942122 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.07218 (* 0.0272727 = 0.00196855 loss) | |
| I0525 00:41:29.942137 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0291235 (* 0.0272727 = 0.000794276 loss) | |
| I0525 00:41:29.942150 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.039615 (* 0.0272727 = 0.00108041 loss) | |
| I0525 00:41:29.942164 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.0332074 (* 0.0272727 = 0.000905655 loss) | |
| I0525 00:41:29.942178 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.0357341 (* 0.0272727 = 0.000974567 loss) | |
| I0525 00:41:29.942193 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.0290932 (* 0.0272727 = 0.00079345 loss) | |
| I0525 00:41:29.942205 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0 | |
| I0525 00:41:29.942217 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0 | |
| I0525 00:41:29.942229 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0 | |
| I0525 00:41:29.942240 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0 | |
| I0525 00:41:29.942251 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0 | |
| I0525 00:41:29.942263 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.125 | |
| I0525 00:41:29.942275 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.625 | |
| I0525 00:41:29.942286 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.875 | |
| I0525 00:41:29.942298 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 1 | |
| I0525 00:41:29.942309 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 1 | |
| I0525 00:41:29.942322 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 1 | |
| I0525 00:41:29.942332 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 00:41:29.942344 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 00:41:29.942356 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 00:41:29.942368 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 00:41:29.942375 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 00:41:29.942384 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 00:41:29.942395 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 00:41:29.942407 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 00:41:29.942419 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 00:41:29.942430 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 00:41:29.942441 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 00:41:29.942452 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 00:41:29.942464 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.755682 | |
| I0525 00:41:29.942476 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.0930233 | |
| I0525 00:41:29.942489 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 4.13513 (* 0.3 = 1.24054 loss) | |
| I0525 00:41:29.942503 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.19938 (* 0.3 = 0.359815 loss) | |
| I0525 00:41:29.942517 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 4.41432 (* 0.0272727 = 0.12039 loss) | |
| I0525 00:41:29.942530 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 4.14429 (* 0.0272727 = 0.113026 loss) | |
| I0525 00:41:29.942548 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 4.26111 (* 0.0272727 = 0.116212 loss) | |
| I0525 00:41:29.942574 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 4.07413 (* 0.0272727 = 0.111113 loss) | |
| I0525 00:41:29.942587 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 3.92212 (* 0.0272727 = 0.106967 loss) | |
| I0525 00:41:29.942601 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 2.0807 (* 0.0272727 = 0.0567463 loss) | |
| I0525 00:41:29.942615 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 1.31967 (* 0.0272727 = 0.0359911 loss) | |
| I0525 00:41:29.942630 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 0.289858 (* 0.0272727 = 0.00790522 loss) | |
| I0525 00:41:29.942643 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.147687 (* 0.0272727 = 0.00402782 loss) | |
| I0525 00:41:29.942657 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.123971 (* 0.0272727 = 0.00338102 loss) | |
| I0525 00:41:29.942672 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.147 (* 0.0272727 = 0.00400909 loss) | |
| I0525 00:41:29.942684 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.0952754 (* 0.0272727 = 0.00259842 loss) | |
| I0525 00:41:29.942698 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.105477 (* 0.0272727 = 0.00287665 loss) | |
| I0525 00:41:29.942713 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.0624571 (* 0.0272727 = 0.00170338 loss) | |
| I0525 00:41:29.942726 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.127862 (* 0.0272727 = 0.00348716 loss) | |
| I0525 00:41:29.942740 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.0815335 (* 0.0272727 = 0.00222364 loss) | |
| I0525 00:41:29.942754 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.0439283 (* 0.0272727 = 0.00119804 loss) | |
| I0525 00:41:29.942767 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.0585262 (* 0.0272727 = 0.00159617 loss) | |
| I0525 00:41:29.942781 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.0785093 (* 0.0272727 = 0.00214116 loss) | |
| I0525 00:41:29.942795 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.0581652 (* 0.0272727 = 0.00158632 loss) | |
| I0525 00:41:29.942809 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.0680433 (* 0.0272727 = 0.00185573 loss) | |
| I0525 00:41:29.942823 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.0286516 (* 0.0272727 = 0.000781408 loss) | |
| I0525 00:41:29.942836 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0 | |
| I0525 00:41:29.942847 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.125 | |
| I0525 00:41:29.942859 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0 | |
| I0525 00:41:29.942870 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0.125 | |
| I0525 00:41:29.942883 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0 | |
| I0525 00:41:29.942893 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.125 | |
| I0525 00:41:29.942905 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.625 | |
| I0525 00:41:29.942917 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.875 | |
| I0525 00:41:29.942931 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 1 | |
| I0525 00:41:29.942944 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 1 | |
| I0525 00:41:29.942955 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 1 | |
| I0525 00:41:29.942966 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 00:41:29.942978 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 00:41:29.942989 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 00:41:29.943001 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 00:41:29.943012 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 00:41:29.943023 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 00:41:29.943035 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 00:41:29.943055 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 00:41:29.943068 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 00:41:29.943080 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 00:41:29.943091 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 00:41:29.943104 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 00:41:29.943114 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.755682 | |
| I0525 00:41:29.943126 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.0465116 | |
| I0525 00:41:29.943140 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.91883 (* 1 = 3.91883 loss) | |
| I0525 00:41:29.943153 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.18991 (* 1 = 1.18991 loss) | |
| I0525 00:41:29.943167 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 3.8382 (* 0.0909091 = 0.348927 loss) | |
| I0525 00:41:29.943181 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.78463 (* 0.0909091 = 0.344057 loss) | |
| I0525 00:41:29.943195 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 4.10665 (* 0.0909091 = 0.373332 loss) | |
| I0525 00:41:29.943209 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.90022 (* 0.0909091 = 0.354565 loss) | |
| I0525 00:41:29.943223 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 3.87986 (* 0.0909091 = 0.352715 loss) | |
| I0525 00:41:29.943236 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 2.33136 (* 0.0909091 = 0.211942 loss) | |
| I0525 00:41:29.943250 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 0.991427 (* 0.0909091 = 0.0901297 loss) | |
| I0525 00:41:29.943264 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.253009 (* 0.0909091 = 0.0230008 loss) | |
| I0525 00:41:29.943279 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.166617 (* 0.0909091 = 0.015147 loss) | |
| I0525 00:41:29.943292 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.125126 (* 0.0909091 = 0.0113751 loss) | |
| I0525 00:41:29.943305 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.0899374 (* 0.0909091 = 0.00817613 loss) | |
| I0525 00:41:29.943320 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.0972507 (* 0.0909091 = 0.00884098 loss) | |
| I0525 00:41:29.943333 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.0888271 (* 0.0909091 = 0.00807519 loss) | |
| I0525 00:41:29.943347 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.0637309 (* 0.0909091 = 0.00579372 loss) | |
| I0525 00:41:29.943361 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.0531034 (* 0.0909091 = 0.00482758 loss) | |
| I0525 00:41:29.943375 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.0408775 (* 0.0909091 = 0.00371613 loss) | |
| I0525 00:41:29.943389 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.0162169 (* 0.0909091 = 0.00147426 loss) | |
| I0525 00:41:29.943403 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.00952436 (* 0.0909091 = 0.000865851 loss) | |
| I0525 00:41:29.943418 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00832199 (* 0.0909091 = 0.000756544 loss) | |
| I0525 00:41:29.943431 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00610849 (* 0.0909091 = 0.000555317 loss) | |
| I0525 00:41:29.943445 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00634939 (* 0.0909091 = 0.000577217 loss) | |
| I0525 00:41:29.943459 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.00501891 (* 0.0909091 = 0.000456264 loss) | |
| I0525 00:41:29.943471 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 00:41:29.943483 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 00:41:29.943495 5272 solver.cpp:245] Train net output #149: total_confidence = 8.6717e-09 | |
| I0525 00:41:29.943506 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 7.53332e-07 | |
| I0525 00:41:29.943528 5272 sgd_solver.cpp:106] Iteration 2500, lr = 0.001 | |
| I0525 00:47:54.740547 5272 solver.cpp:229] Iteration 3000, loss = 12.6279 | |
| I0525 00:47:54.740674 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0149254 | |
| I0525 00:47:54.740695 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0 | |
| I0525 00:47:54.740708 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0525 00:47:54.740720 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0.125 | |
| I0525 00:47:54.740732 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.375 | |
| I0525 00:47:54.740744 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.125 | |
| I0525 00:47:54.740757 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.125 | |
| I0525 00:47:54.740770 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.25 | |
| I0525 00:47:54.740782 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.5 | |
| I0525 00:47:54.740794 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 0.75 | |
| I0525 00:47:54.740805 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 0.75 | |
| I0525 00:47:54.740818 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 0.875 | |
| I0525 00:47:54.740829 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 0.875 | |
| I0525 00:47:54.740841 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 0.875 | |
| I0525 00:47:54.740854 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 0.875 | |
| I0525 00:47:54.740865 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 0.875 | |
| I0525 00:47:54.740880 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 0.875 | |
| I0525 00:47:54.740891 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 0.875 | |
| I0525 00:47:54.740903 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 0.875 | |
| I0525 00:47:54.740916 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 00:47:54.740927 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 00:47:54.740938 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 00:47:54.740949 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 00:47:54.740962 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.625 | |
| I0525 00:47:54.740973 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.0746269 | |
| I0525 00:47:54.740989 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 4.24946 (* 0.3 = 1.27484 loss) | |
| I0525 00:47:54.741003 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.73441 (* 0.3 = 0.520322 loss) | |
| I0525 00:47:54.741017 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 4.62352 (* 0.0272727 = 0.126096 loss) | |
| I0525 00:47:54.741034 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.98568 (* 0.0272727 = 0.1087 loss) | |
| I0525 00:47:54.741047 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.70204 (* 0.0272727 = 0.100965 loss) | |
| I0525 00:47:54.741060 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.37382 (* 0.0272727 = 0.0920132 loss) | |
| I0525 00:47:54.741075 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 3.37772 (* 0.0272727 = 0.0921196 loss) | |
| I0525 00:47:54.741088 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 4.35502 (* 0.0272727 = 0.118773 loss) | |
| I0525 00:47:54.741102 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 3.97541 (* 0.0272727 = 0.10842 loss) | |
| I0525 00:47:54.741116 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 2.78381 (* 0.0272727 = 0.0759221 loss) | |
| I0525 00:47:54.741145 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 1.38435 (* 0.0272727 = 0.037755 loss) | |
| I0525 00:47:54.741159 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 1.50124 (* 0.0272727 = 0.040943 loss) | |
| I0525 00:47:54.741173 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.82868 (* 0.0272727 = 0.0226004 loss) | |
| I0525 00:47:54.741188 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.902771 (* 0.0272727 = 0.024621 loss) | |
| I0525 00:47:54.741219 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.758071 (* 0.0272727 = 0.0206747 loss) | |
| I0525 00:47:54.741235 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.910692 (* 0.0272727 = 0.0248371 loss) | |
| I0525 00:47:54.741248 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.766525 (* 0.0272727 = 0.0209052 loss) | |
| I0525 00:47:54.741262 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.99003 (* 0.0272727 = 0.0270008 loss) | |
| I0525 00:47:54.741276 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.679101 (* 0.0272727 = 0.0185209 loss) | |
| I0525 00:47:54.741289 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.704541 (* 0.0272727 = 0.0192148 loss) | |
| I0525 00:47:54.741304 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.0199109 (* 0.0272727 = 0.000543024 loss) | |
| I0525 00:47:54.741318 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.0297044 (* 0.0272727 = 0.000810121 loss) | |
| I0525 00:47:54.741331 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.0268899 (* 0.0272727 = 0.00073336 loss) | |
| I0525 00:47:54.741345 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.0212802 (* 0.0272727 = 0.00058037 loss) | |
| I0525 00:47:54.741358 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.0149254 | |
| I0525 00:47:54.741369 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0.125 | |
| I0525 00:47:54.741381 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0 | |
| I0525 00:47:54.741392 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0 | |
| I0525 00:47:54.741403 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0.125 | |
| I0525 00:47:54.741415 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.125 | |
| I0525 00:47:54.741426 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.125 | |
| I0525 00:47:54.741438 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.25 | |
| I0525 00:47:54.741449 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.5 | |
| I0525 00:47:54.741461 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 0.75 | |
| I0525 00:47:54.741473 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 0.75 | |
| I0525 00:47:54.741484 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 0.875 | |
| I0525 00:47:54.741497 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 0.875 | |
| I0525 00:47:54.741508 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 0.875 | |
| I0525 00:47:54.741518 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 0.875 | |
| I0525 00:47:54.741530 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 0.875 | |
| I0525 00:47:54.741541 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 0.875 | |
| I0525 00:47:54.741552 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 0.875 | |
| I0525 00:47:54.741564 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 0.875 | |
| I0525 00:47:54.741575 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 00:47:54.741586 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 00:47:54.741598 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 00:47:54.741610 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 00:47:54.741621 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.625 | |
| I0525 00:47:54.741631 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.0746269 | |
| I0525 00:47:54.741646 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 4.21009 (* 0.3 = 1.26303 loss) | |
| I0525 00:47:54.741659 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.73829 (* 0.3 = 0.521488 loss) | |
| I0525 00:47:54.741672 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 4.31466 (* 0.0272727 = 0.117672 loss) | |
| I0525 00:47:54.741688 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 4.11623 (* 0.0272727 = 0.112261 loss) | |
| I0525 00:47:54.741714 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 4.33444 (* 0.0272727 = 0.118212 loss) | |
| I0525 00:47:54.741729 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 4.05153 (* 0.0272727 = 0.110496 loss) | |
| I0525 00:47:54.741744 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 3.58904 (* 0.0272727 = 0.0978829 loss) | |
| I0525 00:47:54.741757 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 4.40439 (* 0.0272727 = 0.12012 loss) | |
| I0525 00:47:54.741770 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 4.24856 (* 0.0272727 = 0.11587 loss) | |
| I0525 00:47:54.741783 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 2.52428 (* 0.0272727 = 0.0688441 loss) | |
| I0525 00:47:54.741797 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 1.38601 (* 0.0272727 = 0.0378002 loss) | |
| I0525 00:47:54.741811 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 1.62495 (* 0.0272727 = 0.0443169 loss) | |
| I0525 00:47:54.741824 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.757404 (* 0.0272727 = 0.0206565 loss) | |
| I0525 00:47:54.741838 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.728316 (* 0.0272727 = 0.0198632 loss) | |
| I0525 00:47:54.741855 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.813051 (* 0.0272727 = 0.0221741 loss) | |
| I0525 00:47:54.741865 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.766242 (* 0.0272727 = 0.0208975 loss) | |
| I0525 00:47:54.741879 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.945189 (* 0.0272727 = 0.0257779 loss) | |
| I0525 00:47:54.741894 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 1.07776 (* 0.0272727 = 0.0293935 loss) | |
| I0525 00:47:54.741907 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 1.0765 (* 0.0272727 = 0.029359 loss) | |
| I0525 00:47:54.741920 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 1.13546 (* 0.0272727 = 0.0309672 loss) | |
| I0525 00:47:54.741937 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.012686 (* 0.0272727 = 0.000345981 loss) | |
| I0525 00:47:54.741951 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.0177177 (* 0.0272727 = 0.00048321 loss) | |
| I0525 00:47:54.741966 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.0177239 (* 0.0272727 = 0.000483379 loss) | |
| I0525 00:47:54.741979 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.0213743 (* 0.0272727 = 0.000582935 loss) | |
| I0525 00:47:54.741991 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.0597015 | |
| I0525 00:47:54.742003 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0 | |
| I0525 00:47:54.742015 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0 | |
| I0525 00:47:54.742027 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0 | |
| I0525 00:47:54.742038 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.125 | |
| I0525 00:47:54.742048 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.125 | |
| I0525 00:47:54.742060 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.125 | |
| I0525 00:47:54.742071 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.25 | |
| I0525 00:47:54.742082 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.5 | |
| I0525 00:47:54.742094 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 0.75 | |
| I0525 00:47:54.742105 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 0.75 | |
| I0525 00:47:54.742116 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 0.875 | |
| I0525 00:47:54.742127 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 0.875 | |
| I0525 00:47:54.742138 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 0.875 | |
| I0525 00:47:54.742149 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 0.875 | |
| I0525 00:47:54.742161 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 0.875 | |
| I0525 00:47:54.742172 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 0.875 | |
| I0525 00:47:54.742193 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 0.875 | |
| I0525 00:47:54.742207 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 0.875 | |
| I0525 00:47:54.742218 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 00:47:54.742229 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 00:47:54.742240 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 00:47:54.742251 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 00:47:54.742262 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.636364 | |
| I0525 00:47:54.742274 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.134328 | |
| I0525 00:47:54.742287 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.95572 (* 1 = 3.95572 loss) | |
| I0525 00:47:54.742300 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.63339 (* 1 = 1.63339 loss) | |
| I0525 00:47:54.742314 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 4.03244 (* 0.0909091 = 0.366586 loss) | |
| I0525 00:47:54.742327 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.88254 (* 0.0909091 = 0.352959 loss) | |
| I0525 00:47:54.742341 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 4.2057 (* 0.0909091 = 0.382336 loss) | |
| I0525 00:47:54.742354 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.75199 (* 0.0909091 = 0.34109 loss) | |
| I0525 00:47:54.742367 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 3.51788 (* 0.0909091 = 0.319807 loss) | |
| I0525 00:47:54.742382 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 4.16721 (* 0.0909091 = 0.378837 loss) | |
| I0525 00:47:54.742394 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 4.01801 (* 0.0909091 = 0.365273 loss) | |
| I0525 00:47:54.742408 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 2.59122 (* 0.0909091 = 0.235566 loss) | |
| I0525 00:47:54.742422 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 1.37916 (* 0.0909091 = 0.125379 loss) | |
| I0525 00:47:54.742436 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 1.68781 (* 0.0909091 = 0.153437 loss) | |
| I0525 00:47:54.742449 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.878813 (* 0.0909091 = 0.0798921 loss) | |
| I0525 00:47:54.742463 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.97025 (* 0.0909091 = 0.0882046 loss) | |
| I0525 00:47:54.742477 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.779983 (* 0.0909091 = 0.0709075 loss) | |
| I0525 00:47:54.742491 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.959548 (* 0.0909091 = 0.0872317 loss) | |
| I0525 00:47:54.742504 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 1.01181 (* 0.0909091 = 0.0919831 loss) | |
| I0525 00:47:54.742517 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.999385 (* 0.0909091 = 0.0908532 loss) | |
| I0525 00:47:54.742532 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 1.2285 (* 0.0909091 = 0.111681 loss) | |
| I0525 00:47:54.742544 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 1.30267 (* 0.0909091 = 0.118424 loss) | |
| I0525 00:47:54.742558 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00785119 (* 0.0909091 = 0.000713744 loss) | |
| I0525 00:47:54.742573 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00550414 (* 0.0909091 = 0.000500376 loss) | |
| I0525 00:47:54.742585 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00578178 (* 0.0909091 = 0.000525616 loss) | |
| I0525 00:47:54.742599 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.00487508 (* 0.0909091 = 0.000443189 loss) | |
| I0525 00:47:54.742611 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 00:47:54.742624 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 00:47:54.742635 5272 solver.cpp:245] Train net output #149: total_confidence = 1.25812e-08 | |
| I0525 00:47:54.742655 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 0.00010585 | |
| I0525 00:47:54.742671 5272 sgd_solver.cpp:106] Iteration 3000, lr = 0.001 | |
| I0525 00:51:00.725512 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 33.8013 > 30) by scale factor 0.887541 | |
| I0525 00:54:19.569465 5272 solver.cpp:229] Iteration 3500, loss = 12.3235 | |
| I0525 00:54:19.569600 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.04 | |
| I0525 00:54:19.569631 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.25 | |
| I0525 00:54:19.569656 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0525 00:54:19.569679 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0525 00:54:19.569700 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.125 | |
| I0525 00:54:19.569723 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.125 | |
| I0525 00:54:19.569746 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.25 | |
| I0525 00:54:19.569771 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.5 | |
| I0525 00:54:19.569792 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.875 | |
| I0525 00:54:19.569815 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 0.875 | |
| I0525 00:54:19.569836 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 1 | |
| I0525 00:54:19.569857 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 00:54:19.569882 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 00:54:19.569905 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 00:54:19.569926 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 00:54:19.569947 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 00:54:19.569967 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 00:54:19.569989 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 00:54:19.570009 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 00:54:19.570029 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 00:54:19.570051 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 00:54:19.570072 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 00:54:19.570092 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 00:54:19.570112 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.727273 | |
| I0525 00:54:19.570133 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.06 | |
| I0525 00:54:19.570160 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 4.05289 (* 0.3 = 1.21587 loss) | |
| I0525 00:54:19.570186 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.30261 (* 0.3 = 0.390783 loss) | |
| I0525 00:54:19.570211 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.6169 (* 0.0272727 = 0.0986427 loss) | |
| I0525 00:54:19.570240 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 4.12462 (* 0.0272727 = 0.11249 loss) | |
| I0525 00:54:19.570269 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 4.2791 (* 0.0272727 = 0.116703 loss) | |
| I0525 00:54:19.570297 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.66772 (* 0.0272727 = 0.100029 loss) | |
| I0525 00:54:19.570322 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 3.93488 (* 0.0272727 = 0.107315 loss) | |
| I0525 00:54:19.570346 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 3.64059 (* 0.0272727 = 0.0992888 loss) | |
| I0525 00:54:19.570371 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 2.60979 (* 0.0272727 = 0.071176 loss) | |
| I0525 00:54:19.570397 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 0.766985 (* 0.0272727 = 0.0209178 loss) | |
| I0525 00:54:19.570423 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.686941 (* 0.0272727 = 0.0187348 loss) | |
| I0525 00:54:19.570451 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.174644 (* 0.0272727 = 0.00476303 loss) | |
| I0525 00:54:19.570477 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.128736 (* 0.0272727 = 0.00351097 loss) | |
| I0525 00:54:19.570502 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.0868422 (* 0.0272727 = 0.00236842 loss) | |
| I0525 00:54:19.570528 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.0528018 (* 0.0272727 = 0.00144005 loss) | |
| I0525 00:54:19.570577 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.0887583 (* 0.0272727 = 0.00242068 loss) | |
| I0525 00:54:19.570605 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0665068 (* 0.0272727 = 0.00181382 loss) | |
| I0525 00:54:19.570639 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.0624142 (* 0.0272727 = 0.0017022 loss) | |
| I0525 00:54:19.570667 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.0258059 (* 0.0272727 = 0.000703796 loss) | |
| I0525 00:54:19.570693 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0243421 (* 0.0272727 = 0.000663875 loss) | |
| I0525 00:54:19.570718 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.0162986 (* 0.0272727 = 0.000444507 loss) | |
| I0525 00:54:19.570744 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.0347205 (* 0.0272727 = 0.000946922 loss) | |
| I0525 00:54:19.570770 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.0296229 (* 0.0272727 = 0.000807897 loss) | |
| I0525 00:54:19.570794 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.0319445 (* 0.0272727 = 0.000871213 loss) | |
| I0525 00:54:19.570816 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.02 | |
| I0525 00:54:19.570838 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0.25 | |
| I0525 00:54:19.570859 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0 | |
| I0525 00:54:19.570879 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0.125 | |
| I0525 00:54:19.570897 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0 | |
| I0525 00:54:19.570914 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.125 | |
| I0525 00:54:19.570936 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.25 | |
| I0525 00:54:19.570958 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.5 | |
| I0525 00:54:19.570979 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.875 | |
| I0525 00:54:19.571001 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 0.875 | |
| I0525 00:54:19.571022 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 1 | |
| I0525 00:54:19.571043 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 00:54:19.571065 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 00:54:19.571085 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 00:54:19.571106 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 00:54:19.571126 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 00:54:19.571147 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 00:54:19.571167 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 00:54:19.571188 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 00:54:19.571208 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 00:54:19.571229 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 00:54:19.571250 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 00:54:19.571271 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 00:54:19.571291 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.721591 | |
| I0525 00:54:19.571312 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.08 | |
| I0525 00:54:19.571338 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 4.01737 (* 0.3 = 1.20521 loss) | |
| I0525 00:54:19.571363 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.31319 (* 0.3 = 0.393957 loss) | |
| I0525 00:54:19.571388 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.72539 (* 0.0272727 = 0.101601 loss) | |
| I0525 00:54:19.571413 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 3.90458 (* 0.0272727 = 0.106488 loss) | |
| I0525 00:54:19.571439 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 4.10439 (* 0.0272727 = 0.111938 loss) | |
| I0525 00:54:19.571481 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.39497 (* 0.0272727 = 0.0925902 loss) | |
| I0525 00:54:19.571507 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 3.85229 (* 0.0272727 = 0.105062 loss) | |
| I0525 00:54:19.571532 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 3.55364 (* 0.0272727 = 0.0969174 loss) | |
| I0525 00:54:19.571557 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 2.68186 (* 0.0272727 = 0.0731416 loss) | |
| I0525 00:54:19.571583 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 0.830551 (* 0.0272727 = 0.0226514 loss) | |
| I0525 00:54:19.571607 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.859805 (* 0.0272727 = 0.0234492 loss) | |
| I0525 00:54:19.571633 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.337482 (* 0.0272727 = 0.00920407 loss) | |
| I0525 00:54:19.571665 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.148599 (* 0.0272727 = 0.0040527 loss) | |
| I0525 00:54:19.571692 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.219055 (* 0.0272727 = 0.00597422 loss) | |
| I0525 00:54:19.571717 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.192707 (* 0.0272727 = 0.00525566 loss) | |
| I0525 00:54:19.571743 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.116718 (* 0.0272727 = 0.00318322 loss) | |
| I0525 00:54:19.571769 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.127619 (* 0.0272727 = 0.00348052 loss) | |
| I0525 00:54:19.571794 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.124627 (* 0.0272727 = 0.00339893 loss) | |
| I0525 00:54:19.571820 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.114652 (* 0.0272727 = 0.00312687 loss) | |
| I0525 00:54:19.571846 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.135244 (* 0.0272727 = 0.00368848 loss) | |
| I0525 00:54:19.571871 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.0786351 (* 0.0272727 = 0.00214459 loss) | |
| I0525 00:54:19.571897 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.0842862 (* 0.0272727 = 0.00229871 loss) | |
| I0525 00:54:19.571923 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.120936 (* 0.0272727 = 0.00329824 loss) | |
| I0525 00:54:19.571945 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.0646458 (* 0.0272727 = 0.00176307 loss) | |
| I0525 00:54:19.571970 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.06 | |
| I0525 00:54:19.571997 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.125 | |
| I0525 00:54:19.572021 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0 | |
| I0525 00:54:19.572041 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0 | |
| I0525 00:54:19.572062 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.125 | |
| I0525 00:54:19.572083 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.125 | |
| I0525 00:54:19.572104 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.25 | |
| I0525 00:54:19.572125 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.5 | |
| I0525 00:54:19.572146 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.875 | |
| I0525 00:54:19.572167 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 0.875 | |
| I0525 00:54:19.572187 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 1 | |
| I0525 00:54:19.572209 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 00:54:19.572229 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 00:54:19.572250 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 00:54:19.572271 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 00:54:19.572291 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 00:54:19.572312 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 00:54:19.572332 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 00:54:19.572371 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 00:54:19.572393 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 00:54:19.572414 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 00:54:19.572435 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 00:54:19.572455 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 00:54:19.572476 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.732955 | |
| I0525 00:54:19.572499 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.18 | |
| I0525 00:54:19.572525 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.81453 (* 1 = 3.81453 loss) | |
| I0525 00:54:19.572548 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.17502 (* 1 = 1.17502 loss) | |
| I0525 00:54:19.572573 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 3.54513 (* 0.0909091 = 0.322285 loss) | |
| I0525 00:54:19.572599 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 4.13379 (* 0.0909091 = 0.375799 loss) | |
| I0525 00:54:19.572624 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 4.02421 (* 0.0909091 = 0.365837 loss) | |
| I0525 00:54:19.572649 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.46215 (* 0.0909091 = 0.314741 loss) | |
| I0525 00:54:19.572675 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 3.68126 (* 0.0909091 = 0.33466 loss) | |
| I0525 00:54:19.572700 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 3.33668 (* 0.0909091 = 0.303335 loss) | |
| I0525 00:54:19.572734 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 2.37313 (* 0.0909091 = 0.215739 loss) | |
| I0525 00:54:19.572762 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.62296 (* 0.0909091 = 0.0566327 loss) | |
| I0525 00:54:19.572787 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.802836 (* 0.0909091 = 0.0729851 loss) | |
| I0525 00:54:19.572813 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.105153 (* 0.0909091 = 0.00955941 loss) | |
| I0525 00:54:19.572839 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.08439 (* 0.0909091 = 0.00767182 loss) | |
| I0525 00:54:19.572865 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.0541126 (* 0.0909091 = 0.00491933 loss) | |
| I0525 00:54:19.572890 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.0473339 (* 0.0909091 = 0.00430308 loss) | |
| I0525 00:54:19.572914 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.037998 (* 0.0909091 = 0.00345436 loss) | |
| I0525 00:54:19.572942 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.0308387 (* 0.0909091 = 0.00280352 loss) | |
| I0525 00:54:19.572967 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.0181048 (* 0.0909091 = 0.00164589 loss) | |
| I0525 00:54:19.572991 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.0133417 (* 0.0909091 = 0.00121288 loss) | |
| I0525 00:54:19.573017 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.00768539 (* 0.0909091 = 0.000698672 loss) | |
| I0525 00:54:19.573047 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00717772 (* 0.0909091 = 0.00065252 loss) | |
| I0525 00:54:19.573073 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00418342 (* 0.0909091 = 0.000380311 loss) | |
| I0525 00:54:19.573101 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00446216 (* 0.0909091 = 0.000405651 loss) | |
| I0525 00:54:19.573143 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.0033466 (* 0.0909091 = 0.000304236 loss) | |
| I0525 00:54:19.573170 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 00:54:19.573192 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 00:54:19.573213 5272 solver.cpp:245] Train net output #149: total_confidence = 1.8921e-06 | |
| I0525 00:54:19.573235 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 2.47078e-05 | |
| I0525 00:54:19.573276 5272 sgd_solver.cpp:106] Iteration 3500, lr = 0.001 | |
| I0525 01:00:44.207233 5272 solver.cpp:229] Iteration 4000, loss = 12.2027 | |
| I0525 01:00:44.207389 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0784314 | |
| I0525 01:00:44.207409 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.125 | |
| I0525 01:00:44.207422 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0525 01:00:44.207434 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0525 01:00:44.207447 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0 | |
| I0525 01:00:44.207458 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0 | |
| I0525 01:00:44.207470 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.375 | |
| I0525 01:00:44.207482 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.75 | |
| I0525 01:00:44.207494 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.75 | |
| I0525 01:00:44.207507 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 0.875 | |
| I0525 01:00:44.207520 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 0.875 | |
| I0525 01:00:44.207531 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 01:00:44.207543 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 01:00:44.207556 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 01:00:44.207567 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 01:00:44.207578 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 01:00:44.207590 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 01:00:44.207602 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 01:00:44.207613 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 01:00:44.207625 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 01:00:44.207638 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 01:00:44.207649 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 01:00:44.207660 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 01:00:44.207672 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.732955 | |
| I0525 01:00:44.207685 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.235294 | |
| I0525 01:00:44.207705 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.7898 (* 0.3 = 1.13694 loss) | |
| I0525 01:00:44.207720 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.40071 (* 0.3 = 0.420214 loss) | |
| I0525 01:00:44.207734 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.56248 (* 0.0272727 = 0.0971586 loss) | |
| I0525 01:00:44.207748 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 4.15332 (* 0.0272727 = 0.113272 loss) | |
| I0525 01:00:44.207762 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 4.1731 (* 0.0272727 = 0.113812 loss) | |
| I0525 01:00:44.207777 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 4.2464 (* 0.0272727 = 0.115811 loss) | |
| I0525 01:00:44.207790 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 4.54459 (* 0.0272727 = 0.123943 loss) | |
| I0525 01:00:44.207804 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 3.27699 (* 0.0272727 = 0.0893724 loss) | |
| I0525 01:00:44.207818 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 1.56313 (* 0.0272727 = 0.0426307 loss) | |
| I0525 01:00:44.207833 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 1.40193 (* 0.0272727 = 0.0382346 loss) | |
| I0525 01:00:44.207846 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.924763 (* 0.0272727 = 0.0252208 loss) | |
| I0525 01:00:44.207860 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.940588 (* 0.0272727 = 0.0256524 loss) | |
| I0525 01:00:44.207875 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.113318 (* 0.0272727 = 0.0030905 loss) | |
| I0525 01:00:44.207890 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.0450705 (* 0.0272727 = 0.0012292 loss) | |
| I0525 01:00:44.207904 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.027961 (* 0.0272727 = 0.000762574 loss) | |
| I0525 01:00:44.207940 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.0386235 (* 0.0272727 = 0.00105337 loss) | |
| I0525 01:00:44.207955 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0196546 (* 0.0272727 = 0.000536034 loss) | |
| I0525 01:00:44.207969 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.0193924 (* 0.0272727 = 0.000528883 loss) | |
| I0525 01:00:44.207984 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.0110779 (* 0.0272727 = 0.000302125 loss) | |
| I0525 01:00:44.207998 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0192586 (* 0.0272727 = 0.000525235 loss) | |
| I0525 01:00:44.208012 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.0179756 (* 0.0272727 = 0.000490245 loss) | |
| I0525 01:00:44.208026 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.00727792 (* 0.0272727 = 0.000198489 loss) | |
| I0525 01:00:44.208040 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.00470918 (* 0.0272727 = 0.000128432 loss) | |
| I0525 01:00:44.208055 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.0066181 (* 0.0272727 = 0.000180494 loss) | |
| I0525 01:00:44.208067 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.0588235 | |
| I0525 01:00:44.208079 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0 | |
| I0525 01:00:44.208091 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0.125 | |
| I0525 01:00:44.208103 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0 | |
| I0525 01:00:44.208115 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0 | |
| I0525 01:00:44.208127 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0 | |
| I0525 01:00:44.208138 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.375 | |
| I0525 01:00:44.208149 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.75 | |
| I0525 01:00:44.208161 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.75 | |
| I0525 01:00:44.208173 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 0.875 | |
| I0525 01:00:44.208186 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 0.875 | |
| I0525 01:00:44.208199 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 01:00:44.208209 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 01:00:44.208221 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 01:00:44.208233 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 01:00:44.208245 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 01:00:44.208256 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 01:00:44.208267 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 01:00:44.208278 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 01:00:44.208289 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 01:00:44.208300 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 01:00:44.208312 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 01:00:44.208324 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 01:00:44.208335 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.721591 | |
| I0525 01:00:44.208348 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.0980392 | |
| I0525 01:00:44.208361 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.72966 (* 0.3 = 1.1189 loss) | |
| I0525 01:00:44.208375 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.41466 (* 0.3 = 0.424399 loss) | |
| I0525 01:00:44.208392 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.97659 (* 0.0272727 = 0.108452 loss) | |
| I0525 01:00:44.208406 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 3.44373 (* 0.0272727 = 0.09392 loss) | |
| I0525 01:00:44.208432 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 4.38585 (* 0.0272727 = 0.119614 loss) | |
| I0525 01:00:44.208446 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.97046 (* 0.0272727 = 0.108285 loss) | |
| I0525 01:00:44.208461 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 4.13731 (* 0.0272727 = 0.112836 loss) | |
| I0525 01:00:44.208474 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 3.48074 (* 0.0272727 = 0.0949293 loss) | |
| I0525 01:00:44.208488 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 1.64627 (* 0.0272727 = 0.0448984 loss) | |
| I0525 01:00:44.208501 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 1.62735 (* 0.0272727 = 0.0443823 loss) | |
| I0525 01:00:44.208515 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.684521 (* 0.0272727 = 0.0186688 loss) | |
| I0525 01:00:44.208529 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 1.07091 (* 0.0272727 = 0.0292067 loss) | |
| I0525 01:00:44.208544 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.103075 (* 0.0272727 = 0.00281115 loss) | |
| I0525 01:00:44.208559 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.0655288 (* 0.0272727 = 0.00178715 loss) | |
| I0525 01:00:44.208572 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.0295464 (* 0.0272727 = 0.000805811 loss) | |
| I0525 01:00:44.208586 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.0470807 (* 0.0272727 = 0.00128402 loss) | |
| I0525 01:00:44.208600 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.0281291 (* 0.0272727 = 0.000767158 loss) | |
| I0525 01:00:44.208616 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.0386638 (* 0.0272727 = 0.00105447 loss) | |
| I0525 01:00:44.208629 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.0501453 (* 0.0272727 = 0.0013676 loss) | |
| I0525 01:00:44.208644 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.0227461 (* 0.0272727 = 0.000620349 loss) | |
| I0525 01:00:44.208658 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.0133243 (* 0.0272727 = 0.000363389 loss) | |
| I0525 01:00:44.208673 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.0135677 (* 0.0272727 = 0.000370029 loss) | |
| I0525 01:00:44.208685 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.0372969 (* 0.0272727 = 0.00101719 loss) | |
| I0525 01:00:44.208699 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.0168166 (* 0.0272727 = 0.000458634 loss) | |
| I0525 01:00:44.208712 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.0392157 | |
| I0525 01:00:44.208724 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.125 | |
| I0525 01:00:44.208735 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0.125 | |
| I0525 01:00:44.208750 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0 | |
| I0525 01:00:44.208762 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.125 | |
| I0525 01:00:44.208775 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0 | |
| I0525 01:00:44.208783 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.375 | |
| I0525 01:00:44.208791 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.75 | |
| I0525 01:00:44.208798 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.75 | |
| I0525 01:00:44.208811 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 0.875 | |
| I0525 01:00:44.208822 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 0.875 | |
| I0525 01:00:44.208834 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 01:00:44.208847 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 01:00:44.208858 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 01:00:44.208868 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 01:00:44.208879 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 01:00:44.208891 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 01:00:44.208912 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 01:00:44.208925 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 01:00:44.208937 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 01:00:44.208950 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 01:00:44.208961 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 01:00:44.208972 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 01:00:44.208983 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.704545 | |
| I0525 01:00:44.208997 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.0980392 | |
| I0525 01:00:44.209010 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.61695 (* 1 = 3.61695 loss) | |
| I0525 01:00:44.209023 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.46096 (* 1 = 1.46096 loss) | |
| I0525 01:00:44.209038 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 3.31787 (* 0.0909091 = 0.301625 loss) | |
| I0525 01:00:44.209051 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.79495 (* 0.0909091 = 0.344995 loss) | |
| I0525 01:00:44.209064 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.81922 (* 0.0909091 = 0.347202 loss) | |
| I0525 01:00:44.209079 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.78443 (* 0.0909091 = 0.344039 loss) | |
| I0525 01:00:44.209092 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 4.17981 (* 0.0909091 = 0.379983 loss) | |
| I0525 01:00:44.209105 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 3.38597 (* 0.0909091 = 0.307816 loss) | |
| I0525 01:00:44.209133 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 1.61152 (* 0.0909091 = 0.146502 loss) | |
| I0525 01:00:44.209151 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 1.03527 (* 0.0909091 = 0.0941153 loss) | |
| I0525 01:00:44.209164 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.832669 (* 0.0909091 = 0.0756972 loss) | |
| I0525 01:00:44.209177 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.91665 (* 0.0909091 = 0.0833318 loss) | |
| I0525 01:00:44.209192 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.102732 (* 0.0909091 = 0.00933928 loss) | |
| I0525 01:00:44.209206 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.119427 (* 0.0909091 = 0.010857 loss) | |
| I0525 01:00:44.209219 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.0545666 (* 0.0909091 = 0.0049606 loss) | |
| I0525 01:00:44.209233 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.0432863 (* 0.0909091 = 0.00393512 loss) | |
| I0525 01:00:44.209247 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.0279589 (* 0.0909091 = 0.00254171 loss) | |
| I0525 01:00:44.209261 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.0160858 (* 0.0909091 = 0.00146235 loss) | |
| I0525 01:00:44.209275 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.00682722 (* 0.0909091 = 0.000620656 loss) | |
| I0525 01:00:44.209288 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.0033138 (* 0.0909091 = 0.000301255 loss) | |
| I0525 01:00:44.209303 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00289934 (* 0.0909091 = 0.000263576 loss) | |
| I0525 01:00:44.209317 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00295362 (* 0.0909091 = 0.000268511 loss) | |
| I0525 01:00:44.209331 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00258164 (* 0.0909091 = 0.000234694 loss) | |
| I0525 01:00:44.209345 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.00228437 (* 0.0909091 = 0.00020767 loss) | |
| I0525 01:00:44.209358 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 01:00:44.209369 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 01:00:44.209381 5272 solver.cpp:245] Train net output #149: total_confidence = 4.48232e-09 | |
| I0525 01:00:44.209403 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 4.0606e-07 | |
| I0525 01:00:44.209419 5272 sgd_solver.cpp:106] Iteration 4000, lr = 0.001 | |
| I0525 01:06:38.358430 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 35.2945 > 30) by scale factor 0.84999 | |
| I0525 01:06:41.443186 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 40.4866 > 30) by scale factor 0.740985 | |
| I0525 01:07:08.783363 5272 solver.cpp:229] Iteration 4500, loss = 11.9827 | |
| I0525 01:07:08.783520 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0208333 | |
| I0525 01:07:08.783541 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0 | |
| I0525 01:07:08.783555 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0525 01:07:08.783566 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0525 01:07:08.783578 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0 | |
| I0525 01:07:08.783591 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.375 | |
| I0525 01:07:08.783602 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.625 | |
| I0525 01:07:08.783615 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.75 | |
| I0525 01:07:08.783627 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.875 | |
| I0525 01:07:08.783641 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 0.875 | |
| I0525 01:07:08.783653 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 0.875 | |
| I0525 01:07:08.783665 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 0.875 | |
| I0525 01:07:08.783677 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 0.875 | |
| I0525 01:07:08.783690 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 0.875 | |
| I0525 01:07:08.783702 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 0.875 | |
| I0525 01:07:08.783715 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 01:07:08.783726 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 01:07:08.783738 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 01:07:08.783751 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 01:07:08.783762 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 01:07:08.783774 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 01:07:08.783787 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 01:07:08.783798 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 01:07:08.783809 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.715909 | |
| I0525 01:07:08.783821 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.125 | |
| I0525 01:07:08.783838 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.79793 (* 0.3 = 1.13938 loss) | |
| I0525 01:07:08.783852 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.27764 (* 0.3 = 0.383293 loss) | |
| I0525 01:07:08.783867 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 4.29758 (* 0.0272727 = 0.117207 loss) | |
| I0525 01:07:08.783885 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 4.08246 (* 0.0272727 = 0.11134 loss) | |
| I0525 01:07:08.783900 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.77282 (* 0.0272727 = 0.102895 loss) | |
| I0525 01:07:08.783913 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.5288 (* 0.0272727 = 0.09624 loss) | |
| I0525 01:07:08.783928 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 3.54183 (* 0.0272727 = 0.0965954 loss) | |
| I0525 01:07:08.783942 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 2.30282 (* 0.0272727 = 0.0628042 loss) | |
| I0525 01:07:08.783957 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 1.62065 (* 0.0272727 = 0.0441996 loss) | |
| I0525 01:07:08.783970 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 1.01805 (* 0.0272727 = 0.027765 loss) | |
| I0525 01:07:08.783984 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.969495 (* 0.0272727 = 0.0264408 loss) | |
| I0525 01:07:08.783998 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 1.06902 (* 0.0272727 = 0.029155 loss) | |
| I0525 01:07:08.784013 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 1.04953 (* 0.0272727 = 0.0286235 loss) | |
| I0525 01:07:08.784026 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 1.37767 (* 0.0272727 = 0.0375727 loss) | |
| I0525 01:07:08.784041 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 1.28079 (* 0.0272727 = 0.0349306 loss) | |
| I0525 01:07:08.784077 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 1.14559 (* 0.0272727 = 0.0312433 loss) | |
| I0525 01:07:08.784093 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0276929 (* 0.0272727 = 0.00075526 loss) | |
| I0525 01:07:08.784107 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.0252679 (* 0.0272727 = 0.000689125 loss) | |
| I0525 01:07:08.784122 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.0147689 (* 0.0272727 = 0.000402788 loss) | |
| I0525 01:07:08.784137 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0118867 (* 0.0272727 = 0.000324184 loss) | |
| I0525 01:07:08.784150 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.0108161 (* 0.0272727 = 0.000294985 loss) | |
| I0525 01:07:08.784164 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.0129691 (* 0.0272727 = 0.000353704 loss) | |
| I0525 01:07:08.784178 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.0119833 (* 0.0272727 = 0.000326817 loss) | |
| I0525 01:07:08.784193 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.0096225 (* 0.0272727 = 0.000262432 loss) | |
| I0525 01:07:08.784205 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0 | |
| I0525 01:07:08.784217 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0 | |
| I0525 01:07:08.784229 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0 | |
| I0525 01:07:08.784240 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0 | |
| I0525 01:07:08.784251 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0 | |
| I0525 01:07:08.784263 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.25 | |
| I0525 01:07:08.784276 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.625 | |
| I0525 01:07:08.784287 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.75 | |
| I0525 01:07:08.784301 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.875 | |
| I0525 01:07:08.784312 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 0.875 | |
| I0525 01:07:08.784324 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 0.875 | |
| I0525 01:07:08.784337 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 0.875 | |
| I0525 01:07:08.784348 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 0.875 | |
| I0525 01:07:08.784360 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 0.875 | |
| I0525 01:07:08.784373 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 0.875 | |
| I0525 01:07:08.784384 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 01:07:08.784395 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 01:07:08.784407 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 01:07:08.784418 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 01:07:08.784430 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 01:07:08.784441 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 01:07:08.784453 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 01:07:08.784464 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 01:07:08.784476 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.710227 | |
| I0525 01:07:08.784487 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.0625 | |
| I0525 01:07:08.784502 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 4.05831 (* 0.3 = 1.21749 loss) | |
| I0525 01:07:08.784515 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.32194 (* 0.3 = 0.396583 loss) | |
| I0525 01:07:08.784533 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 4.29454 (* 0.0272727 = 0.117124 loss) | |
| I0525 01:07:08.784548 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 4.29894 (* 0.0272727 = 0.117244 loss) | |
| I0525 01:07:08.784571 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.75448 (* 0.0272727 = 0.102395 loss) | |
| I0525 01:07:08.784586 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.9861 (* 0.0272727 = 0.108712 loss) | |
| I0525 01:07:08.784600 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 3.36769 (* 0.0272727 = 0.0918461 loss) | |
| I0525 01:07:08.784615 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 2.19088 (* 0.0272727 = 0.0597512 loss) | |
| I0525 01:07:08.784628 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 1.56729 (* 0.0272727 = 0.0427443 loss) | |
| I0525 01:07:08.784642 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 0.960175 (* 0.0272727 = 0.0261866 loss) | |
| I0525 01:07:08.784657 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.918177 (* 0.0272727 = 0.0250412 loss) | |
| I0525 01:07:08.784670 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.955058 (* 0.0272727 = 0.026047 loss) | |
| I0525 01:07:08.784684 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.794209 (* 0.0272727 = 0.0216602 loss) | |
| I0525 01:07:08.784698 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 1.16649 (* 0.0272727 = 0.0318134 loss) | |
| I0525 01:07:08.784713 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.886968 (* 0.0272727 = 0.02419 loss) | |
| I0525 01:07:08.784726 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.82919 (* 0.0272727 = 0.0226143 loss) | |
| I0525 01:07:08.784740 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.062004 (* 0.0272727 = 0.00169102 loss) | |
| I0525 01:07:08.784754 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.0467766 (* 0.0272727 = 0.00127573 loss) | |
| I0525 01:07:08.784768 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.0457334 (* 0.0272727 = 0.00124728 loss) | |
| I0525 01:07:08.784782 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.0400594 (* 0.0272727 = 0.00109253 loss) | |
| I0525 01:07:08.784796 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.0234523 (* 0.0272727 = 0.000639608 loss) | |
| I0525 01:07:08.784811 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.0289231 (* 0.0272727 = 0.000788811 loss) | |
| I0525 01:07:08.784824 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.0274025 (* 0.0272727 = 0.000747342 loss) | |
| I0525 01:07:08.784837 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.0184842 (* 0.0272727 = 0.000504115 loss) | |
| I0525 01:07:08.784850 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0 | |
| I0525 01:07:08.784862 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.125 | |
| I0525 01:07:08.784873 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0 | |
| I0525 01:07:08.784885 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0 | |
| I0525 01:07:08.784898 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.125 | |
| I0525 01:07:08.784905 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.375 | |
| I0525 01:07:08.784914 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.625 | |
| I0525 01:07:08.784929 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.75 | |
| I0525 01:07:08.784941 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.875 | |
| I0525 01:07:08.784952 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 0.875 | |
| I0525 01:07:08.784965 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 0.875 | |
| I0525 01:07:08.784976 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 0.875 | |
| I0525 01:07:08.784988 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 0.875 | |
| I0525 01:07:08.784999 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 0.875 | |
| I0525 01:07:08.785012 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 0.875 | |
| I0525 01:07:08.785022 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 01:07:08.785034 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 01:07:08.785055 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 01:07:08.785068 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 01:07:08.785080 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 01:07:08.785092 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 01:07:08.785104 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 01:07:08.785115 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 01:07:08.785145 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.721591 | |
| I0525 01:07:08.785157 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.166667 | |
| I0525 01:07:08.785171 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 4.1799 (* 1 = 4.1799 loss) | |
| I0525 01:07:08.785186 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.36976 (* 1 = 1.36976 loss) | |
| I0525 01:07:08.785199 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 3.91394 (* 0.0909091 = 0.355813 loss) | |
| I0525 01:07:08.785213 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 4.01526 (* 0.0909091 = 0.365023 loss) | |
| I0525 01:07:08.785228 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.741 (* 0.0909091 = 0.340091 loss) | |
| I0525 01:07:08.785241 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.64358 (* 0.0909091 = 0.331235 loss) | |
| I0525 01:07:08.785254 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 3.03765 (* 0.0909091 = 0.27615 loss) | |
| I0525 01:07:08.785269 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 2.14734 (* 0.0909091 = 0.195213 loss) | |
| I0525 01:07:08.785281 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 1.51079 (* 0.0909091 = 0.137344 loss) | |
| I0525 01:07:08.785295 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.791434 (* 0.0909091 = 0.0719486 loss) | |
| I0525 01:07:08.785310 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.786366 (* 0.0909091 = 0.0714878 loss) | |
| I0525 01:07:08.785322 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.743416 (* 0.0909091 = 0.0675832 loss) | |
| I0525 01:07:08.785336 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.654977 (* 0.0909091 = 0.0595433 loss) | |
| I0525 01:07:08.785351 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.754803 (* 0.0909091 = 0.0686185 loss) | |
| I0525 01:07:08.785363 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.669805 (* 0.0909091 = 0.0608913 loss) | |
| I0525 01:07:08.785377 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.810451 (* 0.0909091 = 0.0736774 loss) | |
| I0525 01:07:08.785392 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.0349501 (* 0.0909091 = 0.00317728 loss) | |
| I0525 01:07:08.785405 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.0340422 (* 0.0909091 = 0.00309475 loss) | |
| I0525 01:07:08.785419 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.00880054 (* 0.0909091 = 0.000800049 loss) | |
| I0525 01:07:08.785434 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.00378561 (* 0.0909091 = 0.000344146 loss) | |
| I0525 01:07:08.785447 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00396021 (* 0.0909091 = 0.000360019 loss) | |
| I0525 01:07:08.785461 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00263642 (* 0.0909091 = 0.000239674 loss) | |
| I0525 01:07:08.785475 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00161738 (* 0.0909091 = 0.000147034 loss) | |
| I0525 01:07:08.785490 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.001406 (* 0.0909091 = 0.000127818 loss) | |
| I0525 01:07:08.785502 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 01:07:08.785514 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 01:07:08.785526 5272 solver.cpp:245] Train net output #149: total_confidence = 1.35591e-07 | |
| I0525 01:07:08.785548 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 9.73293e-05 | |
| I0525 01:07:08.785562 5272 sgd_solver.cpp:106] Iteration 4500, lr = 0.001 | |
| I0525 01:10:03.713016 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 31.763 > 30) by scale factor 0.944494 | |
| I0525 01:11:50.603463 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 44.0353 > 30) by scale factor 0.681272 | |
| I0525 01:13:32.853703 5272 solver.cpp:338] Iteration 5000, Testing net (#0) | |
| I0525 01:14:31.196054 5272 solver.cpp:393] Test loss: 10.8951 | |
| I0525 01:14:31.196226 5272 solver.cpp:406] Test net output #0: loss1/accuracy = 0.0407952 | |
| I0525 01:14:31.196247 5272 solver.cpp:406] Test net output #1: loss1/accuracy01 = 0.091 | |
| I0525 01:14:31.196260 5272 solver.cpp:406] Test net output #2: loss1/accuracy02 = 0.06 | |
| I0525 01:14:31.196274 5272 solver.cpp:406] Test net output #3: loss1/accuracy03 = 0.043 | |
| I0525 01:14:31.196285 5272 solver.cpp:406] Test net output #4: loss1/accuracy04 = 0.139 | |
| I0525 01:14:31.196296 5272 solver.cpp:406] Test net output #5: loss1/accuracy05 = 0.298 | |
| I0525 01:14:31.196308 5272 solver.cpp:406] Test net output #6: loss1/accuracy06 = 0.472 | |
| I0525 01:14:31.196319 5272 solver.cpp:406] Test net output #7: loss1/accuracy07 = 0.741 | |
| I0525 01:14:31.196331 5272 solver.cpp:406] Test net output #8: loss1/accuracy08 = 0.922 | |
| I0525 01:14:31.196343 5272 solver.cpp:406] Test net output #9: loss1/accuracy09 = 0.984 | |
| I0525 01:14:31.196355 5272 solver.cpp:406] Test net output #10: loss1/accuracy10 = 0.994 | |
| I0525 01:14:31.196367 5272 solver.cpp:406] Test net output #11: loss1/accuracy11 = 1 | |
| I0525 01:14:31.196378 5272 solver.cpp:406] Test net output #12: loss1/accuracy12 = 1 | |
| I0525 01:14:31.196389 5272 solver.cpp:406] Test net output #13: loss1/accuracy13 = 1 | |
| I0525 01:14:31.196400 5272 solver.cpp:406] Test net output #14: loss1/accuracy14 = 1 | |
| I0525 01:14:31.196411 5272 solver.cpp:406] Test net output #15: loss1/accuracy15 = 1 | |
| I0525 01:14:31.196422 5272 solver.cpp:406] Test net output #16: loss1/accuracy16 = 1 | |
| I0525 01:14:31.196434 5272 solver.cpp:406] Test net output #17: loss1/accuracy17 = 1 | |
| I0525 01:14:31.196444 5272 solver.cpp:406] Test net output #18: loss1/accuracy18 = 1 | |
| I0525 01:14:31.196455 5272 solver.cpp:406] Test net output #19: loss1/accuracy19 = 1 | |
| I0525 01:14:31.196467 5272 solver.cpp:406] Test net output #20: loss1/accuracy20 = 1 | |
| I0525 01:14:31.196478 5272 solver.cpp:406] Test net output #21: loss1/accuracy21 = 1 | |
| I0525 01:14:31.196490 5272 solver.cpp:406] Test net output #22: loss1/accuracy22 = 1 | |
| I0525 01:14:31.196501 5272 solver.cpp:406] Test net output #23: loss1/accuracy_incl_empty = 0.76091 | |
| I0525 01:14:31.196512 5272 solver.cpp:406] Test net output #24: loss1/accuracy_top3 = 0.162901 | |
| I0525 01:14:31.196528 5272 solver.cpp:406] Test net output #25: loss1/cross_entropy_loss = 4.18336 (* 0.3 = 1.25501 loss) | |
| I0525 01:14:31.196542 5272 solver.cpp:406] Test net output #26: loss1/cross_entropy_loss_incl_empty = 1.08137 (* 0.3 = 0.324412 loss) | |
| I0525 01:14:31.196557 5272 solver.cpp:406] Test net output #27: loss1/loss01 = 3.50257 (* 0.0272727 = 0.0955248 loss) | |
| I0525 01:14:31.196570 5272 solver.cpp:406] Test net output #28: loss1/loss02 = 3.61815 (* 0.0272727 = 0.0986768 loss) | |
| I0525 01:14:31.196584 5272 solver.cpp:406] Test net output #29: loss1/loss03 = 3.67538 (* 0.0272727 = 0.100238 loss) | |
| I0525 01:14:31.196599 5272 solver.cpp:406] Test net output #30: loss1/loss04 = 3.5151 (* 0.0272727 = 0.0958663 loss) | |
| I0525 01:14:31.196611 5272 solver.cpp:406] Test net output #31: loss1/loss05 = 3.03892 (* 0.0272727 = 0.0828796 loss) | |
| I0525 01:14:31.196629 5272 solver.cpp:406] Test net output #32: loss1/loss06 = 2.51562 (* 0.0272727 = 0.0686077 loss) | |
| I0525 01:14:31.196642 5272 solver.cpp:406] Test net output #33: loss1/loss07 = 1.48975 (* 0.0272727 = 0.0406296 loss) | |
| I0525 01:14:31.196655 5272 solver.cpp:406] Test net output #34: loss1/loss08 = 0.581248 (* 0.0272727 = 0.0158522 loss) | |
| I0525 01:14:31.196669 5272 solver.cpp:406] Test net output #35: loss1/loss09 = 0.170956 (* 0.0272727 = 0.00466244 loss) | |
| I0525 01:14:31.196683 5272 solver.cpp:406] Test net output #36: loss1/loss10 = 0.103576 (* 0.0272727 = 0.00282481 loss) | |
| I0525 01:14:31.196696 5272 solver.cpp:406] Test net output #37: loss1/loss11 = 0.0561049 (* 0.0272727 = 0.00153013 loss) | |
| I0525 01:14:31.196710 5272 solver.cpp:406] Test net output #38: loss1/loss12 = 0.0401162 (* 0.0272727 = 0.00109408 loss) | |
| I0525 01:14:31.196723 5272 solver.cpp:406] Test net output #39: loss1/loss13 = 0.0430491 (* 0.0272727 = 0.00117407 loss) | |
| I0525 01:14:31.196750 5272 solver.cpp:406] Test net output #40: loss1/loss14 = 0.0316757 (* 0.0272727 = 0.000863884 loss) | |
| I0525 01:14:31.196765 5272 solver.cpp:406] Test net output #41: loss1/loss15 = 0.026732 (* 0.0272727 = 0.000729054 loss) | |
| I0525 01:14:31.196779 5272 solver.cpp:406] Test net output #42: loss1/loss16 = 0.020205 (* 0.0272727 = 0.000551045 loss) | |
| I0525 01:14:31.196792 5272 solver.cpp:406] Test net output #43: loss1/loss17 = 0.0142663 (* 0.0272727 = 0.000389082 loss) | |
| I0525 01:14:31.196806 5272 solver.cpp:406] Test net output #44: loss1/loss18 = 0.0140777 (* 0.0272727 = 0.000383936 loss) | |
| I0525 01:14:31.196820 5272 solver.cpp:406] Test net output #45: loss1/loss19 = 0.0128235 (* 0.0272727 = 0.000349732 loss) | |
| I0525 01:14:31.196833 5272 solver.cpp:406] Test net output #46: loss1/loss20 = 0.0143742 (* 0.0272727 = 0.000392025 loss) | |
| I0525 01:14:31.196847 5272 solver.cpp:406] Test net output #47: loss1/loss21 = 0.014323 (* 0.0272727 = 0.000390627 loss) | |
| I0525 01:14:31.196861 5272 solver.cpp:406] Test net output #48: loss1/loss22 = 0.0134079 (* 0.0272727 = 0.000365669 loss) | |
| I0525 01:14:31.196872 5272 solver.cpp:406] Test net output #49: loss2/accuracy = 0.0392413 | |
| I0525 01:14:31.196884 5272 solver.cpp:406] Test net output #50: loss2/accuracy01 = 0.095 | |
| I0525 01:14:31.196897 5272 solver.cpp:406] Test net output #51: loss2/accuracy02 = 0.057 | |
| I0525 01:14:31.196907 5272 solver.cpp:406] Test net output #52: loss2/accuracy03 = 0.058 | |
| I0525 01:14:31.196918 5272 solver.cpp:406] Test net output #53: loss2/accuracy04 = 0.134 | |
| I0525 01:14:31.196933 5272 solver.cpp:406] Test net output #54: loss2/accuracy05 = 0.298 | |
| I0525 01:14:31.196944 5272 solver.cpp:406] Test net output #55: loss2/accuracy06 = 0.472 | |
| I0525 01:14:31.196956 5272 solver.cpp:406] Test net output #56: loss2/accuracy07 = 0.741 | |
| I0525 01:14:31.196967 5272 solver.cpp:406] Test net output #57: loss2/accuracy08 = 0.922 | |
| I0525 01:14:31.196979 5272 solver.cpp:406] Test net output #58: loss2/accuracy09 = 0.984 | |
| I0525 01:14:31.196990 5272 solver.cpp:406] Test net output #59: loss2/accuracy10 = 0.994 | |
| I0525 01:14:31.197001 5272 solver.cpp:406] Test net output #60: loss2/accuracy11 = 1 | |
| I0525 01:14:31.197012 5272 solver.cpp:406] Test net output #61: loss2/accuracy12 = 1 | |
| I0525 01:14:31.197024 5272 solver.cpp:406] Test net output #62: loss2/accuracy13 = 1 | |
| I0525 01:14:31.197036 5272 solver.cpp:406] Test net output #63: loss2/accuracy14 = 1 | |
| I0525 01:14:31.197046 5272 solver.cpp:406] Test net output #64: loss2/accuracy15 = 1 | |
| I0525 01:14:31.197057 5272 solver.cpp:406] Test net output #65: loss2/accuracy16 = 1 | |
| I0525 01:14:31.197068 5272 solver.cpp:406] Test net output #66: loss2/accuracy17 = 1 | |
| I0525 01:14:31.197079 5272 solver.cpp:406] Test net output #67: loss2/accuracy18 = 1 | |
| I0525 01:14:31.197090 5272 solver.cpp:406] Test net output #68: loss2/accuracy19 = 1 | |
| I0525 01:14:31.197101 5272 solver.cpp:406] Test net output #69: loss2/accuracy20 = 1 | |
| I0525 01:14:31.197113 5272 solver.cpp:406] Test net output #70: loss2/accuracy21 = 1 | |
| I0525 01:14:31.197136 5272 solver.cpp:406] Test net output #71: loss2/accuracy22 = 1 | |
| I0525 01:14:31.197149 5272 solver.cpp:406] Test net output #72: loss2/accuracy_incl_empty = 0.760728 | |
| I0525 01:14:31.197161 5272 solver.cpp:406] Test net output #73: loss2/accuracy_top3 = 0.156201 | |
| I0525 01:14:31.197175 5272 solver.cpp:406] Test net output #74: loss2/cross_entropy_loss = 4.24936 (* 0.3 = 1.27481 loss) | |
| I0525 01:14:31.197190 5272 solver.cpp:406] Test net output #75: loss2/cross_entropy_loss_incl_empty = 1.09876 (* 0.3 = 0.329628 loss) | |
| I0525 01:14:31.197202 5272 solver.cpp:406] Test net output #76: loss2/loss01 = 3.52398 (* 0.0272727 = 0.0961086 loss) | |
| I0525 01:14:31.197216 5272 solver.cpp:406] Test net output #77: loss2/loss02 = 3.62354 (* 0.0272727 = 0.0988237 loss) | |
| I0525 01:14:31.197229 5272 solver.cpp:406] Test net output #78: loss2/loss03 = 3.65058 (* 0.0272727 = 0.0995613 loss) | |
| I0525 01:14:31.197254 5272 solver.cpp:406] Test net output #79: loss2/loss04 = 3.51706 (* 0.0272727 = 0.0959199 loss) | |
| I0525 01:14:31.197268 5272 solver.cpp:406] Test net output #80: loss2/loss05 = 3.05321 (* 0.0272727 = 0.0832693 loss) | |
| I0525 01:14:31.197283 5272 solver.cpp:406] Test net output #81: loss2/loss06 = 2.54011 (* 0.0272727 = 0.0692758 loss) | |
| I0525 01:14:31.197295 5272 solver.cpp:406] Test net output #82: loss2/loss07 = 1.51205 (* 0.0272727 = 0.0412376 loss) | |
| I0525 01:14:31.197309 5272 solver.cpp:406] Test net output #83: loss2/loss08 = 0.585978 (* 0.0272727 = 0.0159812 loss) | |
| I0525 01:14:31.197337 5272 solver.cpp:406] Test net output #84: loss2/loss09 = 0.176286 (* 0.0272727 = 0.00480779 loss) | |
| I0525 01:14:31.197352 5272 solver.cpp:406] Test net output #85: loss2/loss10 = 0.106274 (* 0.0272727 = 0.00289838 loss) | |
| I0525 01:14:31.197366 5272 solver.cpp:406] Test net output #86: loss2/loss11 = 0.0574618 (* 0.0272727 = 0.00156714 loss) | |
| I0525 01:14:31.197381 5272 solver.cpp:406] Test net output #87: loss2/loss12 = 0.0483056 (* 0.0272727 = 0.00131743 loss) | |
| I0525 01:14:31.197394 5272 solver.cpp:406] Test net output #88: loss2/loss13 = 0.0378245 (* 0.0272727 = 0.00103158 loss) | |
| I0525 01:14:31.197407 5272 solver.cpp:406] Test net output #89: loss2/loss14 = 0.0309816 (* 0.0272727 = 0.000844952 loss) | |
| I0525 01:14:31.197422 5272 solver.cpp:406] Test net output #90: loss2/loss15 = 0.03057 (* 0.0272727 = 0.000833727 loss) | |
| I0525 01:14:31.197434 5272 solver.cpp:406] Test net output #91: loss2/loss16 = 0.0270264 (* 0.0272727 = 0.000737084 loss) | |
| I0525 01:14:31.197448 5272 solver.cpp:406] Test net output #92: loss2/loss17 = 0.0206887 (* 0.0272727 = 0.000564238 loss) | |
| I0525 01:14:31.197461 5272 solver.cpp:406] Test net output #93: loss2/loss18 = 0.0206279 (* 0.0272727 = 0.00056258 loss) | |
| I0525 01:14:31.197475 5272 solver.cpp:406] Test net output #94: loss2/loss19 = 0.0137704 (* 0.0272727 = 0.000375556 loss) | |
| I0525 01:14:31.197489 5272 solver.cpp:406] Test net output #95: loss2/loss20 = 0.0170247 (* 0.0272727 = 0.00046431 loss) | |
| I0525 01:14:31.197502 5272 solver.cpp:406] Test net output #96: loss2/loss21 = 0.0130431 (* 0.0272727 = 0.000355722 loss) | |
| I0525 01:14:31.197516 5272 solver.cpp:406] Test net output #97: loss2/loss22 = 0.0137607 (* 0.0272727 = 0.000375293 loss) | |
| I0525 01:14:31.197527 5272 solver.cpp:406] Test net output #98: loss3/accuracy = 0.0611627 | |
| I0525 01:14:31.197540 5272 solver.cpp:406] Test net output #99: loss3/accuracy01 = 0.097 | |
| I0525 01:14:31.197551 5272 solver.cpp:406] Test net output #100: loss3/accuracy02 = 0.082 | |
| I0525 01:14:31.197561 5272 solver.cpp:406] Test net output #101: loss3/accuracy03 = 0.064 | |
| I0525 01:14:31.197573 5272 solver.cpp:406] Test net output #102: loss3/accuracy04 = 0.147 | |
| I0525 01:14:31.197584 5272 solver.cpp:406] Test net output #103: loss3/accuracy05 = 0.293 | |
| I0525 01:14:31.197594 5272 solver.cpp:406] Test net output #104: loss3/accuracy06 = 0.472 | |
| I0525 01:14:31.197607 5272 solver.cpp:406] Test net output #105: loss3/accuracy07 = 0.741 | |
| I0525 01:14:31.197618 5272 solver.cpp:406] Test net output #106: loss3/accuracy08 = 0.922 | |
| I0525 01:14:31.197629 5272 solver.cpp:406] Test net output #107: loss3/accuracy09 = 0.984 | |
| I0525 01:14:31.197640 5272 solver.cpp:406] Test net output #108: loss3/accuracy10 = 0.994 | |
| I0525 01:14:31.197651 5272 solver.cpp:406] Test net output #109: loss3/accuracy11 = 1 | |
| I0525 01:14:31.197662 5272 solver.cpp:406] Test net output #110: loss3/accuracy12 = 1 | |
| I0525 01:14:31.197676 5272 solver.cpp:406] Test net output #111: loss3/accuracy13 = 1 | |
| I0525 01:14:31.197687 5272 solver.cpp:406] Test net output #112: loss3/accuracy14 = 1 | |
| I0525 01:14:31.197698 5272 solver.cpp:406] Test net output #113: loss3/accuracy15 = 1 | |
| I0525 01:14:31.197710 5272 solver.cpp:406] Test net output #114: loss3/accuracy16 = 1 | |
| I0525 01:14:31.197721 5272 solver.cpp:406] Test net output #115: loss3/accuracy17 = 1 | |
| I0525 01:14:31.197741 5272 solver.cpp:406] Test net output #116: loss3/accuracy18 = 1 | |
| I0525 01:14:31.197754 5272 solver.cpp:406] Test net output #117: loss3/accuracy19 = 1 | |
| I0525 01:14:31.197765 5272 solver.cpp:406] Test net output #118: loss3/accuracy20 = 1 | |
| I0525 01:14:31.197777 5272 solver.cpp:406] Test net output #119: loss3/accuracy21 = 1 | |
| I0525 01:14:31.197788 5272 solver.cpp:406] Test net output #120: loss3/accuracy22 = 1 | |
| I0525 01:14:31.197798 5272 solver.cpp:406] Test net output #121: loss3/accuracy_incl_empty = 0.763046 | |
| I0525 01:14:31.197809 5272 solver.cpp:406] Test net output #122: loss3/accuracy_top3 = 0.186017 | |
| I0525 01:14:31.197823 5272 solver.cpp:406] Test net output #123: loss3/cross_entropy_loss = 3.53036 (* 1 = 3.53036 loss) | |
| I0525 01:14:31.197839 5272 solver.cpp:406] Test net output #124: loss3/cross_entropy_loss_incl_empty = 0.981813 (* 1 = 0.981813 loss) | |
| I0525 01:14:31.197849 5272 solver.cpp:406] Test net output #125: loss3/loss01 = 3.3441 (* 0.0909091 = 0.304009 loss) | |
| I0525 01:14:31.197862 5272 solver.cpp:406] Test net output #126: loss3/loss02 = 3.45409 (* 0.0909091 = 0.314008 loss) | |
| I0525 01:14:31.197876 5272 solver.cpp:406] Test net output #127: loss3/loss03 = 3.5222 (* 0.0909091 = 0.3202 loss) | |
| I0525 01:14:31.197890 5272 solver.cpp:406] Test net output #128: loss3/loss04 = 3.38196 (* 0.0909091 = 0.307451 loss) | |
| I0525 01:14:31.197902 5272 solver.cpp:406] Test net output #129: loss3/loss05 = 2.95404 (* 0.0909091 = 0.268549 loss) | |
| I0525 01:14:31.197916 5272 solver.cpp:406] Test net output #130: loss3/loss06 = 2.45104 (* 0.0909091 = 0.222822 loss) | |
| I0525 01:14:31.197928 5272 solver.cpp:406] Test net output #131: loss3/loss07 = 1.47183 (* 0.0909091 = 0.133803 loss) | |
| I0525 01:14:31.197942 5272 solver.cpp:406] Test net output #132: loss3/loss08 = 0.552402 (* 0.0909091 = 0.0502184 loss) | |
| I0525 01:14:31.197954 5272 solver.cpp:406] Test net output #133: loss3/loss09 = 0.16017 (* 0.0909091 = 0.0145609 loss) | |
| I0525 01:14:31.197968 5272 solver.cpp:406] Test net output #134: loss3/loss10 = 0.0998079 (* 0.0909091 = 0.00907344 loss) | |
| I0525 01:14:31.197984 5272 solver.cpp:406] Test net output #135: loss3/loss11 = 0.0605407 (* 0.0909091 = 0.0055037 loss) | |
| I0525 01:14:31.197999 5272 solver.cpp:406] Test net output #136: loss3/loss12 = 0.0498019 (* 0.0909091 = 0.00452745 loss) | |
| I0525 01:14:31.198012 5272 solver.cpp:406] Test net output #137: loss3/loss13 = 0.0410195 (* 0.0909091 = 0.00372905 loss) | |
| I0525 01:14:31.198025 5272 solver.cpp:406] Test net output #138: loss3/loss14 = 0.0319506 (* 0.0909091 = 0.0029046 loss) | |
| I0525 01:14:31.198040 5272 solver.cpp:406] Test net output #139: loss3/loss15 = 0.0252223 (* 0.0909091 = 0.00229293 loss) | |
| I0525 01:14:31.198052 5272 solver.cpp:406] Test net output #140: loss3/loss16 = 0.017384 (* 0.0909091 = 0.00158036 loss) | |
| I0525 01:14:31.198066 5272 solver.cpp:406] Test net output #141: loss3/loss17 = 0.009152 (* 0.0909091 = 0.000832 loss) | |
| I0525 01:14:31.198079 5272 solver.cpp:406] Test net output #142: loss3/loss18 = 0.00729522 (* 0.0909091 = 0.000663202 loss) | |
| I0525 01:14:31.198092 5272 solver.cpp:406] Test net output #143: loss3/loss19 = 0.00471872 (* 0.0909091 = 0.000428975 loss) | |
| I0525 01:14:31.198106 5272 solver.cpp:406] Test net output #144: loss3/loss20 = 0.00411859 (* 0.0909091 = 0.000374418 loss) | |
| I0525 01:14:31.198118 5272 solver.cpp:406] Test net output #145: loss3/loss21 = 0.00318579 (* 0.0909091 = 0.000289618 loss) | |
| I0525 01:14:31.198132 5272 solver.cpp:406] Test net output #146: loss3/loss22 = 0.00360116 (* 0.0909091 = 0.000327378 loss) | |
| I0525 01:14:31.198143 5272 solver.cpp:406] Test net output #147: total_accuracy = 0 | |
| I0525 01:14:31.198154 5272 solver.cpp:406] Test net output #148: total_accuracy_not_rec = 0 | |
| I0525 01:14:31.198164 5272 solver.cpp:406] Test net output #149: total_confidence = 2.65895e-05 | |
| I0525 01:14:31.198176 5272 solver.cpp:406] Test net output #150: total_confidence_not_rec = 0.000229805 | |
| I0525 01:14:31.198199 5272 solver.cpp:338] Iteration 5000, Testing net (#1) | |
| I0525 01:15:29.690523 5272 solver.cpp:393] Test loss: 11.8057 | |
| I0525 01:15:29.690655 5272 solver.cpp:406] Test net output #0: loss1/accuracy = 0.0328547 | |
| I0525 01:15:29.690682 5272 solver.cpp:406] Test net output #1: loss1/accuracy01 = 0.091 | |
| I0525 01:15:29.690708 5272 solver.cpp:406] Test net output #2: loss1/accuracy02 = 0.07 | |
| I0525 01:15:29.690724 5272 solver.cpp:406] Test net output #3: loss1/accuracy03 = 0.049 | |
| I0525 01:15:29.690737 5272 solver.cpp:406] Test net output #4: loss1/accuracy04 = 0.142 | |
| I0525 01:15:29.690749 5272 solver.cpp:406] Test net output #5: loss1/accuracy05 = 0.281 | |
| I0525 01:15:29.690762 5272 solver.cpp:406] Test net output #6: loss1/accuracy06 = 0.427 | |
| I0525 01:15:29.690773 5272 solver.cpp:406] Test net output #7: loss1/accuracy07 = 0.655 | |
| I0525 01:15:29.690784 5272 solver.cpp:406] Test net output #8: loss1/accuracy08 = 0.813 | |
| I0525 01:15:29.690796 5272 solver.cpp:406] Test net output #9: loss1/accuracy09 = 0.88 | |
| I0525 01:15:29.690807 5272 solver.cpp:406] Test net output #10: loss1/accuracy10 = 0.901 | |
| I0525 01:15:29.690819 5272 solver.cpp:406] Test net output #11: loss1/accuracy11 = 0.924 | |
| I0525 01:15:29.690830 5272 solver.cpp:406] Test net output #12: loss1/accuracy12 = 0.941 | |
| I0525 01:15:29.690843 5272 solver.cpp:406] Test net output #13: loss1/accuracy13 = 0.95 | |
| I0525 01:15:29.690855 5272 solver.cpp:406] Test net output #14: loss1/accuracy14 = 0.96 | |
| I0525 01:15:29.690865 5272 solver.cpp:406] Test net output #15: loss1/accuracy15 = 0.963 | |
| I0525 01:15:29.690881 5272 solver.cpp:406] Test net output #16: loss1/accuracy16 = 0.981 | |
| I0525 01:15:29.690892 5272 solver.cpp:406] Test net output #17: loss1/accuracy17 = 0.991 | |
| I0525 01:15:29.690904 5272 solver.cpp:406] Test net output #18: loss1/accuracy18 = 0.992 | |
| I0525 01:15:29.690917 5272 solver.cpp:406] Test net output #19: loss1/accuracy19 = 0.994 | |
| I0525 01:15:29.690927 5272 solver.cpp:406] Test net output #20: loss1/accuracy20 = 0.999 | |
| I0525 01:15:29.690938 5272 solver.cpp:406] Test net output #21: loss1/accuracy21 = 0.999 | |
| I0525 01:15:29.690949 5272 solver.cpp:406] Test net output #22: loss1/accuracy22 = 0.999 | |
| I0525 01:15:29.690963 5272 solver.cpp:406] Test net output #23: loss1/accuracy_incl_empty = 0.724319 | |
| I0525 01:15:29.690986 5272 solver.cpp:406] Test net output #24: loss1/accuracy_top3 = 0.159007 | |
| I0525 01:15:29.691015 5272 solver.cpp:406] Test net output #25: loss1/cross_entropy_loss = 4.2718 (* 0.3 = 1.28154 loss) | |
| I0525 01:15:29.691031 5272 solver.cpp:406] Test net output #26: loss1/cross_entropy_loss_incl_empty = 1.28014 (* 0.3 = 0.384043 loss) | |
| I0525 01:15:29.691045 5272 solver.cpp:406] Test net output #27: loss1/loss01 = 3.55082 (* 0.0272727 = 0.0968407 loss) | |
| I0525 01:15:29.691059 5272 solver.cpp:406] Test net output #28: loss1/loss02 = 3.58116 (* 0.0272727 = 0.0976681 loss) | |
| I0525 01:15:29.691072 5272 solver.cpp:406] Test net output #29: loss1/loss03 = 3.69745 (* 0.0272727 = 0.10084 loss) | |
| I0525 01:15:29.691087 5272 solver.cpp:406] Test net output #30: loss1/loss04 = 3.51273 (* 0.0272727 = 0.0958017 loss) | |
| I0525 01:15:29.691099 5272 solver.cpp:406] Test net output #31: loss1/loss05 = 3.06272 (* 0.0272727 = 0.0835288 loss) | |
| I0525 01:15:29.691112 5272 solver.cpp:406] Test net output #32: loss1/loss06 = 2.67913 (* 0.0272727 = 0.0730672 loss) | |
| I0525 01:15:29.691126 5272 solver.cpp:406] Test net output #33: loss1/loss07 = 1.78855 (* 0.0272727 = 0.0487786 loss) | |
| I0525 01:15:29.691139 5272 solver.cpp:406] Test net output #34: loss1/loss08 = 1.02746 (* 0.0272727 = 0.0280216 loss) | |
| I0525 01:15:29.691153 5272 solver.cpp:406] Test net output #35: loss1/loss09 = 0.66014 (* 0.0272727 = 0.0180038 loss) | |
| I0525 01:15:29.691165 5272 solver.cpp:406] Test net output #36: loss1/loss10 = 0.58698 (* 0.0272727 = 0.0160086 loss) | |
| I0525 01:15:29.691179 5272 solver.cpp:406] Test net output #37: loss1/loss11 = 0.474315 (* 0.0272727 = 0.0129359 loss) | |
| I0525 01:15:29.691192 5272 solver.cpp:406] Test net output #38: loss1/loss12 = 0.39144 (* 0.0272727 = 0.0106756 loss) | |
| I0525 01:15:29.691206 5272 solver.cpp:406] Test net output #39: loss1/loss13 = 0.341931 (* 0.0272727 = 0.0093254 loss) | |
| I0525 01:15:29.691241 5272 solver.cpp:406] Test net output #40: loss1/loss14 = 0.284074 (* 0.0272727 = 0.00774747 loss) | |
| I0525 01:15:29.691256 5272 solver.cpp:406] Test net output #41: loss1/loss15 = 0.263264 (* 0.0272727 = 0.00717993 loss) | |
| I0525 01:15:29.691268 5272 solver.cpp:406] Test net output #42: loss1/loss16 = 0.156059 (* 0.0272727 = 0.00425615 loss) | |
| I0525 01:15:29.691282 5272 solver.cpp:406] Test net output #43: loss1/loss17 = 0.089202 (* 0.0272727 = 0.00243278 loss) | |
| I0525 01:15:29.691296 5272 solver.cpp:406] Test net output #44: loss1/loss18 = 0.0800309 (* 0.0272727 = 0.00218266 loss) | |
| I0525 01:15:29.691309 5272 solver.cpp:406] Test net output #45: loss1/loss19 = 0.0629195 (* 0.0272727 = 0.00171599 loss) | |
| I0525 01:15:29.691323 5272 solver.cpp:406] Test net output #46: loss1/loss20 = 0.0240276 (* 0.0272727 = 0.000655299 loss) | |
| I0525 01:15:29.691336 5272 solver.cpp:406] Test net output #47: loss1/loss21 = 0.0237058 (* 0.0272727 = 0.000646522 loss) | |
| I0525 01:15:29.691352 5272 solver.cpp:406] Test net output #48: loss1/loss22 = 0.0228417 (* 0.0272727 = 0.000622956 loss) | |
| I0525 01:15:29.691375 5272 solver.cpp:406] Test net output #49: loss2/accuracy = 0.0339731 | |
| I0525 01:15:29.691397 5272 solver.cpp:406] Test net output #50: loss2/accuracy01 = 0.09 | |
| I0525 01:15:29.691411 5272 solver.cpp:406] Test net output #51: loss2/accuracy02 = 0.063 | |
| I0525 01:15:29.691423 5272 solver.cpp:406] Test net output #52: loss2/accuracy03 = 0.057 | |
| I0525 01:15:29.691434 5272 solver.cpp:406] Test net output #53: loss2/accuracy04 = 0.124 | |
| I0525 01:15:29.691447 5272 solver.cpp:406] Test net output #54: loss2/accuracy05 = 0.276 | |
| I0525 01:15:29.691457 5272 solver.cpp:406] Test net output #55: loss2/accuracy06 = 0.427 | |
| I0525 01:15:29.691468 5272 solver.cpp:406] Test net output #56: loss2/accuracy07 = 0.655 | |
| I0525 01:15:29.691479 5272 solver.cpp:406] Test net output #57: loss2/accuracy08 = 0.813 | |
| I0525 01:15:29.691490 5272 solver.cpp:406] Test net output #58: loss2/accuracy09 = 0.88 | |
| I0525 01:15:29.691501 5272 solver.cpp:406] Test net output #59: loss2/accuracy10 = 0.901 | |
| I0525 01:15:29.691512 5272 solver.cpp:406] Test net output #60: loss2/accuracy11 = 0.924 | |
| I0525 01:15:29.691524 5272 solver.cpp:406] Test net output #61: loss2/accuracy12 = 0.941 | |
| I0525 01:15:29.691534 5272 solver.cpp:406] Test net output #62: loss2/accuracy13 = 0.95 | |
| I0525 01:15:29.691546 5272 solver.cpp:406] Test net output #63: loss2/accuracy14 = 0.96 | |
| I0525 01:15:29.691557 5272 solver.cpp:406] Test net output #64: loss2/accuracy15 = 0.963 | |
| I0525 01:15:29.691570 5272 solver.cpp:406] Test net output #65: loss2/accuracy16 = 0.981 | |
| I0525 01:15:29.691581 5272 solver.cpp:406] Test net output #66: loss2/accuracy17 = 0.991 | |
| I0525 01:15:29.691591 5272 solver.cpp:406] Test net output #67: loss2/accuracy18 = 0.992 | |
| I0525 01:15:29.691602 5272 solver.cpp:406] Test net output #68: loss2/accuracy19 = 0.994 | |
| I0525 01:15:29.691613 5272 solver.cpp:406] Test net output #69: loss2/accuracy20 = 0.999 | |
| I0525 01:15:29.691625 5272 solver.cpp:406] Test net output #70: loss2/accuracy21 = 0.999 | |
| I0525 01:15:29.691637 5272 solver.cpp:406] Test net output #71: loss2/accuracy22 = 0.999 | |
| I0525 01:15:29.691648 5272 solver.cpp:406] Test net output #72: loss2/accuracy_incl_empty = 0.725273 | |
| I0525 01:15:29.691658 5272 solver.cpp:406] Test net output #73: loss2/accuracy_top3 = 0.158243 | |
| I0525 01:15:29.691675 5272 solver.cpp:406] Test net output #74: loss2/cross_entropy_loss = 4.35725 (* 0.3 = 1.30718 loss) | |
| I0525 01:15:29.691689 5272 solver.cpp:406] Test net output #75: loss2/cross_entropy_loss_incl_empty = 1.31034 (* 0.3 = 0.393101 loss) | |
| I0525 01:15:29.691714 5272 solver.cpp:406] Test net output #76: loss2/loss01 = 3.5784 (* 0.0272727 = 0.0975926 loss) | |
| I0525 01:15:29.691740 5272 solver.cpp:406] Test net output #77: loss2/loss02 = 3.59583 (* 0.0272727 = 0.0980682 loss) | |
| I0525 01:15:29.691773 5272 solver.cpp:406] Test net output #78: loss2/loss03 = 3.68726 (* 0.0272727 = 0.100562 loss) | |
| I0525 01:15:29.691787 5272 solver.cpp:406] Test net output #79: loss2/loss04 = 3.52559 (* 0.0272727 = 0.0961524 loss) | |
| I0525 01:15:29.691805 5272 solver.cpp:406] Test net output #80: loss2/loss05 = 3.08803 (* 0.0272727 = 0.084219 loss) | |
| I0525 01:15:29.691831 5272 solver.cpp:406] Test net output #81: loss2/loss06 = 2.69858 (* 0.0272727 = 0.0735976 loss) | |
| I0525 01:15:29.691854 5272 solver.cpp:406] Test net output #82: loss2/loss07 = 1.8094 (* 0.0272727 = 0.0493474 loss) | |
| I0525 01:15:29.691869 5272 solver.cpp:406] Test net output #83: loss2/loss08 = 1.02441 (* 0.0272727 = 0.0279383 loss) | |
| I0525 01:15:29.691882 5272 solver.cpp:406] Test net output #84: loss2/loss09 = 0.677464 (* 0.0272727 = 0.0184763 loss) | |
| I0525 01:15:29.691895 5272 solver.cpp:406] Test net output #85: loss2/loss10 = 0.584583 (* 0.0272727 = 0.0159432 loss) | |
| I0525 01:15:29.691910 5272 solver.cpp:406] Test net output #86: loss2/loss11 = 0.486788 (* 0.0272727 = 0.013276 loss) | |
| I0525 01:15:29.691922 5272 solver.cpp:406] Test net output #87: loss2/loss12 = 0.392599 (* 0.0272727 = 0.0107073 loss) | |
| I0525 01:15:29.691939 5272 solver.cpp:406] Test net output #88: loss2/loss13 = 0.344252 (* 0.0272727 = 0.00938869 loss) | |
| I0525 01:15:29.691952 5272 solver.cpp:406] Test net output #89: loss2/loss14 = 0.278492 (* 0.0272727 = 0.00759523 loss) | |
| I0525 01:15:29.691967 5272 solver.cpp:406] Test net output #90: loss2/loss15 = 0.27383 (* 0.0272727 = 0.0074681 loss) | |
| I0525 01:15:29.691979 5272 solver.cpp:406] Test net output #91: loss2/loss16 = 0.158455 (* 0.0272727 = 0.0043215 loss) | |
| I0525 01:15:29.691993 5272 solver.cpp:406] Test net output #92: loss2/loss17 = 0.0918658 (* 0.0272727 = 0.00250543 loss) | |
| I0525 01:15:29.692006 5272 solver.cpp:406] Test net output #93: loss2/loss18 = 0.0831915 (* 0.0272727 = 0.00226886 loss) | |
| I0525 01:15:29.692019 5272 solver.cpp:406] Test net output #94: loss2/loss19 = 0.0618085 (* 0.0272727 = 0.00168569 loss) | |
| I0525 01:15:29.692034 5272 solver.cpp:406] Test net output #95: loss2/loss20 = 0.026766 (* 0.0272727 = 0.000729982 loss) | |
| I0525 01:15:29.692046 5272 solver.cpp:406] Test net output #96: loss2/loss21 = 0.0234775 (* 0.0272727 = 0.000640296 loss) | |
| I0525 01:15:29.692060 5272 solver.cpp:406] Test net output #97: loss2/loss22 = 0.0245529 (* 0.0272727 = 0.000669626 loss) | |
| I0525 01:15:29.692071 5272 solver.cpp:406] Test net output #98: loss3/accuracy = 0.0580329 | |
| I0525 01:15:29.692083 5272 solver.cpp:406] Test net output #99: loss3/accuracy01 = 0.094 | |
| I0525 01:15:29.692095 5272 solver.cpp:406] Test net output #100: loss3/accuracy02 = 0.077 | |
| I0525 01:15:29.692106 5272 solver.cpp:406] Test net output #101: loss3/accuracy03 = 0.084 | |
| I0525 01:15:29.692117 5272 solver.cpp:406] Test net output #102: loss3/accuracy04 = 0.139 | |
| I0525 01:15:29.692128 5272 solver.cpp:406] Test net output #103: loss3/accuracy05 = 0.279 | |
| I0525 01:15:29.692139 5272 solver.cpp:406] Test net output #104: loss3/accuracy06 = 0.427 | |
| I0525 01:15:29.692150 5272 solver.cpp:406] Test net output #105: loss3/accuracy07 = 0.655 | |
| I0525 01:15:29.692162 5272 solver.cpp:406] Test net output #106: loss3/accuracy08 = 0.813 | |
| I0525 01:15:29.692173 5272 solver.cpp:406] Test net output #107: loss3/accuracy09 = 0.88 | |
| I0525 01:15:29.692184 5272 solver.cpp:406] Test net output #108: loss3/accuracy10 = 0.901 | |
| I0525 01:15:29.692195 5272 solver.cpp:406] Test net output #109: loss3/accuracy11 = 0.924 | |
| I0525 01:15:29.692206 5272 solver.cpp:406] Test net output #110: loss3/accuracy12 = 0.941 | |
| I0525 01:15:29.692217 5272 solver.cpp:406] Test net output #111: loss3/accuracy13 = 0.95 | |
| I0525 01:15:29.692229 5272 solver.cpp:406] Test net output #112: loss3/accuracy14 = 0.96 | |
| I0525 01:15:29.692240 5272 solver.cpp:406] Test net output #113: loss3/accuracy15 = 0.963 | |
| I0525 01:15:29.692248 5272 solver.cpp:406] Test net output #114: loss3/accuracy16 = 0.981 | |
| I0525 01:15:29.692270 5272 solver.cpp:406] Test net output #115: loss3/accuracy17 = 0.991 | |
| I0525 01:15:29.692283 5272 solver.cpp:406] Test net output #116: loss3/accuracy18 = 0.992 | |
| I0525 01:15:29.692294 5272 solver.cpp:406] Test net output #117: loss3/accuracy19 = 0.994 | |
| I0525 01:15:29.692306 5272 solver.cpp:406] Test net output #118: loss3/accuracy20 = 0.999 | |
| I0525 01:15:29.692325 5272 solver.cpp:406] Test net output #119: loss3/accuracy21 = 0.999 | |
| I0525 01:15:29.692347 5272 solver.cpp:406] Test net output #120: loss3/accuracy22 = 0.999 | |
| I0525 01:15:29.692365 5272 solver.cpp:406] Test net output #121: loss3/accuracy_incl_empty = 0.729046 | |
| I0525 01:15:29.692378 5272 solver.cpp:406] Test net output #122: loss3/accuracy_top3 = 0.180027 | |
| I0525 01:15:29.692391 5272 solver.cpp:406] Test net output #123: loss3/cross_entropy_loss = 3.57124 (* 1 = 3.57124 loss) | |
| I0525 01:15:29.692404 5272 solver.cpp:406] Test net output #124: loss3/cross_entropy_loss_incl_empty = 1.12514 (* 1 = 1.12514 loss) | |
| I0525 01:15:29.692419 5272 solver.cpp:406] Test net output #125: loss3/loss01 = 3.39906 (* 0.0909091 = 0.309005 loss) | |
| I0525 01:15:29.692431 5272 solver.cpp:406] Test net output #126: loss3/loss02 = 3.42135 (* 0.0909091 = 0.311032 loss) | |
| I0525 01:15:29.692445 5272 solver.cpp:406] Test net output #127: loss3/loss03 = 3.54321 (* 0.0909091 = 0.32211 loss) | |
| I0525 01:15:29.692457 5272 solver.cpp:406] Test net output #128: loss3/loss04 = 3.40175 (* 0.0909091 = 0.30925 loss) | |
| I0525 01:15:29.692471 5272 solver.cpp:406] Test net output #129: loss3/loss05 = 3.0095 (* 0.0909091 = 0.273591 loss) | |
| I0525 01:15:29.692483 5272 solver.cpp:406] Test net output #130: loss3/loss06 = 2.64451 (* 0.0909091 = 0.24041 loss) | |
| I0525 01:15:29.692497 5272 solver.cpp:406] Test net output #131: loss3/loss07 = 1.7668 (* 0.0909091 = 0.160618 loss) | |
| I0525 01:15:29.692509 5272 solver.cpp:406] Test net output #132: loss3/loss08 = 0.977754 (* 0.0909091 = 0.0888867 loss) | |
| I0525 01:15:29.692523 5272 solver.cpp:406] Test net output #133: loss3/loss09 = 0.61344 (* 0.0909091 = 0.0557672 loss) | |
| I0525 01:15:29.692535 5272 solver.cpp:406] Test net output #134: loss3/loss10 = 0.536173 (* 0.0909091 = 0.048743 loss) | |
| I0525 01:15:29.692548 5272 solver.cpp:406] Test net output #135: loss3/loss11 = 0.429213 (* 0.0909091 = 0.0390194 loss) | |
| I0525 01:15:29.692562 5272 solver.cpp:406] Test net output #136: loss3/loss12 = 0.343277 (* 0.0909091 = 0.031207 loss) | |
| I0525 01:15:29.692575 5272 solver.cpp:406] Test net output #137: loss3/loss13 = 0.312462 (* 0.0909091 = 0.0284056 loss) | |
| I0525 01:15:29.692589 5272 solver.cpp:406] Test net output #138: loss3/loss14 = 0.261479 (* 0.0909091 = 0.0237708 loss) | |
| I0525 01:15:29.692601 5272 solver.cpp:406] Test net output #139: loss3/loss15 = 0.256072 (* 0.0909091 = 0.0232793 loss) | |
| I0525 01:15:29.692615 5272 solver.cpp:406] Test net output #140: loss3/loss16 = 0.142444 (* 0.0909091 = 0.0129495 loss) | |
| I0525 01:15:29.692628 5272 solver.cpp:406] Test net output #141: loss3/loss17 = 0.0785858 (* 0.0909091 = 0.00714416 loss) | |
| I0525 01:15:29.692641 5272 solver.cpp:406] Test net output #142: loss3/loss18 = 0.0754316 (* 0.0909091 = 0.00685742 loss) | |
| I0525 01:15:29.692654 5272 solver.cpp:406] Test net output #143: loss3/loss19 = 0.0613554 (* 0.0909091 = 0.00557776 loss) | |
| I0525 01:15:29.692667 5272 solver.cpp:406] Test net output #144: loss3/loss20 = 0.014015 (* 0.0909091 = 0.00127409 loss) | |
| I0525 01:15:29.692680 5272 solver.cpp:406] Test net output #145: loss3/loss21 = 0.0138255 (* 0.0909091 = 0.00125686 loss) | |
| I0525 01:15:29.692693 5272 solver.cpp:406] Test net output #146: loss3/loss22 = 0.0138513 (* 0.0909091 = 0.00125921 loss) | |
| I0525 01:15:29.692704 5272 solver.cpp:406] Test net output #147: total_accuracy = 0 | |
| I0525 01:15:29.692715 5272 solver.cpp:406] Test net output #148: total_accuracy_not_rec = 0 | |
| I0525 01:15:29.692730 5272 solver.cpp:406] Test net output #149: total_confidence = 2.33363e-05 | |
| I0525 01:15:29.692756 5272 solver.cpp:406] Test net output #150: total_confidence_not_rec = 0.000198021 | |
| I0525 01:15:30.050091 5272 solver.cpp:229] Iteration 5000, loss = 11.7774 | |
| I0525 01:15:30.050176 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0263158 | |
| I0525 01:15:30.050195 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.125 | |
| I0525 01:15:30.050209 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0.125 | |
| I0525 01:15:30.050221 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0525 01:15:30.050233 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.25 | |
| I0525 01:15:30.050246 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.5 | |
| I0525 01:15:30.050257 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.625 | |
| I0525 01:15:30.050271 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.875 | |
| I0525 01:15:30.050282 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 1 | |
| I0525 01:15:30.050294 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 1 | |
| I0525 01:15:30.050307 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 1 | |
| I0525 01:15:30.050318 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 01:15:30.050330 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 01:15:30.050345 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 01:15:30.050359 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 01:15:30.050370 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 01:15:30.050384 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 01:15:30.050395 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 01:15:30.050407 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 01:15:30.050420 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 01:15:30.050431 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 01:15:30.050443 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 01:15:30.050454 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 01:15:30.050467 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.789773 | |
| I0525 01:15:30.050478 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.0789474 | |
| I0525 01:15:30.050495 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.61124 (* 0.3 = 1.08337 loss) | |
| I0525 01:15:30.050509 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 0.951132 (* 0.3 = 0.28534 loss) | |
| I0525 01:15:30.050523 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.92659 (* 0.0272727 = 0.107089 loss) | |
| I0525 01:15:30.050539 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.55139 (* 0.0272727 = 0.096856 loss) | |
| I0525 01:15:30.050551 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 4.12024 (* 0.0272727 = 0.11237 loss) | |
| I0525 01:15:30.050565 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.75165 (* 0.0272727 = 0.102318 loss) | |
| I0525 01:15:30.050580 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 2.09121 (* 0.0272727 = 0.0570331 loss) | |
| I0525 01:15:30.050593 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 2.0255 (* 0.0272727 = 0.0552408 loss) | |
| I0525 01:15:30.050607 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 0.943919 (* 0.0272727 = 0.0257433 loss) | |
| I0525 01:15:30.050622 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 0.163657 (* 0.0272727 = 0.00446338 loss) | |
| I0525 01:15:30.050637 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.0730641 (* 0.0272727 = 0.00199266 loss) | |
| I0525 01:15:30.050652 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.0668919 (* 0.0272727 = 0.00182433 loss) | |
| I0525 01:15:30.050665 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.0426135 (* 0.0272727 = 0.00116219 loss) | |
| I0525 01:15:30.050717 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.0370983 (* 0.0272727 = 0.00101177 loss) | |
| I0525 01:15:30.050734 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.0428163 (* 0.0272727 = 0.00116772 loss) | |
| I0525 01:15:30.050750 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.0310513 (* 0.0272727 = 0.000846855 loss) | |
| I0525 01:15:30.050765 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0144841 (* 0.0272727 = 0.000395022 loss) | |
| I0525 01:15:30.050778 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.0320794 (* 0.0272727 = 0.000874893 loss) | |
| I0525 01:15:30.050792 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.017461 (* 0.0272727 = 0.000476209 loss) | |
| I0525 01:15:30.050806 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0128127 (* 0.0272727 = 0.000349437 loss) | |
| I0525 01:15:30.050820 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.00974174 (* 0.0272727 = 0.000265684 loss) | |
| I0525 01:15:30.050834 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.00721823 (* 0.0272727 = 0.000196861 loss) | |
| I0525 01:15:30.050848 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.0113255 (* 0.0272727 = 0.000308877 loss) | |
| I0525 01:15:30.050863 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.00850658 (* 0.0272727 = 0.000231998 loss) | |
| I0525 01:15:30.050874 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.0263158 | |
| I0525 01:15:30.050886 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0.125 | |
| I0525 01:15:30.050899 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0.125 | |
| I0525 01:15:30.050910 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0 | |
| I0525 01:15:30.050922 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0.25 | |
| I0525 01:15:30.050935 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.5 | |
| I0525 01:15:30.050946 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.625 | |
| I0525 01:15:30.050958 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.875 | |
| I0525 01:15:30.050971 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 1 | |
| I0525 01:15:30.050982 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 1 | |
| I0525 01:15:30.050993 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 1 | |
| I0525 01:15:30.051005 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 01:15:30.051017 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 01:15:30.051028 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 01:15:30.051040 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 01:15:30.051051 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 01:15:30.051062 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 01:15:30.051074 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 01:15:30.051085 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 01:15:30.051096 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 01:15:30.051108 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 01:15:30.051120 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 01:15:30.051131 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 01:15:30.051142 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.784091 | |
| I0525 01:15:30.051154 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.131579 | |
| I0525 01:15:30.051168 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.80572 (* 0.3 = 1.14172 loss) | |
| I0525 01:15:30.051182 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 0.983299 (* 0.3 = 0.29499 loss) | |
| I0525 01:15:30.051195 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.68561 (* 0.0272727 = 0.100517 loss) | |
| I0525 01:15:30.051220 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 3.53513 (* 0.0272727 = 0.0964126 loss) | |
| I0525 01:15:30.051235 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 4.0635 (* 0.0272727 = 0.110823 loss) | |
| I0525 01:15:30.051249 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.96364 (* 0.0272727 = 0.108099 loss) | |
| I0525 01:15:30.051262 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 2.15026 (* 0.0272727 = 0.0586434 loss) | |
| I0525 01:15:30.051276 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 1.83167 (* 0.0272727 = 0.0499548 loss) | |
| I0525 01:15:30.051286 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 0.993102 (* 0.0272727 = 0.0270846 loss) | |
| I0525 01:15:30.051296 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 0.227612 (* 0.0272727 = 0.0062076 loss) | |
| I0525 01:15:30.051312 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.175445 (* 0.0272727 = 0.00478487 loss) | |
| I0525 01:15:30.051326 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.0872124 (* 0.0272727 = 0.00237852 loss) | |
| I0525 01:15:30.051340 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.0781888 (* 0.0272727 = 0.00213242 loss) | |
| I0525 01:15:30.051354 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.094235 (* 0.0272727 = 0.00257005 loss) | |
| I0525 01:15:30.051367 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.0569788 (* 0.0272727 = 0.00155397 loss) | |
| I0525 01:15:30.051381 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.0493121 (* 0.0272727 = 0.00134487 loss) | |
| I0525 01:15:30.051399 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.0343773 (* 0.0272727 = 0.000937564 loss) | |
| I0525 01:15:30.051414 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.0205342 (* 0.0272727 = 0.000560024 loss) | |
| I0525 01:15:30.051429 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.0255752 (* 0.0272727 = 0.000697504 loss) | |
| I0525 01:15:30.051442 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.0156056 (* 0.0272727 = 0.000425608 loss) | |
| I0525 01:15:30.051455 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.0176291 (* 0.0272727 = 0.000480794 loss) | |
| I0525 01:15:30.051470 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.0187614 (* 0.0272727 = 0.000511675 loss) | |
| I0525 01:15:30.051483 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.00849466 (* 0.0272727 = 0.000231672 loss) | |
| I0525 01:15:30.051497 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.0150648 (* 0.0272727 = 0.000410857 loss) | |
| I0525 01:15:30.051509 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.0526316 | |
| I0525 01:15:30.051522 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0 | |
| I0525 01:15:30.051533 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0.125 | |
| I0525 01:15:30.051544 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0 | |
| I0525 01:15:30.051556 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.25 | |
| I0525 01:15:30.051568 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.5 | |
| I0525 01:15:30.051580 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.625 | |
| I0525 01:15:30.051591 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.875 | |
| I0525 01:15:30.051604 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 1 | |
| I0525 01:15:30.051615 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 1 | |
| I0525 01:15:30.051626 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 1 | |
| I0525 01:15:30.051638 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 01:15:30.051650 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 01:15:30.051661 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 01:15:30.051672 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 01:15:30.051695 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 01:15:30.051708 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 01:15:30.051719 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 01:15:30.051731 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 01:15:30.051743 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 01:15:30.051754 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 01:15:30.051766 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 01:15:30.051777 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 01:15:30.051789 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.789773 | |
| I0525 01:15:30.051802 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.157895 | |
| I0525 01:15:30.051817 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.6909 (* 1 = 3.6909 loss) | |
| I0525 01:15:30.051831 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 0.980071 (* 1 = 0.980071 loss) | |
| I0525 01:15:30.051846 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 3.45222 (* 0.0909091 = 0.313838 loss) | |
| I0525 01:15:30.051859 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.09269 (* 0.0909091 = 0.281154 loss) | |
| I0525 01:15:30.051872 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.75668 (* 0.0909091 = 0.341516 loss) | |
| I0525 01:15:30.051887 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.46372 (* 0.0909091 = 0.314884 loss) | |
| I0525 01:15:30.051900 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 2.06079 (* 0.0909091 = 0.187345 loss) | |
| I0525 01:15:30.051914 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 1.88538 (* 0.0909091 = 0.171398 loss) | |
| I0525 01:15:30.051928 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 0.896321 (* 0.0909091 = 0.0814837 loss) | |
| I0525 01:15:30.051941 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.1649 (* 0.0909091 = 0.0149909 loss) | |
| I0525 01:15:30.051955 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.0658796 (* 0.0909091 = 0.00598905 loss) | |
| I0525 01:15:30.051970 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.0704603 (* 0.0909091 = 0.00640548 loss) | |
| I0525 01:15:30.051983 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.0686437 (* 0.0909091 = 0.00624034 loss) | |
| I0525 01:15:30.051997 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.048662 (* 0.0909091 = 0.00442381 loss) | |
| I0525 01:15:30.052007 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.0391164 (* 0.0909091 = 0.00355604 loss) | |
| I0525 01:15:30.052024 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.0263761 (* 0.0909091 = 0.00239783 loss) | |
| I0525 01:15:30.052038 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.025218 (* 0.0909091 = 0.00229255 loss) | |
| I0525 01:15:30.052052 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.0138686 (* 0.0909091 = 0.00126078 loss) | |
| I0525 01:15:30.052067 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.0163264 (* 0.0909091 = 0.00148422 loss) | |
| I0525 01:15:30.052080 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.00967876 (* 0.0909091 = 0.000879888 loss) | |
| I0525 01:15:30.052094 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00776347 (* 0.0909091 = 0.00070577 loss) | |
| I0525 01:15:30.052109 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00348213 (* 0.0909091 = 0.000316557 loss) | |
| I0525 01:15:30.052122 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00702622 (* 0.0909091 = 0.000638747 loss) | |
| I0525 01:15:30.052136 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.00480392 (* 0.0909091 = 0.00043672 loss) | |
| I0525 01:15:30.052148 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 01:15:30.052175 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 01:15:30.052187 5272 solver.cpp:245] Train net output #149: total_confidence = 4.0887e-06 | |
| I0525 01:15:30.052199 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 0.000138115 | |
| I0525 01:15:30.052212 5272 sgd_solver.cpp:106] Iteration 5000, lr = 0.001 | |
| I0525 01:15:55.036623 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 30.4848 > 30) by scale factor 0.984098 | |
| I0525 01:21:05.942739 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 38.4828 > 30) by scale factor 0.77957 | |
| I0525 01:21:19.789552 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 43.1334 > 30) by scale factor 0.695516 | |
| I0525 01:21:54.824642 5272 solver.cpp:229] Iteration 5500, loss = 11.7086 | |
| I0525 01:21:54.824808 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0612245 | |
| I0525 01:21:54.824831 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.125 | |
| I0525 01:21:54.824844 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0.125 | |
| I0525 01:21:54.824856 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0525 01:21:54.824868 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.125 | |
| I0525 01:21:54.824883 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.25 | |
| I0525 01:21:54.824897 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.25 | |
| I0525 01:21:54.824908 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.625 | |
| I0525 01:21:54.824921 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.875 | |
| I0525 01:21:54.824934 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 0.875 | |
| I0525 01:21:54.824946 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 0.875 | |
| I0525 01:21:54.824959 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 01:21:54.824970 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 01:21:54.824982 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 01:21:54.824995 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 01:21:54.825006 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 01:21:54.825018 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 01:21:54.825031 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 01:21:54.825042 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 01:21:54.825053 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 01:21:54.825065 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 01:21:54.825076 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 01:21:54.825088 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 01:21:54.825099 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.738636 | |
| I0525 01:21:54.825112 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.142857 | |
| I0525 01:21:54.825142 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.8654 (* 0.3 = 1.15962 loss) | |
| I0525 01:21:54.825158 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.20237 (* 0.3 = 0.360711 loss) | |
| I0525 01:21:54.825173 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 4.17281 (* 0.0272727 = 0.113804 loss) | |
| I0525 01:21:54.825187 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 4.07229 (* 0.0272727 = 0.111063 loss) | |
| I0525 01:21:54.825201 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 4.44505 (* 0.0272727 = 0.121229 loss) | |
| I0525 01:21:54.825215 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.8333 (* 0.0272727 = 0.104545 loss) | |
| I0525 01:21:54.825229 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 3.0852 (* 0.0272727 = 0.0841419 loss) | |
| I0525 01:21:54.825243 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 3.16553 (* 0.0272727 = 0.0863327 loss) | |
| I0525 01:21:54.825258 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 2.35628 (* 0.0272727 = 0.0642622 loss) | |
| I0525 01:21:54.825271 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 0.759412 (* 0.0272727 = 0.0207112 loss) | |
| I0525 01:21:54.825285 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 1.09411 (* 0.0272727 = 0.0298393 loss) | |
| I0525 01:21:54.825299 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.842985 (* 0.0272727 = 0.0229905 loss) | |
| I0525 01:21:54.825314 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.0740819 (* 0.0272727 = 0.00202042 loss) | |
| I0525 01:21:54.825328 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.0872207 (* 0.0272727 = 0.00237875 loss) | |
| I0525 01:21:54.825342 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.097248 (* 0.0272727 = 0.00265222 loss) | |
| I0525 01:21:54.825381 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.0437392 (* 0.0272727 = 0.00119289 loss) | |
| I0525 01:21:54.825395 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0427714 (* 0.0272727 = 0.00116649 loss) | |
| I0525 01:21:54.825409 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.0414018 (* 0.0272727 = 0.00112914 loss) | |
| I0525 01:21:54.825423 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.0479304 (* 0.0272727 = 0.00130719 loss) | |
| I0525 01:21:54.825438 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0264771 (* 0.0272727 = 0.000722101 loss) | |
| I0525 01:21:54.825453 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.0292656 (* 0.0272727 = 0.000798152 loss) | |
| I0525 01:21:54.825465 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.0229532 (* 0.0272727 = 0.000625997 loss) | |
| I0525 01:21:54.825479 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.0362936 (* 0.0272727 = 0.000989827 loss) | |
| I0525 01:21:54.825494 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.0350493 (* 0.0272727 = 0.000955891 loss) | |
| I0525 01:21:54.825506 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.0408163 | |
| I0525 01:21:54.825518 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0.125 | |
| I0525 01:21:54.825531 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0.125 | |
| I0525 01:21:54.825542 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0 | |
| I0525 01:21:54.825553 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0.125 | |
| I0525 01:21:54.825565 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.25 | |
| I0525 01:21:54.825577 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.25 | |
| I0525 01:21:54.825589 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.625 | |
| I0525 01:21:54.825600 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.875 | |
| I0525 01:21:54.825613 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 0.875 | |
| I0525 01:21:54.825624 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 0.875 | |
| I0525 01:21:54.825636 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 01:21:54.825647 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 01:21:54.825659 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 01:21:54.825670 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 01:21:54.825682 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 01:21:54.825693 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 01:21:54.825705 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 01:21:54.825716 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 01:21:54.825727 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 01:21:54.825738 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 01:21:54.825750 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 01:21:54.825762 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 01:21:54.825773 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.732955 | |
| I0525 01:21:54.825784 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.142857 | |
| I0525 01:21:54.825798 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 4.28597 (* 0.3 = 1.28579 loss) | |
| I0525 01:21:54.825811 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.40897 (* 0.3 = 0.422692 loss) | |
| I0525 01:21:54.825829 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.92282 (* 0.0272727 = 0.106986 loss) | |
| I0525 01:21:54.825844 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 4.28764 (* 0.0272727 = 0.116936 loss) | |
| I0525 01:21:54.825868 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.95566 (* 0.0272727 = 0.107882 loss) | |
| I0525 01:21:54.825882 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.81599 (* 0.0272727 = 0.104072 loss) | |
| I0525 01:21:54.825896 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 3.57889 (* 0.0272727 = 0.097606 loss) | |
| I0525 01:21:54.825911 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 3.24965 (* 0.0272727 = 0.0886267 loss) | |
| I0525 01:21:54.825927 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 2.33922 (* 0.0272727 = 0.0637969 loss) | |
| I0525 01:21:54.825942 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 0.924673 (* 0.0272727 = 0.0252184 loss) | |
| I0525 01:21:54.825955 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.974992 (* 0.0272727 = 0.0265907 loss) | |
| I0525 01:21:54.825966 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.777068 (* 0.0272727 = 0.0211928 loss) | |
| I0525 01:21:54.825976 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.0911114 (* 0.0272727 = 0.00248486 loss) | |
| I0525 01:21:54.825990 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.0619259 (* 0.0272727 = 0.00168889 loss) | |
| I0525 01:21:54.826004 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.051186 (* 0.0272727 = 0.00139598 loss) | |
| I0525 01:21:54.826017 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.0393038 (* 0.0272727 = 0.00107192 loss) | |
| I0525 01:21:54.826031 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.0370045 (* 0.0272727 = 0.00100921 loss) | |
| I0525 01:21:54.826045 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.0222412 (* 0.0272727 = 0.000606579 loss) | |
| I0525 01:21:54.826059 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.0186889 (* 0.0272727 = 0.000509697 loss) | |
| I0525 01:21:54.826073 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.0208906 (* 0.0272727 = 0.000569745 loss) | |
| I0525 01:21:54.826086 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.0145325 (* 0.0272727 = 0.000396342 loss) | |
| I0525 01:21:54.826100 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.0134465 (* 0.0272727 = 0.000366724 loss) | |
| I0525 01:21:54.826114 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.0175038 (* 0.0272727 = 0.000477378 loss) | |
| I0525 01:21:54.826128 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.014018 (* 0.0272727 = 0.000382308 loss) | |
| I0525 01:21:54.826140 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.0816327 | |
| I0525 01:21:54.826153 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.125 | |
| I0525 01:21:54.826164 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0.125 | |
| I0525 01:21:54.826176 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0 | |
| I0525 01:21:54.826189 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.125 | |
| I0525 01:21:54.826200 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.25 | |
| I0525 01:21:54.826211 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.25 | |
| I0525 01:21:54.826223 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.625 | |
| I0525 01:21:54.826236 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.875 | |
| I0525 01:21:54.826247 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 0.875 | |
| I0525 01:21:54.826258 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 0.875 | |
| I0525 01:21:54.826270 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 01:21:54.826282 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 01:21:54.826293 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 01:21:54.826304 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 01:21:54.826315 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 01:21:54.826328 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 01:21:54.826349 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 01:21:54.826361 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 01:21:54.826373 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 01:21:54.826385 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 01:21:54.826396 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 01:21:54.826407 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 01:21:54.826419 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.715909 | |
| I0525 01:21:54.826431 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.204082 | |
| I0525 01:21:54.826444 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 4.38161 (* 1 = 4.38161 loss) | |
| I0525 01:21:54.826458 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.6397 (* 1 = 1.6397 loss) | |
| I0525 01:21:54.826472 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 3.85716 (* 0.0909091 = 0.350651 loss) | |
| I0525 01:21:54.826485 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 4.16593 (* 0.0909091 = 0.378721 loss) | |
| I0525 01:21:54.826499 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 4.03415 (* 0.0909091 = 0.366741 loss) | |
| I0525 01:21:54.826514 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.70777 (* 0.0909091 = 0.33707 loss) | |
| I0525 01:21:54.826526 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 3.58276 (* 0.0909091 = 0.325705 loss) | |
| I0525 01:21:54.826540 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 3.42536 (* 0.0909091 = 0.311396 loss) | |
| I0525 01:21:54.826553 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 2.17362 (* 0.0909091 = 0.197602 loss) | |
| I0525 01:21:54.826567 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.801666 (* 0.0909091 = 0.0728788 loss) | |
| I0525 01:21:54.826581 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 1.27326 (* 0.0909091 = 0.115751 loss) | |
| I0525 01:21:54.826594 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.933234 (* 0.0909091 = 0.0848395 loss) | |
| I0525 01:21:54.826608 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.193865 (* 0.0909091 = 0.0176241 loss) | |
| I0525 01:21:54.826622 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.185962 (* 0.0909091 = 0.0169057 loss) | |
| I0525 01:21:54.826635 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.166974 (* 0.0909091 = 0.0151795 loss) | |
| I0525 01:21:54.826649 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.0826608 (* 0.0909091 = 0.00751462 loss) | |
| I0525 01:21:54.826663 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.0643418 (* 0.0909091 = 0.00584926 loss) | |
| I0525 01:21:54.826676 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.0505717 (* 0.0909091 = 0.00459743 loss) | |
| I0525 01:21:54.826690 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.0123263 (* 0.0909091 = 0.00112057 loss) | |
| I0525 01:21:54.826704 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.00664821 (* 0.0909091 = 0.000604382 loss) | |
| I0525 01:21:54.826719 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00309728 (* 0.0909091 = 0.000281571 loss) | |
| I0525 01:21:54.826731 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00375836 (* 0.0909091 = 0.000341669 loss) | |
| I0525 01:21:54.826745 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00203365 (* 0.0909091 = 0.000184877 loss) | |
| I0525 01:21:54.826762 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.00190314 (* 0.0909091 = 0.000173013 loss) | |
| I0525 01:21:54.826776 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 01:21:54.826786 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 01:21:54.826797 5272 solver.cpp:245] Train net output #149: total_confidence = 1.11675e-07 | |
| I0525 01:21:54.826819 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 4.57212e-05 | |
| I0525 01:21:54.826833 5272 sgd_solver.cpp:106] Iteration 5500, lr = 0.001 | |
| I0525 01:23:22.183063 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 34.2565 > 30) by scale factor 0.875746 | |
| I0525 01:24:37.573218 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 31.1512 > 30) by scale factor 0.963044 | |
| I0525 01:26:52.223706 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 34.1043 > 30) by scale factor 0.879654 | |
| I0525 01:28:19.594398 5272 solver.cpp:229] Iteration 6000, loss = 11.6458 | |
| I0525 01:28:19.594529 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0425532 | |
| I0525 01:28:19.594549 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.125 | |
| I0525 01:28:19.594563 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0.125 | |
| I0525 01:28:19.594574 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0.125 | |
| I0525 01:28:19.594586 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.25 | |
| I0525 01:28:19.594599 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.25 | |
| I0525 01:28:19.594611 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.5 | |
| I0525 01:28:19.594624 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.5 | |
| I0525 01:28:19.594635 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.875 | |
| I0525 01:28:19.594647 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 0.875 | |
| I0525 01:28:19.594660 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 1 | |
| I0525 01:28:19.594672 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 01:28:19.594684 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 01:28:19.594696 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 01:28:19.594707 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 01:28:19.594719 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 01:28:19.594732 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 01:28:19.594743 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 01:28:19.594754 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 01:28:19.594766 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 01:28:19.594779 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 01:28:19.594790 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 01:28:19.594802 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 01:28:19.594815 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.744318 | |
| I0525 01:28:19.594826 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.148936 | |
| I0525 01:28:19.594842 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.6204 (* 0.3 = 1.08612 loss) | |
| I0525 01:28:19.594856 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.14304 (* 0.3 = 0.342911 loss) | |
| I0525 01:28:19.594871 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 4.12695 (* 0.0272727 = 0.112553 loss) | |
| I0525 01:28:19.594887 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.25012 (* 0.0272727 = 0.0886398 loss) | |
| I0525 01:28:19.594902 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.52438 (* 0.0272727 = 0.0961196 loss) | |
| I0525 01:28:19.594915 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.51415 (* 0.0272727 = 0.0958404 loss) | |
| I0525 01:28:19.594929 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 3.05499 (* 0.0272727 = 0.083318 loss) | |
| I0525 01:28:19.594944 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 2.43731 (* 0.0272727 = 0.0664722 loss) | |
| I0525 01:28:19.594956 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 2.44943 (* 0.0272727 = 0.0668025 loss) | |
| I0525 01:28:19.594970 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 0.614644 (* 0.0272727 = 0.016763 loss) | |
| I0525 01:28:19.594985 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.532718 (* 0.0272727 = 0.0145287 loss) | |
| I0525 01:28:19.595000 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.0448328 (* 0.0272727 = 0.00122271 loss) | |
| I0525 01:28:19.595013 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.0357748 (* 0.0272727 = 0.000975677 loss) | |
| I0525 01:28:19.595027 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.0491628 (* 0.0272727 = 0.0013408 loss) | |
| I0525 01:28:19.595041 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.0249795 (* 0.0272727 = 0.00068126 loss) | |
| I0525 01:28:19.595075 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.0133067 (* 0.0272727 = 0.000362909 loss) | |
| I0525 01:28:19.595091 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0192937 (* 0.0272727 = 0.000526192 loss) | |
| I0525 01:28:19.595105 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.0093134 (* 0.0272727 = 0.000254002 loss) | |
| I0525 01:28:19.595119 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.0102828 (* 0.0272727 = 0.00028044 loss) | |
| I0525 01:28:19.595132 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0245455 (* 0.0272727 = 0.000669424 loss) | |
| I0525 01:28:19.595146 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.0282189 (* 0.0272727 = 0.000769606 loss) | |
| I0525 01:28:19.595160 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.0182786 (* 0.0272727 = 0.000498507 loss) | |
| I0525 01:28:19.595175 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.0268492 (* 0.0272727 = 0.000732251 loss) | |
| I0525 01:28:19.595188 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.0229486 (* 0.0272727 = 0.000625871 loss) | |
| I0525 01:28:19.595201 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0 | |
| I0525 01:28:19.595213 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0 | |
| I0525 01:28:19.595226 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0 | |
| I0525 01:28:19.595237 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0 | |
| I0525 01:28:19.595248 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0.375 | |
| I0525 01:28:19.595260 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.25 | |
| I0525 01:28:19.595273 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.5 | |
| I0525 01:28:19.595283 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.5 | |
| I0525 01:28:19.595295 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.875 | |
| I0525 01:28:19.595307 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 0.875 | |
| I0525 01:28:19.595319 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 1 | |
| I0525 01:28:19.595330 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 01:28:19.595342 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 01:28:19.595353 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 01:28:19.595366 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 01:28:19.595376 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 01:28:19.595387 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 01:28:19.595399 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 01:28:19.595410 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 01:28:19.595422 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 01:28:19.595433 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 01:28:19.595445 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 01:28:19.595456 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 01:28:19.595468 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.727273 | |
| I0525 01:28:19.595479 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.12766 | |
| I0525 01:28:19.595494 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.54078 (* 0.3 = 1.06224 loss) | |
| I0525 01:28:19.595507 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.15198 (* 0.3 = 0.345593 loss) | |
| I0525 01:28:19.595521 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.96571 (* 0.0272727 = 0.108156 loss) | |
| I0525 01:28:19.595535 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 4.00419 (* 0.0272727 = 0.109205 loss) | |
| I0525 01:28:19.595563 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.92938 (* 0.0272727 = 0.107165 loss) | |
| I0525 01:28:19.595578 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.21865 (* 0.0272727 = 0.0877814 loss) | |
| I0525 01:28:19.595592 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 3.18609 (* 0.0272727 = 0.0868933 loss) | |
| I0525 01:28:19.595607 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 2.1694 (* 0.0272727 = 0.0591656 loss) | |
| I0525 01:28:19.595620 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 2.70447 (* 0.0272727 = 0.0737584 loss) | |
| I0525 01:28:19.595633 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 0.872938 (* 0.0272727 = 0.0238074 loss) | |
| I0525 01:28:19.595648 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.760215 (* 0.0272727 = 0.0207331 loss) | |
| I0525 01:28:19.595661 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.0151378 (* 0.0272727 = 0.00041285 loss) | |
| I0525 01:28:19.595675 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.014434 (* 0.0272727 = 0.000393655 loss) | |
| I0525 01:28:19.595690 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.0217488 (* 0.0272727 = 0.000593148 loss) | |
| I0525 01:28:19.595703 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.00969083 (* 0.0272727 = 0.000264295 loss) | |
| I0525 01:28:19.595717 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.0101362 (* 0.0272727 = 0.000276442 loss) | |
| I0525 01:28:19.595731 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.00463198 (* 0.0272727 = 0.000126327 loss) | |
| I0525 01:28:19.595744 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.00762395 (* 0.0272727 = 0.000207926 loss) | |
| I0525 01:28:19.595758 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.00534835 (* 0.0272727 = 0.000145864 loss) | |
| I0525 01:28:19.595772 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.00569893 (* 0.0272727 = 0.000155425 loss) | |
| I0525 01:28:19.595787 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.00596906 (* 0.0272727 = 0.000162792 loss) | |
| I0525 01:28:19.595800 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.00305128 (* 0.0272727 = 8.32166e-05 loss) | |
| I0525 01:28:19.595810 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.00458369 (* 0.0272727 = 0.00012501 loss) | |
| I0525 01:28:19.595820 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.00339497 (* 0.0272727 = 9.259e-05 loss) | |
| I0525 01:28:19.595834 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.0212766 | |
| I0525 01:28:19.595845 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0 | |
| I0525 01:28:19.595857 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0.125 | |
| I0525 01:28:19.595870 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0.125 | |
| I0525 01:28:19.595881 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.25 | |
| I0525 01:28:19.595892 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.25 | |
| I0525 01:28:19.595904 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.5 | |
| I0525 01:28:19.595916 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.5 | |
| I0525 01:28:19.595930 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.875 | |
| I0525 01:28:19.595942 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 0.875 | |
| I0525 01:28:19.595954 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 1 | |
| I0525 01:28:19.595966 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 01:28:19.595978 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 01:28:19.595988 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 01:28:19.596000 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 01:28:19.596011 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 01:28:19.596024 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 01:28:19.596045 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 01:28:19.596057 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 01:28:19.596070 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 01:28:19.596081 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 01:28:19.596091 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 01:28:19.596103 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 01:28:19.596114 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.732955 | |
| I0525 01:28:19.596127 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.12766 | |
| I0525 01:28:19.596140 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.4685 (* 1 = 3.4685 loss) | |
| I0525 01:28:19.596153 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.01921 (* 1 = 1.01921 loss) | |
| I0525 01:28:19.596168 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 3.54116 (* 0.0909091 = 0.321923 loss) | |
| I0525 01:28:19.596180 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.04179 (* 0.0909091 = 0.276527 loss) | |
| I0525 01:28:19.596194 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 2.89629 (* 0.0909091 = 0.263299 loss) | |
| I0525 01:28:19.596207 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.19986 (* 0.0909091 = 0.290896 loss) | |
| I0525 01:28:19.596220 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 2.76122 (* 0.0909091 = 0.25102 loss) | |
| I0525 01:28:19.596235 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 2.09655 (* 0.0909091 = 0.190595 loss) | |
| I0525 01:28:19.596247 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 2.47341 (* 0.0909091 = 0.224855 loss) | |
| I0525 01:28:19.596261 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.688439 (* 0.0909091 = 0.0625854 loss) | |
| I0525 01:28:19.596274 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.506619 (* 0.0909091 = 0.0460563 loss) | |
| I0525 01:28:19.596288 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.0386434 (* 0.0909091 = 0.00351304 loss) | |
| I0525 01:28:19.596302 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.0174129 (* 0.0909091 = 0.00158299 loss) | |
| I0525 01:28:19.596315 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.027014 (* 0.0909091 = 0.00245581 loss) | |
| I0525 01:28:19.596329 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.0181237 (* 0.0909091 = 0.00164761 loss) | |
| I0525 01:28:19.596343 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.0156944 (* 0.0909091 = 0.00142676 loss) | |
| I0525 01:28:19.596356 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.0159921 (* 0.0909091 = 0.00145383 loss) | |
| I0525 01:28:19.596370 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.00795425 (* 0.0909091 = 0.000723114 loss) | |
| I0525 01:28:19.596384 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.00478161 (* 0.0909091 = 0.000434691 loss) | |
| I0525 01:28:19.596397 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.00284472 (* 0.0909091 = 0.000258611 loss) | |
| I0525 01:28:19.596410 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00146289 (* 0.0909091 = 0.00013299 loss) | |
| I0525 01:28:19.596424 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00146997 (* 0.0909091 = 0.000133633 loss) | |
| I0525 01:28:19.596438 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00141295 (* 0.0909091 = 0.00012845 loss) | |
| I0525 01:28:19.596452 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.000765025 (* 0.0909091 = 6.95478e-05 loss) | |
| I0525 01:28:19.596464 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 01:28:19.596477 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 01:28:19.596487 5272 solver.cpp:245] Train net output #149: total_confidence = 6.92402e-05 | |
| I0525 01:28:19.596504 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 0.000671815 | |
| I0525 01:28:19.596520 5272 sgd_solver.cpp:106] Iteration 6000, lr = 0.001 | |
| I0525 01:30:43.841531 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 52.7029 > 30) by scale factor 0.569229 | |
| I0525 01:31:18.461650 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 35.6182 > 30) by scale factor 0.842266 | |
| I0525 01:32:09.255059 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 30.1813 > 30) by scale factor 0.993994 | |
| I0525 01:32:56.974020 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 32.8621 > 30) by scale factor 0.912906 | |
| I0525 01:34:44.327571 5272 solver.cpp:229] Iteration 6500, loss = 11.2361 | |
| I0525 01:34:44.327715 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.133333 | |
| I0525 01:34:44.327736 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.25 | |
| I0525 01:34:44.327749 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0525 01:34:44.327762 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0525 01:34:44.327775 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.25 | |
| I0525 01:34:44.327786 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.125 | |
| I0525 01:34:44.327800 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.25 | |
| I0525 01:34:44.327811 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.875 | |
| I0525 01:34:44.327823 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.875 | |
| I0525 01:34:44.327836 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 1 | |
| I0525 01:34:44.327847 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 1 | |
| I0525 01:34:44.327859 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 01:34:44.327872 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 01:34:44.327886 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 01:34:44.327898 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 01:34:44.327911 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 01:34:44.327924 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 01:34:44.327935 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 01:34:44.327947 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 01:34:44.327958 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 01:34:44.327970 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 01:34:44.327982 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 01:34:44.327993 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 01:34:44.328006 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.755682 | |
| I0525 01:34:44.328017 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.266667 | |
| I0525 01:34:44.328032 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.45076 (* 0.3 = 1.03523 loss) | |
| I0525 01:34:44.328047 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.15443 (* 0.3 = 0.34633 loss) | |
| I0525 01:34:44.328063 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.3358 (* 0.0272727 = 0.0909764 loss) | |
| I0525 01:34:44.328076 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.78348 (* 0.0272727 = 0.103186 loss) | |
| I0525 01:34:44.328090 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.83739 (* 0.0272727 = 0.104656 loss) | |
| I0525 01:34:44.328104 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.13074 (* 0.0272727 = 0.0853839 loss) | |
| I0525 01:34:44.328117 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 3.43036 (* 0.0272727 = 0.0935552 loss) | |
| I0525 01:34:44.328132 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 2.89787 (* 0.0272727 = 0.0790328 loss) | |
| I0525 01:34:44.328146 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 0.792108 (* 0.0272727 = 0.021603 loss) | |
| I0525 01:34:44.328161 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 0.817986 (* 0.0272727 = 0.0223087 loss) | |
| I0525 01:34:44.328176 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.173852 (* 0.0272727 = 0.00474141 loss) | |
| I0525 01:34:44.328189 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.103415 (* 0.0272727 = 0.0028204 loss) | |
| I0525 01:34:44.328204 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.112341 (* 0.0272727 = 0.00306384 loss) | |
| I0525 01:34:44.328218 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.036446 (* 0.0272727 = 0.000993982 loss) | |
| I0525 01:34:44.328233 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.0270094 (* 0.0272727 = 0.000736619 loss) | |
| I0525 01:34:44.328270 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.0250317 (* 0.0272727 = 0.000682681 loss) | |
| I0525 01:34:44.328285 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0127098 (* 0.0272727 = 0.00034663 loss) | |
| I0525 01:34:44.328299 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.0124264 (* 0.0272727 = 0.000338901 loss) | |
| I0525 01:34:44.328313 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.0096954 (* 0.0272727 = 0.00026442 loss) | |
| I0525 01:34:44.328328 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.00476268 (* 0.0272727 = 0.000129891 loss) | |
| I0525 01:34:44.328342 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.00552775 (* 0.0272727 = 0.000150757 loss) | |
| I0525 01:34:44.328356 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.00390874 (* 0.0272727 = 0.000106602 loss) | |
| I0525 01:34:44.328371 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.00294472 (* 0.0272727 = 8.03107e-05 loss) | |
| I0525 01:34:44.328384 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.00363078 (* 0.0272727 = 9.90213e-05 loss) | |
| I0525 01:34:44.328397 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.155556 | |
| I0525 01:34:44.328409 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0 | |
| I0525 01:34:44.328420 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0.125 | |
| I0525 01:34:44.328433 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0 | |
| I0525 01:34:44.328444 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0.375 | |
| I0525 01:34:44.328456 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.125 | |
| I0525 01:34:44.328469 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.375 | |
| I0525 01:34:44.328480 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.875 | |
| I0525 01:34:44.328492 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.875 | |
| I0525 01:34:44.328503 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 1 | |
| I0525 01:34:44.328516 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 1 | |
| I0525 01:34:44.328526 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 01:34:44.328538 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 01:34:44.328549 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 01:34:44.328560 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 01:34:44.328572 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 01:34:44.328583 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 01:34:44.328595 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 01:34:44.328606 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 01:34:44.328618 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 01:34:44.328629 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 01:34:44.328641 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 01:34:44.328652 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 01:34:44.328665 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.772727 | |
| I0525 01:34:44.328675 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.266667 | |
| I0525 01:34:44.328690 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.41064 (* 0.3 = 1.02319 loss) | |
| I0525 01:34:44.328703 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.07871 (* 0.3 = 0.323612 loss) | |
| I0525 01:34:44.328717 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.72189 (* 0.0272727 = 0.101506 loss) | |
| I0525 01:34:44.328734 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 3.84512 (* 0.0272727 = 0.104867 loss) | |
| I0525 01:34:44.328759 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.54188 (* 0.0272727 = 0.0965967 loss) | |
| I0525 01:34:44.328774 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.23111 (* 0.0272727 = 0.0881211 loss) | |
| I0525 01:34:44.328789 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 3.72981 (* 0.0272727 = 0.101722 loss) | |
| I0525 01:34:44.328802 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 3.21684 (* 0.0272727 = 0.0877319 loss) | |
| I0525 01:34:44.328816 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 0.959989 (* 0.0272727 = 0.0261815 loss) | |
| I0525 01:34:44.328830 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 1.04457 (* 0.0272727 = 0.0284882 loss) | |
| I0525 01:34:44.328845 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.192759 (* 0.0272727 = 0.00525706 loss) | |
| I0525 01:34:44.328858 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.178468 (* 0.0272727 = 0.0048673 loss) | |
| I0525 01:34:44.328872 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.0993469 (* 0.0272727 = 0.00270946 loss) | |
| I0525 01:34:44.328886 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.0654412 (* 0.0272727 = 0.00178476 loss) | |
| I0525 01:34:44.328902 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.150113 (* 0.0272727 = 0.004094 loss) | |
| I0525 01:34:44.328915 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.060924 (* 0.0272727 = 0.00166156 loss) | |
| I0525 01:34:44.328932 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.0358927 (* 0.0272727 = 0.000978892 loss) | |
| I0525 01:34:44.328946 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.0247097 (* 0.0272727 = 0.000673901 loss) | |
| I0525 01:34:44.328960 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.0160443 (* 0.0272727 = 0.000437573 loss) | |
| I0525 01:34:44.328974 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.00849203 (* 0.0272727 = 0.000231601 loss) | |
| I0525 01:34:44.328987 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.00995381 (* 0.0272727 = 0.000271468 loss) | |
| I0525 01:34:44.329001 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.00575897 (* 0.0272727 = 0.000157063 loss) | |
| I0525 01:34:44.329015 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.00569467 (* 0.0272727 = 0.000155309 loss) | |
| I0525 01:34:44.329028 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.0170782 (* 0.0272727 = 0.00046577 loss) | |
| I0525 01:34:44.329041 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.0888889 | |
| I0525 01:34:44.329053 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0 | |
| I0525 01:34:44.329064 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0 | |
| I0525 01:34:44.329077 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0 | |
| I0525 01:34:44.329087 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.25 | |
| I0525 01:34:44.329099 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.25 | |
| I0525 01:34:44.329112 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.375 | |
| I0525 01:34:44.329138 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.875 | |
| I0525 01:34:44.329151 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.875 | |
| I0525 01:34:44.329164 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 1 | |
| I0525 01:34:44.329175 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 1 | |
| I0525 01:34:44.329187 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 01:34:44.329200 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 01:34:44.329210 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 01:34:44.329222 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 01:34:44.329233 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 01:34:44.329246 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 01:34:44.329267 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 01:34:44.329282 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 01:34:44.329289 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 01:34:44.329298 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 01:34:44.329309 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 01:34:44.329320 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 01:34:44.329332 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.767045 | |
| I0525 01:34:44.329344 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.222222 | |
| I0525 01:34:44.329357 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.35219 (* 1 = 3.35219 loss) | |
| I0525 01:34:44.329371 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 0.988062 (* 1 = 0.988062 loss) | |
| I0525 01:34:44.329385 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 3.10535 (* 0.0909091 = 0.282305 loss) | |
| I0525 01:34:44.329398 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.40507 (* 0.0909091 = 0.309552 loss) | |
| I0525 01:34:44.329412 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.54959 (* 0.0909091 = 0.32269 loss) | |
| I0525 01:34:44.329426 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.03632 (* 0.0909091 = 0.276029 loss) | |
| I0525 01:34:44.329439 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 3.35887 (* 0.0909091 = 0.305352 loss) | |
| I0525 01:34:44.329452 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 2.60731 (* 0.0909091 = 0.237028 loss) | |
| I0525 01:34:44.329466 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 0.718144 (* 0.0909091 = 0.0652858 loss) | |
| I0525 01:34:44.329480 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.819801 (* 0.0909091 = 0.0745274 loss) | |
| I0525 01:34:44.329494 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.0457272 (* 0.0909091 = 0.00415702 loss) | |
| I0525 01:34:44.329509 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.0265212 (* 0.0909091 = 0.00241102 loss) | |
| I0525 01:34:44.329522 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.0336291 (* 0.0909091 = 0.0030572 loss) | |
| I0525 01:34:44.329536 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.0267228 (* 0.0909091 = 0.00242934 loss) | |
| I0525 01:34:44.329550 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.0171956 (* 0.0909091 = 0.00156324 loss) | |
| I0525 01:34:44.329565 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.0111593 (* 0.0909091 = 0.00101448 loss) | |
| I0525 01:34:44.329577 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.0125119 (* 0.0909091 = 0.00113745 loss) | |
| I0525 01:34:44.329591 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.00551288 (* 0.0909091 = 0.000501171 loss) | |
| I0525 01:34:44.329605 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.0039477 (* 0.0909091 = 0.000358882 loss) | |
| I0525 01:34:44.329619 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.00226272 (* 0.0909091 = 0.000205702 loss) | |
| I0525 01:34:44.329633 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00140612 (* 0.0909091 = 0.000127829 loss) | |
| I0525 01:34:44.329646 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00132471 (* 0.0909091 = 0.000120428 loss) | |
| I0525 01:34:44.329660 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.000658678 (* 0.0909091 = 5.98798e-05 loss) | |
| I0525 01:34:44.329674 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.000450713 (* 0.0909091 = 4.09739e-05 loss) | |
| I0525 01:34:44.329686 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 01:34:44.329697 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 01:34:44.329708 5272 solver.cpp:245] Train net output #149: total_confidence = 7.13444e-06 | |
| I0525 01:34:44.329730 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 0.000192928 | |
| I0525 01:34:44.329744 5272 sgd_solver.cpp:106] Iteration 6500, lr = 0.001 | |
| I0525 01:35:16.247216 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 37.6775 > 30) by scale factor 0.796232 | |
| I0525 01:35:32.398084 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 31.5412 > 30) by scale factor 0.951138 | |
| I0525 01:36:41.681705 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 31.9593 > 30) by scale factor 0.938694 | |
| I0525 01:37:53.278947 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 43.8261 > 30) by scale factor 0.684524 | |
| I0525 01:39:02.571017 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 30.9009 > 30) by scale factor 0.970847 | |
| I0525 01:40:32.632555 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 30.3401 > 30) by scale factor 0.988789 | |
| I0525 01:41:09.211504 5272 solver.cpp:229] Iteration 7000, loss = 11.1777 | |
| I0525 01:41:09.211596 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0196078 | |
| I0525 01:41:09.211614 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.125 | |
| I0525 01:41:09.211627 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0525 01:41:09.211639 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0.25 | |
| I0525 01:41:09.211652 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.375 | |
| I0525 01:41:09.211663 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.25 | |
| I0525 01:41:09.211675 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.25 | |
| I0525 01:41:09.211688 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.375 | |
| I0525 01:41:09.211699 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.625 | |
| I0525 01:41:09.211710 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 1 | |
| I0525 01:41:09.211722 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 1 | |
| I0525 01:41:09.211733 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 01:41:09.211745 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 01:41:09.211756 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 01:41:09.211767 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 01:41:09.211781 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 01:41:09.211805 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 01:41:09.211829 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 01:41:09.211843 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 01:41:09.211853 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 01:41:09.211865 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 01:41:09.211877 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 01:41:09.211889 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 01:41:09.211900 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.710227 | |
| I0525 01:41:09.211912 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.196078 | |
| I0525 01:41:09.211927 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.39343 (* 0.3 = 1.01803 loss) | |
| I0525 01:41:09.211942 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.10281 (* 0.3 = 0.330842 loss) | |
| I0525 01:41:09.211956 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.37448 (* 0.0272727 = 0.0920312 loss) | |
| I0525 01:41:09.211969 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.38246 (* 0.0272727 = 0.092249 loss) | |
| I0525 01:41:09.211983 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.71065 (* 0.0272727 = 0.101199 loss) | |
| I0525 01:41:09.211997 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 2.82135 (* 0.0272727 = 0.076946 loss) | |
| I0525 01:41:09.212010 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 2.98644 (* 0.0272727 = 0.0814485 loss) | |
| I0525 01:41:09.212024 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 3.09287 (* 0.0272727 = 0.084351 loss) | |
| I0525 01:41:09.212038 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 3.53398 (* 0.0272727 = 0.0963812 loss) | |
| I0525 01:41:09.212051 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 2.37116 (* 0.0272727 = 0.0646681 loss) | |
| I0525 01:41:09.212065 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.0150004 (* 0.0272727 = 0.000409103 loss) | |
| I0525 01:41:09.212080 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.0197339 (* 0.0272727 = 0.000538198 loss) | |
| I0525 01:41:09.212093 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.0107874 (* 0.0272727 = 0.000294201 loss) | |
| I0525 01:41:09.212107 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.00916167 (* 0.0272727 = 0.000249864 loss) | |
| I0525 01:41:09.212124 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.00963324 (* 0.0272727 = 0.000262725 loss) | |
| I0525 01:41:09.212157 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.00448462 (* 0.0272727 = 0.000122308 loss) | |
| I0525 01:41:09.212172 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.00602586 (* 0.0272727 = 0.000164342 loss) | |
| I0525 01:41:09.212187 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.00489558 (* 0.0272727 = 0.000133516 loss) | |
| I0525 01:41:09.212200 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.00264398 (* 0.0272727 = 7.21087e-05 loss) | |
| I0525 01:41:09.212213 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.00129137 (* 0.0272727 = 3.52192e-05 loss) | |
| I0525 01:41:09.212227 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.00271744 (* 0.0272727 = 7.41119e-05 loss) | |
| I0525 01:41:09.212241 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.00293754 (* 0.0272727 = 8.01148e-05 loss) | |
| I0525 01:41:09.212255 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.00190446 (* 0.0272727 = 5.19399e-05 loss) | |
| I0525 01:41:09.212268 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.000886508 (* 0.0272727 = 2.41775e-05 loss) | |
| I0525 01:41:09.212280 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0 | |
| I0525 01:41:09.212292 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0 | |
| I0525 01:41:09.212303 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0.125 | |
| I0525 01:41:09.212314 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0 | |
| I0525 01:41:09.212327 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0.25 | |
| I0525 01:41:09.212337 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.25 | |
| I0525 01:41:09.212349 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.25 | |
| I0525 01:41:09.212362 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.375 | |
| I0525 01:41:09.212373 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.625 | |
| I0525 01:41:09.212384 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 1 | |
| I0525 01:41:09.212395 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 1 | |
| I0525 01:41:09.212407 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 01:41:09.212419 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 01:41:09.212430 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 01:41:09.212440 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 01:41:09.212451 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 01:41:09.212462 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 01:41:09.212474 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 01:41:09.212486 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 01:41:09.212496 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 01:41:09.212507 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 01:41:09.212518 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 01:41:09.212529 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 01:41:09.212540 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.710227 | |
| I0525 01:41:09.212553 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.156863 | |
| I0525 01:41:09.212565 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.47728 (* 0.3 = 1.04318 loss) | |
| I0525 01:41:09.212579 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.09801 (* 0.3 = 0.329402 loss) | |
| I0525 01:41:09.212592 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.32217 (* 0.0272727 = 0.0906046 loss) | |
| I0525 01:41:09.212606 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 3.69972 (* 0.0272727 = 0.100901 loss) | |
| I0525 01:41:09.212630 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.39013 (* 0.0272727 = 0.0924582 loss) | |
| I0525 01:41:09.212644 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.27105 (* 0.0272727 = 0.0892104 loss) | |
| I0525 01:41:09.212658 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 3.13515 (* 0.0272727 = 0.0855041 loss) | |
| I0525 01:41:09.212671 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 3.51957 (* 0.0272727 = 0.0959884 loss) | |
| I0525 01:41:09.212684 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 3.30441 (* 0.0272727 = 0.0901203 loss) | |
| I0525 01:41:09.212698 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 2.91285 (* 0.0272727 = 0.0794414 loss) | |
| I0525 01:41:09.212712 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.0204903 (* 0.0272727 = 0.000558826 loss) | |
| I0525 01:41:09.212725 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.0145741 (* 0.0272727 = 0.000397476 loss) | |
| I0525 01:41:09.212739 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.0110597 (* 0.0272727 = 0.000301628 loss) | |
| I0525 01:41:09.212752 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.0118365 (* 0.0272727 = 0.000322814 loss) | |
| I0525 01:41:09.212766 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.00944735 (* 0.0272727 = 0.000257655 loss) | |
| I0525 01:41:09.212779 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.00581357 (* 0.0272727 = 0.000158552 loss) | |
| I0525 01:41:09.212793 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.00653237 (* 0.0272727 = 0.000178155 loss) | |
| I0525 01:41:09.212807 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.00480134 (* 0.0272727 = 0.000130946 loss) | |
| I0525 01:41:09.212821 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.00313386 (* 0.0272727 = 8.54688e-05 loss) | |
| I0525 01:41:09.212834 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.00282644 (* 0.0272727 = 7.70848e-05 loss) | |
| I0525 01:41:09.212848 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.00308487 (* 0.0272727 = 8.41327e-05 loss) | |
| I0525 01:41:09.212864 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.00252112 (* 0.0272727 = 6.87578e-05 loss) | |
| I0525 01:41:09.212879 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.00204601 (* 0.0272727 = 5.58003e-05 loss) | |
| I0525 01:41:09.212893 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.00272406 (* 0.0272727 = 7.42925e-05 loss) | |
| I0525 01:41:09.212905 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.0784314 | |
| I0525 01:41:09.212918 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0 | |
| I0525 01:41:09.212929 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0.125 | |
| I0525 01:41:09.212939 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0 | |
| I0525 01:41:09.212951 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.125 | |
| I0525 01:41:09.212962 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.25 | |
| I0525 01:41:09.212975 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.25 | |
| I0525 01:41:09.212985 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.375 | |
| I0525 01:41:09.212997 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.625 | |
| I0525 01:41:09.213008 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 1 | |
| I0525 01:41:09.213021 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 1 | |
| I0525 01:41:09.213032 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 01:41:09.213042 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 01:41:09.213054 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 01:41:09.213065 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 01:41:09.213076 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 01:41:09.213088 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 01:41:09.213107 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 01:41:09.213135 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 01:41:09.213150 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 01:41:09.213161 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 01:41:09.213172 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 01:41:09.213183 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 01:41:09.213194 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.721591 | |
| I0525 01:41:09.213207 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.294118 | |
| I0525 01:41:09.213220 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.05322 (* 1 = 3.05322 loss) | |
| I0525 01:41:09.213233 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 0.966724 (* 1 = 0.966724 loss) | |
| I0525 01:41:09.213248 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 2.98365 (* 0.0909091 = 0.271241 loss) | |
| I0525 01:41:09.213261 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.30543 (* 0.0909091 = 0.300493 loss) | |
| I0525 01:41:09.213274 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.15522 (* 0.0909091 = 0.286839 loss) | |
| I0525 01:41:09.213289 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.12256 (* 0.0909091 = 0.283869 loss) | |
| I0525 01:41:09.213301 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 2.68687 (* 0.0909091 = 0.244261 loss) | |
| I0525 01:41:09.213315 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 3.15187 (* 0.0909091 = 0.286533 loss) | |
| I0525 01:41:09.213330 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 3.3449 (* 0.0909091 = 0.304082 loss) | |
| I0525 01:41:09.213343 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 2.55492 (* 0.0909091 = 0.232266 loss) | |
| I0525 01:41:09.213353 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.00810991 (* 0.0909091 = 0.000737264 loss) | |
| I0525 01:41:09.213362 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.00804949 (* 0.0909091 = 0.000731772 loss) | |
| I0525 01:41:09.213377 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.00493125 (* 0.0909091 = 0.000448296 loss) | |
| I0525 01:41:09.213392 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.00528493 (* 0.0909091 = 0.000480448 loss) | |
| I0525 01:41:09.213404 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.00546518 (* 0.0909091 = 0.000496835 loss) | |
| I0525 01:41:09.213418 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.00435257 (* 0.0909091 = 0.000395688 loss) | |
| I0525 01:41:09.213433 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.0031808 (* 0.0909091 = 0.000289164 loss) | |
| I0525 01:41:09.213445 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.00174619 (* 0.0909091 = 0.000158745 loss) | |
| I0525 01:41:09.213459 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.00248791 (* 0.0909091 = 0.000226174 loss) | |
| I0525 01:41:09.213472 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.00136565 (* 0.0909091 = 0.00012415 loss) | |
| I0525 01:41:09.213486 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.000859398 (* 0.0909091 = 7.81271e-05 loss) | |
| I0525 01:41:09.213500 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.000562007 (* 0.0909091 = 5.10916e-05 loss) | |
| I0525 01:41:09.213515 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.000412822 (* 0.0909091 = 3.75292e-05 loss) | |
| I0525 01:41:09.213527 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.000325635 (* 0.0909091 = 2.96032e-05 loss) | |
| I0525 01:41:09.213539 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 01:41:09.213551 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 01:41:09.213562 5272 solver.cpp:245] Train net output #149: total_confidence = 2.85074e-06 | |
| I0525 01:41:09.213584 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 0.000257008 | |
| I0525 01:41:09.213598 5272 sgd_solver.cpp:106] Iteration 7000, lr = 0.001 | |
| I0525 01:42:31.897976 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 54.6448 > 30) by scale factor 0.549 | |
| I0525 01:44:15.763684 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 40.1021 > 30) by scale factor 0.74809 | |
| I0525 01:47:34.059463 5272 solver.cpp:229] Iteration 7500, loss = 11.139 | |
| I0525 01:47:34.059594 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.107143 | |
| I0525 01:47:34.059615 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.125 | |
| I0525 01:47:34.059628 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0.125 | |
| I0525 01:47:34.059641 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0.125 | |
| I0525 01:47:34.059654 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.125 | |
| I0525 01:47:34.059666 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0 | |
| I0525 01:47:34.059679 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.125 | |
| I0525 01:47:34.059690 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.5 | |
| I0525 01:47:34.059702 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.75 | |
| I0525 01:47:34.059715 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 0.875 | |
| I0525 01:47:34.059727 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 0.875 | |
| I0525 01:47:34.059739 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 0.875 | |
| I0525 01:47:34.059751 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 01:47:34.059763 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 01:47:34.059774 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 01:47:34.059787 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 01:47:34.059798 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 01:47:34.059810 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 01:47:34.059823 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 01:47:34.059834 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 01:47:34.059846 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 01:47:34.059857 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 01:47:34.059870 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 01:47:34.059883 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.698864 | |
| I0525 01:47:34.059896 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.196429 | |
| I0525 01:47:34.059912 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.70661 (* 0.3 = 1.11198 loss) | |
| I0525 01:47:34.059926 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.31571 (* 0.3 = 0.394713 loss) | |
| I0525 01:47:34.059940 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.83821 (* 0.0272727 = 0.104679 loss) | |
| I0525 01:47:34.059954 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.47871 (* 0.0272727 = 0.094874 loss) | |
| I0525 01:47:34.059968 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.73681 (* 0.0272727 = 0.101913 loss) | |
| I0525 01:47:34.059981 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 4.05485 (* 0.0272727 = 0.110587 loss) | |
| I0525 01:47:34.059995 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 4.32254 (* 0.0272727 = 0.117888 loss) | |
| I0525 01:47:34.060009 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 4.51899 (* 0.0272727 = 0.123245 loss) | |
| I0525 01:47:34.060022 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 2.38146 (* 0.0272727 = 0.0649489 loss) | |
| I0525 01:47:34.060036 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 1.50198 (* 0.0272727 = 0.040963 loss) | |
| I0525 01:47:34.060050 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.749451 (* 0.0272727 = 0.0204396 loss) | |
| I0525 01:47:34.060063 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.619563 (* 0.0272727 = 0.0168972 loss) | |
| I0525 01:47:34.060077 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.576313 (* 0.0272727 = 0.0157176 loss) | |
| I0525 01:47:34.060092 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.0897589 (* 0.0272727 = 0.00244797 loss) | |
| I0525 01:47:34.060106 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.0759434 (* 0.0272727 = 0.00207118 loss) | |
| I0525 01:47:34.060139 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.0595898 (* 0.0272727 = 0.00162518 loss) | |
| I0525 01:47:34.060155 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0434796 (* 0.0272727 = 0.00118581 loss) | |
| I0525 01:47:34.060169 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.0372218 (* 0.0272727 = 0.00101514 loss) | |
| I0525 01:47:34.060183 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.0540745 (* 0.0272727 = 0.00147476 loss) | |
| I0525 01:47:34.060197 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0360407 (* 0.0272727 = 0.000982928 loss) | |
| I0525 01:47:34.060211 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.0362794 (* 0.0272727 = 0.000989438 loss) | |
| I0525 01:47:34.060225 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.0241073 (* 0.0272727 = 0.000657472 loss) | |
| I0525 01:47:34.060240 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.0283435 (* 0.0272727 = 0.000773003 loss) | |
| I0525 01:47:34.060253 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.039574 (* 0.0272727 = 0.00107929 loss) | |
| I0525 01:47:34.060266 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.0892857 | |
| I0525 01:47:34.060278 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0 | |
| I0525 01:47:34.060289 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0 | |
| I0525 01:47:34.060302 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0.125 | |
| I0525 01:47:34.060313 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0 | |
| I0525 01:47:34.060324 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0 | |
| I0525 01:47:34.060340 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.125 | |
| I0525 01:47:34.060364 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.5 | |
| I0525 01:47:34.060384 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.75 | |
| I0525 01:47:34.060397 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 0.875 | |
| I0525 01:47:34.060410 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 0.875 | |
| I0525 01:47:34.060421 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 0.875 | |
| I0525 01:47:34.060432 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 01:47:34.060444 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 01:47:34.060456 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 01:47:34.060467 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 01:47:34.060478 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 01:47:34.060489 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 01:47:34.060500 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 01:47:34.060513 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 01:47:34.060523 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 01:47:34.060534 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 01:47:34.060546 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 01:47:34.060557 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.710227 | |
| I0525 01:47:34.060570 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.267857 | |
| I0525 01:47:34.060583 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.73421 (* 0.3 = 1.12026 loss) | |
| I0525 01:47:34.060597 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.22424 (* 0.3 = 0.367273 loss) | |
| I0525 01:47:34.060616 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 4.18054 (* 0.0272727 = 0.114015 loss) | |
| I0525 01:47:34.060631 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 3.27276 (* 0.0272727 = 0.0892572 loss) | |
| I0525 01:47:34.060657 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.53983 (* 0.0272727 = 0.096541 loss) | |
| I0525 01:47:34.060672 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.96197 (* 0.0272727 = 0.108054 loss) | |
| I0525 01:47:34.060685 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 3.97925 (* 0.0272727 = 0.108525 loss) | |
| I0525 01:47:34.060699 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 4.50442 (* 0.0272727 = 0.122848 loss) | |
| I0525 01:47:34.060713 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 2.64991 (* 0.0272727 = 0.0722704 loss) | |
| I0525 01:47:34.060726 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 1.7004 (* 0.0272727 = 0.0463747 loss) | |
| I0525 01:47:34.060739 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.707858 (* 0.0272727 = 0.0193052 loss) | |
| I0525 01:47:34.060753 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.5563 (* 0.0272727 = 0.0151718 loss) | |
| I0525 01:47:34.060767 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.878436 (* 0.0272727 = 0.0239573 loss) | |
| I0525 01:47:34.060781 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.109182 (* 0.0272727 = 0.00297768 loss) | |
| I0525 01:47:34.060796 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.0460682 (* 0.0272727 = 0.00125641 loss) | |
| I0525 01:47:34.060808 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.0536117 (* 0.0272727 = 0.00146214 loss) | |
| I0525 01:47:34.060822 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.0390222 (* 0.0272727 = 0.00106424 loss) | |
| I0525 01:47:34.060837 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.0453714 (* 0.0272727 = 0.0012374 loss) | |
| I0525 01:47:34.060850 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.0338976 (* 0.0272727 = 0.000924479 loss) | |
| I0525 01:47:34.060864 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.0419012 (* 0.0272727 = 0.00114276 loss) | |
| I0525 01:47:34.060878 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.0316819 (* 0.0272727 = 0.000864053 loss) | |
| I0525 01:47:34.060892 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.0328677 (* 0.0272727 = 0.000896391 loss) | |
| I0525 01:47:34.060905 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.0127353 (* 0.0272727 = 0.000347327 loss) | |
| I0525 01:47:34.060920 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.0248026 (* 0.0272727 = 0.000676434 loss) | |
| I0525 01:47:34.060933 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.0892857 | |
| I0525 01:47:34.060946 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.125 | |
| I0525 01:47:34.060958 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0.125 | |
| I0525 01:47:34.060969 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0 | |
| I0525 01:47:34.060981 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0 | |
| I0525 01:47:34.060992 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0 | |
| I0525 01:47:34.061003 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.125 | |
| I0525 01:47:34.061015 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.5 | |
| I0525 01:47:34.061027 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.75 | |
| I0525 01:47:34.061038 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 0.875 | |
| I0525 01:47:34.061050 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 0.875 | |
| I0525 01:47:34.061061 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 0.875 | |
| I0525 01:47:34.061074 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 01:47:34.061085 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 01:47:34.061096 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 01:47:34.061107 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 01:47:34.061131 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 01:47:34.061158 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 01:47:34.061172 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 01:47:34.061183 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 01:47:34.061195 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 01:47:34.061206 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 01:47:34.061218 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 01:47:34.061229 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.710227 | |
| I0525 01:47:34.061241 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.285714 | |
| I0525 01:47:34.061255 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.4727 (* 1 = 3.4727 loss) | |
| I0525 01:47:34.061269 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.14198 (* 1 = 1.14198 loss) | |
| I0525 01:47:34.061282 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 3.16414 (* 0.0909091 = 0.287649 loss) | |
| I0525 01:47:34.061296 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.0435 (* 0.0909091 = 0.276682 loss) | |
| I0525 01:47:34.061310 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.17354 (* 0.0909091 = 0.288504 loss) | |
| I0525 01:47:34.061323 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.99009 (* 0.0909091 = 0.362736 loss) | |
| I0525 01:47:34.061336 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 3.73101 (* 0.0909091 = 0.339183 loss) | |
| I0525 01:47:34.061350 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 3.84399 (* 0.0909091 = 0.349454 loss) | |
| I0525 01:47:34.061364 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 2.11593 (* 0.0909091 = 0.192357 loss) | |
| I0525 01:47:34.061374 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 1.85874 (* 0.0909091 = 0.168976 loss) | |
| I0525 01:47:34.061383 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.677261 (* 0.0909091 = 0.0615691 loss) | |
| I0525 01:47:34.061393 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.765279 (* 0.0909091 = 0.0695708 loss) | |
| I0525 01:47:34.061408 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.832122 (* 0.0909091 = 0.0756475 loss) | |
| I0525 01:47:34.061422 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.0261005 (* 0.0909091 = 0.00237277 loss) | |
| I0525 01:47:34.061436 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.0292434 (* 0.0909091 = 0.00265849 loss) | |
| I0525 01:47:34.061450 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.0178083 (* 0.0909091 = 0.00161894 loss) | |
| I0525 01:47:34.061463 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.0195543 (* 0.0909091 = 0.00177767 loss) | |
| I0525 01:47:34.061477 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.0164549 (* 0.0909091 = 0.0014959 loss) | |
| I0525 01:47:34.061491 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.0202718 (* 0.0909091 = 0.00184289 loss) | |
| I0525 01:47:34.061506 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.0129819 (* 0.0909091 = 0.00118017 loss) | |
| I0525 01:47:34.061519 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.0119746 (* 0.0909091 = 0.0010886 loss) | |
| I0525 01:47:34.061533 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00923158 (* 0.0909091 = 0.000839234 loss) | |
| I0525 01:47:34.061547 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00720708 (* 0.0909091 = 0.000655189 loss) | |
| I0525 01:47:34.061560 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.0119367 (* 0.0909091 = 0.00108516 loss) | |
| I0525 01:47:34.061573 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 01:47:34.061584 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 01:47:34.061595 5272 solver.cpp:245] Train net output #149: total_confidence = 3.45977e-05 | |
| I0525 01:47:34.061616 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 0.00125718 | |
| I0525 01:47:34.061631 5272 sgd_solver.cpp:106] Iteration 7500, lr = 0.001 | |
| I0525 01:49:56.031536 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 39.4072 > 30) by scale factor 0.761283 | |
| I0525 01:49:58.343458 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 56.848 > 30) by scale factor 0.527723 | |
| I0525 01:50:45.273576 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 32.1743 > 30) by scale factor 0.932423 | |
| I0525 01:52:23.794315 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 40.4524 > 30) by scale factor 0.741612 | |
| I0525 01:52:26.876194 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 34.9805 > 30) by scale factor 0.85762 | |
| I0525 01:53:58.859163 5272 solver.cpp:229] Iteration 8000, loss = 10.8864 | |
| I0525 01:53:58.859300 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0535714 | |
| I0525 01:53:58.859321 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0 | |
| I0525 01:53:58.859335 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0.125 | |
| I0525 01:53:58.859349 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0.125 | |
| I0525 01:53:58.859361 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.375 | |
| I0525 01:53:58.859374 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.375 | |
| I0525 01:53:58.859385 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.5 | |
| I0525 01:53:58.859397 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.5 | |
| I0525 01:53:58.859410 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.75 | |
| I0525 01:53:58.859421 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 0.75 | |
| I0525 01:53:58.859433 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 0.875 | |
| I0525 01:53:58.859447 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 0.875 | |
| I0525 01:53:58.859458 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 0.875 | |
| I0525 01:53:58.859470 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 0.875 | |
| I0525 01:53:58.859483 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 0.875 | |
| I0525 01:53:58.859494 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 0.875 | |
| I0525 01:53:58.859506 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 0.875 | |
| I0525 01:53:58.859518 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 0.875 | |
| I0525 01:53:58.859529 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 0.875 | |
| I0525 01:53:58.859541 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 01:53:58.859554 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 01:53:58.859565 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 01:53:58.859576 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 01:53:58.859588 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.6875 | |
| I0525 01:53:58.859601 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.214286 | |
| I0525 01:53:58.859616 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.78388 (* 0.3 = 1.13516 loss) | |
| I0525 01:53:58.859630 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.38411 (* 0.3 = 0.415233 loss) | |
| I0525 01:53:58.859645 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.373 (* 0.0272727 = 0.0919908 loss) | |
| I0525 01:53:58.859659 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.49751 (* 0.0272727 = 0.0953867 loss) | |
| I0525 01:53:58.859673 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.61831 (* 0.0272727 = 0.0986813 loss) | |
| I0525 01:53:58.859686 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.03267 (* 0.0272727 = 0.0827092 loss) | |
| I0525 01:53:58.859700 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 2.57303 (* 0.0272727 = 0.0701736 loss) | |
| I0525 01:53:58.859714 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 2.18166 (* 0.0272727 = 0.0594998 loss) | |
| I0525 01:53:58.859729 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 2.60866 (* 0.0272727 = 0.0711453 loss) | |
| I0525 01:53:58.859741 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 1.40907 (* 0.0272727 = 0.0384292 loss) | |
| I0525 01:53:58.859755 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 1.16809 (* 0.0272727 = 0.0318569 loss) | |
| I0525 01:53:58.859769 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.876062 (* 0.0272727 = 0.0238926 loss) | |
| I0525 01:53:58.859783 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.771861 (* 0.0272727 = 0.0210508 loss) | |
| I0525 01:53:58.859797 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 1.11626 (* 0.0272727 = 0.0304434 loss) | |
| I0525 01:53:58.859832 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 1.14765 (* 0.0272727 = 0.0312997 loss) | |
| I0525 01:53:58.859846 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 1.04524 (* 0.0272727 = 0.0285065 loss) | |
| I0525 01:53:58.859860 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 1.20448 (* 0.0272727 = 0.0328496 loss) | |
| I0525 01:53:58.859877 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.88867 (* 0.0272727 = 0.0242364 loss) | |
| I0525 01:53:58.859892 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 1.04917 (* 0.0272727 = 0.0286137 loss) | |
| I0525 01:53:58.859906 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 1.03483 (* 0.0272727 = 0.0282227 loss) | |
| I0525 01:53:58.859920 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.00314976 (* 0.0272727 = 8.59024e-05 loss) | |
| I0525 01:53:58.859935 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.00195826 (* 0.0272727 = 5.34072e-05 loss) | |
| I0525 01:53:58.859948 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.0019175 (* 0.0272727 = 5.22955e-05 loss) | |
| I0525 01:53:58.859962 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.00178133 (* 0.0272727 = 4.85817e-05 loss) | |
| I0525 01:53:58.859975 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.0892857 | |
| I0525 01:53:58.859987 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0.125 | |
| I0525 01:53:58.859999 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0 | |
| I0525 01:53:58.860011 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0 | |
| I0525 01:53:58.860023 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0.25 | |
| I0525 01:53:58.860034 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.5 | |
| I0525 01:53:58.860045 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.5 | |
| I0525 01:53:58.860057 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.5 | |
| I0525 01:53:58.860069 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.75 | |
| I0525 01:53:58.860080 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 0.75 | |
| I0525 01:53:58.860092 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 0.875 | |
| I0525 01:53:58.860105 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 0.875 | |
| I0525 01:53:58.860116 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 0.875 | |
| I0525 01:53:58.860127 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 0.875 | |
| I0525 01:53:58.860138 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 0.875 | |
| I0525 01:53:58.860151 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 0.875 | |
| I0525 01:53:58.860162 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 0.875 | |
| I0525 01:53:58.860173 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 0.875 | |
| I0525 01:53:58.860185 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 0.875 | |
| I0525 01:53:58.860198 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 01:53:58.860208 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 01:53:58.860220 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 01:53:58.860229 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 01:53:58.860235 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.693182 | |
| I0525 01:53:58.860249 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.25 | |
| I0525 01:53:58.860262 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.64118 (* 0.3 = 1.09236 loss) | |
| I0525 01:53:58.860276 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.36725 (* 0.3 = 0.410175 loss) | |
| I0525 01:53:58.860291 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.29495 (* 0.0272727 = 0.0898624 loss) | |
| I0525 01:53:58.860304 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 4.51058 (* 0.0272727 = 0.123016 loss) | |
| I0525 01:53:58.860333 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.92163 (* 0.0272727 = 0.106954 loss) | |
| I0525 01:53:58.860348 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.13927 (* 0.0272727 = 0.0856165 loss) | |
| I0525 01:53:58.860363 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 2.73348 (* 0.0272727 = 0.0745494 loss) | |
| I0525 01:53:58.860375 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 2.41893 (* 0.0272727 = 0.0659707 loss) | |
| I0525 01:53:58.860389 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 2.39883 (* 0.0272727 = 0.0654227 loss) | |
| I0525 01:53:58.860402 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 1.36857 (* 0.0272727 = 0.0373246 loss) | |
| I0525 01:53:58.860416 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.950654 (* 0.0272727 = 0.0259269 loss) | |
| I0525 01:53:58.860430 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.921312 (* 0.0272727 = 0.0251267 loss) | |
| I0525 01:53:58.860443 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.952763 (* 0.0272727 = 0.0259844 loss) | |
| I0525 01:53:58.860457 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 1.04418 (* 0.0272727 = 0.0284776 loss) | |
| I0525 01:53:58.860471 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 1.11922 (* 0.0272727 = 0.0305242 loss) | |
| I0525 01:53:58.860484 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.85363 (* 0.0272727 = 0.0232808 loss) | |
| I0525 01:53:58.860498 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 1.09577 (* 0.0272727 = 0.0298846 loss) | |
| I0525 01:53:58.860512 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 1.18136 (* 0.0272727 = 0.0322188 loss) | |
| I0525 01:53:58.860525 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.930875 (* 0.0272727 = 0.0253875 loss) | |
| I0525 01:53:58.860539 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 1.17568 (* 0.0272727 = 0.032064 loss) | |
| I0525 01:53:58.860553 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.0240429 (* 0.0272727 = 0.000655717 loss) | |
| I0525 01:53:58.860566 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.00897186 (* 0.0272727 = 0.000244687 loss) | |
| I0525 01:53:58.860580 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.00976135 (* 0.0272727 = 0.000266219 loss) | |
| I0525 01:53:58.860594 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.015623 (* 0.0272727 = 0.000426082 loss) | |
| I0525 01:53:58.860606 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.125 | |
| I0525 01:53:58.860618 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.125 | |
| I0525 01:53:58.860630 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0.125 | |
| I0525 01:53:58.860641 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0 | |
| I0525 01:53:58.860653 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.125 | |
| I0525 01:53:58.860664 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.25 | |
| I0525 01:53:58.860677 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.5 | |
| I0525 01:53:58.860688 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.625 | |
| I0525 01:53:58.860699 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.75 | |
| I0525 01:53:58.860712 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 0.75 | |
| I0525 01:53:58.860723 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 0.875 | |
| I0525 01:53:58.860733 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 0.875 | |
| I0525 01:53:58.860745 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 0.875 | |
| I0525 01:53:58.860757 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 0.875 | |
| I0525 01:53:58.860769 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 0.875 | |
| I0525 01:53:58.860780 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 0.875 | |
| I0525 01:53:58.860792 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 0.875 | |
| I0525 01:53:58.860813 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 0.875 | |
| I0525 01:53:58.860826 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 0.875 | |
| I0525 01:53:58.860838 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 01:53:58.860851 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 01:53:58.860862 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 01:53:58.860873 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 01:53:58.860885 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.704545 | |
| I0525 01:53:58.860896 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.339286 | |
| I0525 01:53:58.860910 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.37032 (* 1 = 3.37032 loss) | |
| I0525 01:53:58.860924 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.33828 (* 1 = 1.33828 loss) | |
| I0525 01:53:58.860941 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 3.16327 (* 0.0909091 = 0.28757 loss) | |
| I0525 01:53:58.860955 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.29743 (* 0.0909091 = 0.299767 loss) | |
| I0525 01:53:58.860970 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.34765 (* 0.0909091 = 0.304332 loss) | |
| I0525 01:53:58.860982 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 2.92708 (* 0.0909091 = 0.266098 loss) | |
| I0525 01:53:58.860996 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 2.5584 (* 0.0909091 = 0.232582 loss) | |
| I0525 01:53:58.861006 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 2.10811 (* 0.0909091 = 0.191647 loss) | |
| I0525 01:53:58.861016 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 2.13003 (* 0.0909091 = 0.193639 loss) | |
| I0525 01:53:58.861029 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 1.21617 (* 0.0909091 = 0.110561 loss) | |
| I0525 01:53:58.861043 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.898435 (* 0.0909091 = 0.0816759 loss) | |
| I0525 01:53:58.861057 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.850684 (* 0.0909091 = 0.0773349 loss) | |
| I0525 01:53:58.861071 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.82365 (* 0.0909091 = 0.0748773 loss) | |
| I0525 01:53:58.861085 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 1.0669 (* 0.0909091 = 0.0969913 loss) | |
| I0525 01:53:58.861099 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.821967 (* 0.0909091 = 0.0747242 loss) | |
| I0525 01:53:58.861112 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.759522 (* 0.0909091 = 0.0690475 loss) | |
| I0525 01:53:58.861140 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 1.13005 (* 0.0909091 = 0.102732 loss) | |
| I0525 01:53:58.861156 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.68099 (* 0.0909091 = 0.0619082 loss) | |
| I0525 01:53:58.861169 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.913378 (* 0.0909091 = 0.0830344 loss) | |
| I0525 01:53:58.861183 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 1.07236 (* 0.0909091 = 0.0974871 loss) | |
| I0525 01:53:58.861197 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00341045 (* 0.0909091 = 0.000310041 loss) | |
| I0525 01:53:58.861212 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00107248 (* 0.0909091 = 9.74978e-05 loss) | |
| I0525 01:53:58.861225 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00075675 (* 0.0909091 = 6.87954e-05 loss) | |
| I0525 01:53:58.861238 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.000565158 (* 0.0909091 = 5.1378e-05 loss) | |
| I0525 01:53:58.861250 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 01:53:58.861263 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 01:53:58.861274 5272 solver.cpp:245] Train net output #149: total_confidence = 4.91878e-06 | |
| I0525 01:53:58.861295 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 9.80873e-05 | |
| I0525 01:53:58.861310 5272 sgd_solver.cpp:106] Iteration 8000, lr = 0.001 | |
| I0525 01:54:09.996558 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 32.7448 > 30) by scale factor 0.916177 | |
| I0525 01:54:46.928495 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 40.3652 > 30) by scale factor 0.743215 | |
| I0525 01:55:52.398910 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 36.2681 > 30) by scale factor 0.827173 | |
| I0525 01:57:37.858790 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 32.8314 > 30) by scale factor 0.913758 | |
| I0525 01:59:34.024374 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 46.7965 > 30) by scale factor 0.641073 | |
| I0525 02:00:23.710636 5272 solver.cpp:229] Iteration 8500, loss = 10.7341 | |
| I0525 02:00:23.710764 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0 | |
| I0525 02:00:23.710784 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0 | |
| I0525 02:00:23.710796 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0.125 | |
| I0525 02:00:23.710809 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0.125 | |
| I0525 02:00:23.710821 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.125 | |
| I0525 02:00:23.710834 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.25 | |
| I0525 02:00:23.710846 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.625 | |
| I0525 02:00:23.710858 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.75 | |
| I0525 02:00:23.710870 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.875 | |
| I0525 02:00:23.710886 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 1 | |
| I0525 02:00:23.710898 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 1 | |
| I0525 02:00:23.710911 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 02:00:23.710922 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 02:00:23.710933 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 02:00:23.710945 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 02:00:23.710958 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 02:00:23.710968 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 02:00:23.710980 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 02:00:23.710993 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 02:00:23.711004 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 02:00:23.711015 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 02:00:23.711027 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 02:00:23.711040 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 02:00:23.711050 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.732955 | |
| I0525 02:00:23.711062 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.136364 | |
| I0525 02:00:23.711078 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.45275 (* 0.3 = 1.03583 loss) | |
| I0525 02:00:23.711092 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.05491 (* 0.3 = 0.316473 loss) | |
| I0525 02:00:23.711107 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.93602 (* 0.0272727 = 0.107346 loss) | |
| I0525 02:00:23.711120 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.72846 (* 0.0272727 = 0.101685 loss) | |
| I0525 02:00:23.711134 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.60583 (* 0.0272727 = 0.0983408 loss) | |
| I0525 02:00:23.711148 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.60037 (* 0.0272727 = 0.0981919 loss) | |
| I0525 02:00:23.711163 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 2.79114 (* 0.0272727 = 0.076122 loss) | |
| I0525 02:00:23.711176 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 2.31816 (* 0.0272727 = 0.0632224 loss) | |
| I0525 02:00:23.711189 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 1.31524 (* 0.0272727 = 0.0358701 loss) | |
| I0525 02:00:23.711204 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 0.968286 (* 0.0272727 = 0.0264078 loss) | |
| I0525 02:00:23.711218 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.188955 (* 0.0272727 = 0.00515331 loss) | |
| I0525 02:00:23.711232 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.197029 (* 0.0272727 = 0.00537352 loss) | |
| I0525 02:00:23.711246 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.11399 (* 0.0272727 = 0.00310882 loss) | |
| I0525 02:00:23.711261 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.141564 (* 0.0272727 = 0.00386083 loss) | |
| I0525 02:00:23.711274 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.0633773 (* 0.0272727 = 0.00172847 loss) | |
| I0525 02:00:23.711308 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.0542592 (* 0.0272727 = 0.0014798 loss) | |
| I0525 02:00:23.711324 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0639472 (* 0.0272727 = 0.00174401 loss) | |
| I0525 02:00:23.711338 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.0540718 (* 0.0272727 = 0.00147468 loss) | |
| I0525 02:00:23.711352 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.0362595 (* 0.0272727 = 0.000988897 loss) | |
| I0525 02:00:23.711366 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0346971 (* 0.0272727 = 0.000946286 loss) | |
| I0525 02:00:23.711380 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.0258803 (* 0.0272727 = 0.000705826 loss) | |
| I0525 02:00:23.711395 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.04423 (* 0.0272727 = 0.00120627 loss) | |
| I0525 02:00:23.711408 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.0121073 (* 0.0272727 = 0.0003302 loss) | |
| I0525 02:00:23.711422 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.0140672 (* 0.0272727 = 0.000383652 loss) | |
| I0525 02:00:23.711434 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.0681818 | |
| I0525 02:00:23.711447 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0.375 | |
| I0525 02:00:23.711458 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0 | |
| I0525 02:00:23.711469 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0 | |
| I0525 02:00:23.711480 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0.25 | |
| I0525 02:00:23.711493 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.375 | |
| I0525 02:00:23.711504 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.5 | |
| I0525 02:00:23.711516 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.75 | |
| I0525 02:00:23.711527 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.875 | |
| I0525 02:00:23.711540 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 1 | |
| I0525 02:00:23.711551 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 1 | |
| I0525 02:00:23.711562 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 02:00:23.711573 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 02:00:23.711585 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 02:00:23.711596 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 02:00:23.711607 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 02:00:23.711619 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 02:00:23.711630 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 02:00:23.711642 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 02:00:23.711653 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 02:00:23.711664 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 02:00:23.711676 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 02:00:23.711688 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 02:00:23.711699 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.761364 | |
| I0525 02:00:23.711710 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.136364 | |
| I0525 02:00:23.711724 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.31637 (* 0.3 = 0.994912 loss) | |
| I0525 02:00:23.711737 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.07234 (* 0.3 = 0.321701 loss) | |
| I0525 02:00:23.711751 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 2.76523 (* 0.0272727 = 0.0754154 loss) | |
| I0525 02:00:23.711765 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 4.02498 (* 0.0272727 = 0.109772 loss) | |
| I0525 02:00:23.711778 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.68976 (* 0.0272727 = 0.10063 loss) | |
| I0525 02:00:23.711807 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.9057 (* 0.0272727 = 0.106519 loss) | |
| I0525 02:00:23.711822 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 2.88556 (* 0.0272727 = 0.0786971 loss) | |
| I0525 02:00:23.711836 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 2.20065 (* 0.0272727 = 0.0600176 loss) | |
| I0525 02:00:23.711849 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 1.51796 (* 0.0272727 = 0.0413988 loss) | |
| I0525 02:00:23.711863 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 1.14035 (* 0.0272727 = 0.0311004 loss) | |
| I0525 02:00:23.711877 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.0608464 (* 0.0272727 = 0.00165945 loss) | |
| I0525 02:00:23.711891 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.0461119 (* 0.0272727 = 0.0012576 loss) | |
| I0525 02:00:23.711905 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.0513955 (* 0.0272727 = 0.0014017 loss) | |
| I0525 02:00:23.711920 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.0191378 (* 0.0272727 = 0.000521939 loss) | |
| I0525 02:00:23.711936 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.0133266 (* 0.0272727 = 0.000363453 loss) | |
| I0525 02:00:23.711951 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.0111529 (* 0.0272727 = 0.000304169 loss) | |
| I0525 02:00:23.711964 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.0133932 (* 0.0272727 = 0.000365268 loss) | |
| I0525 02:00:23.711979 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.00262937 (* 0.0272727 = 7.171e-05 loss) | |
| I0525 02:00:23.711993 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.00284424 (* 0.0272727 = 7.75701e-05 loss) | |
| I0525 02:00:23.712007 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.00184793 (* 0.0272727 = 5.0398e-05 loss) | |
| I0525 02:00:23.712020 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.00189623 (* 0.0272727 = 5.17154e-05 loss) | |
| I0525 02:00:23.712034 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.00187828 (* 0.0272727 = 5.12257e-05 loss) | |
| I0525 02:00:23.712049 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.00186272 (* 0.0272727 = 5.08015e-05 loss) | |
| I0525 02:00:23.712062 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.00276296 (* 0.0272727 = 7.53534e-05 loss) | |
| I0525 02:00:23.712074 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.0227273 | |
| I0525 02:00:23.712085 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0 | |
| I0525 02:00:23.712097 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0.125 | |
| I0525 02:00:23.712105 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0.125 | |
| I0525 02:00:23.712113 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.125 | |
| I0525 02:00:23.712126 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.25 | |
| I0525 02:00:23.712138 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.5 | |
| I0525 02:00:23.712149 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.75 | |
| I0525 02:00:23.712162 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.875 | |
| I0525 02:00:23.712173 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 1 | |
| I0525 02:00:23.712185 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 1 | |
| I0525 02:00:23.712196 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 02:00:23.712208 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 02:00:23.712219 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 02:00:23.712230 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 02:00:23.712242 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 02:00:23.712254 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 02:00:23.712275 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 02:00:23.712288 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 02:00:23.712299 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 02:00:23.712311 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 02:00:23.712322 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 02:00:23.712334 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 02:00:23.712345 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.755682 | |
| I0525 02:00:23.712357 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.295455 | |
| I0525 02:00:23.712370 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.20822 (* 1 = 3.20822 loss) | |
| I0525 02:00:23.712384 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 0.925512 (* 1 = 0.925512 loss) | |
| I0525 02:00:23.712399 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 3.16606 (* 0.0909091 = 0.287824 loss) | |
| I0525 02:00:23.712412 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.30318 (* 0.0909091 = 0.300289 loss) | |
| I0525 02:00:23.712425 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 2.96121 (* 0.0909091 = 0.269201 loss) | |
| I0525 02:00:23.712440 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.53237 (* 0.0909091 = 0.321125 loss) | |
| I0525 02:00:23.712452 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 2.83622 (* 0.0909091 = 0.257838 loss) | |
| I0525 02:00:23.712466 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 2.038 (* 0.0909091 = 0.185273 loss) | |
| I0525 02:00:23.712479 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 1.01494 (* 0.0909091 = 0.0922673 loss) | |
| I0525 02:00:23.712493 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.8627 (* 0.0909091 = 0.0784273 loss) | |
| I0525 02:00:23.712507 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.0755781 (* 0.0909091 = 0.00687073 loss) | |
| I0525 02:00:23.712522 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.0220414 (* 0.0909091 = 0.00200377 loss) | |
| I0525 02:00:23.712534 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.0163476 (* 0.0909091 = 0.00148615 loss) | |
| I0525 02:00:23.712548 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.0169783 (* 0.0909091 = 0.00154349 loss) | |
| I0525 02:00:23.712563 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.00921395 (* 0.0909091 = 0.000837632 loss) | |
| I0525 02:00:23.712576 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.0076564 (* 0.0909091 = 0.000696037 loss) | |
| I0525 02:00:23.712589 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.00792762 (* 0.0909091 = 0.000720693 loss) | |
| I0525 02:00:23.712604 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.00583303 (* 0.0909091 = 0.000530276 loss) | |
| I0525 02:00:23.712616 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.00602691 (* 0.0909091 = 0.000547901 loss) | |
| I0525 02:00:23.712630 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.00258678 (* 0.0909091 = 0.000235161 loss) | |
| I0525 02:00:23.712644 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00198702 (* 0.0909091 = 0.000180638 loss) | |
| I0525 02:00:23.712658 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00184639 (* 0.0909091 = 0.000167853 loss) | |
| I0525 02:00:23.712672 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.000865449 (* 0.0909091 = 7.86771e-05 loss) | |
| I0525 02:00:23.712685 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.000791186 (* 0.0909091 = 7.1926e-05 loss) | |
| I0525 02:00:23.712697 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 02:00:23.712709 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 02:00:23.712720 5272 solver.cpp:245] Train net output #149: total_confidence = 0.00010174 | |
| I0525 02:00:23.712741 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 0.000433083 | |
| I0525 02:00:23.712755 5272 sgd_solver.cpp:106] Iteration 8500, lr = 0.001 | |
| I0525 02:03:41.112161 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 30.8669 > 30) by scale factor 0.971915 | |
| I0525 02:06:48.461539 5272 solver.cpp:229] Iteration 9000, loss = 10.6014 | |
| I0525 02:06:48.461696 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0454545 | |
| I0525 02:06:48.461717 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.125 | |
| I0525 02:06:48.461731 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0525 02:06:48.461745 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0525 02:06:48.461757 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0 | |
| I0525 02:06:48.461769 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.25 | |
| I0525 02:06:48.461781 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.5 | |
| I0525 02:06:48.461793 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.875 | |
| I0525 02:06:48.461805 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.875 | |
| I0525 02:06:48.461818 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 1 | |
| I0525 02:06:48.461829 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 1 | |
| I0525 02:06:48.461841 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 02:06:48.461853 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 02:06:48.461865 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 02:06:48.461879 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 02:06:48.461892 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 02:06:48.461905 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 02:06:48.461916 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 02:06:48.461928 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 02:06:48.461941 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 02:06:48.461952 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 02:06:48.461964 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 02:06:48.461976 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 02:06:48.461987 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.761364 | |
| I0525 02:06:48.461999 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.204545 | |
| I0525 02:06:48.462015 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.2905 (* 0.3 = 0.987151 loss) | |
| I0525 02:06:48.462030 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 0.934881 (* 0.3 = 0.280464 loss) | |
| I0525 02:06:48.462044 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 2.92566 (* 0.0272727 = 0.0797907 loss) | |
| I0525 02:06:48.462064 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.41233 (* 0.0272727 = 0.0930636 loss) | |
| I0525 02:06:48.462091 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.63043 (* 0.0272727 = 0.0990117 loss) | |
| I0525 02:06:48.462118 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.81988 (* 0.0272727 = 0.104178 loss) | |
| I0525 02:06:48.462144 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 2.91326 (* 0.0272727 = 0.0794526 loss) | |
| I0525 02:06:48.462167 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 2.6599 (* 0.0272727 = 0.0725428 loss) | |
| I0525 02:06:48.462189 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 1.10958 (* 0.0272727 = 0.0302613 loss) | |
| I0525 02:06:48.462213 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 1.02383 (* 0.0272727 = 0.0279226 loss) | |
| I0525 02:06:48.462235 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.0274324 (* 0.0272727 = 0.000748155 loss) | |
| I0525 02:06:48.462260 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.0283349 (* 0.0272727 = 0.000772769 loss) | |
| I0525 02:06:48.462281 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.0243095 (* 0.0272727 = 0.000662988 loss) | |
| I0525 02:06:48.462303 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.0184351 (* 0.0272727 = 0.000502777 loss) | |
| I0525 02:06:48.462327 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.0127289 (* 0.0272727 = 0.000347152 loss) | |
| I0525 02:06:48.462383 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.0173868 (* 0.0272727 = 0.000474186 loss) | |
| I0525 02:06:48.462409 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0104953 (* 0.0272727 = 0.000286234 loss) | |
| I0525 02:06:48.462435 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.0161775 (* 0.0272727 = 0.000441205 loss) | |
| I0525 02:06:48.462461 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.013427 (* 0.0272727 = 0.000366191 loss) | |
| I0525 02:06:48.462486 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0124264 (* 0.0272727 = 0.000338902 loss) | |
| I0525 02:06:48.462512 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.012312 (* 0.0272727 = 0.00033578 loss) | |
| I0525 02:06:48.462538 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.0143283 (* 0.0272727 = 0.000390773 loss) | |
| I0525 02:06:48.462565 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.0160374 (* 0.0272727 = 0.000437385 loss) | |
| I0525 02:06:48.462591 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.0091108 (* 0.0272727 = 0.000248476 loss) | |
| I0525 02:06:48.462613 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.0909091 | |
| I0525 02:06:48.462635 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0.125 | |
| I0525 02:06:48.462656 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0 | |
| I0525 02:06:48.462676 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0 | |
| I0525 02:06:48.462697 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0 | |
| I0525 02:06:48.462723 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.25 | |
| I0525 02:06:48.462745 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.5 | |
| I0525 02:06:48.462767 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.875 | |
| I0525 02:06:48.462788 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.875 | |
| I0525 02:06:48.462810 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 1 | |
| I0525 02:06:48.462831 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 1 | |
| I0525 02:06:48.462852 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 02:06:48.462873 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 02:06:48.462896 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 02:06:48.462918 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 02:06:48.462944 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 02:06:48.462965 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 02:06:48.462986 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 02:06:48.463007 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 02:06:48.463029 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 02:06:48.463052 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 02:06:48.463073 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 02:06:48.463095 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 02:06:48.463116 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.75 | |
| I0525 02:06:48.463138 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.227273 | |
| I0525 02:06:48.463165 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.21606 (* 0.3 = 0.964817 loss) | |
| I0525 02:06:48.463191 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.0471 (* 0.3 = 0.314131 loss) | |
| I0525 02:06:48.463217 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.31807 (* 0.0272727 = 0.0904929 loss) | |
| I0525 02:06:48.463240 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 3.58032 (* 0.0272727 = 0.0976452 loss) | |
| I0525 02:06:48.463282 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.74134 (* 0.0272727 = 0.102037 loss) | |
| I0525 02:06:48.463310 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.37695 (* 0.0272727 = 0.0920986 loss) | |
| I0525 02:06:48.463335 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 3.30345 (* 0.0272727 = 0.090094 loss) | |
| I0525 02:06:48.463358 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 2.51754 (* 0.0272727 = 0.0686602 loss) | |
| I0525 02:06:48.463382 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 1.24359 (* 0.0272727 = 0.0339161 loss) | |
| I0525 02:06:48.463407 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 1.14515 (* 0.0272727 = 0.0312312 loss) | |
| I0525 02:06:48.463435 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.0495629 (* 0.0272727 = 0.00135171 loss) | |
| I0525 02:06:48.463460 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.0401712 (* 0.0272727 = 0.00109558 loss) | |
| I0525 02:06:48.463485 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.0386994 (* 0.0272727 = 0.00105544 loss) | |
| I0525 02:06:48.463510 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.0203508 (* 0.0272727 = 0.000555022 loss) | |
| I0525 02:06:48.463536 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.0341986 (* 0.0272727 = 0.000932689 loss) | |
| I0525 02:06:48.463562 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.0336644 (* 0.0272727 = 0.00091812 loss) | |
| I0525 02:06:48.463587 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.0176802 (* 0.0272727 = 0.000482186 loss) | |
| I0525 02:06:48.463610 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.0108395 (* 0.0272727 = 0.000295623 loss) | |
| I0525 02:06:48.463636 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.00564106 (* 0.0272727 = 0.000153847 loss) | |
| I0525 02:06:48.463662 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.00481375 (* 0.0272727 = 0.000131284 loss) | |
| I0525 02:06:48.463690 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.00289966 (* 0.0272727 = 7.90816e-05 loss) | |
| I0525 02:06:48.463716 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.00364745 (* 0.0272727 = 9.94759e-05 loss) | |
| I0525 02:06:48.463739 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.00319706 (* 0.0272727 = 8.71926e-05 loss) | |
| I0525 02:06:48.463769 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.00267019 (* 0.0272727 = 7.28233e-05 loss) | |
| I0525 02:06:48.463791 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.0681818 | |
| I0525 02:06:48.463810 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.375 | |
| I0525 02:06:48.463831 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0.25 | |
| I0525 02:06:48.463855 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0 | |
| I0525 02:06:48.463876 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.125 | |
| I0525 02:06:48.463896 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.25 | |
| I0525 02:06:48.463917 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.5 | |
| I0525 02:06:48.463939 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.875 | |
| I0525 02:06:48.463958 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.875 | |
| I0525 02:06:48.463971 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 1 | |
| I0525 02:06:48.463985 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 1 | |
| I0525 02:06:48.463997 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 02:06:48.464010 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 02:06:48.464020 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 02:06:48.464032 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 02:06:48.464043 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 02:06:48.464056 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 02:06:48.464079 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 02:06:48.464092 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 02:06:48.464104 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 02:06:48.464117 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 02:06:48.464128 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 02:06:48.464139 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 02:06:48.464151 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.761364 | |
| I0525 02:06:48.464164 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.272727 | |
| I0525 02:06:48.464179 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.14527 (* 1 = 3.14527 loss) | |
| I0525 02:06:48.464191 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 0.865455 (* 1 = 0.865455 loss) | |
| I0525 02:06:48.464205 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 2.75123 (* 0.0909091 = 0.250112 loss) | |
| I0525 02:06:48.464220 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 2.88901 (* 0.0909091 = 0.262637 loss) | |
| I0525 02:06:48.464233 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.34774 (* 0.0909091 = 0.30434 loss) | |
| I0525 02:06:48.464247 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.52955 (* 0.0909091 = 0.320868 loss) | |
| I0525 02:06:48.464260 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 2.76007 (* 0.0909091 = 0.250915 loss) | |
| I0525 02:06:48.464274 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 2.13938 (* 0.0909091 = 0.194489 loss) | |
| I0525 02:06:48.464288 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 0.639256 (* 0.0909091 = 0.0581142 loss) | |
| I0525 02:06:48.464303 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.577519 (* 0.0909091 = 0.0525018 loss) | |
| I0525 02:06:48.464316 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.0470034 (* 0.0909091 = 0.00427304 loss) | |
| I0525 02:06:48.464330 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.02836 (* 0.0909091 = 0.00257818 loss) | |
| I0525 02:06:48.464344 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.0219587 (* 0.0909091 = 0.00199625 loss) | |
| I0525 02:06:48.464359 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.00828307 (* 0.0909091 = 0.000753007 loss) | |
| I0525 02:06:48.464371 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.0177632 (* 0.0909091 = 0.00161483 loss) | |
| I0525 02:06:48.464386 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.0114985 (* 0.0909091 = 0.00104532 loss) | |
| I0525 02:06:48.464401 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.00804281 (* 0.0909091 = 0.000731165 loss) | |
| I0525 02:06:48.464413 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.0052305 (* 0.0909091 = 0.0004755 loss) | |
| I0525 02:06:48.464428 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.00891069 (* 0.0909091 = 0.000810063 loss) | |
| I0525 02:06:48.464442 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.00359177 (* 0.0909091 = 0.000326525 loss) | |
| I0525 02:06:48.464455 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00278682 (* 0.0909091 = 0.000253347 loss) | |
| I0525 02:06:48.464469 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00379981 (* 0.0909091 = 0.000345437 loss) | |
| I0525 02:06:48.464483 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00323816 (* 0.0909091 = 0.000294379 loss) | |
| I0525 02:06:48.464498 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.00219976 (* 0.0909091 = 0.000199978 loss) | |
| I0525 02:06:48.464509 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 02:06:48.464521 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 02:06:48.464532 5272 solver.cpp:245] Train net output #149: total_confidence = 1.59605e-05 | |
| I0525 02:06:48.464553 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 0.000424533 | |
| I0525 02:06:48.464568 5272 sgd_solver.cpp:106] Iteration 9000, lr = 0.001 | |
| I0525 02:07:58.845538 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 39.6896 > 30) by scale factor 0.755866 | |
| I0525 02:10:41.983757 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 43.8368 > 30) by scale factor 0.684356 | |
| I0525 02:13:13.249094 5272 solver.cpp:229] Iteration 9500, loss = 10.592 | |
| I0525 02:13:13.249265 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0425532 | |
| I0525 02:13:13.249286 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.125 | |
| I0525 02:13:13.249300 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0525 02:13:13.249312 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0525 02:13:13.249325 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.25 | |
| I0525 02:13:13.249336 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.125 | |
| I0525 02:13:13.249348 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.125 | |
| I0525 02:13:13.249361 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.625 | |
| I0525 02:13:13.249373 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.875 | |
| I0525 02:13:13.249385 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 1 | |
| I0525 02:13:13.249397 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 1 | |
| I0525 02:13:13.249409 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 02:13:13.249421 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 02:13:13.249433 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 02:13:13.249445 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 02:13:13.249456 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 02:13:13.249469 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 02:13:13.249480 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 02:13:13.249492 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 02:13:13.249505 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 02:13:13.249516 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 02:13:13.249528 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 02:13:13.249539 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 02:13:13.249552 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.738636 | |
| I0525 02:13:13.249563 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.0851064 | |
| I0525 02:13:13.249580 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.58935 (* 0.3 = 1.07681 loss) | |
| I0525 02:13:13.249595 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.0816 (* 0.3 = 0.324479 loss) | |
| I0525 02:13:13.249609 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.16306 (* 0.0272727 = 0.0862652 loss) | |
| I0525 02:13:13.249624 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 4.11088 (* 0.0272727 = 0.112115 loss) | |
| I0525 02:13:13.249637 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.5617 (* 0.0272727 = 0.0971373 loss) | |
| I0525 02:13:13.249651 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.35086 (* 0.0272727 = 0.091387 loss) | |
| I0525 02:13:13.249666 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 3.25701 (* 0.0272727 = 0.0888276 loss) | |
| I0525 02:13:13.249681 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 4.00934 (* 0.0272727 = 0.109346 loss) | |
| I0525 02:13:13.249696 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 1.56966 (* 0.0272727 = 0.0428089 loss) | |
| I0525 02:13:13.249709 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 0.65934 (* 0.0272727 = 0.017982 loss) | |
| I0525 02:13:13.249723 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.340386 (* 0.0272727 = 0.00928325 loss) | |
| I0525 02:13:13.249737 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.257514 (* 0.0272727 = 0.00702312 loss) | |
| I0525 02:13:13.249752 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.226935 (* 0.0272727 = 0.00618915 loss) | |
| I0525 02:13:13.249766 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.142721 (* 0.0272727 = 0.00389238 loss) | |
| I0525 02:13:13.249779 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.134003 (* 0.0272727 = 0.00365462 loss) | |
| I0525 02:13:13.249816 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.0651643 (* 0.0272727 = 0.00177721 loss) | |
| I0525 02:13:13.249831 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0500841 (* 0.0272727 = 0.00136593 loss) | |
| I0525 02:13:13.249846 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.0616478 (* 0.0272727 = 0.0016813 loss) | |
| I0525 02:13:13.249861 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.0238216 (* 0.0272727 = 0.000649681 loss) | |
| I0525 02:13:13.249878 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0367692 (* 0.0272727 = 0.0010028 loss) | |
| I0525 02:13:13.249893 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.0191323 (* 0.0272727 = 0.000521791 loss) | |
| I0525 02:13:13.249908 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.00723268 (* 0.0272727 = 0.000197255 loss) | |
| I0525 02:13:13.249922 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.0132136 (* 0.0272727 = 0.000360371 loss) | |
| I0525 02:13:13.249936 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.0114148 (* 0.0272727 = 0.000311312 loss) | |
| I0525 02:13:13.249948 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.0425532 | |
| I0525 02:13:13.249960 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0 | |
| I0525 02:13:13.249972 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0 | |
| I0525 02:13:13.249984 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0.25 | |
| I0525 02:13:13.249995 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0.25 | |
| I0525 02:13:13.250007 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.25 | |
| I0525 02:13:13.250020 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.25 | |
| I0525 02:13:13.250031 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.75 | |
| I0525 02:13:13.250043 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.875 | |
| I0525 02:13:13.250056 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 1 | |
| I0525 02:13:13.250066 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 1 | |
| I0525 02:13:13.250078 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 02:13:13.250089 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 02:13:13.250102 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 02:13:13.250113 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 02:13:13.250124 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 02:13:13.250135 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 02:13:13.250149 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 02:13:13.250160 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 02:13:13.250171 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 02:13:13.250183 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 02:13:13.250195 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 02:13:13.250206 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 02:13:13.250217 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.698864 | |
| I0525 02:13:13.250229 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.106383 | |
| I0525 02:13:13.250243 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.71447 (* 0.3 = 1.11434 loss) | |
| I0525 02:13:13.250257 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.2879 (* 0.3 = 0.386371 loss) | |
| I0525 02:13:13.250272 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.6602 (* 0.0272727 = 0.0998235 loss) | |
| I0525 02:13:13.250290 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 3.88976 (* 0.0272727 = 0.106084 loss) | |
| I0525 02:13:13.250304 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.45458 (* 0.0272727 = 0.0942157 loss) | |
| I0525 02:13:13.250329 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.43612 (* 0.0272727 = 0.0937123 loss) | |
| I0525 02:13:13.250344 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 3.45908 (* 0.0272727 = 0.0943386 loss) | |
| I0525 02:13:13.250358 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 3.5491 (* 0.0272727 = 0.0967936 loss) | |
| I0525 02:13:13.250372 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 1.78663 (* 0.0272727 = 0.0487263 loss) | |
| I0525 02:13:13.250386 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 1.01118 (* 0.0272727 = 0.0275777 loss) | |
| I0525 02:13:13.250401 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.238145 (* 0.0272727 = 0.00649487 loss) | |
| I0525 02:13:13.250414 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.307087 (* 0.0272727 = 0.00837509 loss) | |
| I0525 02:13:13.250427 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.22737 (* 0.0272727 = 0.00620099 loss) | |
| I0525 02:13:13.250442 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.182438 (* 0.0272727 = 0.00497557 loss) | |
| I0525 02:13:13.250455 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.149378 (* 0.0272727 = 0.00407395 loss) | |
| I0525 02:13:13.250469 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.12995 (* 0.0272727 = 0.00354409 loss) | |
| I0525 02:13:13.250483 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.140215 (* 0.0272727 = 0.00382403 loss) | |
| I0525 02:13:13.250497 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.0795217 (* 0.0272727 = 0.00216877 loss) | |
| I0525 02:13:13.250511 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.0456341 (* 0.0272727 = 0.00124457 loss) | |
| I0525 02:13:13.250525 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.0529744 (* 0.0272727 = 0.00144476 loss) | |
| I0525 02:13:13.250538 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.0272023 (* 0.0272727 = 0.00074188 loss) | |
| I0525 02:13:13.250552 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.0316644 (* 0.0272727 = 0.000863574 loss) | |
| I0525 02:13:13.250567 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.0197323 (* 0.0272727 = 0.000538155 loss) | |
| I0525 02:13:13.250581 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.0158742 (* 0.0272727 = 0.000432932 loss) | |
| I0525 02:13:13.250593 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.0212766 | |
| I0525 02:13:13.250605 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.125 | |
| I0525 02:13:13.250617 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0 | |
| I0525 02:13:13.250628 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0.125 | |
| I0525 02:13:13.250640 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.125 | |
| I0525 02:13:13.250651 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.125 | |
| I0525 02:13:13.250663 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.25 | |
| I0525 02:13:13.250675 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.75 | |
| I0525 02:13:13.250687 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.875 | |
| I0525 02:13:13.250699 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 1 | |
| I0525 02:13:13.250711 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 1 | |
| I0525 02:13:13.250722 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 02:13:13.250733 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 02:13:13.250746 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 02:13:13.250757 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 02:13:13.250768 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 02:13:13.250779 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 02:13:13.250800 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 02:13:13.250814 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 02:13:13.250825 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 02:13:13.250834 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 02:13:13.250841 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 02:13:13.250854 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 02:13:13.250866 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.715909 | |
| I0525 02:13:13.250879 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.12766 | |
| I0525 02:13:13.250892 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.60341 (* 1 = 3.60341 loss) | |
| I0525 02:13:13.250906 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.14314 (* 1 = 1.14314 loss) | |
| I0525 02:13:13.250921 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 3.32619 (* 0.0909091 = 0.302381 loss) | |
| I0525 02:13:13.250936 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.48022 (* 0.0909091 = 0.316383 loss) | |
| I0525 02:13:13.250951 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.20842 (* 0.0909091 = 0.291674 loss) | |
| I0525 02:13:13.250964 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.62752 (* 0.0909091 = 0.329775 loss) | |
| I0525 02:13:13.250978 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 3.15356 (* 0.0909091 = 0.286687 loss) | |
| I0525 02:13:13.250991 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 3.56778 (* 0.0909091 = 0.324343 loss) | |
| I0525 02:13:13.251005 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 1.3118 (* 0.0909091 = 0.119254 loss) | |
| I0525 02:13:13.251019 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.724638 (* 0.0909091 = 0.0658762 loss) | |
| I0525 02:13:13.251034 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.151927 (* 0.0909091 = 0.0138115 loss) | |
| I0525 02:13:13.251047 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.11218 (* 0.0909091 = 0.0101982 loss) | |
| I0525 02:13:13.251061 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.089778 (* 0.0909091 = 0.00816164 loss) | |
| I0525 02:13:13.251075 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.0723804 (* 0.0909091 = 0.00658003 loss) | |
| I0525 02:13:13.251090 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.0299801 (* 0.0909091 = 0.00272546 loss) | |
| I0525 02:13:13.251103 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.022604 (* 0.0909091 = 0.00205491 loss) | |
| I0525 02:13:13.251117 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.017961 (* 0.0909091 = 0.00163282 loss) | |
| I0525 02:13:13.251132 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.010104 (* 0.0909091 = 0.000918546 loss) | |
| I0525 02:13:13.251144 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.0100966 (* 0.0909091 = 0.000917876 loss) | |
| I0525 02:13:13.251158 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.0063393 (* 0.0909091 = 0.0005763 loss) | |
| I0525 02:13:13.251173 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00228252 (* 0.0909091 = 0.000207501 loss) | |
| I0525 02:13:13.251186 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00215484 (* 0.0909091 = 0.000195894 loss) | |
| I0525 02:13:13.251200 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00235377 (* 0.0909091 = 0.000213979 loss) | |
| I0525 02:13:13.251214 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.00204459 (* 0.0909091 = 0.000185872 loss) | |
| I0525 02:13:13.251225 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 02:13:13.251237 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 02:13:13.251248 5272 solver.cpp:245] Train net output #149: total_confidence = 0.000154486 | |
| I0525 02:13:13.251271 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 0.000272474 | |
| I0525 02:13:13.251286 5272 sgd_solver.cpp:106] Iteration 9500, lr = 0.001 | |
| I0525 02:18:47.697013 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 32.7184 > 30) by scale factor 0.916916 | |
| I0525 02:19:37.720718 5272 solver.cpp:456] Snapshotting to binary proto file /mnt/snapshots/mixed_lstm20_iter_10000.caffemodel | |
| I0525 02:19:39.299392 5272 sgd_solver.cpp:273] Snapshotting solver state to binary proto file /mnt/snapshots/mixed_lstm20_iter_10000.solverstate | |
| I0525 02:19:39.575157 5272 solver.cpp:338] Iteration 10000, Testing net (#0) | |
| I0525 02:20:37.407773 5272 solver.cpp:393] Test loss: 9.83334 | |
| I0525 02:20:37.407964 5272 solver.cpp:406] Test net output #0: loss1/accuracy = 0.0600036 | |
| I0525 02:20:37.407989 5272 solver.cpp:406] Test net output #1: loss1/accuracy01 = 0.116 | |
| I0525 02:20:37.408004 5272 solver.cpp:406] Test net output #2: loss1/accuracy02 = 0.075 | |
| I0525 02:20:37.408015 5272 solver.cpp:406] Test net output #3: loss1/accuracy03 = 0.085 | |
| I0525 02:20:37.408028 5272 solver.cpp:406] Test net output #4: loss1/accuracy04 = 0.155 | |
| I0525 02:20:37.408041 5272 solver.cpp:406] Test net output #5: loss1/accuracy05 = 0.307 | |
| I0525 02:20:37.408052 5272 solver.cpp:406] Test net output #6: loss1/accuracy06 = 0.47 | |
| I0525 02:20:37.408066 5272 solver.cpp:406] Test net output #7: loss1/accuracy07 = 0.738 | |
| I0525 02:20:37.408077 5272 solver.cpp:406] Test net output #8: loss1/accuracy08 = 0.92 | |
| I0525 02:20:37.408090 5272 solver.cpp:406] Test net output #9: loss1/accuracy09 = 0.982 | |
| I0525 02:20:37.408102 5272 solver.cpp:406] Test net output #10: loss1/accuracy10 = 0.994 | |
| I0525 02:20:37.408113 5272 solver.cpp:406] Test net output #11: loss1/accuracy11 = 1 | |
| I0525 02:20:37.408125 5272 solver.cpp:406] Test net output #12: loss1/accuracy12 = 1 | |
| I0525 02:20:37.408138 5272 solver.cpp:406] Test net output #13: loss1/accuracy13 = 1 | |
| I0525 02:20:37.408149 5272 solver.cpp:406] Test net output #14: loss1/accuracy14 = 1 | |
| I0525 02:20:37.408159 5272 solver.cpp:406] Test net output #15: loss1/accuracy15 = 1 | |
| I0525 02:20:37.408171 5272 solver.cpp:406] Test net output #16: loss1/accuracy16 = 1 | |
| I0525 02:20:37.408182 5272 solver.cpp:406] Test net output #17: loss1/accuracy17 = 1 | |
| I0525 02:20:37.408193 5272 solver.cpp:406] Test net output #18: loss1/accuracy18 = 1 | |
| I0525 02:20:37.408205 5272 solver.cpp:406] Test net output #19: loss1/accuracy19 = 1 | |
| I0525 02:20:37.408216 5272 solver.cpp:406] Test net output #20: loss1/accuracy20 = 1 | |
| I0525 02:20:37.408227 5272 solver.cpp:406] Test net output #21: loss1/accuracy21 = 1 | |
| I0525 02:20:37.408238 5272 solver.cpp:406] Test net output #22: loss1/accuracy22 = 1 | |
| I0525 02:20:37.408251 5272 solver.cpp:406] Test net output #23: loss1/accuracy_incl_empty = 0.764183 | |
| I0525 02:20:37.408262 5272 solver.cpp:406] Test net output #24: loss1/accuracy_top3 = 0.219971 | |
| I0525 02:20:37.408278 5272 solver.cpp:406] Test net output #25: loss1/cross_entropy_loss = 3.63939 (* 0.3 = 1.09182 loss) | |
| I0525 02:20:37.408294 5272 solver.cpp:406] Test net output #26: loss1/cross_entropy_loss_incl_empty = 0.946998 (* 0.3 = 0.284099 loss) | |
| I0525 02:20:37.408308 5272 solver.cpp:406] Test net output #27: loss1/loss01 = 3.16998 (* 0.0272727 = 0.086454 loss) | |
| I0525 02:20:37.408323 5272 solver.cpp:406] Test net output #28: loss1/loss02 = 3.35321 (* 0.0272727 = 0.091451 loss) | |
| I0525 02:20:37.408336 5272 solver.cpp:406] Test net output #29: loss1/loss03 = 3.42513 (* 0.0272727 = 0.0934127 loss) | |
| I0525 02:20:37.408349 5272 solver.cpp:406] Test net output #30: loss1/loss04 = 3.30432 (* 0.0272727 = 0.0901178 loss) | |
| I0525 02:20:37.408363 5272 solver.cpp:406] Test net output #31: loss1/loss05 = 2.8424 (* 0.0272727 = 0.07752 loss) | |
| I0525 02:20:37.408377 5272 solver.cpp:406] Test net output #32: loss1/loss06 = 2.37879 (* 0.0272727 = 0.0648761 loss) | |
| I0525 02:20:37.408391 5272 solver.cpp:406] Test net output #33: loss1/loss07 = 1.40979 (* 0.0272727 = 0.0384489 loss) | |
| I0525 02:20:37.408404 5272 solver.cpp:406] Test net output #34: loss1/loss08 = 0.49884 (* 0.0272727 = 0.0136047 loss) | |
| I0525 02:20:37.408418 5272 solver.cpp:406] Test net output #35: loss1/loss09 = 0.139968 (* 0.0272727 = 0.0038173 loss) | |
| I0525 02:20:37.408432 5272 solver.cpp:406] Test net output #36: loss1/loss10 = 0.0824474 (* 0.0272727 = 0.00224857 loss) | |
| I0525 02:20:37.408447 5272 solver.cpp:406] Test net output #37: loss1/loss11 = 0.0398696 (* 0.0272727 = 0.00108735 loss) | |
| I0525 02:20:37.408460 5272 solver.cpp:406] Test net output #38: loss1/loss12 = 0.0353996 (* 0.0272727 = 0.000965444 loss) | |
| I0525 02:20:37.408474 5272 solver.cpp:406] Test net output #39: loss1/loss13 = 0.0237104 (* 0.0272727 = 0.000646648 loss) | |
| I0525 02:20:37.408502 5272 solver.cpp:406] Test net output #40: loss1/loss14 = 0.0189621 (* 0.0272727 = 0.000517149 loss) | |
| I0525 02:20:37.408517 5272 solver.cpp:406] Test net output #41: loss1/loss15 = 0.0155713 (* 0.0272727 = 0.000424672 loss) | |
| I0525 02:20:37.408531 5272 solver.cpp:406] Test net output #42: loss1/loss16 = 0.00890219 (* 0.0272727 = 0.000242787 loss) | |
| I0525 02:20:37.408545 5272 solver.cpp:406] Test net output #43: loss1/loss17 = 0.0065179 (* 0.0272727 = 0.000177761 loss) | |
| I0525 02:20:37.408577 5272 solver.cpp:406] Test net output #44: loss1/loss18 = 0.00498743 (* 0.0272727 = 0.000136021 loss) | |
| I0525 02:20:37.408594 5272 solver.cpp:406] Test net output #45: loss1/loss19 = 0.00475685 (* 0.0272727 = 0.000129732 loss) | |
| I0525 02:20:37.408608 5272 solver.cpp:406] Test net output #46: loss1/loss20 = 0.00420073 (* 0.0272727 = 0.000114565 loss) | |
| I0525 02:20:37.408622 5272 solver.cpp:406] Test net output #47: loss1/loss21 = 0.00511386 (* 0.0272727 = 0.000139469 loss) | |
| I0525 02:20:37.408637 5272 solver.cpp:406] Test net output #48: loss1/loss22 = 0.00448325 (* 0.0272727 = 0.00012227 loss) | |
| I0525 02:20:37.408649 5272 solver.cpp:406] Test net output #49: loss2/accuracy = 0.0615175 | |
| I0525 02:20:37.408661 5272 solver.cpp:406] Test net output #50: loss2/accuracy01 = 0.112 | |
| I0525 02:20:37.408674 5272 solver.cpp:406] Test net output #51: loss2/accuracy02 = 0.08 | |
| I0525 02:20:37.408684 5272 solver.cpp:406] Test net output #52: loss2/accuracy03 = 0.08 | |
| I0525 02:20:37.408697 5272 solver.cpp:406] Test net output #53: loss2/accuracy04 = 0.16 | |
| I0525 02:20:37.408710 5272 solver.cpp:406] Test net output #54: loss2/accuracy05 = 0.314 | |
| I0525 02:20:37.408720 5272 solver.cpp:406] Test net output #55: loss2/accuracy06 = 0.471 | |
| I0525 02:20:37.408732 5272 solver.cpp:406] Test net output #56: loss2/accuracy07 = 0.739 | |
| I0525 02:20:37.408743 5272 solver.cpp:406] Test net output #57: loss2/accuracy08 = 0.919 | |
| I0525 02:20:37.408754 5272 solver.cpp:406] Test net output #58: loss2/accuracy09 = 0.982 | |
| I0525 02:20:37.408766 5272 solver.cpp:406] Test net output #59: loss2/accuracy10 = 0.994 | |
| I0525 02:20:37.408777 5272 solver.cpp:406] Test net output #60: loss2/accuracy11 = 1 | |
| I0525 02:20:37.408788 5272 solver.cpp:406] Test net output #61: loss2/accuracy12 = 1 | |
| I0525 02:20:37.408800 5272 solver.cpp:406] Test net output #62: loss2/accuracy13 = 1 | |
| I0525 02:20:37.408812 5272 solver.cpp:406] Test net output #63: loss2/accuracy14 = 1 | |
| I0525 02:20:37.408823 5272 solver.cpp:406] Test net output #64: loss2/accuracy15 = 1 | |
| I0525 02:20:37.408833 5272 solver.cpp:406] Test net output #65: loss2/accuracy16 = 1 | |
| I0525 02:20:37.408844 5272 solver.cpp:406] Test net output #66: loss2/accuracy17 = 1 | |
| I0525 02:20:37.408855 5272 solver.cpp:406] Test net output #67: loss2/accuracy18 = 1 | |
| I0525 02:20:37.408866 5272 solver.cpp:406] Test net output #68: loss2/accuracy19 = 1 | |
| I0525 02:20:37.408880 5272 solver.cpp:406] Test net output #69: loss2/accuracy20 = 1 | |
| I0525 02:20:37.408892 5272 solver.cpp:406] Test net output #70: loss2/accuracy21 = 1 | |
| I0525 02:20:37.408903 5272 solver.cpp:406] Test net output #71: loss2/accuracy22 = 1 | |
| I0525 02:20:37.408915 5272 solver.cpp:406] Test net output #72: loss2/accuracy_incl_empty = 0.764001 | |
| I0525 02:20:37.408926 5272 solver.cpp:406] Test net output #73: loss2/accuracy_top3 = 0.21614 | |
| I0525 02:20:37.408939 5272 solver.cpp:406] Test net output #74: loss2/cross_entropy_loss = 3.61726 (* 0.3 = 1.08518 loss) | |
| I0525 02:20:37.408953 5272 solver.cpp:406] Test net output #75: loss2/cross_entropy_loss_incl_empty = 0.94186 (* 0.3 = 0.282558 loss) | |
| I0525 02:20:37.408969 5272 solver.cpp:406] Test net output #76: loss2/loss01 = 3.17361 (* 0.0272727 = 0.0865531 loss) | |
| I0525 02:20:37.408983 5272 solver.cpp:406] Test net output #77: loss2/loss02 = 3.35399 (* 0.0272727 = 0.0914724 loss) | |
| I0525 02:20:37.408998 5272 solver.cpp:406] Test net output #78: loss2/loss03 = 3.42504 (* 0.0272727 = 0.0934102 loss) | |
| I0525 02:20:37.409023 5272 solver.cpp:406] Test net output #79: loss2/loss04 = 3.32007 (* 0.0272727 = 0.0905474 loss) | |
| I0525 02:20:37.409037 5272 solver.cpp:406] Test net output #80: loss2/loss05 = 2.86623 (* 0.0272727 = 0.0781699 loss) | |
| I0525 02:20:37.409051 5272 solver.cpp:406] Test net output #81: loss2/loss06 = 2.3996 (* 0.0272727 = 0.0654436 loss) | |
| I0525 02:20:37.409065 5272 solver.cpp:406] Test net output #82: loss2/loss07 = 1.41522 (* 0.0272727 = 0.0385969 loss) | |
| I0525 02:20:37.409078 5272 solver.cpp:406] Test net output #83: loss2/loss08 = 0.514244 (* 0.0272727 = 0.0140248 loss) | |
| I0525 02:20:37.409092 5272 solver.cpp:406] Test net output #84: loss2/loss09 = 0.150824 (* 0.0272727 = 0.00411339 loss) | |
| I0525 02:20:37.409106 5272 solver.cpp:406] Test net output #85: loss2/loss10 = 0.0902685 (* 0.0272727 = 0.00246187 loss) | |
| I0525 02:20:37.409133 5272 solver.cpp:406] Test net output #86: loss2/loss11 = 0.043592 (* 0.0272727 = 0.00118887 loss) | |
| I0525 02:20:37.409149 5272 solver.cpp:406] Test net output #87: loss2/loss12 = 0.0331394 (* 0.0272727 = 0.000903802 loss) | |
| I0525 02:20:37.409163 5272 solver.cpp:406] Test net output #88: loss2/loss13 = 0.0255287 (* 0.0272727 = 0.000696237 loss) | |
| I0525 02:20:37.409178 5272 solver.cpp:406] Test net output #89: loss2/loss14 = 0.0193416 (* 0.0272727 = 0.000527498 loss) | |
| I0525 02:20:37.409190 5272 solver.cpp:406] Test net output #90: loss2/loss15 = 0.0148862 (* 0.0272727 = 0.000405987 loss) | |
| I0525 02:20:37.409204 5272 solver.cpp:406] Test net output #91: loss2/loss16 = 0.00954894 (* 0.0272727 = 0.000260426 loss) | |
| I0525 02:20:37.409219 5272 solver.cpp:406] Test net output #92: loss2/loss17 = 0.005174 (* 0.0272727 = 0.000141109 loss) | |
| I0525 02:20:37.409232 5272 solver.cpp:406] Test net output #93: loss2/loss18 = 0.00519823 (* 0.0272727 = 0.00014177 loss) | |
| I0525 02:20:37.409245 5272 solver.cpp:406] Test net output #94: loss2/loss19 = 0.00417005 (* 0.0272727 = 0.000113729 loss) | |
| I0525 02:20:37.409260 5272 solver.cpp:406] Test net output #95: loss2/loss20 = 0.00436042 (* 0.0272727 = 0.000118921 loss) | |
| I0525 02:20:37.409272 5272 solver.cpp:406] Test net output #96: loss2/loss21 = 0.00414404 (* 0.0272727 = 0.000113019 loss) | |
| I0525 02:20:37.409286 5272 solver.cpp:406] Test net output #97: loss2/loss22 = 0.00373517 (* 0.0272727 = 0.000101868 loss) | |
| I0525 02:20:37.409298 5272 solver.cpp:406] Test net output #98: loss3/accuracy = 0.0776722 | |
| I0525 02:20:37.409307 5272 solver.cpp:406] Test net output #99: loss3/accuracy01 = 0.101 | |
| I0525 02:20:37.409314 5272 solver.cpp:406] Test net output #100: loss3/accuracy02 = 0.091 | |
| I0525 02:20:37.409322 5272 solver.cpp:406] Test net output #101: loss3/accuracy03 = 0.082 | |
| I0525 02:20:37.409334 5272 solver.cpp:406] Test net output #102: loss3/accuracy04 = 0.138 | |
| I0525 02:20:37.409345 5272 solver.cpp:406] Test net output #103: loss3/accuracy05 = 0.306 | |
| I0525 02:20:37.409358 5272 solver.cpp:406] Test net output #104: loss3/accuracy06 = 0.457 | |
| I0525 02:20:37.409368 5272 solver.cpp:406] Test net output #105: loss3/accuracy07 = 0.73 | |
| I0525 02:20:37.409380 5272 solver.cpp:406] Test net output #106: loss3/accuracy08 = 0.91 | |
| I0525 02:20:37.409391 5272 solver.cpp:406] Test net output #107: loss3/accuracy09 = 0.979 | |
| I0525 02:20:37.409404 5272 solver.cpp:406] Test net output #108: loss3/accuracy10 = 0.991 | |
| I0525 02:20:37.409415 5272 solver.cpp:406] Test net output #109: loss3/accuracy11 = 1 | |
| I0525 02:20:37.409425 5272 solver.cpp:406] Test net output #110: loss3/accuracy12 = 1 | |
| I0525 02:20:37.409436 5272 solver.cpp:406] Test net output #111: loss3/accuracy13 = 1 | |
| I0525 02:20:37.409447 5272 solver.cpp:406] Test net output #112: loss3/accuracy14 = 1 | |
| I0525 02:20:37.409458 5272 solver.cpp:406] Test net output #113: loss3/accuracy15 = 1 | |
| I0525 02:20:37.409469 5272 solver.cpp:406] Test net output #114: loss3/accuracy16 = 1 | |
| I0525 02:20:37.409481 5272 solver.cpp:406] Test net output #115: loss3/accuracy17 = 1 | |
| I0525 02:20:37.409503 5272 solver.cpp:406] Test net output #116: loss3/accuracy18 = 1 | |
| I0525 02:20:37.409515 5272 solver.cpp:406] Test net output #117: loss3/accuracy19 = 1 | |
| I0525 02:20:37.409528 5272 solver.cpp:406] Test net output #118: loss3/accuracy20 = 1 | |
| I0525 02:20:37.409538 5272 solver.cpp:406] Test net output #119: loss3/accuracy21 = 1 | |
| I0525 02:20:37.409549 5272 solver.cpp:406] Test net output #120: loss3/accuracy22 = 1 | |
| I0525 02:20:37.409560 5272 solver.cpp:406] Test net output #121: loss3/accuracy_incl_empty = 0.755046 | |
| I0525 02:20:37.409572 5272 solver.cpp:406] Test net output #122: loss3/accuracy_top3 = 0.233118 | |
| I0525 02:20:37.409585 5272 solver.cpp:406] Test net output #123: loss3/cross_entropy_loss = 3.20213 (* 1 = 3.20213 loss) | |
| I0525 02:20:37.409600 5272 solver.cpp:406] Test net output #124: loss3/cross_entropy_loss_incl_empty = 0.938449 (* 1 = 0.938449 loss) | |
| I0525 02:20:37.409612 5272 solver.cpp:406] Test net output #125: loss3/loss01 = 2.97184 (* 0.0909091 = 0.270167 loss) | |
| I0525 02:20:37.409626 5272 solver.cpp:406] Test net output #126: loss3/loss02 = 3.17801 (* 0.0909091 = 0.28891 loss) | |
| I0525 02:20:37.409639 5272 solver.cpp:406] Test net output #127: loss3/loss03 = 3.25949 (* 0.0909091 = 0.296317 loss) | |
| I0525 02:20:37.409653 5272 solver.cpp:406] Test net output #128: loss3/loss04 = 3.15739 (* 0.0909091 = 0.287035 loss) | |
| I0525 02:20:37.409667 5272 solver.cpp:406] Test net output #129: loss3/loss05 = 2.73003 (* 0.0909091 = 0.248185 loss) | |
| I0525 02:20:37.409680 5272 solver.cpp:406] Test net output #130: loss3/loss06 = 2.3041 (* 0.0909091 = 0.209464 loss) | |
| I0525 02:20:37.409693 5272 solver.cpp:406] Test net output #131: loss3/loss07 = 1.34969 (* 0.0909091 = 0.122699 loss) | |
| I0525 02:20:37.409706 5272 solver.cpp:406] Test net output #132: loss3/loss08 = 0.555437 (* 0.0909091 = 0.0504943 loss) | |
| I0525 02:20:37.409719 5272 solver.cpp:406] Test net output #133: loss3/loss09 = 0.157872 (* 0.0909091 = 0.014352 loss) | |
| I0525 02:20:37.409734 5272 solver.cpp:406] Test net output #134: loss3/loss10 = 0.0930276 (* 0.0909091 = 0.00845705 loss) | |
| I0525 02:20:37.409747 5272 solver.cpp:406] Test net output #135: loss3/loss11 = 0.0497495 (* 0.0909091 = 0.00452268 loss) | |
| I0525 02:20:37.409760 5272 solver.cpp:406] Test net output #136: loss3/loss12 = 0.0397187 (* 0.0909091 = 0.00361079 loss) | |
| I0525 02:20:37.409775 5272 solver.cpp:406] Test net output #137: loss3/loss13 = 0.0305851 (* 0.0909091 = 0.00278047 loss) | |
| I0525 02:20:37.409787 5272 solver.cpp:406] Test net output #138: loss3/loss14 = 0.0235545 (* 0.0909091 = 0.00214132 loss) | |
| I0525 02:20:37.409801 5272 solver.cpp:406] Test net output #139: loss3/loss15 = 0.0163944 (* 0.0909091 = 0.0014904 loss) | |
| I0525 02:20:37.409814 5272 solver.cpp:406] Test net output #140: loss3/loss16 = 0.00962252 (* 0.0909091 = 0.000874775 loss) | |
| I0525 02:20:37.409828 5272 solver.cpp:406] Test net output #141: loss3/loss17 = 0.00544977 (* 0.0909091 = 0.000495433 loss) | |
| I0525 02:20:37.409842 5272 solver.cpp:406] Test net output #142: loss3/loss18 = 0.00328961 (* 0.0909091 = 0.000299055 loss) | |
| I0525 02:20:37.409855 5272 solver.cpp:406] Test net output #143: loss3/loss19 = 0.00246117 (* 0.0909091 = 0.000223742 loss) | |
| I0525 02:20:37.409868 5272 solver.cpp:406] Test net output #144: loss3/loss20 = 0.00178583 (* 0.0909091 = 0.000162348 loss) | |
| I0525 02:20:37.409883 5272 solver.cpp:406] Test net output #145: loss3/loss21 = 0.00155015 (* 0.0909091 = 0.000140923 loss) | |
| I0525 02:20:37.409895 5272 solver.cpp:406] Test net output #146: loss3/loss22 = 0.00135665 (* 0.0909091 = 0.000123332 loss) | |
| I0525 02:20:37.409907 5272 solver.cpp:406] Test net output #147: total_accuracy = 0 | |
| I0525 02:20:37.409919 5272 solver.cpp:406] Test net output #148: total_accuracy_not_rec = 0 | |
| I0525 02:20:37.409932 5272 solver.cpp:406] Test net output #149: total_confidence = 2.20222e-05 | |
| I0525 02:20:37.409945 5272 solver.cpp:406] Test net output #150: total_confidence_not_rec = 6.82075e-05 | |
| I0525 02:20:37.409968 5272 solver.cpp:338] Iteration 10000, Testing net (#1) | |
| I0525 02:21:35.310981 5272 solver.cpp:393] Test loss: 10.465 | |
| I0525 02:21:35.311115 5272 solver.cpp:406] Test net output #0: loss1/accuracy = 0.0578559 | |
| I0525 02:21:35.311136 5272 solver.cpp:406] Test net output #1: loss1/accuracy01 = 0.109 | |
| I0525 02:21:35.311151 5272 solver.cpp:406] Test net output #2: loss1/accuracy02 = 0.112 | |
| I0525 02:21:35.311162 5272 solver.cpp:406] Test net output #3: loss1/accuracy03 = 0.084 | |
| I0525 02:21:35.311175 5272 solver.cpp:406] Test net output #4: loss1/accuracy04 = 0.168 | |
| I0525 02:21:35.311187 5272 solver.cpp:406] Test net output #5: loss1/accuracy05 = 0.32 | |
| I0525 02:21:35.311200 5272 solver.cpp:406] Test net output #6: loss1/accuracy06 = 0.441 | |
| I0525 02:21:35.311213 5272 solver.cpp:406] Test net output #7: loss1/accuracy07 = 0.656 | |
| I0525 02:21:35.311224 5272 solver.cpp:406] Test net output #8: loss1/accuracy08 = 0.825 | |
| I0525 02:21:35.311238 5272 solver.cpp:406] Test net output #9: loss1/accuracy09 = 0.887 | |
| I0525 02:21:35.311249 5272 solver.cpp:406] Test net output #10: loss1/accuracy10 = 0.902 | |
| I0525 02:21:35.311261 5272 solver.cpp:406] Test net output #11: loss1/accuracy11 = 0.926 | |
| I0525 02:21:35.311274 5272 solver.cpp:406] Test net output #12: loss1/accuracy12 = 0.943 | |
| I0525 02:21:35.311285 5272 solver.cpp:406] Test net output #13: loss1/accuracy13 = 0.952 | |
| I0525 02:21:35.311296 5272 solver.cpp:406] Test net output #14: loss1/accuracy14 = 0.963 | |
| I0525 02:21:35.311308 5272 solver.cpp:406] Test net output #15: loss1/accuracy15 = 0.966 | |
| I0525 02:21:35.311321 5272 solver.cpp:406] Test net output #16: loss1/accuracy16 = 0.982 | |
| I0525 02:21:35.311332 5272 solver.cpp:406] Test net output #17: loss1/accuracy17 = 0.992 | |
| I0525 02:21:35.311343 5272 solver.cpp:406] Test net output #18: loss1/accuracy18 = 0.993 | |
| I0525 02:21:35.311355 5272 solver.cpp:406] Test net output #19: loss1/accuracy19 = 0.996 | |
| I0525 02:21:35.311367 5272 solver.cpp:406] Test net output #20: loss1/accuracy20 = 0.999 | |
| I0525 02:21:35.311378 5272 solver.cpp:406] Test net output #21: loss1/accuracy21 = 0.999 | |
| I0525 02:21:35.311390 5272 solver.cpp:406] Test net output #22: loss1/accuracy22 = 0.999 | |
| I0525 02:21:35.311401 5272 solver.cpp:406] Test net output #23: loss1/accuracy_incl_empty = 0.73191 | |
| I0525 02:21:35.311414 5272 solver.cpp:406] Test net output #24: loss1/accuracy_top3 = 0.219995 | |
| I0525 02:21:35.311429 5272 solver.cpp:406] Test net output #25: loss1/cross_entropy_loss = 3.68745 (* 0.3 = 1.10624 loss) | |
| I0525 02:21:35.311444 5272 solver.cpp:406] Test net output #26: loss1/cross_entropy_loss_incl_empty = 1.09099 (* 0.3 = 0.327298 loss) | |
| I0525 02:21:35.311458 5272 solver.cpp:406] Test net output #27: loss1/loss01 = 3.24691 (* 0.0272727 = 0.0885522 loss) | |
| I0525 02:21:35.311472 5272 solver.cpp:406] Test net output #28: loss1/loss02 = 3.3158 (* 0.0272727 = 0.0904308 loss) | |
| I0525 02:21:35.311486 5272 solver.cpp:406] Test net output #29: loss1/loss03 = 3.43561 (* 0.0272727 = 0.0936985 loss) | |
| I0525 02:21:35.311499 5272 solver.cpp:406] Test net output #30: loss1/loss04 = 3.24865 (* 0.0272727 = 0.0885995 loss) | |
| I0525 02:21:35.311513 5272 solver.cpp:406] Test net output #31: loss1/loss05 = 2.82589 (* 0.0272727 = 0.0770696 loss) | |
| I0525 02:21:35.311527 5272 solver.cpp:406] Test net output #32: loss1/loss06 = 2.49535 (* 0.0272727 = 0.0680549 loss) | |
| I0525 02:21:35.311540 5272 solver.cpp:406] Test net output #33: loss1/loss07 = 1.66249 (* 0.0272727 = 0.0453406 loss) | |
| I0525 02:21:35.311554 5272 solver.cpp:406] Test net output #34: loss1/loss08 = 0.874205 (* 0.0272727 = 0.0238419 loss) | |
| I0525 02:21:35.311568 5272 solver.cpp:406] Test net output #35: loss1/loss09 = 0.544059 (* 0.0272727 = 0.014838 loss) | |
| I0525 02:21:35.311581 5272 solver.cpp:406] Test net output #36: loss1/loss10 = 0.47089 (* 0.0272727 = 0.0128425 loss) | |
| I0525 02:21:35.311595 5272 solver.cpp:406] Test net output #37: loss1/loss11 = 0.371633 (* 0.0272727 = 0.0101354 loss) | |
| I0525 02:21:35.311609 5272 solver.cpp:406] Test net output #38: loss1/loss12 = 0.297776 (* 0.0272727 = 0.00812116 loss) | |
| I0525 02:21:35.311642 5272 solver.cpp:406] Test net output #39: loss1/loss13 = 0.257627 (* 0.0272727 = 0.00702618 loss) | |
| I0525 02:21:35.311657 5272 solver.cpp:406] Test net output #40: loss1/loss14 = 0.210675 (* 0.0272727 = 0.00574567 loss) | |
| I0525 02:21:35.311671 5272 solver.cpp:406] Test net output #41: loss1/loss15 = 0.192944 (* 0.0272727 = 0.00526211 loss) | |
| I0525 02:21:35.311686 5272 solver.cpp:406] Test net output #42: loss1/loss16 = 0.121605 (* 0.0272727 = 0.0033165 loss) | |
| I0525 02:21:35.311699 5272 solver.cpp:406] Test net output #43: loss1/loss17 = 0.0683839 (* 0.0272727 = 0.00186502 loss) | |
| I0525 02:21:35.311713 5272 solver.cpp:406] Test net output #44: loss1/loss18 = 0.0591718 (* 0.0272727 = 0.00161378 loss) | |
| I0525 02:21:35.311728 5272 solver.cpp:406] Test net output #45: loss1/loss19 = 0.038888 (* 0.0272727 = 0.00106058 loss) | |
| I0525 02:21:35.311741 5272 solver.cpp:406] Test net output #46: loss1/loss20 = 0.0154692 (* 0.0272727 = 0.000421886 loss) | |
| I0525 02:21:35.311755 5272 solver.cpp:406] Test net output #47: loss1/loss21 = 0.0160951 (* 0.0272727 = 0.000438958 loss) | |
| I0525 02:21:35.311769 5272 solver.cpp:406] Test net output #48: loss1/loss22 = 0.0141512 (* 0.0272727 = 0.000385941 loss) | |
| I0525 02:21:35.311780 5272 solver.cpp:406] Test net output #49: loss2/accuracy = 0.062623 | |
| I0525 02:21:35.311792 5272 solver.cpp:406] Test net output #50: loss2/accuracy01 = 0.119 | |
| I0525 02:21:35.311805 5272 solver.cpp:406] Test net output #51: loss2/accuracy02 = 0.104 | |
| I0525 02:21:35.311815 5272 solver.cpp:406] Test net output #52: loss2/accuracy03 = 0.081 | |
| I0525 02:21:35.311827 5272 solver.cpp:406] Test net output #53: loss2/accuracy04 = 0.16 | |
| I0525 02:21:35.311839 5272 solver.cpp:406] Test net output #54: loss2/accuracy05 = 0.326 | |
| I0525 02:21:35.311851 5272 solver.cpp:406] Test net output #55: loss2/accuracy06 = 0.444 | |
| I0525 02:21:35.311862 5272 solver.cpp:406] Test net output #56: loss2/accuracy07 = 0.654 | |
| I0525 02:21:35.311877 5272 solver.cpp:406] Test net output #57: loss2/accuracy08 = 0.824 | |
| I0525 02:21:35.311889 5272 solver.cpp:406] Test net output #58: loss2/accuracy09 = 0.887 | |
| I0525 02:21:35.311902 5272 solver.cpp:406] Test net output #59: loss2/accuracy10 = 0.902 | |
| I0525 02:21:35.311913 5272 solver.cpp:406] Test net output #60: loss2/accuracy11 = 0.926 | |
| I0525 02:21:35.311925 5272 solver.cpp:406] Test net output #61: loss2/accuracy12 = 0.943 | |
| I0525 02:21:35.311936 5272 solver.cpp:406] Test net output #62: loss2/accuracy13 = 0.952 | |
| I0525 02:21:35.311947 5272 solver.cpp:406] Test net output #63: loss2/accuracy14 = 0.963 | |
| I0525 02:21:35.311959 5272 solver.cpp:406] Test net output #64: loss2/accuracy15 = 0.966 | |
| I0525 02:21:35.311970 5272 solver.cpp:406] Test net output #65: loss2/accuracy16 = 0.982 | |
| I0525 02:21:35.311981 5272 solver.cpp:406] Test net output #66: loss2/accuracy17 = 0.992 | |
| I0525 02:21:35.311992 5272 solver.cpp:406] Test net output #67: loss2/accuracy18 = 0.993 | |
| I0525 02:21:35.312005 5272 solver.cpp:406] Test net output #68: loss2/accuracy19 = 0.996 | |
| I0525 02:21:35.312016 5272 solver.cpp:406] Test net output #69: loss2/accuracy20 = 0.999 | |
| I0525 02:21:35.312027 5272 solver.cpp:406] Test net output #70: loss2/accuracy21 = 0.999 | |
| I0525 02:21:35.312038 5272 solver.cpp:406] Test net output #71: loss2/accuracy22 = 0.999 | |
| I0525 02:21:35.312050 5272 solver.cpp:406] Test net output #72: loss2/accuracy_incl_empty = 0.733455 | |
| I0525 02:21:35.312062 5272 solver.cpp:406] Test net output #73: loss2/accuracy_top3 = 0.211085 | |
| I0525 02:21:35.312075 5272 solver.cpp:406] Test net output #74: loss2/cross_entropy_loss = 3.63767 (* 0.3 = 1.0913 loss) | |
| I0525 02:21:35.312089 5272 solver.cpp:406] Test net output #75: loss2/cross_entropy_loss_incl_empty = 1.07434 (* 0.3 = 0.322303 loss) | |
| I0525 02:21:35.312103 5272 solver.cpp:406] Test net output #76: loss2/loss01 = 3.25445 (* 0.0272727 = 0.0887578 loss) | |
| I0525 02:21:35.312116 5272 solver.cpp:406] Test net output #77: loss2/loss02 = 3.31663 (* 0.0272727 = 0.0904535 loss) | |
| I0525 02:21:35.312144 5272 solver.cpp:406] Test net output #78: loss2/loss03 = 3.42929 (* 0.0272727 = 0.093526 loss) | |
| I0525 02:21:35.312158 5272 solver.cpp:406] Test net output #79: loss2/loss04 = 3.25517 (* 0.0272727 = 0.0887773 loss) | |
| I0525 02:21:35.312172 5272 solver.cpp:406] Test net output #80: loss2/loss05 = 2.8289 (* 0.0272727 = 0.0771517 loss) | |
| I0525 02:21:35.312186 5272 solver.cpp:406] Test net output #81: loss2/loss06 = 2.50525 (* 0.0272727 = 0.068325 loss) | |
| I0525 02:21:35.312199 5272 solver.cpp:406] Test net output #82: loss2/loss07 = 1.66849 (* 0.0272727 = 0.0455044 loss) | |
| I0525 02:21:35.312212 5272 solver.cpp:406] Test net output #83: loss2/loss08 = 0.881974 (* 0.0272727 = 0.0240538 loss) | |
| I0525 02:21:35.312225 5272 solver.cpp:406] Test net output #84: loss2/loss09 = 0.562683 (* 0.0272727 = 0.0153459 loss) | |
| I0525 02:21:35.312239 5272 solver.cpp:406] Test net output #85: loss2/loss10 = 0.471991 (* 0.0272727 = 0.0128725 loss) | |
| I0525 02:21:35.312253 5272 solver.cpp:406] Test net output #86: loss2/loss11 = 0.368717 (* 0.0272727 = 0.0100559 loss) | |
| I0525 02:21:35.312266 5272 solver.cpp:406] Test net output #87: loss2/loss12 = 0.302846 (* 0.0272727 = 0.00825942 loss) | |
| I0525 02:21:35.312280 5272 solver.cpp:406] Test net output #88: loss2/loss13 = 0.261626 (* 0.0272727 = 0.00713525 loss) | |
| I0525 02:21:35.312304 5272 solver.cpp:406] Test net output #89: loss2/loss14 = 0.210753 (* 0.0272727 = 0.00574782 loss) | |
| I0525 02:21:35.312327 5272 solver.cpp:406] Test net output #90: loss2/loss15 = 0.199207 (* 0.0272727 = 0.00543293 loss) | |
| I0525 02:21:35.312342 5272 solver.cpp:406] Test net output #91: loss2/loss16 = 0.125161 (* 0.0272727 = 0.00341348 loss) | |
| I0525 02:21:35.312356 5272 solver.cpp:406] Test net output #92: loss2/loss17 = 0.0668593 (* 0.0272727 = 0.00182343 loss) | |
| I0525 02:21:35.312369 5272 solver.cpp:406] Test net output #93: loss2/loss18 = 0.06017 (* 0.0272727 = 0.001641 loss) | |
| I0525 02:21:35.312383 5272 solver.cpp:406] Test net output #94: loss2/loss19 = 0.0372799 (* 0.0272727 = 0.00101672 loss) | |
| I0525 02:21:35.312397 5272 solver.cpp:406] Test net output #95: loss2/loss20 = 0.0137686 (* 0.0272727 = 0.000375508 loss) | |
| I0525 02:21:35.312412 5272 solver.cpp:406] Test net output #96: loss2/loss21 = 0.0139979 (* 0.0272727 = 0.000381762 loss) | |
| I0525 02:21:35.312424 5272 solver.cpp:406] Test net output #97: loss2/loss22 = 0.0144818 (* 0.0272727 = 0.000394959 loss) | |
| I0525 02:21:35.312436 5272 solver.cpp:406] Test net output #98: loss3/accuracy = 0.0825973 | |
| I0525 02:21:35.312448 5272 solver.cpp:406] Test net output #99: loss3/accuracy01 = 0.119 | |
| I0525 02:21:35.312459 5272 solver.cpp:406] Test net output #100: loss3/accuracy02 = 0.101 | |
| I0525 02:21:35.312471 5272 solver.cpp:406] Test net output #101: loss3/accuracy03 = 0.09 | |
| I0525 02:21:35.312482 5272 solver.cpp:406] Test net output #102: loss3/accuracy04 = 0.154 | |
| I0525 02:21:35.312494 5272 solver.cpp:406] Test net output #103: loss3/accuracy05 = 0.319 | |
| I0525 02:21:35.312505 5272 solver.cpp:406] Test net output #104: loss3/accuracy06 = 0.442 | |
| I0525 02:21:35.312513 5272 solver.cpp:406] Test net output #105: loss3/accuracy07 = 0.65 | |
| I0525 02:21:35.312520 5272 solver.cpp:406] Test net output #106: loss3/accuracy08 = 0.823 | |
| I0525 02:21:35.312532 5272 solver.cpp:406] Test net output #107: loss3/accuracy09 = 0.886 | |
| I0525 02:21:35.312544 5272 solver.cpp:406] Test net output #108: loss3/accuracy10 = 0.898 | |
| I0525 02:21:35.312556 5272 solver.cpp:406] Test net output #109: loss3/accuracy11 = 0.925 | |
| I0525 02:21:35.312566 5272 solver.cpp:406] Test net output #110: loss3/accuracy12 = 0.943 | |
| I0525 02:21:35.312578 5272 solver.cpp:406] Test net output #111: loss3/accuracy13 = 0.952 | |
| I0525 02:21:35.312589 5272 solver.cpp:406] Test net output #112: loss3/accuracy14 = 0.963 | |
| I0525 02:21:35.312600 5272 solver.cpp:406] Test net output #113: loss3/accuracy15 = 0.966 | |
| I0525 02:21:35.312613 5272 solver.cpp:406] Test net output #114: loss3/accuracy16 = 0.982 | |
| I0525 02:21:35.312634 5272 solver.cpp:406] Test net output #115: loss3/accuracy17 = 0.992 | |
| I0525 02:21:35.312647 5272 solver.cpp:406] Test net output #116: loss3/accuracy18 = 0.993 | |
| I0525 02:21:35.312659 5272 solver.cpp:406] Test net output #117: loss3/accuracy19 = 0.996 | |
| I0525 02:21:35.312670 5272 solver.cpp:406] Test net output #118: loss3/accuracy20 = 0.999 | |
| I0525 02:21:35.312681 5272 solver.cpp:406] Test net output #119: loss3/accuracy21 = 0.999 | |
| I0525 02:21:35.312693 5272 solver.cpp:406] Test net output #120: loss3/accuracy22 = 0.999 | |
| I0525 02:21:35.312705 5272 solver.cpp:406] Test net output #121: loss3/accuracy_incl_empty = 0.728682 | |
| I0525 02:21:35.312716 5272 solver.cpp:406] Test net output #122: loss3/accuracy_top3 = 0.224672 | |
| I0525 02:21:35.312731 5272 solver.cpp:406] Test net output #123: loss3/cross_entropy_loss = 3.21502 (* 1 = 3.21502 loss) | |
| I0525 02:21:35.312755 5272 solver.cpp:406] Test net output #124: loss3/cross_entropy_loss_incl_empty = 1.0456 (* 1 = 1.0456 loss) | |
| I0525 02:21:35.312777 5272 solver.cpp:406] Test net output #125: loss3/loss01 = 3.06666 (* 0.0909091 = 0.278787 loss) | |
| I0525 02:21:35.312793 5272 solver.cpp:406] Test net output #126: loss3/loss02 = 3.14282 (* 0.0909091 = 0.285711 loss) | |
| I0525 02:21:35.312805 5272 solver.cpp:406] Test net output #127: loss3/loss03 = 3.25603 (* 0.0909091 = 0.296003 loss) | |
| I0525 02:21:35.312819 5272 solver.cpp:406] Test net output #128: loss3/loss04 = 3.11557 (* 0.0909091 = 0.283234 loss) | |
| I0525 02:21:35.312832 5272 solver.cpp:406] Test net output #129: loss3/loss05 = 2.69726 (* 0.0909091 = 0.245205 loss) | |
| I0525 02:21:35.312846 5272 solver.cpp:406] Test net output #130: loss3/loss06 = 2.36823 (* 0.0909091 = 0.215294 loss) | |
| I0525 02:21:35.312860 5272 solver.cpp:406] Test net output #131: loss3/loss07 = 1.57995 (* 0.0909091 = 0.143631 loss) | |
| I0525 02:21:35.312872 5272 solver.cpp:406] Test net output #132: loss3/loss08 = 0.88992 (* 0.0909091 = 0.0809018 loss) | |
| I0525 02:21:35.312885 5272 solver.cpp:406] Test net output #133: loss3/loss09 = 0.522865 (* 0.0909091 = 0.0475332 loss) | |
| I0525 02:21:35.312899 5272 solver.cpp:406] Test net output #134: loss3/loss10 = 0.44528 (* 0.0909091 = 0.04048 loss) | |
| I0525 02:21:35.312913 5272 solver.cpp:406] Test net output #135: loss3/loss11 = 0.347268 (* 0.0909091 = 0.0315698 loss) | |
| I0525 02:21:35.312929 5272 solver.cpp:406] Test net output #136: loss3/loss12 = 0.283612 (* 0.0909091 = 0.025783 loss) | |
| I0525 02:21:35.312943 5272 solver.cpp:406] Test net output #137: loss3/loss13 = 0.243715 (* 0.0909091 = 0.0221559 loss) | |
| I0525 02:21:35.312958 5272 solver.cpp:406] Test net output #138: loss3/loss14 = 0.204154 (* 0.0909091 = 0.0185594 loss) | |
| I0525 02:21:35.312970 5272 solver.cpp:406] Test net output #139: loss3/loss15 = 0.177459 (* 0.0909091 = 0.0161326 loss) | |
| I0525 02:21:35.312984 5272 solver.cpp:406] Test net output #140: loss3/loss16 = 0.108902 (* 0.0909091 = 0.00990016 loss) | |
| I0525 02:21:35.312997 5272 solver.cpp:406] Test net output #141: loss3/loss17 = 0.0565278 (* 0.0909091 = 0.00513889 loss) | |
| I0525 02:21:35.313011 5272 solver.cpp:406] Test net output #142: loss3/loss18 = 0.0571759 (* 0.0909091 = 0.00519781 loss) | |
| I0525 02:21:35.313024 5272 solver.cpp:406] Test net output #143: loss3/loss19 = 0.0361376 (* 0.0909091 = 0.00328523 loss) | |
| I0525 02:21:35.313038 5272 solver.cpp:406] Test net output #144: loss3/loss20 = 0.0121723 (* 0.0909091 = 0.00110657 loss) | |
| I0525 02:21:35.313051 5272 solver.cpp:406] Test net output #145: loss3/loss21 = 0.0139018 (* 0.0909091 = 0.0012638 loss) | |
| I0525 02:21:35.313066 5272 solver.cpp:406] Test net output #146: loss3/loss22 = 0.0136048 (* 0.0909091 = 0.0012368 loss) | |
| I0525 02:21:35.313076 5272 solver.cpp:406] Test net output #147: total_accuracy = 0 | |
| I0525 02:21:35.313088 5272 solver.cpp:406] Test net output #148: total_accuracy_not_rec = 0 | |
| I0525 02:21:35.313098 5272 solver.cpp:406] Test net output #149: total_confidence = 2.49571e-05 | |
| I0525 02:21:35.313136 5272 solver.cpp:406] Test net output #150: total_confidence_not_rec = 8.22276e-05 | |
| I0525 02:21:35.671535 5272 solver.cpp:229] Iteration 10000, loss = 10.4865 | |
| I0525 02:21:35.671607 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0681818 | |
| I0525 02:21:35.671625 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.125 | |
| I0525 02:21:35.671639 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0525 02:21:35.671653 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0.125 | |
| I0525 02:21:35.671665 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.125 | |
| I0525 02:21:35.671677 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.25 | |
| I0525 02:21:35.671690 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.5 | |
| I0525 02:21:35.671703 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.625 | |
| I0525 02:21:35.671717 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.875 | |
| I0525 02:21:35.671730 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 1 | |
| I0525 02:21:35.671743 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 1 | |
| I0525 02:21:35.671756 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 02:21:35.671767 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 02:21:35.671782 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 02:21:35.671795 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 02:21:35.671807 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 02:21:35.671819 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 02:21:35.671831 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 02:21:35.671844 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 02:21:35.671855 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 02:21:35.671867 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 02:21:35.671880 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 02:21:35.671891 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 02:21:35.671905 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.738636 | |
| I0525 02:21:35.671916 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.272727 | |
| I0525 02:21:35.671933 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.22828 (* 0.3 = 0.968483 loss) | |
| I0525 02:21:35.671947 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.01134 (* 0.3 = 0.303401 loss) | |
| I0525 02:21:35.671962 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.62114 (* 0.0272727 = 0.0987584 loss) | |
| I0525 02:21:35.671977 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.42471 (* 0.0272727 = 0.0934013 loss) | |
| I0525 02:21:35.671990 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.56778 (* 0.0272727 = 0.097303 loss) | |
| I0525 02:21:35.672004 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.21064 (* 0.0272727 = 0.087563 loss) | |
| I0525 02:21:35.672019 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 2.72688 (* 0.0272727 = 0.0743696 loss) | |
| I0525 02:21:35.672032 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 1.99881 (* 0.0272727 = 0.054513 loss) | |
| I0525 02:21:35.672046 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 1.34254 (* 0.0272727 = 0.0366147 loss) | |
| I0525 02:21:35.672061 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 1.12287 (* 0.0272727 = 0.0306238 loss) | |
| I0525 02:21:35.672075 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.107967 (* 0.0272727 = 0.00294454 loss) | |
| I0525 02:21:35.672089 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.0713379 (* 0.0272727 = 0.00194558 loss) | |
| I0525 02:21:35.672104 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.0545957 (* 0.0272727 = 0.00148897 loss) | |
| I0525 02:21:35.672153 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.0371587 (* 0.0272727 = 0.00101342 loss) | |
| I0525 02:21:35.672168 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.0499097 (* 0.0272727 = 0.00136117 loss) | |
| I0525 02:21:35.672183 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.0293028 (* 0.0272727 = 0.000799168 loss) | |
| I0525 02:21:35.672196 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0119811 (* 0.0272727 = 0.000326756 loss) | |
| I0525 02:21:35.672210 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.0178584 (* 0.0272727 = 0.000487048 loss) | |
| I0525 02:21:35.672224 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.0074372 (* 0.0272727 = 0.000202833 loss) | |
| I0525 02:21:35.672238 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.00500947 (* 0.0272727 = 0.000136622 loss) | |
| I0525 02:21:35.672253 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.00422975 (* 0.0272727 = 0.000115357 loss) | |
| I0525 02:21:35.672268 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.00396952 (* 0.0272727 = 0.00010826 loss) | |
| I0525 02:21:35.672283 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.00366643 (* 0.0272727 = 9.99936e-05 loss) | |
| I0525 02:21:35.672297 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.00524919 (* 0.0272727 = 0.00014316 loss) | |
| I0525 02:21:35.672310 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.0681818 | |
| I0525 02:21:35.672322 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0 | |
| I0525 02:21:35.672334 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0.125 | |
| I0525 02:21:35.672346 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0 | |
| I0525 02:21:35.672358 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0.125 | |
| I0525 02:21:35.672369 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.375 | |
| I0525 02:21:35.672381 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.5 | |
| I0525 02:21:35.672394 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.75 | |
| I0525 02:21:35.672405 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.875 | |
| I0525 02:21:35.672417 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 1 | |
| I0525 02:21:35.672430 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 1 | |
| I0525 02:21:35.672444 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 02:21:35.672456 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 02:21:35.672468 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 02:21:35.672480 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 02:21:35.672492 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 02:21:35.672503 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 02:21:35.672515 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 02:21:35.672526 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 02:21:35.672538 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 02:21:35.672549 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 02:21:35.672561 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 02:21:35.672574 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 02:21:35.672585 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.744318 | |
| I0525 02:21:35.672596 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.318182 | |
| I0525 02:21:35.672610 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.19535 (* 0.3 = 0.958606 loss) | |
| I0525 02:21:35.672624 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.04085 (* 0.3 = 0.312256 loss) | |
| I0525 02:21:35.672638 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.95244 (* 0.0272727 = 0.107794 loss) | |
| I0525 02:21:35.672663 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 3.0055 (* 0.0272727 = 0.0819681 loss) | |
| I0525 02:21:35.672678 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.66933 (* 0.0272727 = 0.100073 loss) | |
| I0525 02:21:35.672693 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.07422 (* 0.0272727 = 0.0838424 loss) | |
| I0525 02:21:35.672706 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 3.02989 (* 0.0272727 = 0.0826333 loss) | |
| I0525 02:21:35.672719 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 2.14249 (* 0.0272727 = 0.0584315 loss) | |
| I0525 02:21:35.672734 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 1.31733 (* 0.0272727 = 0.0359272 loss) | |
| I0525 02:21:35.672746 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 1.00943 (* 0.0272727 = 0.02753 loss) | |
| I0525 02:21:35.672760 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.0678745 (* 0.0272727 = 0.00185112 loss) | |
| I0525 02:21:35.672775 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.0445991 (* 0.0272727 = 0.00121634 loss) | |
| I0525 02:21:35.672788 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.0424249 (* 0.0272727 = 0.00115704 loss) | |
| I0525 02:21:35.672799 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.038086 (* 0.0272727 = 0.00103871 loss) | |
| I0525 02:21:35.672809 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.0265165 (* 0.0272727 = 0.000723177 loss) | |
| I0525 02:21:35.672827 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.0325395 (* 0.0272727 = 0.00088744 loss) | |
| I0525 02:21:35.672840 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.0165017 (* 0.0272727 = 0.000450045 loss) | |
| I0525 02:21:35.672855 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.0179028 (* 0.0272727 = 0.000488257 loss) | |
| I0525 02:21:35.672869 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.00836521 (* 0.0272727 = 0.000228142 loss) | |
| I0525 02:21:35.672883 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.00924377 (* 0.0272727 = 0.000252103 loss) | |
| I0525 02:21:35.672897 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.00869589 (* 0.0272727 = 0.000237161 loss) | |
| I0525 02:21:35.672911 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.00726901 (* 0.0272727 = 0.000198246 loss) | |
| I0525 02:21:35.672925 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.0099611 (* 0.0272727 = 0.000271666 loss) | |
| I0525 02:21:35.672938 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.00892544 (* 0.0272727 = 0.000243421 loss) | |
| I0525 02:21:35.672951 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.0454545 | |
| I0525 02:21:35.672963 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0 | |
| I0525 02:21:35.672976 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0.125 | |
| I0525 02:21:35.672987 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0.25 | |
| I0525 02:21:35.672999 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.125 | |
| I0525 02:21:35.673012 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.25 | |
| I0525 02:21:35.673023 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.5 | |
| I0525 02:21:35.673035 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.625 | |
| I0525 02:21:35.673048 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.875 | |
| I0525 02:21:35.673058 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 1 | |
| I0525 02:21:35.673070 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 1 | |
| I0525 02:21:35.673082 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 02:21:35.673094 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 02:21:35.673105 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 02:21:35.673128 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 02:21:35.673154 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 02:21:35.673168 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 02:21:35.673180 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 02:21:35.673192 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 02:21:35.673203 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 02:21:35.673215 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 02:21:35.673226 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 02:21:35.673238 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 02:21:35.673250 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.727273 | |
| I0525 02:21:35.673262 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.204545 | |
| I0525 02:21:35.673276 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.27141 (* 1 = 3.27141 loss) | |
| I0525 02:21:35.673290 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.05304 (* 1 = 1.05304 loss) | |
| I0525 02:21:35.673305 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 3.41528 (* 0.0909091 = 0.31048 loss) | |
| I0525 02:21:35.673318 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.12796 (* 0.0909091 = 0.28436 loss) | |
| I0525 02:21:35.673331 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.84016 (* 0.0909091 = 0.349105 loss) | |
| I0525 02:21:35.673346 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 2.85887 (* 0.0909091 = 0.259898 loss) | |
| I0525 02:21:35.673359 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 2.57313 (* 0.0909091 = 0.233921 loss) | |
| I0525 02:21:35.673373 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 1.79931 (* 0.0909091 = 0.163574 loss) | |
| I0525 02:21:35.673387 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 1.43675 (* 0.0909091 = 0.130614 loss) | |
| I0525 02:21:35.673400 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.880615 (* 0.0909091 = 0.0800559 loss) | |
| I0525 02:21:35.673413 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.109578 (* 0.0909091 = 0.00996167 loss) | |
| I0525 02:21:35.673427 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.0728514 (* 0.0909091 = 0.00662285 loss) | |
| I0525 02:21:35.673441 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.0556163 (* 0.0909091 = 0.00505603 loss) | |
| I0525 02:21:35.673455 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.0410828 (* 0.0909091 = 0.0037348 loss) | |
| I0525 02:21:35.673470 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.0222269 (* 0.0909091 = 0.00202063 loss) | |
| I0525 02:21:35.673483 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.0348786 (* 0.0909091 = 0.00317078 loss) | |
| I0525 02:21:35.673502 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.0149971 (* 0.0909091 = 0.00136338 loss) | |
| I0525 02:21:35.673516 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.0110018 (* 0.0909091 = 0.00100017 loss) | |
| I0525 02:21:35.673530 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.00713083 (* 0.0909091 = 0.000648258 loss) | |
| I0525 02:21:35.673547 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.00472702 (* 0.0909091 = 0.000429729 loss) | |
| I0525 02:21:35.673560 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00420165 (* 0.0909091 = 0.000381968 loss) | |
| I0525 02:21:35.673574 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00305481 (* 0.0909091 = 0.00027771 loss) | |
| I0525 02:21:35.673588 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00313771 (* 0.0909091 = 0.000285246 loss) | |
| I0525 02:21:35.673602 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.00216713 (* 0.0909091 = 0.000197012 loss) | |
| I0525 02:21:35.673614 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 02:21:35.673636 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 02:21:35.673650 5272 solver.cpp:245] Train net output #149: total_confidence = 1.41469e-05 | |
| I0525 02:21:35.673661 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 0.000203692 | |
| I0525 02:21:35.673676 5272 sgd_solver.cpp:106] Iteration 10000, lr = 0.001 | |
| I0525 02:24:46.944454 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 36.6155 > 30) by scale factor 0.819325 | |
| I0525 02:26:56.324043 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 34.5703 > 30) by scale factor 0.867798 | |
| I0525 02:28:00.645170 5272 solver.cpp:229] Iteration 10500, loss = 10.5161 | |
| I0525 02:28:00.645267 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.113636 | |
| I0525 02:28:00.645287 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0 | |
| I0525 02:28:00.645300 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0525 02:28:00.645313 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0525 02:28:00.645325 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0 | |
| I0525 02:28:00.645337 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.125 | |
| I0525 02:28:00.645350 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.375 | |
| I0525 02:28:00.645362 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.875 | |
| I0525 02:28:00.645375 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 1 | |
| I0525 02:28:00.645387 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 1 | |
| I0525 02:28:00.645401 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 1 | |
| I0525 02:28:00.645412 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 02:28:00.645424 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 02:28:00.645437 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 02:28:00.645448 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 02:28:00.645459 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 02:28:00.645472 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 02:28:00.645483 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 02:28:00.645495 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 02:28:00.645506 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 02:28:00.645519 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 02:28:00.645530 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 02:28:00.645542 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 02:28:00.645555 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.755682 | |
| I0525 02:28:00.645566 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.227273 | |
| I0525 02:28:00.645583 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.93714 (* 0.3 = 1.18114 loss) | |
| I0525 02:28:00.645597 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.19573 (* 0.3 = 0.358719 loss) | |
| I0525 02:28:00.645612 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 4.19738 (* 0.0272727 = 0.114474 loss) | |
| I0525 02:28:00.645627 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 4.30166 (* 0.0272727 = 0.117318 loss) | |
| I0525 02:28:00.645640 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 4.65508 (* 0.0272727 = 0.126957 loss) | |
| I0525 02:28:00.645654 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.8046 (* 0.0272727 = 0.103762 loss) | |
| I0525 02:28:00.645668 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 4.07525 (* 0.0272727 = 0.111143 loss) | |
| I0525 02:28:00.645683 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 3.25911 (* 0.0272727 = 0.0888847 loss) | |
| I0525 02:28:00.645696 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 1.09576 (* 0.0272727 = 0.0298844 loss) | |
| I0525 02:28:00.645710 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 0.109662 (* 0.0272727 = 0.00299079 loss) | |
| I0525 02:28:00.645725 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.0150507 (* 0.0272727 = 0.000410473 loss) | |
| I0525 02:28:00.645745 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.020037 (* 0.0272727 = 0.000546464 loss) | |
| I0525 02:28:00.645761 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.0149847 (* 0.0272727 = 0.000408674 loss) | |
| I0525 02:28:00.645774 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.0141346 (* 0.0272727 = 0.00038549 loss) | |
| I0525 02:28:00.645788 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.0136142 (* 0.0272727 = 0.000371296 loss) | |
| I0525 02:28:00.645823 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.0160565 (* 0.0272727 = 0.000437904 loss) | |
| I0525 02:28:00.645839 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.010644 (* 0.0272727 = 0.000290291 loss) | |
| I0525 02:28:00.645853 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.00852614 (* 0.0272727 = 0.000232531 loss) | |
| I0525 02:28:00.645869 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.00958703 (* 0.0272727 = 0.000261464 loss) | |
| I0525 02:28:00.645882 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.00604765 (* 0.0272727 = 0.000164936 loss) | |
| I0525 02:28:00.645896 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.00766853 (* 0.0272727 = 0.000209142 loss) | |
| I0525 02:28:00.645911 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.00471937 (* 0.0272727 = 0.00012871 loss) | |
| I0525 02:28:00.645925 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.00935873 (* 0.0272727 = 0.000255238 loss) | |
| I0525 02:28:00.645938 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.0117441 (* 0.0272727 = 0.000320292 loss) | |
| I0525 02:28:00.645951 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.0227273 | |
| I0525 02:28:00.645963 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0 | |
| I0525 02:28:00.645975 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0.125 | |
| I0525 02:28:00.645987 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0 | |
| I0525 02:28:00.645998 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0 | |
| I0525 02:28:00.646010 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0 | |
| I0525 02:28:00.646021 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.375 | |
| I0525 02:28:00.646034 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.875 | |
| I0525 02:28:00.646045 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 1 | |
| I0525 02:28:00.646056 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 1 | |
| I0525 02:28:00.646069 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 1 | |
| I0525 02:28:00.646080 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 02:28:00.646091 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 02:28:00.646102 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 02:28:00.646114 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 02:28:00.646126 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 02:28:00.646137 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 02:28:00.646148 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 02:28:00.646159 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 02:28:00.646172 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 02:28:00.646183 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 02:28:00.646194 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 02:28:00.646205 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 02:28:00.646217 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.738636 | |
| I0525 02:28:00.646229 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.181818 | |
| I0525 02:28:00.646244 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.91437 (* 0.3 = 1.17431 loss) | |
| I0525 02:28:00.646257 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.15735 (* 0.3 = 0.347204 loss) | |
| I0525 02:28:00.646270 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 4.16786 (* 0.0272727 = 0.113669 loss) | |
| I0525 02:28:00.646284 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 4.08381 (* 0.0272727 = 0.111377 loss) | |
| I0525 02:28:00.646297 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 4.65205 (* 0.0272727 = 0.126874 loss) | |
| I0525 02:28:00.646322 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.50792 (* 0.0272727 = 0.0956707 loss) | |
| I0525 02:28:00.646337 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 3.84236 (* 0.0272727 = 0.104792 loss) | |
| I0525 02:28:00.646352 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 2.9908 (* 0.0272727 = 0.0815671 loss) | |
| I0525 02:28:00.646365 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 0.923318 (* 0.0272727 = 0.0251814 loss) | |
| I0525 02:28:00.646379 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 0.0650213 (* 0.0272727 = 0.00177331 loss) | |
| I0525 02:28:00.646394 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.0178501 (* 0.0272727 = 0.000486821 loss) | |
| I0525 02:28:00.646409 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.0148369 (* 0.0272727 = 0.000404642 loss) | |
| I0525 02:28:00.646422 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.0104599 (* 0.0272727 = 0.000285269 loss) | |
| I0525 02:28:00.646436 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.0070252 (* 0.0272727 = 0.000191596 loss) | |
| I0525 02:28:00.646450 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.0156712 (* 0.0272727 = 0.000427395 loss) | |
| I0525 02:28:00.646464 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.00604206 (* 0.0272727 = 0.000164783 loss) | |
| I0525 02:28:00.646478 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.00978446 (* 0.0272727 = 0.000266849 loss) | |
| I0525 02:28:00.646492 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.00681665 (* 0.0272727 = 0.000185909 loss) | |
| I0525 02:28:00.646507 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.00238634 (* 0.0272727 = 6.5082e-05 loss) | |
| I0525 02:28:00.646520 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.00880411 (* 0.0272727 = 0.000240112 loss) | |
| I0525 02:28:00.646534 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.00385024 (* 0.0272727 = 0.000105007 loss) | |
| I0525 02:28:00.646548 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.00453315 (* 0.0272727 = 0.000123632 loss) | |
| I0525 02:28:00.646561 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.00390887 (* 0.0272727 = 0.000106605 loss) | |
| I0525 02:28:00.646575 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.00390801 (* 0.0272727 = 0.000106582 loss) | |
| I0525 02:28:00.646587 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.0681818 | |
| I0525 02:28:00.646600 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0 | |
| I0525 02:28:00.646611 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0.25 | |
| I0525 02:28:00.646623 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0 | |
| I0525 02:28:00.646636 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0 | |
| I0525 02:28:00.646647 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.125 | |
| I0525 02:28:00.646659 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.375 | |
| I0525 02:28:00.646672 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.875 | |
| I0525 02:28:00.646683 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 1 | |
| I0525 02:28:00.646694 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 1 | |
| I0525 02:28:00.646705 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 1 | |
| I0525 02:28:00.646718 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 02:28:00.646729 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 02:28:00.646740 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 02:28:00.646751 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 02:28:00.646764 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 02:28:00.646775 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 02:28:00.646801 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 02:28:00.646816 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 02:28:00.646827 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 02:28:00.646839 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 02:28:00.646850 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 02:28:00.646862 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 02:28:00.646873 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.75 | |
| I0525 02:28:00.646886 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.227273 | |
| I0525 02:28:00.646899 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.70604 (* 1 = 3.70604 loss) | |
| I0525 02:28:00.646914 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.11588 (* 1 = 1.11588 loss) | |
| I0525 02:28:00.646927 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 4.00319 (* 0.0909091 = 0.363926 loss) | |
| I0525 02:28:00.646941 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.61836 (* 0.0909091 = 0.328941 loss) | |
| I0525 02:28:00.646955 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 4.3406 (* 0.0909091 = 0.3946 loss) | |
| I0525 02:28:00.646970 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.67213 (* 0.0909091 = 0.33383 loss) | |
| I0525 02:28:00.646982 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 4.03098 (* 0.0909091 = 0.366453 loss) | |
| I0525 02:28:00.646997 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 2.87937 (* 0.0909091 = 0.261761 loss) | |
| I0525 02:28:00.647011 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 0.748941 (* 0.0909091 = 0.0680856 loss) | |
| I0525 02:28:00.647025 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.0794521 (* 0.0909091 = 0.00722292 loss) | |
| I0525 02:28:00.647039 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.0244644 (* 0.0909091 = 0.00222403 loss) | |
| I0525 02:28:00.647053 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.0144105 (* 0.0909091 = 0.00131005 loss) | |
| I0525 02:28:00.647068 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.0109486 (* 0.0909091 = 0.00099533 loss) | |
| I0525 02:28:00.647080 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.00609529 (* 0.0909091 = 0.000554118 loss) | |
| I0525 02:28:00.647095 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.00528298 (* 0.0909091 = 0.000480271 loss) | |
| I0525 02:28:00.647109 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.00484999 (* 0.0909091 = 0.000440909 loss) | |
| I0525 02:28:00.647119 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.00344551 (* 0.0909091 = 0.000313228 loss) | |
| I0525 02:28:00.647130 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.0030429 (* 0.0909091 = 0.000276627 loss) | |
| I0525 02:28:00.647145 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.00524567 (* 0.0909091 = 0.000476879 loss) | |
| I0525 02:28:00.647159 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.00378059 (* 0.0909091 = 0.00034369 loss) | |
| I0525 02:28:00.647173 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00375345 (* 0.0909091 = 0.000341222 loss) | |
| I0525 02:28:00.647187 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00401738 (* 0.0909091 = 0.000365217 loss) | |
| I0525 02:28:00.647202 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00264488 (* 0.0909091 = 0.000240444 loss) | |
| I0525 02:28:00.647214 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.00167358 (* 0.0909091 = 0.000152143 loss) | |
| I0525 02:28:00.647228 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 02:28:00.647238 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 02:28:00.647249 5272 solver.cpp:245] Train net output #149: total_confidence = 7.321e-07 | |
| I0525 02:28:00.647271 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 2.81173e-05 | |
| I0525 02:28:00.647286 5272 sgd_solver.cpp:106] Iteration 10500, lr = 0.001 | |
| I0525 02:28:27.982177 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 31.6898 > 30) by scale factor 0.946676 | |
| I0525 02:29:21.902336 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 33.3312 > 30) by scale factor 0.900059 | |
| I0525 02:30:11.175292 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 34.8269 > 30) by scale factor 0.861403 | |
| I0525 02:30:38.887442 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 35.3263 > 30) by scale factor 0.849225 | |
| I0525 02:30:55.048616 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 30.9548 > 30) by scale factor 0.969156 | |
| I0525 02:30:57.361604 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 121.946 > 30) by scale factor 0.24601 | |
| I0525 02:32:04.335583 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 64.8467 > 30) by scale factor 0.462629 | |
| I0525 02:33:31.359506 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 34.6863 > 30) by scale factor 0.864895 | |
| I0525 02:34:25.661705 5272 solver.cpp:229] Iteration 11000, loss = 10.4521 | |
| I0525 02:34:25.661849 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.06 | |
| I0525 02:34:25.661870 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.125 | |
| I0525 02:34:25.661885 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0525 02:34:25.661898 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0525 02:34:25.661911 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.25 | |
| I0525 02:34:25.661926 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.25 | |
| I0525 02:34:25.661938 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.25 | |
| I0525 02:34:25.661950 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.875 | |
| I0525 02:34:25.661963 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.875 | |
| I0525 02:34:25.661977 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 0.875 | |
| I0525 02:34:25.661989 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 0.875 | |
| I0525 02:34:25.662001 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 0.875 | |
| I0525 02:34:25.662014 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 0.875 | |
| I0525 02:34:25.662027 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 0.875 | |
| I0525 02:34:25.662039 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 0.875 | |
| I0525 02:34:25.662051 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 02:34:25.662063 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 02:34:25.662075 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 02:34:25.662087 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 02:34:25.662099 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 02:34:25.662111 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 02:34:25.662123 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 02:34:25.662134 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 02:34:25.662147 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.670455 | |
| I0525 02:34:25.662158 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.22 | |
| I0525 02:34:25.662174 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.30386 (* 0.3 = 0.991158 loss) | |
| I0525 02:34:25.662189 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.25399 (* 0.3 = 0.376196 loss) | |
| I0525 02:34:25.662204 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.27002 (* 0.0272727 = 0.0891824 loss) | |
| I0525 02:34:25.662217 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.33604 (* 0.0272727 = 0.090983 loss) | |
| I0525 02:34:25.662231 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.67329 (* 0.0272727 = 0.100181 loss) | |
| I0525 02:34:25.662245 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.06781 (* 0.0272727 = 0.0836675 loss) | |
| I0525 02:34:25.662259 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 2.86534 (* 0.0272727 = 0.0781455 loss) | |
| I0525 02:34:25.662273 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 3.12376 (* 0.0272727 = 0.0851934 loss) | |
| I0525 02:34:25.662287 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 0.839753 (* 0.0272727 = 0.0229024 loss) | |
| I0525 02:34:25.662302 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 0.433767 (* 0.0272727 = 0.01183 loss) | |
| I0525 02:34:25.662315 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.462224 (* 0.0272727 = 0.0126061 loss) | |
| I0525 02:34:25.662330 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.610093 (* 0.0272727 = 0.0166389 loss) | |
| I0525 02:34:25.662344 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.679484 (* 0.0272727 = 0.0185314 loss) | |
| I0525 02:34:25.662358 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.589567 (* 0.0272727 = 0.0160791 loss) | |
| I0525 02:34:25.662371 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.469102 (* 0.0272727 = 0.0127937 loss) | |
| I0525 02:34:25.662407 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.4895 (* 0.0272727 = 0.01335 loss) | |
| I0525 02:34:25.662422 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.215133 (* 0.0272727 = 0.00586727 loss) | |
| I0525 02:34:25.662437 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.0876558 (* 0.0272727 = 0.00239061 loss) | |
| I0525 02:34:25.662451 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.0503884 (* 0.0272727 = 0.00137423 loss) | |
| I0525 02:34:25.662466 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0269345 (* 0.0272727 = 0.000734577 loss) | |
| I0525 02:34:25.662480 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.00856045 (* 0.0272727 = 0.000233467 loss) | |
| I0525 02:34:25.662494 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.0116226 (* 0.0272727 = 0.000316981 loss) | |
| I0525 02:34:25.662508 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.0152611 (* 0.0272727 = 0.000416211 loss) | |
| I0525 02:34:25.662523 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.0148711 (* 0.0272727 = 0.000405576 loss) | |
| I0525 02:34:25.662535 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.06 | |
| I0525 02:34:25.662547 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0.25 | |
| I0525 02:34:25.662560 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0 | |
| I0525 02:34:25.662571 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0 | |
| I0525 02:34:25.662583 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0.25 | |
| I0525 02:34:25.662595 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.25 | |
| I0525 02:34:25.662607 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.25 | |
| I0525 02:34:25.662619 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.875 | |
| I0525 02:34:25.662631 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 1 | |
| I0525 02:34:25.662643 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 0.875 | |
| I0525 02:34:25.662655 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 0.875 | |
| I0525 02:34:25.662667 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 0.875 | |
| I0525 02:34:25.662678 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 0.875 | |
| I0525 02:34:25.662690 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 0.875 | |
| I0525 02:34:25.662703 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 0.875 | |
| I0525 02:34:25.662714 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 02:34:25.662726 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 02:34:25.662739 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 02:34:25.662750 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 02:34:25.662761 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 02:34:25.662773 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 02:34:25.662784 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 02:34:25.662796 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 02:34:25.662807 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.732955 | |
| I0525 02:34:25.662819 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.18 | |
| I0525 02:34:25.662833 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.42695 (* 0.3 = 1.02808 loss) | |
| I0525 02:34:25.662847 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.09081 (* 0.3 = 0.327243 loss) | |
| I0525 02:34:25.662864 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.26311 (* 0.0272727 = 0.088994 loss) | |
| I0525 02:34:25.662879 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 3.57417 (* 0.0272727 = 0.0974773 loss) | |
| I0525 02:34:25.662904 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.56997 (* 0.0272727 = 0.0973628 loss) | |
| I0525 02:34:25.662919 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.44516 (* 0.0272727 = 0.093959 loss) | |
| I0525 02:34:25.662936 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 2.99968 (* 0.0272727 = 0.0818096 loss) | |
| I0525 02:34:25.662950 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 3.04439 (* 0.0272727 = 0.0830289 loss) | |
| I0525 02:34:25.662963 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 1.22552 (* 0.0272727 = 0.0334234 loss) | |
| I0525 02:34:25.662977 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 0.378498 (* 0.0272727 = 0.0103227 loss) | |
| I0525 02:34:25.662992 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.697961 (* 0.0272727 = 0.0190353 loss) | |
| I0525 02:34:25.663005 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.497688 (* 0.0272727 = 0.0135733 loss) | |
| I0525 02:34:25.663019 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.522105 (* 0.0272727 = 0.0142392 loss) | |
| I0525 02:34:25.663033 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.571712 (* 0.0272727 = 0.0155921 loss) | |
| I0525 02:34:25.663048 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.426438 (* 0.0272727 = 0.0116301 loss) | |
| I0525 02:34:25.663061 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.539218 (* 0.0272727 = 0.014706 loss) | |
| I0525 02:34:25.663075 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.122262 (* 0.0272727 = 0.00333443 loss) | |
| I0525 02:34:25.663090 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.0811688 (* 0.0272727 = 0.0022137 loss) | |
| I0525 02:34:25.663105 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.0681039 (* 0.0272727 = 0.00185738 loss) | |
| I0525 02:34:25.663118 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.0211841 (* 0.0272727 = 0.000577747 loss) | |
| I0525 02:34:25.663132 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.0206871 (* 0.0272727 = 0.000564194 loss) | |
| I0525 02:34:25.663146 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.0233919 (* 0.0272727 = 0.000637961 loss) | |
| I0525 02:34:25.663161 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.0166734 (* 0.0272727 = 0.000454728 loss) | |
| I0525 02:34:25.663174 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.0120139 (* 0.0272727 = 0.000327651 loss) | |
| I0525 02:34:25.663187 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.08 | |
| I0525 02:34:25.663198 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.25 | |
| I0525 02:34:25.663210 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0 | |
| I0525 02:34:25.663223 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0 | |
| I0525 02:34:25.663234 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.25 | |
| I0525 02:34:25.663246 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.25 | |
| I0525 02:34:25.663259 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.25 | |
| I0525 02:34:25.663270 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.875 | |
| I0525 02:34:25.663282 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 1 | |
| I0525 02:34:25.663295 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 0.875 | |
| I0525 02:34:25.663306 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 0.875 | |
| I0525 02:34:25.663318 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 0.875 | |
| I0525 02:34:25.663331 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 0.875 | |
| I0525 02:34:25.663342 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 0.875 | |
| I0525 02:34:25.663353 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 0.875 | |
| I0525 02:34:25.663365 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 02:34:25.663378 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 02:34:25.663398 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 02:34:25.663411 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 02:34:25.663422 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 02:34:25.663434 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 02:34:25.663446 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 02:34:25.663458 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 02:34:25.663470 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.738636 | |
| I0525 02:34:25.663482 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.16 | |
| I0525 02:34:25.663496 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.27506 (* 1 = 3.27506 loss) | |
| I0525 02:34:25.663509 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.05463 (* 1 = 1.05463 loss) | |
| I0525 02:34:25.663524 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 3.02914 (* 0.0909091 = 0.275376 loss) | |
| I0525 02:34:25.663534 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.3254 (* 0.0909091 = 0.302309 loss) | |
| I0525 02:34:25.663550 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.24472 (* 0.0909091 = 0.294975 loss) | |
| I0525 02:34:25.663565 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 2.85569 (* 0.0909091 = 0.259609 loss) | |
| I0525 02:34:25.663578 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 2.93663 (* 0.0909091 = 0.266966 loss) | |
| I0525 02:34:25.663592 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 3.01443 (* 0.0909091 = 0.27404 loss) | |
| I0525 02:34:25.663606 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 0.686808 (* 0.0909091 = 0.0624371 loss) | |
| I0525 02:34:25.663619 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.24189 (* 0.0909091 = 0.02199 loss) | |
| I0525 02:34:25.663633 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.528777 (* 0.0909091 = 0.0480707 loss) | |
| I0525 02:34:25.663647 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.297723 (* 0.0909091 = 0.0270657 loss) | |
| I0525 02:34:25.663661 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.459846 (* 0.0909091 = 0.0418042 loss) | |
| I0525 02:34:25.663676 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.560964 (* 0.0909091 = 0.0509967 loss) | |
| I0525 02:34:25.663689 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.405331 (* 0.0909091 = 0.0368483 loss) | |
| I0525 02:34:25.663703 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.445693 (* 0.0909091 = 0.0405175 loss) | |
| I0525 02:34:25.663718 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.188324 (* 0.0909091 = 0.0171204 loss) | |
| I0525 02:34:25.663733 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.126951 (* 0.0909091 = 0.011541 loss) | |
| I0525 02:34:25.663746 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.0188411 (* 0.0909091 = 0.00171282 loss) | |
| I0525 02:34:25.663760 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.0147675 (* 0.0909091 = 0.0013425 loss) | |
| I0525 02:34:25.663775 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.0099363 (* 0.0909091 = 0.0009033 loss) | |
| I0525 02:34:25.663789 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00753917 (* 0.0909091 = 0.000685379 loss) | |
| I0525 02:34:25.663803 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00505063 (* 0.0909091 = 0.000459148 loss) | |
| I0525 02:34:25.663818 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.00374615 (* 0.0909091 = 0.000340559 loss) | |
| I0525 02:34:25.663830 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 02:34:25.663842 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 02:34:25.663853 5272 solver.cpp:245] Train net output #149: total_confidence = 4.82095e-05 | |
| I0525 02:34:25.663874 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 0.000520887 | |
| I0525 02:34:25.663888 5272 sgd_solver.cpp:106] Iteration 11000, lr = 0.001 | |
| I0525 02:35:24.522387 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 30.8059 > 30) by scale factor 0.973839 | |
| I0525 02:37:30.804821 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 65.8581 > 30) by scale factor 0.455525 | |
| I0525 02:40:18.634148 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 30.6774 > 30) by scale factor 0.977918 | |
| I0525 02:40:25.571470 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 34.0927 > 30) by scale factor 0.879954 | |
| I0525 02:40:50.595798 5272 solver.cpp:229] Iteration 11500, loss = 10.3291 | |
| I0525 02:40:50.595916 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0784314 | |
| I0525 02:40:50.595937 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0 | |
| I0525 02:40:50.595950 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0.125 | |
| I0525 02:40:50.595963 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0525 02:40:50.595975 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.125 | |
| I0525 02:40:50.595988 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.125 | |
| I0525 02:40:50.596000 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.25 | |
| I0525 02:40:50.596014 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.625 | |
| I0525 02:40:50.596026 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.875 | |
| I0525 02:40:50.596038 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 0.875 | |
| I0525 02:40:50.596051 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 0.875 | |
| I0525 02:40:50.596065 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 0.875 | |
| I0525 02:40:50.596081 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 0.875 | |
| I0525 02:40:50.596103 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 02:40:50.596122 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 02:40:50.596138 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 02:40:50.596151 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 02:40:50.596163 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 02:40:50.596174 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 02:40:50.596186 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 02:40:50.596199 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 02:40:50.596210 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 02:40:50.596221 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 02:40:50.596233 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.704545 | |
| I0525 02:40:50.596253 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.176471 | |
| I0525 02:40:50.596279 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.42657 (* 0.3 = 1.02797 loss) | |
| I0525 02:40:50.596295 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.26096 (* 0.3 = 0.378289 loss) | |
| I0525 02:40:50.596309 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.94878 (* 0.0272727 = 0.107694 loss) | |
| I0525 02:40:50.596323 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.57616 (* 0.0272727 = 0.0975317 loss) | |
| I0525 02:40:50.596338 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 4.17248 (* 0.0272727 = 0.113795 loss) | |
| I0525 02:40:50.596351 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.35388 (* 0.0272727 = 0.0914694 loss) | |
| I0525 02:40:50.596365 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 3.04976 (* 0.0272727 = 0.0831753 loss) | |
| I0525 02:40:50.596379 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 2.95395 (* 0.0272727 = 0.0805624 loss) | |
| I0525 02:40:50.596393 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 2.25185 (* 0.0272727 = 0.0614141 loss) | |
| I0525 02:40:50.596407 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 0.707424 (* 0.0272727 = 0.0192934 loss) | |
| I0525 02:40:50.596421 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.477193 (* 0.0272727 = 0.0130144 loss) | |
| I0525 02:40:50.596436 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.782575 (* 0.0272727 = 0.0213429 loss) | |
| I0525 02:40:50.596449 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.475722 (* 0.0272727 = 0.0129742 loss) | |
| I0525 02:40:50.596463 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.666057 (* 0.0272727 = 0.0181652 loss) | |
| I0525 02:40:50.596478 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.0716908 (* 0.0272727 = 0.0019552 loss) | |
| I0525 02:40:50.596513 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.0513454 (* 0.0272727 = 0.00140033 loss) | |
| I0525 02:40:50.596529 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0256102 (* 0.0272727 = 0.000698461 loss) | |
| I0525 02:40:50.596544 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.027763 (* 0.0272727 = 0.000757173 loss) | |
| I0525 02:40:50.596557 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.0154844 (* 0.0272727 = 0.000422302 loss) | |
| I0525 02:40:50.596571 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0216072 (* 0.0272727 = 0.000589287 loss) | |
| I0525 02:40:50.596585 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.0148684 (* 0.0272727 = 0.000405503 loss) | |
| I0525 02:40:50.596599 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.0117548 (* 0.0272727 = 0.000320587 loss) | |
| I0525 02:40:50.596613 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.0240704 (* 0.0272727 = 0.000656465 loss) | |
| I0525 02:40:50.596627 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.00909316 (* 0.0272727 = 0.000247995 loss) | |
| I0525 02:40:50.596639 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.0784314 | |
| I0525 02:40:50.596652 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0 | |
| I0525 02:40:50.596664 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0.125 | |
| I0525 02:40:50.596676 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0 | |
| I0525 02:40:50.596688 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0.25 | |
| I0525 02:40:50.596700 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.25 | |
| I0525 02:40:50.596712 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.25 | |
| I0525 02:40:50.596724 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.625 | |
| I0525 02:40:50.596736 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.875 | |
| I0525 02:40:50.596748 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 0.875 | |
| I0525 02:40:50.596760 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 0.875 | |
| I0525 02:40:50.596771 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 0.875 | |
| I0525 02:40:50.596783 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 0.875 | |
| I0525 02:40:50.596797 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 02:40:50.596810 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 02:40:50.596822 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 02:40:50.596834 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 02:40:50.596845 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 02:40:50.596858 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 02:40:50.596868 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 02:40:50.596880 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 02:40:50.596892 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 02:40:50.596904 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 02:40:50.596915 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.715909 | |
| I0525 02:40:50.596926 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.137255 | |
| I0525 02:40:50.596940 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.35836 (* 0.3 = 1.00751 loss) | |
| I0525 02:40:50.596954 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.19902 (* 0.3 = 0.359705 loss) | |
| I0525 02:40:50.596968 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 4.31821 (* 0.0272727 = 0.117769 loss) | |
| I0525 02:40:50.596982 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 3.82222 (* 0.0272727 = 0.104242 loss) | |
| I0525 02:40:50.597007 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 4.08618 (* 0.0272727 = 0.111441 loss) | |
| I0525 02:40:50.597021 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.14727 (* 0.0272727 = 0.0858346 loss) | |
| I0525 02:40:50.597036 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 3.03893 (* 0.0272727 = 0.0828798 loss) | |
| I0525 02:40:50.597061 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 3.19486 (* 0.0272727 = 0.0871327 loss) | |
| I0525 02:40:50.597087 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 2.01338 (* 0.0272727 = 0.0549104 loss) | |
| I0525 02:40:50.597105 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 0.553043 (* 0.0272727 = 0.015083 loss) | |
| I0525 02:40:50.597132 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.376881 (* 0.0272727 = 0.0102786 loss) | |
| I0525 02:40:50.597149 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.535015 (* 0.0272727 = 0.0145913 loss) | |
| I0525 02:40:50.597163 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.445996 (* 0.0272727 = 0.0121635 loss) | |
| I0525 02:40:50.597177 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.612891 (* 0.0272727 = 0.0167152 loss) | |
| I0525 02:40:50.597195 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.0930959 (* 0.0272727 = 0.00253898 loss) | |
| I0525 02:40:50.597210 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.0614963 (* 0.0272727 = 0.00167717 loss) | |
| I0525 02:40:50.597224 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.0474584 (* 0.0272727 = 0.00129432 loss) | |
| I0525 02:40:50.597239 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.0264458 (* 0.0272727 = 0.000721249 loss) | |
| I0525 02:40:50.597252 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.0189328 (* 0.0272727 = 0.00051635 loss) | |
| I0525 02:40:50.597262 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.00799538 (* 0.0272727 = 0.000218056 loss) | |
| I0525 02:40:50.597277 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.00849798 (* 0.0272727 = 0.000231763 loss) | |
| I0525 02:40:50.597292 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.0117907 (* 0.0272727 = 0.000321564 loss) | |
| I0525 02:40:50.597306 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.00699201 (* 0.0272727 = 0.000190691 loss) | |
| I0525 02:40:50.597319 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.00597752 (* 0.0272727 = 0.000163023 loss) | |
| I0525 02:40:50.597332 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.0588235 | |
| I0525 02:40:50.597343 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0 | |
| I0525 02:40:50.597355 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0.25 | |
| I0525 02:40:50.597368 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0 | |
| I0525 02:40:50.597379 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.25 | |
| I0525 02:40:50.597390 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.25 | |
| I0525 02:40:50.597403 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.25 | |
| I0525 02:40:50.597414 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.625 | |
| I0525 02:40:50.597425 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.875 | |
| I0525 02:40:50.597437 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 0.875 | |
| I0525 02:40:50.597450 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 0.875 | |
| I0525 02:40:50.597460 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 0.875 | |
| I0525 02:40:50.597472 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 0.875 | |
| I0525 02:40:50.597483 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 02:40:50.597496 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 02:40:50.597506 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 02:40:50.597518 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 02:40:50.597543 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 02:40:50.597554 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 02:40:50.597566 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 02:40:50.597578 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 02:40:50.597589 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 02:40:50.597600 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 02:40:50.597612 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.715909 | |
| I0525 02:40:50.597623 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.176471 | |
| I0525 02:40:50.597637 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.33208 (* 1 = 3.33208 loss) | |
| I0525 02:40:50.597651 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.08258 (* 1 = 1.08258 loss) | |
| I0525 02:40:50.597666 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 4.04539 (* 0.0909091 = 0.367763 loss) | |
| I0525 02:40:50.597678 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.44273 (* 0.0909091 = 0.312976 loss) | |
| I0525 02:40:50.597692 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.51712 (* 0.0909091 = 0.319738 loss) | |
| I0525 02:40:50.597705 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 2.66002 (* 0.0909091 = 0.24182 loss) | |
| I0525 02:40:50.597719 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 2.60911 (* 0.0909091 = 0.237192 loss) | |
| I0525 02:40:50.597733 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 2.89707 (* 0.0909091 = 0.26337 loss) | |
| I0525 02:40:50.597746 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 1.94152 (* 0.0909091 = 0.176502 loss) | |
| I0525 02:40:50.597760 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.544194 (* 0.0909091 = 0.0494722 loss) | |
| I0525 02:40:50.597774 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.295606 (* 0.0909091 = 0.0268733 loss) | |
| I0525 02:40:50.597787 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.669447 (* 0.0909091 = 0.0608588 loss) | |
| I0525 02:40:50.597801 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.493635 (* 0.0909091 = 0.0448759 loss) | |
| I0525 02:40:50.597815 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.678522 (* 0.0909091 = 0.0616839 loss) | |
| I0525 02:40:50.597828 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.0271028 (* 0.0909091 = 0.00246389 loss) | |
| I0525 02:40:50.597843 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.0324675 (* 0.0909091 = 0.00295159 loss) | |
| I0525 02:40:50.597861 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.0100096 (* 0.0909091 = 0.000909964 loss) | |
| I0525 02:40:50.597874 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.00932357 (* 0.0909091 = 0.000847598 loss) | |
| I0525 02:40:50.597889 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.00817514 (* 0.0909091 = 0.000743194 loss) | |
| I0525 02:40:50.597903 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.00484145 (* 0.0909091 = 0.000440132 loss) | |
| I0525 02:40:50.597916 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00303621 (* 0.0909091 = 0.000276019 loss) | |
| I0525 02:40:50.597930 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00211655 (* 0.0909091 = 0.000192413 loss) | |
| I0525 02:40:50.597944 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00201174 (* 0.0909091 = 0.000182886 loss) | |
| I0525 02:40:50.597959 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.00108973 (* 0.0909091 = 9.90664e-05 loss) | |
| I0525 02:40:50.597967 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 02:40:50.597980 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 02:40:50.597991 5272 solver.cpp:245] Train net output #149: total_confidence = 1.21884e-06 | |
| I0525 02:40:50.598013 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 2.53115e-05 | |
| I0525 02:40:50.598028 5272 sgd_solver.cpp:106] Iteration 11500, lr = 0.001 | |
| I0525 02:42:07.130846 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 34.4887 > 30) by scale factor 0.869849 | |
| I0525 02:47:15.463932 5272 solver.cpp:229] Iteration 12000, loss = 10.3201 | |
| I0525 02:47:15.464093 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0508475 | |
| I0525 02:47:15.464115 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0 | |
| I0525 02:47:15.464134 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0525 02:47:15.464154 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0.125 | |
| I0525 02:47:15.464167 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.125 | |
| I0525 02:47:15.464182 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.25 | |
| I0525 02:47:15.464201 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.375 | |
| I0525 02:47:15.464215 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.5 | |
| I0525 02:47:15.464228 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.5 | |
| I0525 02:47:15.464241 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 0.625 | |
| I0525 02:47:15.464253 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 0.875 | |
| I0525 02:47:15.464267 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 0.875 | |
| I0525 02:47:15.464278 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 0.875 | |
| I0525 02:47:15.464290 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 0.875 | |
| I0525 02:47:15.464303 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 02:47:15.464314 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 02:47:15.464326 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 02:47:15.464339 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 02:47:15.464349 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 02:47:15.464361 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 02:47:15.464373 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 02:47:15.464385 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 02:47:15.464396 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 02:47:15.464408 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.681818 | |
| I0525 02:47:15.464421 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.186441 | |
| I0525 02:47:15.464437 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.26478 (* 0.3 = 0.979435 loss) | |
| I0525 02:47:15.464450 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.2857 (* 0.3 = 0.38571 loss) | |
| I0525 02:47:15.464465 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.42404 (* 0.0272727 = 0.093383 loss) | |
| I0525 02:47:15.464479 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.70486 (* 0.0272727 = 0.101042 loss) | |
| I0525 02:47:15.464495 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.1733 (* 0.0272727 = 0.0865445 loss) | |
| I0525 02:47:15.464509 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.26134 (* 0.0272727 = 0.0889457 loss) | |
| I0525 02:47:15.464524 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 2.68376 (* 0.0272727 = 0.0731934 loss) | |
| I0525 02:47:15.464537 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 2.64407 (* 0.0272727 = 0.072111 loss) | |
| I0525 02:47:15.464550 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 2.20124 (* 0.0272727 = 0.0600339 loss) | |
| I0525 02:47:15.464565 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 1.983 (* 0.0272727 = 0.0540817 loss) | |
| I0525 02:47:15.464578 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 1.56478 (* 0.0272727 = 0.0426759 loss) | |
| I0525 02:47:15.464592 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.781675 (* 0.0272727 = 0.0213184 loss) | |
| I0525 02:47:15.464607 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.646583 (* 0.0272727 = 0.0176341 loss) | |
| I0525 02:47:15.464620 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.63094 (* 0.0272727 = 0.0172075 loss) | |
| I0525 02:47:15.464634 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.825503 (* 0.0272727 = 0.0225137 loss) | |
| I0525 02:47:15.464670 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.0709609 (* 0.0272727 = 0.0019353 loss) | |
| I0525 02:47:15.464686 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0666526 (* 0.0272727 = 0.0018178 loss) | |
| I0525 02:47:15.464700 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.0407651 (* 0.0272727 = 0.00111178 loss) | |
| I0525 02:47:15.464715 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.0315376 (* 0.0272727 = 0.000860115 loss) | |
| I0525 02:47:15.464730 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0160632 (* 0.0272727 = 0.000438086 loss) | |
| I0525 02:47:15.464743 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.013271 (* 0.0272727 = 0.000361937 loss) | |
| I0525 02:47:15.464757 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.0114999 (* 0.0272727 = 0.000313633 loss) | |
| I0525 02:47:15.464771 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.0105122 (* 0.0272727 = 0.000286697 loss) | |
| I0525 02:47:15.464786 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.00871918 (* 0.0272727 = 0.000237796 loss) | |
| I0525 02:47:15.464797 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.0847458 | |
| I0525 02:47:15.464809 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0.375 | |
| I0525 02:47:15.464823 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0.125 | |
| I0525 02:47:15.464834 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0.125 | |
| I0525 02:47:15.464846 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0.125 | |
| I0525 02:47:15.464857 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.375 | |
| I0525 02:47:15.464870 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.375 | |
| I0525 02:47:15.464885 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.5 | |
| I0525 02:47:15.464897 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.5 | |
| I0525 02:47:15.464910 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 0.625 | |
| I0525 02:47:15.464925 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 0.875 | |
| I0525 02:47:15.464946 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 0.875 | |
| I0525 02:47:15.464959 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 0.875 | |
| I0525 02:47:15.464972 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 0.875 | |
| I0525 02:47:15.464988 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 02:47:15.465004 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 02:47:15.465018 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 02:47:15.465029 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 02:47:15.465040 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 02:47:15.465052 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 02:47:15.465064 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 02:47:15.465075 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 02:47:15.465086 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 02:47:15.465098 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.693182 | |
| I0525 02:47:15.465127 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.322034 | |
| I0525 02:47:15.465142 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.13707 (* 0.3 = 0.941122 loss) | |
| I0525 02:47:15.465157 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.22715 (* 0.3 = 0.368146 loss) | |
| I0525 02:47:15.465169 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 2.79942 (* 0.0272727 = 0.0763478 loss) | |
| I0525 02:47:15.465183 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 3.62237 (* 0.0272727 = 0.0987919 loss) | |
| I0525 02:47:15.465211 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.0321 (* 0.0272727 = 0.0826935 loss) | |
| I0525 02:47:15.465226 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.50749 (* 0.0272727 = 0.0956587 loss) | |
| I0525 02:47:15.465240 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 2.82561 (* 0.0272727 = 0.077062 loss) | |
| I0525 02:47:15.465255 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 2.72742 (* 0.0272727 = 0.0743841 loss) | |
| I0525 02:47:15.465267 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 2.42663 (* 0.0272727 = 0.0661809 loss) | |
| I0525 02:47:15.465282 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 2.20712 (* 0.0272727 = 0.0601941 loss) | |
| I0525 02:47:15.465296 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 1.21751 (* 0.0272727 = 0.0332047 loss) | |
| I0525 02:47:15.465309 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.652865 (* 0.0272727 = 0.0178054 loss) | |
| I0525 02:47:15.465323 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.744584 (* 0.0272727 = 0.0203068 loss) | |
| I0525 02:47:15.465337 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.647154 (* 0.0272727 = 0.0176496 loss) | |
| I0525 02:47:15.465351 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.984918 (* 0.0272727 = 0.0268614 loss) | |
| I0525 02:47:15.465365 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.0356069 (* 0.0272727 = 0.000971097 loss) | |
| I0525 02:47:15.465379 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.0473983 (* 0.0272727 = 0.00129268 loss) | |
| I0525 02:47:15.465394 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.010702 (* 0.0272727 = 0.000291873 loss) | |
| I0525 02:47:15.465409 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.00669342 (* 0.0272727 = 0.000182548 loss) | |
| I0525 02:47:15.465422 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.00251353 (* 0.0272727 = 6.85508e-05 loss) | |
| I0525 02:47:15.465436 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.00257808 (* 0.0272727 = 7.03114e-05 loss) | |
| I0525 02:47:15.465451 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.00218635 (* 0.0272727 = 5.96278e-05 loss) | |
| I0525 02:47:15.465464 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.00195691 (* 0.0272727 = 5.33702e-05 loss) | |
| I0525 02:47:15.465477 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.00258035 (* 0.0272727 = 7.03732e-05 loss) | |
| I0525 02:47:15.465490 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.152542 | |
| I0525 02:47:15.465502 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.25 | |
| I0525 02:47:15.465514 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0.125 | |
| I0525 02:47:15.465528 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0.25 | |
| I0525 02:47:15.465539 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.125 | |
| I0525 02:47:15.465550 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.375 | |
| I0525 02:47:15.465562 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.5 | |
| I0525 02:47:15.465574 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.625 | |
| I0525 02:47:15.465586 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.5 | |
| I0525 02:47:15.465597 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 0.75 | |
| I0525 02:47:15.465610 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 0.875 | |
| I0525 02:47:15.465621 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 0.875 | |
| I0525 02:47:15.465633 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 0.875 | |
| I0525 02:47:15.465646 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 0.875 | |
| I0525 02:47:15.465657 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 02:47:15.465668 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 02:47:15.465680 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 02:47:15.465698 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 02:47:15.465716 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 02:47:15.465734 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 02:47:15.465747 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 02:47:15.465764 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 02:47:15.465778 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 02:47:15.465790 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.704545 | |
| I0525 02:47:15.465802 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.338983 | |
| I0525 02:47:15.465817 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 2.92974 (* 1 = 2.92974 loss) | |
| I0525 02:47:15.465831 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.16516 (* 1 = 1.16516 loss) | |
| I0525 02:47:15.465844 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 2.46726 (* 0.0909091 = 0.224297 loss) | |
| I0525 02:47:15.465858 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.39848 (* 0.0909091 = 0.308953 loss) | |
| I0525 02:47:15.465873 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 2.69394 (* 0.0909091 = 0.244904 loss) | |
| I0525 02:47:15.465886 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 2.86157 (* 0.0909091 = 0.260143 loss) | |
| I0525 02:47:15.465899 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 2.5146 (* 0.0909091 = 0.2286 loss) | |
| I0525 02:47:15.465914 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 1.9573 (* 0.0909091 = 0.177936 loss) | |
| I0525 02:47:15.465930 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 1.77448 (* 0.0909091 = 0.161316 loss) | |
| I0525 02:47:15.465945 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 1.72743 (* 0.0909091 = 0.157039 loss) | |
| I0525 02:47:15.465958 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.984024 (* 0.0909091 = 0.0894567 loss) | |
| I0525 02:47:15.465972 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.599245 (* 0.0909091 = 0.0544768 loss) | |
| I0525 02:47:15.465986 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.526548 (* 0.0909091 = 0.047868 loss) | |
| I0525 02:47:15.466001 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.405981 (* 0.0909091 = 0.0369074 loss) | |
| I0525 02:47:15.466013 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.597492 (* 0.0909091 = 0.0543174 loss) | |
| I0525 02:47:15.466028 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.108092 (* 0.0909091 = 0.00982653 loss) | |
| I0525 02:47:15.466042 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.0813336 (* 0.0909091 = 0.00739396 loss) | |
| I0525 02:47:15.466056 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.0197809 (* 0.0909091 = 0.00179826 loss) | |
| I0525 02:47:15.466070 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.0109689 (* 0.0909091 = 0.000997171 loss) | |
| I0525 02:47:15.466084 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.00615124 (* 0.0909091 = 0.000559204 loss) | |
| I0525 02:47:15.466097 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00338673 (* 0.0909091 = 0.000307884 loss) | |
| I0525 02:47:15.466111 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00114281 (* 0.0909091 = 0.000103892 loss) | |
| I0525 02:47:15.466125 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.000616909 (* 0.0909091 = 5.60826e-05 loss) | |
| I0525 02:47:15.466138 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.000255305 (* 0.0909091 = 2.32095e-05 loss) | |
| I0525 02:47:15.466150 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 02:47:15.466166 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 02:47:15.466186 5272 solver.cpp:245] Train net output #149: total_confidence = 1.91328e-05 | |
| I0525 02:47:15.466212 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 0.00019134 | |
| I0525 02:47:15.466233 5272 sgd_solver.cpp:106] Iteration 12000, lr = 0.001 | |
| I0525 02:47:38.932745 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 71.5104 > 30) by scale factor 0.419519 | |
| I0525 02:49:08.235553 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 35.1562 > 30) by scale factor 0.853334 | |
| I0525 02:50:22.878186 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 61.7182 > 30) by scale factor 0.48608 | |
| I0525 02:50:45.199411 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 51.4936 > 30) by scale factor 0.582597 | |
| I0525 02:51:41.361454 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 36.1841 > 30) by scale factor 0.829092 | |
| I0525 02:53:36.006780 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 37.3767 > 30) by scale factor 0.80264 | |
| I0525 02:53:40.262481 5272 solver.cpp:229] Iteration 12500, loss = 10.2808 | |
| I0525 02:53:40.262545 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.137931 | |
| I0525 02:53:40.262563 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0 | |
| I0525 02:53:40.262583 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0.25 | |
| I0525 02:53:40.262609 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0.125 | |
| I0525 02:53:40.262625 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.25 | |
| I0525 02:53:40.262639 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.25 | |
| I0525 02:53:40.262651 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.375 | |
| I0525 02:53:40.262663 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.5 | |
| I0525 02:53:40.262676 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 1 | |
| I0525 02:53:40.262689 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 0.875 | |
| I0525 02:53:40.262701 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 0.875 | |
| I0525 02:53:40.262715 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 0.875 | |
| I0525 02:53:40.262727 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 0.875 | |
| I0525 02:53:40.262747 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 0.875 | |
| I0525 02:53:40.262773 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 0.875 | |
| I0525 02:53:40.262787 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 0.875 | |
| I0525 02:53:40.262800 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 0.875 | |
| I0525 02:53:40.262812 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 0.875 | |
| I0525 02:53:40.262825 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 0.875 | |
| I0525 02:53:40.262836 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 02:53:40.262850 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 02:53:40.262861 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 02:53:40.262872 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 02:53:40.262884 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.704545 | |
| I0525 02:53:40.262897 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.362069 | |
| I0525 02:53:40.262912 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.06629 (* 0.3 = 0.919887 loss) | |
| I0525 02:53:40.262928 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.15324 (* 0.3 = 0.345972 loss) | |
| I0525 02:53:40.262943 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 2.76091 (* 0.0272727 = 0.0752975 loss) | |
| I0525 02:53:40.262956 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.20251 (* 0.0272727 = 0.0873412 loss) | |
| I0525 02:53:40.262970 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.00768 (* 0.0272727 = 0.0820275 loss) | |
| I0525 02:53:40.262984 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.12238 (* 0.0272727 = 0.0851557 loss) | |
| I0525 02:53:40.262998 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 2.87431 (* 0.0272727 = 0.0783902 loss) | |
| I0525 02:53:40.263012 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 2.57214 (* 0.0272727 = 0.0701492 loss) | |
| I0525 02:53:40.263025 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 2.92674 (* 0.0272727 = 0.0798202 loss) | |
| I0525 02:53:40.263041 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 0.2146 (* 0.0272727 = 0.00585272 loss) | |
| I0525 02:53:40.263054 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.561619 (* 0.0272727 = 0.0153169 loss) | |
| I0525 02:53:40.263068 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.467 (* 0.0272727 = 0.0127364 loss) | |
| I0525 02:53:40.263082 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.722842 (* 0.0272727 = 0.0197139 loss) | |
| I0525 02:53:40.263098 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.457214 (* 0.0272727 = 0.0124695 loss) | |
| I0525 02:53:40.263144 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.501079 (* 0.0272727 = 0.0136658 loss) | |
| I0525 02:53:40.263159 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.625255 (* 0.0272727 = 0.0170524 loss) | |
| I0525 02:53:40.263175 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.657307 (* 0.0272727 = 0.0179266 loss) | |
| I0525 02:53:40.263188 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 1.02872 (* 0.0272727 = 0.0280559 loss) | |
| I0525 02:53:40.263202 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 1.0249 (* 0.0272727 = 0.0279517 loss) | |
| I0525 02:53:40.263216 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.919519 (* 0.0272727 = 0.0250778 loss) | |
| I0525 02:53:40.263231 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.00190191 (* 0.0272727 = 5.18703e-05 loss) | |
| I0525 02:53:40.263245 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.00328753 (* 0.0272727 = 8.96599e-05 loss) | |
| I0525 02:53:40.263259 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.00113713 (* 0.0272727 = 3.10127e-05 loss) | |
| I0525 02:53:40.263273 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.000949502 (* 0.0272727 = 2.58955e-05 loss) | |
| I0525 02:53:40.263286 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.0689655 | |
| I0525 02:53:40.263298 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0 | |
| I0525 02:53:40.263311 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0.375 | |
| I0525 02:53:40.263322 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0.125 | |
| I0525 02:53:40.263334 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0.25 | |
| I0525 02:53:40.263347 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.25 | |
| I0525 02:53:40.263360 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.25 | |
| I0525 02:53:40.263371 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.625 | |
| I0525 02:53:40.263382 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 1 | |
| I0525 02:53:40.263394 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 0.875 | |
| I0525 02:53:40.263406 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 0.875 | |
| I0525 02:53:40.263418 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 0.875 | |
| I0525 02:53:40.263430 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 0.875 | |
| I0525 02:53:40.263442 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 0.875 | |
| I0525 02:53:40.263453 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 0.875 | |
| I0525 02:53:40.263465 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 0.875 | |
| I0525 02:53:40.263478 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 0.875 | |
| I0525 02:53:40.263489 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 0.875 | |
| I0525 02:53:40.263501 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 0.875 | |
| I0525 02:53:40.263512 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 02:53:40.263525 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 02:53:40.263536 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 02:53:40.263547 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 02:53:40.263559 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.693182 | |
| I0525 02:53:40.263571 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.258621 | |
| I0525 02:53:40.263586 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.07766 (* 0.3 = 0.923298 loss) | |
| I0525 02:53:40.263599 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.12056 (* 0.3 = 0.336167 loss) | |
| I0525 02:53:40.263613 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.3003 (* 0.0272727 = 0.0900082 loss) | |
| I0525 02:53:40.263638 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 3.08696 (* 0.0272727 = 0.0841899 loss) | |
| I0525 02:53:40.263653 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.70705 (* 0.0272727 = 0.101101 loss) | |
| I0525 02:53:40.263667 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 2.8739 (* 0.0272727 = 0.0783792 loss) | |
| I0525 02:53:40.263681 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 2.63683 (* 0.0272727 = 0.0719135 loss) | |
| I0525 02:53:40.263695 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 2.97925 (* 0.0272727 = 0.0812522 loss) | |
| I0525 02:53:40.263710 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 2.14341 (* 0.0272727 = 0.0584567 loss) | |
| I0525 02:53:40.263723 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 0.441174 (* 0.0272727 = 0.012032 loss) | |
| I0525 02:53:40.263737 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.825685 (* 0.0272727 = 0.0225187 loss) | |
| I0525 02:53:40.263751 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.503092 (* 0.0272727 = 0.0137207 loss) | |
| I0525 02:53:40.263767 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.782765 (* 0.0272727 = 0.0213481 loss) | |
| I0525 02:53:40.263793 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.479955 (* 0.0272727 = 0.0130897 loss) | |
| I0525 02:53:40.263820 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.834026 (* 0.0272727 = 0.0227462 loss) | |
| I0525 02:53:40.263835 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.660875 (* 0.0272727 = 0.0180239 loss) | |
| I0525 02:53:40.263851 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.595649 (* 0.0272727 = 0.016245 loss) | |
| I0525 02:53:40.263861 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.905326 (* 0.0272727 = 0.0246907 loss) | |
| I0525 02:53:40.263876 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.886569 (* 0.0272727 = 0.0241792 loss) | |
| I0525 02:53:40.263890 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 1.05707 (* 0.0272727 = 0.0288291 loss) | |
| I0525 02:53:40.263905 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.0162294 (* 0.0272727 = 0.000442619 loss) | |
| I0525 02:53:40.263919 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.015836 (* 0.0272727 = 0.000431891 loss) | |
| I0525 02:53:40.263933 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.0127336 (* 0.0272727 = 0.000347281 loss) | |
| I0525 02:53:40.263947 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.00798731 (* 0.0272727 = 0.000217836 loss) | |
| I0525 02:53:40.263959 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.137931 | |
| I0525 02:53:40.263972 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.125 | |
| I0525 02:53:40.263984 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0 | |
| I0525 02:53:40.263995 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0.125 | |
| I0525 02:53:40.264008 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.125 | |
| I0525 02:53:40.264020 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.375 | |
| I0525 02:53:40.264032 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.25 | |
| I0525 02:53:40.264044 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.5 | |
| I0525 02:53:40.264056 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 1 | |
| I0525 02:53:40.264067 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 0.875 | |
| I0525 02:53:40.264080 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 0.875 | |
| I0525 02:53:40.264091 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 0.875 | |
| I0525 02:53:40.264103 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 0.875 | |
| I0525 02:53:40.264116 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 0.875 | |
| I0525 02:53:40.264127 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 0.875 | |
| I0525 02:53:40.264138 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 0.875 | |
| I0525 02:53:40.264163 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 0.875 | |
| I0525 02:53:40.264175 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 0.875 | |
| I0525 02:53:40.264188 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 0.875 | |
| I0525 02:53:40.264199 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 02:53:40.264211 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 02:53:40.264224 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 02:53:40.264235 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 02:53:40.264246 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.704545 | |
| I0525 02:53:40.264258 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.310345 | |
| I0525 02:53:40.264272 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 2.92147 (* 1 = 2.92147 loss) | |
| I0525 02:53:40.264286 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.10729 (* 1 = 1.10729 loss) | |
| I0525 02:53:40.264302 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 2.66969 (* 0.0909091 = 0.242699 loss) | |
| I0525 02:53:40.264315 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 2.92728 (* 0.0909091 = 0.266116 loss) | |
| I0525 02:53:40.264329 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.32159 (* 0.0909091 = 0.301962 loss) | |
| I0525 02:53:40.264343 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 2.80263 (* 0.0909091 = 0.254784 loss) | |
| I0525 02:53:40.264356 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 2.48772 (* 0.0909091 = 0.226156 loss) | |
| I0525 02:53:40.264370 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 2.42969 (* 0.0909091 = 0.220881 loss) | |
| I0525 02:53:40.264384 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 2.32776 (* 0.0909091 = 0.211614 loss) | |
| I0525 02:53:40.264397 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.277731 (* 0.0909091 = 0.0252483 loss) | |
| I0525 02:53:40.264411 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.589188 (* 0.0909091 = 0.0535625 loss) | |
| I0525 02:53:40.264425 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.374044 (* 0.0909091 = 0.034004 loss) | |
| I0525 02:53:40.264439 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.423378 (* 0.0909091 = 0.0384889 loss) | |
| I0525 02:53:40.264453 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.476018 (* 0.0909091 = 0.0432744 loss) | |
| I0525 02:53:40.264467 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.37512 (* 0.0909091 = 0.0341018 loss) | |
| I0525 02:53:40.264480 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.573537 (* 0.0909091 = 0.0521397 loss) | |
| I0525 02:53:40.264494 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.31151 (* 0.0909091 = 0.0283191 loss) | |
| I0525 02:53:40.264508 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.629892 (* 0.0909091 = 0.0572629 loss) | |
| I0525 02:53:40.264521 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.647971 (* 0.0909091 = 0.0589065 loss) | |
| I0525 02:53:40.264535 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.715721 (* 0.0909091 = 0.0650655 loss) | |
| I0525 02:53:40.264549 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00276362 (* 0.0909091 = 0.000251239 loss) | |
| I0525 02:53:40.264564 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00359171 (* 0.0909091 = 0.000326519 loss) | |
| I0525 02:53:40.264577 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.000527144 (* 0.0909091 = 4.79222e-05 loss) | |
| I0525 02:53:40.264591 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.000319462 (* 0.0909091 = 2.9042e-05 loss) | |
| I0525 02:53:40.264603 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 02:53:40.264616 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 02:53:40.264632 5272 solver.cpp:245] Train net output #149: total_confidence = 2.72203e-06 | |
| I0525 02:53:40.264647 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 0.000281044 | |
| I0525 02:53:40.264660 5272 sgd_solver.cpp:106] Iteration 12500, lr = 0.001 | |
| I0525 02:56:09.888660 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 33.7626 > 30) by scale factor 0.888558 | |
| I0525 03:00:04.984876 5272 solver.cpp:229] Iteration 13000, loss = 10.2016 | |
| I0525 03:00:04.985003 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0434783 | |
| I0525 03:00:04.985023 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0 | |
| I0525 03:00:04.985038 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0525 03:00:04.985049 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0.125 | |
| I0525 03:00:04.985062 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0 | |
| I0525 03:00:04.985075 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.375 | |
| I0525 03:00:04.985088 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.375 | |
| I0525 03:00:04.985101 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.625 | |
| I0525 03:00:04.985115 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.875 | |
| I0525 03:00:04.985139 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 1 | |
| I0525 03:00:04.985153 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 1 | |
| I0525 03:00:04.985165 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 03:00:04.985178 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 03:00:04.985190 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 03:00:04.985203 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 03:00:04.985213 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 03:00:04.985226 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 03:00:04.985239 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 03:00:04.985249 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 03:00:04.985261 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 03:00:04.985273 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 03:00:04.985285 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 03:00:04.985297 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 03:00:04.985309 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.75 | |
| I0525 03:00:04.985322 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.217391 | |
| I0525 03:00:04.985339 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.13467 (* 0.3 = 0.940402 loss) | |
| I0525 03:00:04.985353 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 0.874241 (* 0.3 = 0.262272 loss) | |
| I0525 03:00:04.985368 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.46684 (* 0.0272727 = 0.0945503 loss) | |
| I0525 03:00:04.985383 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.22572 (* 0.0272727 = 0.0879742 loss) | |
| I0525 03:00:04.985396 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.37468 (* 0.0272727 = 0.0920368 loss) | |
| I0525 03:00:04.985410 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 4.00705 (* 0.0272727 = 0.109283 loss) | |
| I0525 03:00:04.985424 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 2.38 (* 0.0272727 = 0.064909 loss) | |
| I0525 03:00:04.985438 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 2.70713 (* 0.0272727 = 0.0738309 loss) | |
| I0525 03:00:04.985452 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 1.99212 (* 0.0272727 = 0.0543305 loss) | |
| I0525 03:00:04.985466 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 0.966078 (* 0.0272727 = 0.0263476 loss) | |
| I0525 03:00:04.985481 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.00874336 (* 0.0272727 = 0.000238455 loss) | |
| I0525 03:00:04.985494 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.00450344 (* 0.0272727 = 0.000122821 loss) | |
| I0525 03:00:04.985509 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.00569316 (* 0.0272727 = 0.000155268 loss) | |
| I0525 03:00:04.985523 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.00503099 (* 0.0272727 = 0.000137209 loss) | |
| I0525 03:00:04.985538 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.00505718 (* 0.0272727 = 0.000137923 loss) | |
| I0525 03:00:04.985570 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.00486754 (* 0.0272727 = 0.000132751 loss) | |
| I0525 03:00:04.985586 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.00363545 (* 0.0272727 = 9.91486e-05 loss) | |
| I0525 03:00:04.985600 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.00519197 (* 0.0272727 = 0.000141599 loss) | |
| I0525 03:00:04.985615 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.00338695 (* 0.0272727 = 9.23715e-05 loss) | |
| I0525 03:00:04.985630 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0021278 (* 0.0272727 = 5.80308e-05 loss) | |
| I0525 03:00:04.985643 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.00233622 (* 0.0272727 = 6.37151e-05 loss) | |
| I0525 03:00:04.985657 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.00277386 (* 0.0272727 = 7.56508e-05 loss) | |
| I0525 03:00:04.985671 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.0016814 (* 0.0272727 = 4.58564e-05 loss) | |
| I0525 03:00:04.985685 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.00283452 (* 0.0272727 = 7.7305e-05 loss) | |
| I0525 03:00:04.985698 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.0869565 | |
| I0525 03:00:04.985710 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0 | |
| I0525 03:00:04.985723 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0.125 | |
| I0525 03:00:04.985734 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0 | |
| I0525 03:00:04.985745 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0 | |
| I0525 03:00:04.985757 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.375 | |
| I0525 03:00:04.985769 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.375 | |
| I0525 03:00:04.985780 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.625 | |
| I0525 03:00:04.985792 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.875 | |
| I0525 03:00:04.985805 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 1 | |
| I0525 03:00:04.985816 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 1 | |
| I0525 03:00:04.985827 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 03:00:04.985838 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 03:00:04.985849 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 03:00:04.985860 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 03:00:04.985872 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 03:00:04.985888 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 03:00:04.985899 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 03:00:04.985910 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 03:00:04.985923 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 03:00:04.985934 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 03:00:04.985945 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 03:00:04.985956 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 03:00:04.985967 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.755682 | |
| I0525 03:00:04.985980 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.217391 | |
| I0525 03:00:04.985993 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.01777 (* 0.3 = 0.905332 loss) | |
| I0525 03:00:04.986007 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 0.875113 (* 0.3 = 0.262534 loss) | |
| I0525 03:00:04.986024 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.21462 (* 0.0272727 = 0.0876714 loss) | |
| I0525 03:00:04.986039 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 2.96735 (* 0.0272727 = 0.0809277 loss) | |
| I0525 03:00:04.986063 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.54991 (* 0.0272727 = 0.0968156 loss) | |
| I0525 03:00:04.986078 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.46287 (* 0.0272727 = 0.0944419 loss) | |
| I0525 03:00:04.986093 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 2.88675 (* 0.0272727 = 0.0787295 loss) | |
| I0525 03:00:04.986105 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 2.34243 (* 0.0272727 = 0.0638846 loss) | |
| I0525 03:00:04.986119 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 2.28131 (* 0.0272727 = 0.0622175 loss) | |
| I0525 03:00:04.986132 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 1.0257 (* 0.0272727 = 0.0279736 loss) | |
| I0525 03:00:04.986147 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.0211147 (* 0.0272727 = 0.000575854 loss) | |
| I0525 03:00:04.986160 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.0116302 (* 0.0272727 = 0.000317188 loss) | |
| I0525 03:00:04.986174 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.0094277 (* 0.0272727 = 0.000257119 loss) | |
| I0525 03:00:04.986188 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.0111263 (* 0.0272727 = 0.000303445 loss) | |
| I0525 03:00:04.986202 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.00945274 (* 0.0272727 = 0.000257802 loss) | |
| I0525 03:00:04.986217 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.00796373 (* 0.0272727 = 0.000217193 loss) | |
| I0525 03:00:04.986230 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.00867668 (* 0.0272727 = 0.000236637 loss) | |
| I0525 03:00:04.986245 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.00412891 (* 0.0272727 = 0.000112607 loss) | |
| I0525 03:00:04.986259 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.0044009 (* 0.0272727 = 0.000120025 loss) | |
| I0525 03:00:04.986274 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.00244736 (* 0.0272727 = 6.67463e-05 loss) | |
| I0525 03:00:04.986286 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.00535599 (* 0.0272727 = 0.000146072 loss) | |
| I0525 03:00:04.986301 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.00524647 (* 0.0272727 = 0.000143086 loss) | |
| I0525 03:00:04.986311 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.00177785 (* 0.0272727 = 4.84869e-05 loss) | |
| I0525 03:00:04.986321 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.00240523 (* 0.0272727 = 6.55973e-05 loss) | |
| I0525 03:00:04.986333 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.0869565 | |
| I0525 03:00:04.986346 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.25 | |
| I0525 03:00:04.986357 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0 | |
| I0525 03:00:04.986369 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0.25 | |
| I0525 03:00:04.986382 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0 | |
| I0525 03:00:04.986392 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.375 | |
| I0525 03:00:04.986403 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.375 | |
| I0525 03:00:04.986415 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.625 | |
| I0525 03:00:04.986428 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.875 | |
| I0525 03:00:04.986438 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 1 | |
| I0525 03:00:04.986450 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 1 | |
| I0525 03:00:04.986461 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 03:00:04.986472 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 03:00:04.986485 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 03:00:04.986495 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 03:00:04.986506 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 03:00:04.986518 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 03:00:04.986539 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 03:00:04.986552 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 03:00:04.986563 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 03:00:04.986575 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 03:00:04.986587 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 03:00:04.986598 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 03:00:04.986609 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.755682 | |
| I0525 03:00:04.986620 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.195652 | |
| I0525 03:00:04.986634 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 2.90268 (* 1 = 2.90268 loss) | |
| I0525 03:00:04.986649 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 0.854645 (* 1 = 0.854645 loss) | |
| I0525 03:00:04.986663 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 3.11388 (* 0.0909091 = 0.28308 loss) | |
| I0525 03:00:04.986676 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.04574 (* 0.0909091 = 0.276886 loss) | |
| I0525 03:00:04.986690 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 2.70287 (* 0.0909091 = 0.245715 loss) | |
| I0525 03:00:04.986703 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.72335 (* 0.0909091 = 0.338486 loss) | |
| I0525 03:00:04.986717 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 2.31195 (* 0.0909091 = 0.210178 loss) | |
| I0525 03:00:04.986731 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 1.91392 (* 0.0909091 = 0.173993 loss) | |
| I0525 03:00:04.986744 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 1.65413 (* 0.0909091 = 0.150376 loss) | |
| I0525 03:00:04.986758 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.674919 (* 0.0909091 = 0.0613563 loss) | |
| I0525 03:00:04.986776 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.00161501 (* 0.0909091 = 0.000146819 loss) | |
| I0525 03:00:04.986804 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.00139108 (* 0.0909091 = 0.000126461 loss) | |
| I0525 03:00:04.986831 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.00119534 (* 0.0909091 = 0.000108667 loss) | |
| I0525 03:00:04.986852 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.00134054 (* 0.0909091 = 0.000121868 loss) | |
| I0525 03:00:04.986866 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.00124815 (* 0.0909091 = 0.000113468 loss) | |
| I0525 03:00:04.986881 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.000974644 (* 0.0909091 = 8.8604e-05 loss) | |
| I0525 03:00:04.986896 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.000885804 (* 0.0909091 = 8.05277e-05 loss) | |
| I0525 03:00:04.986909 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.000582676 (* 0.0909091 = 5.29705e-05 loss) | |
| I0525 03:00:04.986923 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.000812431 (* 0.0909091 = 7.38574e-05 loss) | |
| I0525 03:00:04.986940 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.000430967 (* 0.0909091 = 3.91788e-05 loss) | |
| I0525 03:00:04.986955 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.000466808 (* 0.0909091 = 4.24371e-05 loss) | |
| I0525 03:00:04.986969 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.000470292 (* 0.0909091 = 4.27539e-05 loss) | |
| I0525 03:00:04.986984 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.000339967 (* 0.0909091 = 3.09061e-05 loss) | |
| I0525 03:00:04.986997 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.000196093 (* 0.0909091 = 1.78267e-05 loss) | |
| I0525 03:00:04.987010 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 03:00:04.987021 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 03:00:04.987040 5272 solver.cpp:245] Train net output #149: total_confidence = 4.47047e-05 | |
| I0525 03:00:04.987049 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 0.00067437 | |
| I0525 03:00:04.987067 5272 sgd_solver.cpp:106] Iteration 13000, lr = 0.001 | |
| I0525 03:00:52.282081 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 44.5046 > 30) by scale factor 0.674088 | |
| I0525 03:03:23.126121 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 31.2313 > 30) by scale factor 0.960573 | |
| I0525 03:04:00.079668 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 30.3914 > 30) by scale factor 0.987121 | |
| I0525 03:05:35.481935 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 35.8578 > 30) by scale factor 0.836637 | |
| I0525 03:06:01.635527 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 41.9476 > 30) by scale factor 0.715178 | |
| I0525 03:06:13.186782 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 35.5609 > 30) by scale factor 0.843624 | |
| I0525 03:06:29.743352 5272 solver.cpp:229] Iteration 13500, loss = 10.1399 | |
| I0525 03:06:29.743428 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0512821 | |
| I0525 03:06:29.743448 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.125 | |
| I0525 03:06:29.743461 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0.125 | |
| I0525 03:06:29.743474 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0525 03:06:29.743487 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.25 | |
| I0525 03:06:29.743499 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.5 | |
| I0525 03:06:29.743512 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.625 | |
| I0525 03:06:29.743525 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.75 | |
| I0525 03:06:29.743537 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 1 | |
| I0525 03:06:29.743549 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 1 | |
| I0525 03:06:29.743562 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 1 | |
| I0525 03:06:29.743576 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 03:06:29.743587 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 03:06:29.743599 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 03:06:29.743613 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 03:06:29.743623 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 03:06:29.743635 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 03:06:29.743648 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 03:06:29.743659 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 03:06:29.743671 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 03:06:29.743683 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 03:06:29.743695 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 03:06:29.743706 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 03:06:29.743718 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.789773 | |
| I0525 03:06:29.743731 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.153846 | |
| I0525 03:06:29.743751 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.31886 (* 0.3 = 0.995658 loss) | |
| I0525 03:06:29.743765 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 0.7997 (* 0.3 = 0.23991 loss) | |
| I0525 03:06:29.743779 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.25373 (* 0.0272727 = 0.088738 loss) | |
| I0525 03:06:29.743793 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.12515 (* 0.0272727 = 0.0852313 loss) | |
| I0525 03:06:29.743808 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.80012 (* 0.0272727 = 0.10364 loss) | |
| I0525 03:06:29.743823 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.39482 (* 0.0272727 = 0.0925861 loss) | |
| I0525 03:06:29.743836 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 1.88191 (* 0.0272727 = 0.0513248 loss) | |
| I0525 03:06:29.743850 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 1.94251 (* 0.0272727 = 0.0529775 loss) | |
| I0525 03:06:29.743865 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 1.04494 (* 0.0272727 = 0.0284982 loss) | |
| I0525 03:06:29.743878 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 0.119656 (* 0.0272727 = 0.00326336 loss) | |
| I0525 03:06:29.743893 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.0388553 (* 0.0272727 = 0.00105969 loss) | |
| I0525 03:06:29.743907 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.022958 (* 0.0272727 = 0.000626126 loss) | |
| I0525 03:06:29.743921 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.0172133 (* 0.0272727 = 0.000469453 loss) | |
| I0525 03:06:29.743935 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.0068379 (* 0.0272727 = 0.000186488 loss) | |
| I0525 03:06:29.743993 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.00559391 (* 0.0272727 = 0.000152561 loss) | |
| I0525 03:06:29.744009 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.00366881 (* 0.0272727 = 0.000100058 loss) | |
| I0525 03:06:29.744022 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.00343014 (* 0.0272727 = 9.35493e-05 loss) | |
| I0525 03:06:29.744036 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.00253565 (* 0.0272727 = 6.91541e-05 loss) | |
| I0525 03:06:29.744050 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.00152215 (* 0.0272727 = 4.15133e-05 loss) | |
| I0525 03:06:29.744065 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0011334 (* 0.0272727 = 3.0911e-05 loss) | |
| I0525 03:06:29.744078 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.00078968 (* 0.0272727 = 2.15367e-05 loss) | |
| I0525 03:06:29.744092 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.00167102 (* 0.0272727 = 4.55733e-05 loss) | |
| I0525 03:06:29.744107 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.000710153 (* 0.0272727 = 1.93678e-05 loss) | |
| I0525 03:06:29.744120 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.000525491 (* 0.0272727 = 1.43316e-05 loss) | |
| I0525 03:06:29.744133 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.025641 | |
| I0525 03:06:29.744145 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0 | |
| I0525 03:06:29.744158 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0.125 | |
| I0525 03:06:29.744169 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0.125 | |
| I0525 03:06:29.744181 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0.375 | |
| I0525 03:06:29.744192 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.5 | |
| I0525 03:06:29.744205 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.625 | |
| I0525 03:06:29.744217 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.75 | |
| I0525 03:06:29.744230 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 1 | |
| I0525 03:06:29.744241 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 1 | |
| I0525 03:06:29.744252 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 1 | |
| I0525 03:06:29.744264 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 03:06:29.744276 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 03:06:29.744287 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 03:06:29.744299 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 03:06:29.744310 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 03:06:29.744323 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 03:06:29.744333 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 03:06:29.744344 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 03:06:29.744356 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 03:06:29.744367 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 03:06:29.744379 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 03:06:29.744391 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 03:06:29.744402 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.772727 | |
| I0525 03:06:29.744415 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.230769 | |
| I0525 03:06:29.744428 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.39419 (* 0.3 = 1.01826 loss) | |
| I0525 03:06:29.744441 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 0.851331 (* 0.3 = 0.255399 loss) | |
| I0525 03:06:29.744456 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.60404 (* 0.0272727 = 0.098292 loss) | |
| I0525 03:06:29.744469 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 2.97243 (* 0.0272727 = 0.0810663 loss) | |
| I0525 03:06:29.744494 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.44948 (* 0.0272727 = 0.0940767 loss) | |
| I0525 03:06:29.744508 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.01737 (* 0.0272727 = 0.0822918 loss) | |
| I0525 03:06:29.744523 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 1.56064 (* 0.0272727 = 0.042563 loss) | |
| I0525 03:06:29.744536 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 1.93347 (* 0.0272727 = 0.0527311 loss) | |
| I0525 03:06:29.744550 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 0.97303 (* 0.0272727 = 0.0265372 loss) | |
| I0525 03:06:29.744565 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 0.161033 (* 0.0272727 = 0.00439181 loss) | |
| I0525 03:06:29.744578 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.0764242 (* 0.0272727 = 0.0020843 loss) | |
| I0525 03:06:29.744593 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.0229605 (* 0.0272727 = 0.000626195 loss) | |
| I0525 03:06:29.744606 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.0196934 (* 0.0272727 = 0.000537094 loss) | |
| I0525 03:06:29.744621 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.0112483 (* 0.0272727 = 0.000306771 loss) | |
| I0525 03:06:29.744634 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.00668883 (* 0.0272727 = 0.000182423 loss) | |
| I0525 03:06:29.744648 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.0084138 (* 0.0272727 = 0.000229467 loss) | |
| I0525 03:06:29.744663 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.00506988 (* 0.0272727 = 0.00013827 loss) | |
| I0525 03:06:29.744676 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.00436511 (* 0.0272727 = 0.000119049 loss) | |
| I0525 03:06:29.744690 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.00406082 (* 0.0272727 = 0.00011075 loss) | |
| I0525 03:06:29.744704 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.00206583 (* 0.0272727 = 5.63408e-05 loss) | |
| I0525 03:06:29.744719 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.0012821 (* 0.0272727 = 3.49664e-05 loss) | |
| I0525 03:06:29.744732 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.00117685 (* 0.0272727 = 3.20958e-05 loss) | |
| I0525 03:06:29.744746 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.00127415 (* 0.0272727 = 3.47495e-05 loss) | |
| I0525 03:06:29.744760 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.00113219 (* 0.0272727 = 3.08779e-05 loss) | |
| I0525 03:06:29.744772 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.102564 | |
| I0525 03:06:29.744784 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.125 | |
| I0525 03:06:29.744799 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0.125 | |
| I0525 03:06:29.744812 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0.125 | |
| I0525 03:06:29.744824 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.25 | |
| I0525 03:06:29.744837 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.5 | |
| I0525 03:06:29.744848 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.625 | |
| I0525 03:06:29.744861 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.75 | |
| I0525 03:06:29.744874 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 1 | |
| I0525 03:06:29.744885 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 1 | |
| I0525 03:06:29.744896 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 1 | |
| I0525 03:06:29.744909 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 03:06:29.744920 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 03:06:29.744933 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 03:06:29.744942 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 03:06:29.744954 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 03:06:29.744976 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 03:06:29.744988 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 03:06:29.745000 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 03:06:29.745012 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 03:06:29.745028 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 03:06:29.745039 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 03:06:29.745051 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 03:06:29.745064 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.801136 | |
| I0525 03:06:29.745075 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.307692 | |
| I0525 03:06:29.745090 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.0596 (* 1 = 3.0596 loss) | |
| I0525 03:06:29.745103 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 0.742618 (* 1 = 0.742618 loss) | |
| I0525 03:06:29.745129 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 3.24854 (* 0.0909091 = 0.295322 loss) | |
| I0525 03:06:29.745147 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 2.96913 (* 0.0909091 = 0.269921 loss) | |
| I0525 03:06:29.745162 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.21857 (* 0.0909091 = 0.292597 loss) | |
| I0525 03:06:29.745175 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 2.81778 (* 0.0909091 = 0.256162 loss) | |
| I0525 03:06:29.745189 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 1.36325 (* 0.0909091 = 0.123932 loss) | |
| I0525 03:06:29.745203 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 1.47907 (* 0.0909091 = 0.134461 loss) | |
| I0525 03:06:29.745218 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 0.77484 (* 0.0909091 = 0.07044 loss) | |
| I0525 03:06:29.745230 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.12039 (* 0.0909091 = 0.0109446 loss) | |
| I0525 03:06:29.745245 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.0433997 (* 0.0909091 = 0.00394543 loss) | |
| I0525 03:06:29.745260 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.0172939 (* 0.0909091 = 0.00157217 loss) | |
| I0525 03:06:29.745273 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.00502935 (* 0.0909091 = 0.000457214 loss) | |
| I0525 03:06:29.745287 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.00371122 (* 0.0909091 = 0.000337383 loss) | |
| I0525 03:06:29.745301 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.00483404 (* 0.0909091 = 0.000439459 loss) | |
| I0525 03:06:29.745314 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.00309594 (* 0.0909091 = 0.000281449 loss) | |
| I0525 03:06:29.745328 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.00215051 (* 0.0909091 = 0.000195501 loss) | |
| I0525 03:06:29.745342 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.00257554 (* 0.0909091 = 0.00023414 loss) | |
| I0525 03:06:29.745357 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.00275208 (* 0.0909091 = 0.000250189 loss) | |
| I0525 03:06:29.745369 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.00177781 (* 0.0909091 = 0.000161619 loss) | |
| I0525 03:06:29.745383 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00148582 (* 0.0909091 = 0.000135074 loss) | |
| I0525 03:06:29.745398 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00131686 (* 0.0909091 = 0.000119714 loss) | |
| I0525 03:06:29.745411 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.000900455 (* 0.0909091 = 8.18596e-05 loss) | |
| I0525 03:06:29.745425 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.00069871 (* 0.0909091 = 6.35191e-05 loss) | |
| I0525 03:06:29.745439 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 03:06:29.745450 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 03:06:29.745472 5272 solver.cpp:245] Train net output #149: total_confidence = 0.00010129 | |
| I0525 03:06:29.745486 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 0.000350062 | |
| I0525 03:06:29.745499 5272 sgd_solver.cpp:106] Iteration 13500, lr = 0.001 | |
| I0525 03:08:14.797674 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 34.9022 > 30) by scale factor 0.859545 | |
| I0525 03:09:30.191488 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 34.4005 > 30) by scale factor 0.872079 | |
| I0525 03:11:31.725409 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 45.2166 > 30) by scale factor 0.663474 | |
| I0525 03:12:54.462980 5272 solver.cpp:229] Iteration 14000, loss = 10.1608 | |
| I0525 03:12:54.463075 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0943396 | |
| I0525 03:12:54.463095 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.125 | |
| I0525 03:12:54.463111 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0525 03:12:54.463124 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0525 03:12:54.463137 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.125 | |
| I0525 03:12:54.463150 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.125 | |
| I0525 03:12:54.463163 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.5 | |
| I0525 03:12:54.463176 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.75 | |
| I0525 03:12:54.463188 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.75 | |
| I0525 03:12:54.463201 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 0.875 | |
| I0525 03:12:54.463213 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 0.875 | |
| I0525 03:12:54.463227 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 0.875 | |
| I0525 03:12:54.463239 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 0.875 | |
| I0525 03:12:54.463251 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 0.875 | |
| I0525 03:12:54.463264 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 0.875 | |
| I0525 03:12:54.463276 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 0.875 | |
| I0525 03:12:54.463289 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 0.875 | |
| I0525 03:12:54.463300 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 03:12:54.463312 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 03:12:54.463325 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 03:12:54.463336 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 03:12:54.463348 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 03:12:54.463361 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 03:12:54.463372 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.710227 | |
| I0525 03:12:54.463385 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.283019 | |
| I0525 03:12:54.463402 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.03152 (* 0.3 = 0.909457 loss) | |
| I0525 03:12:54.463416 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.06279 (* 0.3 = 0.318837 loss) | |
| I0525 03:12:54.463430 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 2.74712 (* 0.0272727 = 0.0749213 loss) | |
| I0525 03:12:54.463444 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.18125 (* 0.0272727 = 0.0867614 loss) | |
| I0525 03:12:54.463459 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.38212 (* 0.0272727 = 0.0922397 loss) | |
| I0525 03:12:54.463472 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.21076 (* 0.0272727 = 0.0875663 loss) | |
| I0525 03:12:54.463486 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 3.21107 (* 0.0272727 = 0.0875746 loss) | |
| I0525 03:12:54.463500 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 2.11388 (* 0.0272727 = 0.0576512 loss) | |
| I0525 03:12:54.463515 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 0.859994 (* 0.0272727 = 0.0234544 loss) | |
| I0525 03:12:54.463528 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 1.21496 (* 0.0272727 = 0.0331353 loss) | |
| I0525 03:12:54.463546 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.327197 (* 0.0272727 = 0.00892355 loss) | |
| I0525 03:12:54.463559 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.660401 (* 0.0272727 = 0.0180109 loss) | |
| I0525 03:12:54.463573 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.42954 (* 0.0272727 = 0.0117147 loss) | |
| I0525 03:12:54.463587 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.400203 (* 0.0272727 = 0.0109146 loss) | |
| I0525 03:12:54.463620 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.46168 (* 0.0272727 = 0.0125913 loss) | |
| I0525 03:12:54.463636 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.357086 (* 0.0272727 = 0.00973871 loss) | |
| I0525 03:12:54.463651 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.495131 (* 0.0272727 = 0.0135036 loss) | |
| I0525 03:12:54.463665 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.569613 (* 0.0272727 = 0.0155349 loss) | |
| I0525 03:12:54.463680 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.016396 (* 0.0272727 = 0.000447164 loss) | |
| I0525 03:12:54.463693 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.00935248 (* 0.0272727 = 0.000255068 loss) | |
| I0525 03:12:54.463708 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.00772858 (* 0.0272727 = 0.00021078 loss) | |
| I0525 03:12:54.463722 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.00954462 (* 0.0272727 = 0.000260308 loss) | |
| I0525 03:12:54.463735 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.00426503 (* 0.0272727 = 0.000116319 loss) | |
| I0525 03:12:54.463749 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.00330752 (* 0.0272727 = 9.02052e-05 loss) | |
| I0525 03:12:54.463765 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.0566038 | |
| I0525 03:12:54.463778 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0.25 | |
| I0525 03:12:54.463790 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0.125 | |
| I0525 03:12:54.463803 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0 | |
| I0525 03:12:54.463814 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0.25 | |
| I0525 03:12:54.463826 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.125 | |
| I0525 03:12:54.463838 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.5 | |
| I0525 03:12:54.463850 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.75 | |
| I0525 03:12:54.463862 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.875 | |
| I0525 03:12:54.463874 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 1 | |
| I0525 03:12:54.463886 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 0.875 | |
| I0525 03:12:54.463897 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 0.875 | |
| I0525 03:12:54.463909 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 0.875 | |
| I0525 03:12:54.463922 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 0.875 | |
| I0525 03:12:54.463933 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 0.875 | |
| I0525 03:12:54.463945 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 0.875 | |
| I0525 03:12:54.463958 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 0.875 | |
| I0525 03:12:54.463969 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 03:12:54.463981 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 03:12:54.463994 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 03:12:54.464004 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 03:12:54.464016 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 03:12:54.464028 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 03:12:54.464040 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.693182 | |
| I0525 03:12:54.464051 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.283019 | |
| I0525 03:12:54.464066 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 2.94768 (* 0.3 = 0.884305 loss) | |
| I0525 03:12:54.464079 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.03152 (* 0.3 = 0.309456 loss) | |
| I0525 03:12:54.464093 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 2.90623 (* 0.0272727 = 0.0792609 loss) | |
| I0525 03:12:54.464107 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 3.36424 (* 0.0272727 = 0.091752 loss) | |
| I0525 03:12:54.464131 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.54173 (* 0.0272727 = 0.0965927 loss) | |
| I0525 03:12:54.464146 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.32354 (* 0.0272727 = 0.090642 loss) | |
| I0525 03:12:54.464164 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 2.92551 (* 0.0272727 = 0.0797867 loss) | |
| I0525 03:12:54.464177 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 2.10071 (* 0.0272727 = 0.057292 loss) | |
| I0525 03:12:54.464191 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 1.10607 (* 0.0272727 = 0.0301655 loss) | |
| I0525 03:12:54.464205 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 1.13735 (* 0.0272727 = 0.0310185 loss) | |
| I0525 03:12:54.464220 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.267548 (* 0.0272727 = 0.00729677 loss) | |
| I0525 03:12:54.464233 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.596094 (* 0.0272727 = 0.0162571 loss) | |
| I0525 03:12:54.464248 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.623699 (* 0.0272727 = 0.01701 loss) | |
| I0525 03:12:54.464262 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.432461 (* 0.0272727 = 0.0117944 loss) | |
| I0525 03:12:54.464275 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.353406 (* 0.0272727 = 0.00963835 loss) | |
| I0525 03:12:54.464289 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.550262 (* 0.0272727 = 0.0150071 loss) | |
| I0525 03:12:54.464303 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.604975 (* 0.0272727 = 0.0164993 loss) | |
| I0525 03:12:54.464318 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.59506 (* 0.0272727 = 0.0162289 loss) | |
| I0525 03:12:54.464332 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.0262886 (* 0.0272727 = 0.000716963 loss) | |
| I0525 03:12:54.464345 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.0137888 (* 0.0272727 = 0.000376059 loss) | |
| I0525 03:12:54.464360 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.013693 (* 0.0272727 = 0.000373445 loss) | |
| I0525 03:12:54.464375 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.0141221 (* 0.0272727 = 0.000385148 loss) | |
| I0525 03:12:54.464388 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.00419674 (* 0.0272727 = 0.000114457 loss) | |
| I0525 03:12:54.464402 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.00959846 (* 0.0272727 = 0.000261776 loss) | |
| I0525 03:12:54.464414 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.0754717 | |
| I0525 03:12:54.464426 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.25 | |
| I0525 03:12:54.464438 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0.25 | |
| I0525 03:12:54.464452 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0 | |
| I0525 03:12:54.464463 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.25 | |
| I0525 03:12:54.464474 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.25 | |
| I0525 03:12:54.464486 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.5 | |
| I0525 03:12:54.464498 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.75 | |
| I0525 03:12:54.464510 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.75 | |
| I0525 03:12:54.464521 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 0.875 | |
| I0525 03:12:54.464534 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 0.875 | |
| I0525 03:12:54.464545 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 0.875 | |
| I0525 03:12:54.464557 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 0.875 | |
| I0525 03:12:54.464570 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 0.875 | |
| I0525 03:12:54.464581 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 0.875 | |
| I0525 03:12:54.464592 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 0.875 | |
| I0525 03:12:54.464614 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 0.875 | |
| I0525 03:12:54.464629 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 03:12:54.464637 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 03:12:54.464650 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 03:12:54.464663 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 03:12:54.464673 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 03:12:54.464685 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 03:12:54.464697 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.710227 | |
| I0525 03:12:54.464709 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.283019 | |
| I0525 03:12:54.464723 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 2.9011 (* 1 = 2.9011 loss) | |
| I0525 03:12:54.464737 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 0.993806 (* 1 = 0.993806 loss) | |
| I0525 03:12:54.464751 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 2.50495 (* 0.0909091 = 0.227723 loss) | |
| I0525 03:12:54.464766 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.10065 (* 0.0909091 = 0.281877 loss) | |
| I0525 03:12:54.464779 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.46901 (* 0.0909091 = 0.315364 loss) | |
| I0525 03:12:54.464793 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 2.64199 (* 0.0909091 = 0.240181 loss) | |
| I0525 03:12:54.464807 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 2.66086 (* 0.0909091 = 0.241896 loss) | |
| I0525 03:12:54.464824 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 2.10047 (* 0.0909091 = 0.190951 loss) | |
| I0525 03:12:54.464838 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 0.927365 (* 0.0909091 = 0.0843059 loss) | |
| I0525 03:12:54.464853 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 1.09841 (* 0.0909091 = 0.0998558 loss) | |
| I0525 03:12:54.464866 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.257948 (* 0.0909091 = 0.0234499 loss) | |
| I0525 03:12:54.464880 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.72168 (* 0.0909091 = 0.0656073 loss) | |
| I0525 03:12:54.464895 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.555555 (* 0.0909091 = 0.050505 loss) | |
| I0525 03:12:54.464908 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.63542 (* 0.0909091 = 0.0577655 loss) | |
| I0525 03:12:54.464922 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.456553 (* 0.0909091 = 0.0415048 loss) | |
| I0525 03:12:54.464936 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.49912 (* 0.0909091 = 0.0453746 loss) | |
| I0525 03:12:54.464951 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.447527 (* 0.0909091 = 0.0406843 loss) | |
| I0525 03:12:54.464964 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.54897 (* 0.0909091 = 0.0499064 loss) | |
| I0525 03:12:54.464978 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.00387471 (* 0.0909091 = 0.000352246 loss) | |
| I0525 03:12:54.464993 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.00247859 (* 0.0909091 = 0.000225326 loss) | |
| I0525 03:12:54.465008 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00288135 (* 0.0909091 = 0.000261941 loss) | |
| I0525 03:12:54.465020 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00199457 (* 0.0909091 = 0.000181324 loss) | |
| I0525 03:12:54.465034 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.000966903 (* 0.0909091 = 8.79003e-05 loss) | |
| I0525 03:12:54.465049 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.000568925 (* 0.0909091 = 5.17204e-05 loss) | |
| I0525 03:12:54.465061 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 03:12:54.465072 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 03:12:54.465085 5272 solver.cpp:245] Train net output #149: total_confidence = 3.17824e-05 | |
| I0525 03:12:54.465106 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 0.000568825 | |
| I0525 03:12:54.465137 5272 sgd_solver.cpp:106] Iteration 14000, lr = 0.001 | |
| I0525 03:13:24.824494 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 36.6999 > 30) by scale factor 0.817442 | |
| I0525 03:14:09.448601 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 43.246 > 30) by scale factor 0.693705 | |
| I0525 03:17:43.520668 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 30.9116 > 30) by scale factor 0.97051 | |
| I0525 03:18:25.106947 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 33.9359 > 30) by scale factor 0.884021 | |
| I0525 03:19:19.519412 5272 solver.cpp:229] Iteration 14500, loss = 10.0966 | |
| I0525 03:19:19.519532 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0652174 | |
| I0525 03:19:19.519572 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0 | |
| I0525 03:19:19.519588 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0.125 | |
| I0525 03:19:19.519601 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0525 03:19:19.519614 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.125 | |
| I0525 03:19:19.519626 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.25 | |
| I0525 03:19:19.519639 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.25 | |
| I0525 03:19:19.519652 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.75 | |
| I0525 03:19:19.519665 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.875 | |
| I0525 03:19:19.519677 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 1 | |
| I0525 03:19:19.519690 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 1 | |
| I0525 03:19:19.519702 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 03:19:19.519714 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 03:19:19.519726 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 03:19:19.519740 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 03:19:19.519753 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 03:19:19.519765 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 03:19:19.519778 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 03:19:19.519789 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 03:19:19.519801 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 03:19:19.519814 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 03:19:19.519824 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 03:19:19.519836 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 03:19:19.519848 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.738636 | |
| I0525 03:19:19.519860 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.217391 | |
| I0525 03:19:19.519877 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 2.99777 (* 0.3 = 0.899331 loss) | |
| I0525 03:19:19.519891 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 0.953346 (* 0.3 = 0.286004 loss) | |
| I0525 03:19:19.519906 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.38889 (* 0.0272727 = 0.0924243 loss) | |
| I0525 03:19:19.519920 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.35098 (* 0.0272727 = 0.0913905 loss) | |
| I0525 03:19:19.519934 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.41937 (* 0.0272727 = 0.0932556 loss) | |
| I0525 03:19:19.519948 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.25054 (* 0.0272727 = 0.0886512 loss) | |
| I0525 03:19:19.519961 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 2.39881 (* 0.0272727 = 0.0654221 loss) | |
| I0525 03:19:19.519975 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 3.04982 (* 0.0272727 = 0.0831769 loss) | |
| I0525 03:19:19.519989 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 1.18057 (* 0.0272727 = 0.0321974 loss) | |
| I0525 03:19:19.520004 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 1.00907 (* 0.0272727 = 0.0275201 loss) | |
| I0525 03:19:19.520017 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.0125308 (* 0.0272727 = 0.000341749 loss) | |
| I0525 03:19:19.520031 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.0220301 (* 0.0272727 = 0.000600821 loss) | |
| I0525 03:19:19.520046 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.0112052 (* 0.0272727 = 0.000305598 loss) | |
| I0525 03:19:19.520059 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.0111337 (* 0.0272727 = 0.000303647 loss) | |
| I0525 03:19:19.520073 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.0162398 (* 0.0272727 = 0.000442905 loss) | |
| I0525 03:19:19.520112 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.00860229 (* 0.0272727 = 0.000234608 loss) | |
| I0525 03:19:19.520128 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.00512887 (* 0.0272727 = 0.000139878 loss) | |
| I0525 03:19:19.520143 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.0106722 (* 0.0272727 = 0.00029106 loss) | |
| I0525 03:19:19.520156 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.00517896 (* 0.0272727 = 0.000141244 loss) | |
| I0525 03:19:19.520170 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0120481 (* 0.0272727 = 0.000328584 loss) | |
| I0525 03:19:19.520184 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.0081009 (* 0.0272727 = 0.000220934 loss) | |
| I0525 03:19:19.520198 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.00486691 (* 0.0272727 = 0.000132734 loss) | |
| I0525 03:19:19.520212 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.00991399 (* 0.0272727 = 0.000270381 loss) | |
| I0525 03:19:19.520226 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.00700163 (* 0.0272727 = 0.000190953 loss) | |
| I0525 03:19:19.520239 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.0652174 | |
| I0525 03:19:19.520251 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0 | |
| I0525 03:19:19.520262 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0.125 | |
| I0525 03:19:19.520274 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0.125 | |
| I0525 03:19:19.520287 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0.125 | |
| I0525 03:19:19.520298 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.25 | |
| I0525 03:19:19.520310 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.25 | |
| I0525 03:19:19.520323 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.75 | |
| I0525 03:19:19.520334 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.875 | |
| I0525 03:19:19.520345 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 1 | |
| I0525 03:19:19.520357 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 1 | |
| I0525 03:19:19.520369 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 03:19:19.520380 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 03:19:19.520391 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 03:19:19.520403 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 03:19:19.520414 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 03:19:19.520426 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 03:19:19.520438 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 03:19:19.520449 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 03:19:19.520462 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 03:19:19.520473 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 03:19:19.520484 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 03:19:19.520496 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 03:19:19.520508 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.727273 | |
| I0525 03:19:19.520519 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.282609 | |
| I0525 03:19:19.520534 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 2.85531 (* 0.3 = 0.856593 loss) | |
| I0525 03:19:19.520547 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 0.936045 (* 0.3 = 0.280814 loss) | |
| I0525 03:19:19.520561 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.01637 (* 0.0272727 = 0.0822647 loss) | |
| I0525 03:19:19.520575 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 2.46897 (* 0.0272727 = 0.0673355 loss) | |
| I0525 03:19:19.520599 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.47579 (* 0.0272727 = 0.0947942 loss) | |
| I0525 03:19:19.520614 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.17222 (* 0.0272727 = 0.086515 loss) | |
| I0525 03:19:19.520628 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 2.71052 (* 0.0272727 = 0.0739233 loss) | |
| I0525 03:19:19.520642 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 2.84651 (* 0.0272727 = 0.077632 loss) | |
| I0525 03:19:19.520655 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 1.20185 (* 0.0272727 = 0.0327776 loss) | |
| I0525 03:19:19.520669 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 0.703402 (* 0.0272727 = 0.0191837 loss) | |
| I0525 03:19:19.520684 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.0106011 (* 0.0272727 = 0.000289121 loss) | |
| I0525 03:19:19.520697 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.00664626 (* 0.0272727 = 0.000181262 loss) | |
| I0525 03:19:19.520711 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.00321078 (* 0.0272727 = 8.75668e-05 loss) | |
| I0525 03:19:19.520726 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.00312367 (* 0.0272727 = 8.5191e-05 loss) | |
| I0525 03:19:19.520740 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.00236252 (* 0.0272727 = 6.44324e-05 loss) | |
| I0525 03:19:19.520755 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.00188441 (* 0.0272727 = 5.1393e-05 loss) | |
| I0525 03:19:19.520768 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.00349312 (* 0.0272727 = 9.5267e-05 loss) | |
| I0525 03:19:19.520782 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.00231733 (* 0.0272727 = 6.32e-05 loss) | |
| I0525 03:19:19.520799 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.00142812 (* 0.0272727 = 3.89487e-05 loss) | |
| I0525 03:19:19.520814 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.00283683 (* 0.0272727 = 7.73681e-05 loss) | |
| I0525 03:19:19.520828 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.00179865 (* 0.0272727 = 4.9054e-05 loss) | |
| I0525 03:19:19.520843 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.00261521 (* 0.0272727 = 7.13239e-05 loss) | |
| I0525 03:19:19.520856 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.00348873 (* 0.0272727 = 9.51473e-05 loss) | |
| I0525 03:19:19.520870 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.00274323 (* 0.0272727 = 7.48153e-05 loss) | |
| I0525 03:19:19.520884 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.173913 | |
| I0525 03:19:19.520895 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.25 | |
| I0525 03:19:19.520907 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0.125 | |
| I0525 03:19:19.520920 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0.375 | |
| I0525 03:19:19.520931 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.125 | |
| I0525 03:19:19.520943 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.25 | |
| I0525 03:19:19.520956 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.375 | |
| I0525 03:19:19.520967 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.75 | |
| I0525 03:19:19.520979 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.875 | |
| I0525 03:19:19.520990 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 1 | |
| I0525 03:19:19.521003 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 1 | |
| I0525 03:19:19.521013 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 03:19:19.521025 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 03:19:19.521037 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 03:19:19.521049 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 03:19:19.521060 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 03:19:19.521072 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 03:19:19.521093 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 03:19:19.521106 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 03:19:19.521136 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 03:19:19.521152 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 03:19:19.521162 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 03:19:19.521174 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 03:19:19.521186 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.778409 | |
| I0525 03:19:19.521198 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.391304 | |
| I0525 03:19:19.521209 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 2.69064 (* 1 = 2.69064 loss) | |
| I0525 03:19:19.521219 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 0.800994 (* 1 = 0.800994 loss) | |
| I0525 03:19:19.521234 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 2.33833 (* 0.0909091 = 0.212576 loss) | |
| I0525 03:19:19.521248 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 2.65436 (* 0.0909091 = 0.241306 loss) | |
| I0525 03:19:19.521262 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.00796 (* 0.0909091 = 0.273451 loss) | |
| I0525 03:19:19.521276 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.33343 (* 0.0909091 = 0.303039 loss) | |
| I0525 03:19:19.521289 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 2.31031 (* 0.0909091 = 0.210029 loss) | |
| I0525 03:19:19.521303 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 2.27319 (* 0.0909091 = 0.206654 loss) | |
| I0525 03:19:19.521317 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 0.987878 (* 0.0909091 = 0.0898071 loss) | |
| I0525 03:19:19.521330 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.421453 (* 0.0909091 = 0.0383139 loss) | |
| I0525 03:19:19.521344 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.00227712 (* 0.0909091 = 0.000207011 loss) | |
| I0525 03:19:19.521358 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.00146184 (* 0.0909091 = 0.000132895 loss) | |
| I0525 03:19:19.521373 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.00150392 (* 0.0909091 = 0.00013672 loss) | |
| I0525 03:19:19.521386 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.000993792 (* 0.0909091 = 9.03447e-05 loss) | |
| I0525 03:19:19.521400 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.00130384 (* 0.0909091 = 0.000118531 loss) | |
| I0525 03:19:19.521414 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.000975736 (* 0.0909091 = 8.87033e-05 loss) | |
| I0525 03:19:19.521428 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.00102532 (* 0.0909091 = 9.32111e-05 loss) | |
| I0525 03:19:19.521441 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.000838571 (* 0.0909091 = 7.62337e-05 loss) | |
| I0525 03:19:19.521456 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.000741782 (* 0.0909091 = 6.74347e-05 loss) | |
| I0525 03:19:19.521468 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.000543347 (* 0.0909091 = 4.93951e-05 loss) | |
| I0525 03:19:19.521482 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00108501 (* 0.0909091 = 9.86376e-05 loss) | |
| I0525 03:19:19.521497 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00103212 (* 0.0909091 = 9.38293e-05 loss) | |
| I0525 03:19:19.521510 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.0015249 (* 0.0909091 = 0.000138627 loss) | |
| I0525 03:19:19.521524 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.000969557 (* 0.0909091 = 8.81415e-05 loss) | |
| I0525 03:19:19.521536 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 03:19:19.521548 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 03:19:19.521570 5272 solver.cpp:245] Train net output #149: total_confidence = 1.38009e-05 | |
| I0525 03:19:19.521584 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 0.000273296 | |
| I0525 03:19:19.521596 5272 sgd_solver.cpp:106] Iteration 14500, lr = 0.001 | |
| I0525 03:23:33.840852 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 32.7756 > 30) by scale factor 0.915315 | |
| I0525 03:25:43.898362 5272 solver.cpp:338] Iteration 15000, Testing net (#0) | |
| I0525 03:26:41.757014 5272 solver.cpp:393] Test loss: 9.34947 | |
| I0525 03:26:41.757114 5272 solver.cpp:406] Test net output #0: loss1/accuracy = 0.0662929 | |
| I0525 03:26:41.757148 5272 solver.cpp:406] Test net output #1: loss1/accuracy01 = 0.126 | |
| I0525 03:26:41.757163 5272 solver.cpp:406] Test net output #2: loss1/accuracy02 = 0.097 | |
| I0525 03:26:41.757175 5272 solver.cpp:406] Test net output #3: loss1/accuracy03 = 0.088 | |
| I0525 03:26:41.757187 5272 solver.cpp:406] Test net output #4: loss1/accuracy04 = 0.168 | |
| I0525 03:26:41.757200 5272 solver.cpp:406] Test net output #5: loss1/accuracy05 = 0.319 | |
| I0525 03:26:41.757212 5272 solver.cpp:406] Test net output #6: loss1/accuracy06 = 0.47 | |
| I0525 03:26:41.757225 5272 solver.cpp:406] Test net output #7: loss1/accuracy07 = 0.74 | |
| I0525 03:26:41.757236 5272 solver.cpp:406] Test net output #8: loss1/accuracy08 = 0.919 | |
| I0525 03:26:41.757248 5272 solver.cpp:406] Test net output #9: loss1/accuracy09 = 0.98 | |
| I0525 03:26:41.757261 5272 solver.cpp:406] Test net output #10: loss1/accuracy10 = 0.994 | |
| I0525 03:26:41.757272 5272 solver.cpp:406] Test net output #11: loss1/accuracy11 = 1 | |
| I0525 03:26:41.757283 5272 solver.cpp:406] Test net output #12: loss1/accuracy12 = 1 | |
| I0525 03:26:41.757295 5272 solver.cpp:406] Test net output #13: loss1/accuracy13 = 1 | |
| I0525 03:26:41.757307 5272 solver.cpp:406] Test net output #14: loss1/accuracy14 = 1 | |
| I0525 03:26:41.757318 5272 solver.cpp:406] Test net output #15: loss1/accuracy15 = 1 | |
| I0525 03:26:41.757329 5272 solver.cpp:406] Test net output #16: loss1/accuracy16 = 1 | |
| I0525 03:26:41.757340 5272 solver.cpp:406] Test net output #17: loss1/accuracy17 = 1 | |
| I0525 03:26:41.757351 5272 solver.cpp:406] Test net output #18: loss1/accuracy18 = 1 | |
| I0525 03:26:41.757362 5272 solver.cpp:406] Test net output #19: loss1/accuracy19 = 1 | |
| I0525 03:26:41.757375 5272 solver.cpp:406] Test net output #20: loss1/accuracy20 = 1 | |
| I0525 03:26:41.757385 5272 solver.cpp:406] Test net output #21: loss1/accuracy21 = 1 | |
| I0525 03:26:41.757396 5272 solver.cpp:406] Test net output #22: loss1/accuracy22 = 1 | |
| I0525 03:26:41.757407 5272 solver.cpp:406] Test net output #23: loss1/accuracy_incl_empty = 0.76591 | |
| I0525 03:26:41.757421 5272 solver.cpp:406] Test net output #24: loss1/accuracy_top3 = 0.21944 | |
| I0525 03:26:41.757436 5272 solver.cpp:406] Test net output #25: loss1/cross_entropy_loss = 3.56259 (* 0.3 = 1.06878 loss) | |
| I0525 03:26:41.757450 5272 solver.cpp:406] Test net output #26: loss1/cross_entropy_loss_incl_empty = 0.921492 (* 0.3 = 0.276448 loss) | |
| I0525 03:26:41.757465 5272 solver.cpp:406] Test net output #27: loss1/loss01 = 2.95648 (* 0.0272727 = 0.0806314 loss) | |
| I0525 03:26:41.757478 5272 solver.cpp:406] Test net output #28: loss1/loss02 = 3.18494 (* 0.0272727 = 0.0868619 loss) | |
| I0525 03:26:41.757493 5272 solver.cpp:406] Test net output #29: loss1/loss03 = 3.26209 (* 0.0272727 = 0.0889662 loss) | |
| I0525 03:26:41.757505 5272 solver.cpp:406] Test net output #30: loss1/loss04 = 3.12925 (* 0.0272727 = 0.0853431 loss) | |
| I0525 03:26:41.757519 5272 solver.cpp:406] Test net output #31: loss1/loss05 = 2.64207 (* 0.0272727 = 0.0720564 loss) | |
| I0525 03:26:41.757532 5272 solver.cpp:406] Test net output #32: loss1/loss06 = 2.18369 (* 0.0272727 = 0.0595551 loss) | |
| I0525 03:26:41.757545 5272 solver.cpp:406] Test net output #33: loss1/loss07 = 1.2699 (* 0.0272727 = 0.0346335 loss) | |
| I0525 03:26:41.757560 5272 solver.cpp:406] Test net output #34: loss1/loss08 = 0.457305 (* 0.0272727 = 0.0124719 loss) | |
| I0525 03:26:41.757573 5272 solver.cpp:406] Test net output #35: loss1/loss09 = 0.121033 (* 0.0272727 = 0.00330091 loss) | |
| I0525 03:26:41.757591 5272 solver.cpp:406] Test net output #36: loss1/loss10 = 0.0675041 (* 0.0272727 = 0.00184102 loss) | |
| I0525 03:26:41.757606 5272 solver.cpp:406] Test net output #37: loss1/loss11 = 0.0309848 (* 0.0272727 = 0.000845039 loss) | |
| I0525 03:26:41.757619 5272 solver.cpp:406] Test net output #38: loss1/loss12 = 0.0234151 (* 0.0272727 = 0.000638593 loss) | |
| I0525 03:26:41.757633 5272 solver.cpp:406] Test net output #39: loss1/loss13 = 0.0188042 (* 0.0272727 = 0.000512841 loss) | |
| I0525 03:26:41.757671 5272 solver.cpp:406] Test net output #40: loss1/loss14 = 0.0153167 (* 0.0272727 = 0.000417729 loss) | |
| I0525 03:26:41.757686 5272 solver.cpp:406] Test net output #41: loss1/loss15 = 0.0112174 (* 0.0272727 = 0.000305928 loss) | |
| I0525 03:26:41.757700 5272 solver.cpp:406] Test net output #42: loss1/loss16 = 0.00827308 (* 0.0272727 = 0.000225629 loss) | |
| I0525 03:26:41.757714 5272 solver.cpp:406] Test net output #43: loss1/loss17 = 0.00556261 (* 0.0272727 = 0.000151708 loss) | |
| I0525 03:26:41.757727 5272 solver.cpp:406] Test net output #44: loss1/loss18 = 0.00428337 (* 0.0272727 = 0.000116819 loss) | |
| I0525 03:26:41.757741 5272 solver.cpp:406] Test net output #45: loss1/loss19 = 0.0045138 (* 0.0272727 = 0.000123104 loss) | |
| I0525 03:26:41.757755 5272 solver.cpp:406] Test net output #46: loss1/loss20 = 0.00391397 (* 0.0272727 = 0.000106745 loss) | |
| I0525 03:26:41.757769 5272 solver.cpp:406] Test net output #47: loss1/loss21 = 0.00371399 (* 0.0272727 = 0.000101291 loss) | |
| I0525 03:26:41.757783 5272 solver.cpp:406] Test net output #48: loss1/loss22 = 0.00343956 (* 0.0272727 = 9.38063e-05 loss) | |
| I0525 03:26:41.757796 5272 solver.cpp:406] Test net output #49: loss2/accuracy = 0.062804 | |
| I0525 03:26:41.757807 5272 solver.cpp:406] Test net output #50: loss2/accuracy01 = 0.119 | |
| I0525 03:26:41.757819 5272 solver.cpp:406] Test net output #51: loss2/accuracy02 = 0.098 | |
| I0525 03:26:41.757832 5272 solver.cpp:406] Test net output #52: loss2/accuracy03 = 0.083 | |
| I0525 03:26:41.757843 5272 solver.cpp:406] Test net output #53: loss2/accuracy04 = 0.161 | |
| I0525 03:26:41.757853 5272 solver.cpp:406] Test net output #54: loss2/accuracy05 = 0.33 | |
| I0525 03:26:41.757865 5272 solver.cpp:406] Test net output #55: loss2/accuracy06 = 0.471 | |
| I0525 03:26:41.757876 5272 solver.cpp:406] Test net output #56: loss2/accuracy07 = 0.741 | |
| I0525 03:26:41.757887 5272 solver.cpp:406] Test net output #57: loss2/accuracy08 = 0.919 | |
| I0525 03:26:41.757899 5272 solver.cpp:406] Test net output #58: loss2/accuracy09 = 0.982 | |
| I0525 03:26:41.757910 5272 solver.cpp:406] Test net output #59: loss2/accuracy10 = 0.994 | |
| I0525 03:26:41.757921 5272 solver.cpp:406] Test net output #60: loss2/accuracy11 = 1 | |
| I0525 03:26:41.757936 5272 solver.cpp:406] Test net output #61: loss2/accuracy12 = 1 | |
| I0525 03:26:41.757947 5272 solver.cpp:406] Test net output #62: loss2/accuracy13 = 1 | |
| I0525 03:26:41.757958 5272 solver.cpp:406] Test net output #63: loss2/accuracy14 = 1 | |
| I0525 03:26:41.757969 5272 solver.cpp:406] Test net output #64: loss2/accuracy15 = 1 | |
| I0525 03:26:41.757980 5272 solver.cpp:406] Test net output #65: loss2/accuracy16 = 1 | |
| I0525 03:26:41.757992 5272 solver.cpp:406] Test net output #66: loss2/accuracy17 = 1 | |
| I0525 03:26:41.758002 5272 solver.cpp:406] Test net output #67: loss2/accuracy18 = 1 | |
| I0525 03:26:41.758013 5272 solver.cpp:406] Test net output #68: loss2/accuracy19 = 1 | |
| I0525 03:26:41.758023 5272 solver.cpp:406] Test net output #69: loss2/accuracy20 = 1 | |
| I0525 03:26:41.758034 5272 solver.cpp:406] Test net output #70: loss2/accuracy21 = 1 | |
| I0525 03:26:41.758045 5272 solver.cpp:406] Test net output #71: loss2/accuracy22 = 1 | |
| I0525 03:26:41.758056 5272 solver.cpp:406] Test net output #72: loss2/accuracy_incl_empty = 0.765137 | |
| I0525 03:26:41.758067 5272 solver.cpp:406] Test net output #73: loss2/accuracy_top3 = 0.231335 | |
| I0525 03:26:41.758081 5272 solver.cpp:406] Test net output #74: loss2/cross_entropy_loss = 3.54987 (* 0.3 = 1.06496 loss) | |
| I0525 03:26:41.758095 5272 solver.cpp:406] Test net output #75: loss2/cross_entropy_loss_incl_empty = 0.921071 (* 0.3 = 0.276321 loss) | |
| I0525 03:26:41.758108 5272 solver.cpp:406] Test net output #76: loss2/loss01 = 2.92427 (* 0.0272727 = 0.0797527 loss) | |
| I0525 03:26:41.758121 5272 solver.cpp:406] Test net output #77: loss2/loss02 = 3.13984 (* 0.0272727 = 0.0856321 loss) | |
| I0525 03:26:41.758134 5272 solver.cpp:406] Test net output #78: loss2/loss03 = 3.22669 (* 0.0272727 = 0.0880007 loss) | |
| I0525 03:26:41.758159 5272 solver.cpp:406] Test net output #79: loss2/loss04 = 3.09169 (* 0.0272727 = 0.0843189 loss) | |
| I0525 03:26:41.758174 5272 solver.cpp:406] Test net output #80: loss2/loss05 = 2.60782 (* 0.0272727 = 0.0711223 loss) | |
| I0525 03:26:41.758188 5272 solver.cpp:406] Test net output #81: loss2/loss06 = 2.15695 (* 0.0272727 = 0.0588259 loss) | |
| I0525 03:26:41.758200 5272 solver.cpp:406] Test net output #82: loss2/loss07 = 1.24577 (* 0.0272727 = 0.0339755 loss) | |
| I0525 03:26:41.758213 5272 solver.cpp:406] Test net output #83: loss2/loss08 = 0.445389 (* 0.0272727 = 0.012147 loss) | |
| I0525 03:26:41.758227 5272 solver.cpp:406] Test net output #84: loss2/loss09 = 0.108186 (* 0.0272727 = 0.00295052 loss) | |
| I0525 03:26:41.758241 5272 solver.cpp:406] Test net output #85: loss2/loss10 = 0.0548634 (* 0.0272727 = 0.00149627 loss) | |
| I0525 03:26:41.758255 5272 solver.cpp:406] Test net output #86: loss2/loss11 = 0.0180264 (* 0.0272727 = 0.00049163 loss) | |
| I0525 03:26:41.758268 5272 solver.cpp:406] Test net output #87: loss2/loss12 = 0.0124881 (* 0.0272727 = 0.000340585 loss) | |
| I0525 03:26:41.758281 5272 solver.cpp:406] Test net output #88: loss2/loss13 = 0.0100058 (* 0.0272727 = 0.000272884 loss) | |
| I0525 03:26:41.758294 5272 solver.cpp:406] Test net output #89: loss2/loss14 = 0.00807055 (* 0.0272727 = 0.000220106 loss) | |
| I0525 03:26:41.758308 5272 solver.cpp:406] Test net output #90: loss2/loss15 = 0.00670154 (* 0.0272727 = 0.000182769 loss) | |
| I0525 03:26:41.758322 5272 solver.cpp:406] Test net output #91: loss2/loss16 = 0.00492736 (* 0.0272727 = 0.000134383 loss) | |
| I0525 03:26:41.758335 5272 solver.cpp:406] Test net output #92: loss2/loss17 = 0.00320336 (* 0.0272727 = 8.73644e-05 loss) | |
| I0525 03:26:41.758349 5272 solver.cpp:406] Test net output #93: loss2/loss18 = 0.00302355 (* 0.0272727 = 8.24604e-05 loss) | |
| I0525 03:26:41.758363 5272 solver.cpp:406] Test net output #94: loss2/loss19 = 0.00286073 (* 0.0272727 = 7.80198e-05 loss) | |
| I0525 03:26:41.758376 5272 solver.cpp:406] Test net output #95: loss2/loss20 = 0.00245152 (* 0.0272727 = 6.68596e-05 loss) | |
| I0525 03:26:41.758390 5272 solver.cpp:406] Test net output #96: loss2/loss21 = 0.00218105 (* 0.0272727 = 5.9483e-05 loss) | |
| I0525 03:26:41.758400 5272 solver.cpp:406] Test net output #97: loss2/loss22 = 0.00229509 (* 0.0272727 = 6.25934e-05 loss) | |
| I0525 03:26:41.758407 5272 solver.cpp:406] Test net output #98: loss3/accuracy = 0.0773798 | |
| I0525 03:26:41.758420 5272 solver.cpp:406] Test net output #99: loss3/accuracy01 = 0.123 | |
| I0525 03:26:41.758432 5272 solver.cpp:406] Test net output #100: loss3/accuracy02 = 0.094 | |
| I0525 03:26:41.758445 5272 solver.cpp:406] Test net output #101: loss3/accuracy03 = 0.08 | |
| I0525 03:26:41.758456 5272 solver.cpp:406] Test net output #102: loss3/accuracy04 = 0.169 | |
| I0525 03:26:41.758467 5272 solver.cpp:406] Test net output #103: loss3/accuracy05 = 0.326 | |
| I0525 03:26:41.758478 5272 solver.cpp:406] Test net output #104: loss3/accuracy06 = 0.478 | |
| I0525 03:26:41.758489 5272 solver.cpp:406] Test net output #105: loss3/accuracy07 = 0.74 | |
| I0525 03:26:41.758502 5272 solver.cpp:406] Test net output #106: loss3/accuracy08 = 0.918 | |
| I0525 03:26:41.758512 5272 solver.cpp:406] Test net output #107: loss3/accuracy09 = 0.979 | |
| I0525 03:26:41.758523 5272 solver.cpp:406] Test net output #108: loss3/accuracy10 = 0.992 | |
| I0525 03:26:41.758535 5272 solver.cpp:406] Test net output #109: loss3/accuracy11 = 1 | |
| I0525 03:26:41.758546 5272 solver.cpp:406] Test net output #110: loss3/accuracy12 = 1 | |
| I0525 03:26:41.758558 5272 solver.cpp:406] Test net output #111: loss3/accuracy13 = 1 | |
| I0525 03:26:41.758569 5272 solver.cpp:406] Test net output #112: loss3/accuracy14 = 1 | |
| I0525 03:26:41.758579 5272 solver.cpp:406] Test net output #113: loss3/accuracy15 = 1 | |
| I0525 03:26:41.758589 5272 solver.cpp:406] Test net output #114: loss3/accuracy16 = 1 | |
| I0525 03:26:41.758600 5272 solver.cpp:406] Test net output #115: loss3/accuracy17 = 1 | |
| I0525 03:26:41.758621 5272 solver.cpp:406] Test net output #116: loss3/accuracy18 = 1 | |
| I0525 03:26:41.758636 5272 solver.cpp:406] Test net output #117: loss3/accuracy19 = 1 | |
| I0525 03:26:41.758648 5272 solver.cpp:406] Test net output #118: loss3/accuracy20 = 1 | |
| I0525 03:26:41.758659 5272 solver.cpp:406] Test net output #119: loss3/accuracy21 = 1 | |
| I0525 03:26:41.758671 5272 solver.cpp:406] Test net output #120: loss3/accuracy22 = 1 | |
| I0525 03:26:41.758682 5272 solver.cpp:406] Test net output #121: loss3/accuracy_incl_empty = 0.766592 | |
| I0525 03:26:41.758693 5272 solver.cpp:406] Test net output #122: loss3/accuracy_top3 = 0.245081 | |
| I0525 03:26:41.758707 5272 solver.cpp:406] Test net output #123: loss3/cross_entropy_loss = 3.12194 (* 1 = 3.12194 loss) | |
| I0525 03:26:41.758720 5272 solver.cpp:406] Test net output #124: loss3/cross_entropy_loss_incl_empty = 0.832668 (* 1 = 0.832668 loss) | |
| I0525 03:26:41.758733 5272 solver.cpp:406] Test net output #125: loss3/loss01 = 2.77176 (* 0.0909091 = 0.251978 loss) | |
| I0525 03:26:41.758747 5272 solver.cpp:406] Test net output #126: loss3/loss02 = 3.00864 (* 0.0909091 = 0.273512 loss) | |
| I0525 03:26:41.758760 5272 solver.cpp:406] Test net output #127: loss3/loss03 = 3.09214 (* 0.0909091 = 0.281104 loss) | |
| I0525 03:26:41.758774 5272 solver.cpp:406] Test net output #128: loss3/loss04 = 2.95636 (* 0.0909091 = 0.26876 loss) | |
| I0525 03:26:41.758786 5272 solver.cpp:406] Test net output #129: loss3/loss05 = 2.51062 (* 0.0909091 = 0.228238 loss) | |
| I0525 03:26:41.758800 5272 solver.cpp:406] Test net output #130: loss3/loss06 = 2.04374 (* 0.0909091 = 0.185795 loss) | |
| I0525 03:26:41.758812 5272 solver.cpp:406] Test net output #131: loss3/loss07 = 1.17651 (* 0.0909091 = 0.106955 loss) | |
| I0525 03:26:41.758826 5272 solver.cpp:406] Test net output #132: loss3/loss08 = 0.427845 (* 0.0909091 = 0.038895 loss) | |
| I0525 03:26:41.758839 5272 solver.cpp:406] Test net output #133: loss3/loss09 = 0.107273 (* 0.0909091 = 0.00975207 loss) | |
| I0525 03:26:41.758853 5272 solver.cpp:406] Test net output #134: loss3/loss10 = 0.0562661 (* 0.0909091 = 0.0051151 loss) | |
| I0525 03:26:41.758867 5272 solver.cpp:406] Test net output #135: loss3/loss11 = 0.0227568 (* 0.0909091 = 0.0020688 loss) | |
| I0525 03:26:41.758880 5272 solver.cpp:406] Test net output #136: loss3/loss12 = 0.0180259 (* 0.0909091 = 0.00163872 loss) | |
| I0525 03:26:41.758893 5272 solver.cpp:406] Test net output #137: loss3/loss13 = 0.0141487 (* 0.0909091 = 0.00128625 loss) | |
| I0525 03:26:41.758908 5272 solver.cpp:406] Test net output #138: loss3/loss14 = 0.0125856 (* 0.0909091 = 0.00114414 loss) | |
| I0525 03:26:41.758920 5272 solver.cpp:406] Test net output #139: loss3/loss15 = 0.00979006 (* 0.0909091 = 0.000890005 loss) | |
| I0525 03:26:41.758934 5272 solver.cpp:406] Test net output #140: loss3/loss16 = 0.00596141 (* 0.0909091 = 0.000541946 loss) | |
| I0525 03:26:41.758947 5272 solver.cpp:406] Test net output #141: loss3/loss17 = 0.00309804 (* 0.0909091 = 0.00028164 loss) | |
| I0525 03:26:41.758961 5272 solver.cpp:406] Test net output #142: loss3/loss18 = 0.00217896 (* 0.0909091 = 0.000198087 loss) | |
| I0525 03:26:41.758975 5272 solver.cpp:406] Test net output #143: loss3/loss19 = 0.00183909 (* 0.0909091 = 0.00016719 loss) | |
| I0525 03:26:41.758992 5272 solver.cpp:406] Test net output #144: loss3/loss20 = 0.00185611 (* 0.0909091 = 0.000168737 loss) | |
| I0525 03:26:41.759006 5272 solver.cpp:406] Test net output #145: loss3/loss21 = 0.00161079 (* 0.0909091 = 0.000146435 loss) | |
| I0525 03:26:41.759019 5272 solver.cpp:406] Test net output #146: loss3/loss22 = 0.00121633 (* 0.0909091 = 0.000110576 loss) | |
| I0525 03:26:41.759032 5272 solver.cpp:406] Test net output #147: total_accuracy = 0 | |
| I0525 03:26:41.759042 5272 solver.cpp:406] Test net output #148: total_accuracy_not_rec = 0 | |
| I0525 03:26:41.759053 5272 solver.cpp:406] Test net output #149: total_confidence = 0.000325351 | |
| I0525 03:26:41.759064 5272 solver.cpp:406] Test net output #150: total_confidence_not_rec = 0.000452278 | |
| I0525 03:26:41.759088 5272 solver.cpp:338] Iteration 15000, Testing net (#1) | |
| I0525 03:27:39.668490 5272 solver.cpp:393] Test loss: 10.0552 | |
| I0525 03:27:39.668619 5272 solver.cpp:406] Test net output #0: loss1/accuracy = 0.0624187 | |
| I0525 03:27:39.668638 5272 solver.cpp:406] Test net output #1: loss1/accuracy01 = 0.113 | |
| I0525 03:27:39.668653 5272 solver.cpp:406] Test net output #2: loss1/accuracy02 = 0.11 | |
| I0525 03:27:39.668665 5272 solver.cpp:406] Test net output #3: loss1/accuracy03 = 0.081 | |
| I0525 03:27:39.668678 5272 solver.cpp:406] Test net output #4: loss1/accuracy04 = 0.173 | |
| I0525 03:27:39.668689 5272 solver.cpp:406] Test net output #5: loss1/accuracy05 = 0.328 | |
| I0525 03:27:39.668702 5272 solver.cpp:406] Test net output #6: loss1/accuracy06 = 0.447 | |
| I0525 03:27:39.668715 5272 solver.cpp:406] Test net output #7: loss1/accuracy07 = 0.655 | |
| I0525 03:27:39.668726 5272 solver.cpp:406] Test net output #8: loss1/accuracy08 = 0.825 | |
| I0525 03:27:39.668738 5272 solver.cpp:406] Test net output #9: loss1/accuracy09 = 0.885 | |
| I0525 03:27:39.668751 5272 solver.cpp:406] Test net output #10: loss1/accuracy10 = 0.902 | |
| I0525 03:27:39.668762 5272 solver.cpp:406] Test net output #11: loss1/accuracy11 = 0.925 | |
| I0525 03:27:39.668774 5272 solver.cpp:406] Test net output #12: loss1/accuracy12 = 0.942 | |
| I0525 03:27:39.668787 5272 solver.cpp:406] Test net output #13: loss1/accuracy13 = 0.952 | |
| I0525 03:27:39.668798 5272 solver.cpp:406] Test net output #14: loss1/accuracy14 = 0.961 | |
| I0525 03:27:39.668809 5272 solver.cpp:406] Test net output #15: loss1/accuracy15 = 0.964 | |
| I0525 03:27:39.668822 5272 solver.cpp:406] Test net output #16: loss1/accuracy16 = 0.982 | |
| I0525 03:27:39.668833 5272 solver.cpp:406] Test net output #17: loss1/accuracy17 = 0.992 | |
| I0525 03:27:39.668844 5272 solver.cpp:406] Test net output #18: loss1/accuracy18 = 0.993 | |
| I0525 03:27:39.668856 5272 solver.cpp:406] Test net output #19: loss1/accuracy19 = 0.994 | |
| I0525 03:27:39.668869 5272 solver.cpp:406] Test net output #20: loss1/accuracy20 = 0.998 | |
| I0525 03:27:39.668884 5272 solver.cpp:406] Test net output #21: loss1/accuracy21 = 0.998 | |
| I0525 03:27:39.668896 5272 solver.cpp:406] Test net output #22: loss1/accuracy22 = 0.998 | |
| I0525 03:27:39.668908 5272 solver.cpp:406] Test net output #23: loss1/accuracy_incl_empty = 0.733365 | |
| I0525 03:27:39.668920 5272 solver.cpp:406] Test net output #24: loss1/accuracy_top3 = 0.230859 | |
| I0525 03:27:39.668936 5272 solver.cpp:406] Test net output #25: loss1/cross_entropy_loss = 3.57206 (* 0.3 = 1.07162 loss) | |
| I0525 03:27:39.668951 5272 solver.cpp:406] Test net output #26: loss1/cross_entropy_loss_incl_empty = 1.04843 (* 0.3 = 0.31453 loss) | |
| I0525 03:27:39.668965 5272 solver.cpp:406] Test net output #27: loss1/loss01 = 3.07091 (* 0.0272727 = 0.0837521 loss) | |
| I0525 03:27:39.668979 5272 solver.cpp:406] Test net output #28: loss1/loss02 = 3.16638 (* 0.0272727 = 0.0863558 loss) | |
| I0525 03:27:39.668993 5272 solver.cpp:406] Test net output #29: loss1/loss03 = 3.27769 (* 0.0272727 = 0.0893916 loss) | |
| I0525 03:27:39.669008 5272 solver.cpp:406] Test net output #30: loss1/loss04 = 3.10727 (* 0.0272727 = 0.0847437 loss) | |
| I0525 03:27:39.669020 5272 solver.cpp:406] Test net output #31: loss1/loss05 = 2.65066 (* 0.0272727 = 0.0722907 loss) | |
| I0525 03:27:39.669034 5272 solver.cpp:406] Test net output #32: loss1/loss06 = 2.29253 (* 0.0272727 = 0.0625234 loss) | |
| I0525 03:27:39.669047 5272 solver.cpp:406] Test net output #33: loss1/loss07 = 1.54685 (* 0.0272727 = 0.0421868 loss) | |
| I0525 03:27:39.669061 5272 solver.cpp:406] Test net output #34: loss1/loss08 = 0.836177 (* 0.0272727 = 0.0228048 loss) | |
| I0525 03:27:39.669075 5272 solver.cpp:406] Test net output #35: loss1/loss09 = 0.52312 (* 0.0272727 = 0.0142669 loss) | |
| I0525 03:27:39.669088 5272 solver.cpp:406] Test net output #36: loss1/loss10 = 0.44185 (* 0.0272727 = 0.0120504 loss) | |
| I0525 03:27:39.669102 5272 solver.cpp:406] Test net output #37: loss1/loss11 = 0.350504 (* 0.0272727 = 0.0095592 loss) | |
| I0525 03:27:39.669116 5272 solver.cpp:406] Test net output #38: loss1/loss12 = 0.278084 (* 0.0272727 = 0.0075841 loss) | |
| I0525 03:27:39.669167 5272 solver.cpp:406] Test net output #39: loss1/loss13 = 0.249441 (* 0.0272727 = 0.00680295 loss) | |
| I0525 03:27:39.669183 5272 solver.cpp:406] Test net output #40: loss1/loss14 = 0.211546 (* 0.0272727 = 0.00576944 loss) | |
| I0525 03:27:39.669196 5272 solver.cpp:406] Test net output #41: loss1/loss15 = 0.200438 (* 0.0272727 = 0.00546649 loss) | |
| I0525 03:27:39.669209 5272 solver.cpp:406] Test net output #42: loss1/loss16 = 0.119281 (* 0.0272727 = 0.00325311 loss) | |
| I0525 03:27:39.669224 5272 solver.cpp:406] Test net output #43: loss1/loss17 = 0.065333 (* 0.0272727 = 0.00178181 loss) | |
| I0525 03:27:39.669237 5272 solver.cpp:406] Test net output #44: loss1/loss18 = 0.0578593 (* 0.0272727 = 0.00157798 loss) | |
| I0525 03:27:39.669251 5272 solver.cpp:406] Test net output #45: loss1/loss19 = 0.0543099 (* 0.0272727 = 0.00148118 loss) | |
| I0525 03:27:39.669265 5272 solver.cpp:406] Test net output #46: loss1/loss20 = 0.0208983 (* 0.0272727 = 0.000569953 loss) | |
| I0525 03:27:39.669280 5272 solver.cpp:406] Test net output #47: loss1/loss21 = 0.0210826 (* 0.0272727 = 0.000574981 loss) | |
| I0525 03:27:39.669292 5272 solver.cpp:406] Test net output #48: loss1/loss22 = 0.0193138 (* 0.0272727 = 0.000526741 loss) | |
| I0525 03:27:39.669304 5272 solver.cpp:406] Test net output #49: loss2/accuracy = 0.0620986 | |
| I0525 03:27:39.669317 5272 solver.cpp:406] Test net output #50: loss2/accuracy01 = 0.103 | |
| I0525 03:27:39.669328 5272 solver.cpp:406] Test net output #51: loss2/accuracy02 = 0.089 | |
| I0525 03:27:39.669340 5272 solver.cpp:406] Test net output #52: loss2/accuracy03 = 0.09 | |
| I0525 03:27:39.669353 5272 solver.cpp:406] Test net output #53: loss2/accuracy04 = 0.176 | |
| I0525 03:27:39.669363 5272 solver.cpp:406] Test net output #54: loss2/accuracy05 = 0.339 | |
| I0525 03:27:39.669375 5272 solver.cpp:406] Test net output #55: loss2/accuracy06 = 0.444 | |
| I0525 03:27:39.669386 5272 solver.cpp:406] Test net output #56: loss2/accuracy07 = 0.656 | |
| I0525 03:27:39.669399 5272 solver.cpp:406] Test net output #57: loss2/accuracy08 = 0.827 | |
| I0525 03:27:39.669409 5272 solver.cpp:406] Test net output #58: loss2/accuracy09 = 0.885 | |
| I0525 03:27:39.669420 5272 solver.cpp:406] Test net output #59: loss2/accuracy10 = 0.902 | |
| I0525 03:27:39.669432 5272 solver.cpp:406] Test net output #60: loss2/accuracy11 = 0.925 | |
| I0525 03:27:39.669443 5272 solver.cpp:406] Test net output #61: loss2/accuracy12 = 0.942 | |
| I0525 03:27:39.669456 5272 solver.cpp:406] Test net output #62: loss2/accuracy13 = 0.952 | |
| I0525 03:27:39.669467 5272 solver.cpp:406] Test net output #63: loss2/accuracy14 = 0.961 | |
| I0525 03:27:39.669479 5272 solver.cpp:406] Test net output #64: loss2/accuracy15 = 0.964 | |
| I0525 03:27:39.669491 5272 solver.cpp:406] Test net output #65: loss2/accuracy16 = 0.982 | |
| I0525 03:27:39.669502 5272 solver.cpp:406] Test net output #66: loss2/accuracy17 = 0.992 | |
| I0525 03:27:39.669513 5272 solver.cpp:406] Test net output #67: loss2/accuracy18 = 0.993 | |
| I0525 03:27:39.669524 5272 solver.cpp:406] Test net output #68: loss2/accuracy19 = 0.994 | |
| I0525 03:27:39.669536 5272 solver.cpp:406] Test net output #69: loss2/accuracy20 = 0.998 | |
| I0525 03:27:39.669548 5272 solver.cpp:406] Test net output #70: loss2/accuracy21 = 0.998 | |
| I0525 03:27:39.669559 5272 solver.cpp:406] Test net output #71: loss2/accuracy22 = 0.998 | |
| I0525 03:27:39.669570 5272 solver.cpp:406] Test net output #72: loss2/accuracy_incl_empty = 0.733728 | |
| I0525 03:27:39.669581 5272 solver.cpp:406] Test net output #73: loss2/accuracy_top3 = 0.23036 | |
| I0525 03:27:39.669595 5272 solver.cpp:406] Test net output #74: loss2/cross_entropy_loss = 3.57128 (* 0.3 = 1.07138 loss) | |
| I0525 03:27:39.669608 5272 solver.cpp:406] Test net output #75: loss2/cross_entropy_loss_incl_empty = 1.05228 (* 0.3 = 0.315684 loss) | |
| I0525 03:27:39.669622 5272 solver.cpp:406] Test net output #76: loss2/loss01 = 3.03695 (* 0.0272727 = 0.0828259 loss) | |
| I0525 03:27:39.669639 5272 solver.cpp:406] Test net output #77: loss2/loss02 = 3.1255 (* 0.0272727 = 0.085241 loss) | |
| I0525 03:27:39.669664 5272 solver.cpp:406] Test net output #78: loss2/loss03 = 3.24062 (* 0.0272727 = 0.0883805 loss) | |
| I0525 03:27:39.669679 5272 solver.cpp:406] Test net output #79: loss2/loss04 = 3.07091 (* 0.0272727 = 0.083752 loss) | |
| I0525 03:27:39.669693 5272 solver.cpp:406] Test net output #80: loss2/loss05 = 2.60847 (* 0.0272727 = 0.0711402 loss) | |
| I0525 03:27:39.669706 5272 solver.cpp:406] Test net output #81: loss2/loss06 = 2.26639 (* 0.0272727 = 0.0618107 loss) | |
| I0525 03:27:39.669720 5272 solver.cpp:406] Test net output #82: loss2/loss07 = 1.52486 (* 0.0272727 = 0.041587 loss) | |
| I0525 03:27:39.669734 5272 solver.cpp:406] Test net output #83: loss2/loss08 = 0.830165 (* 0.0272727 = 0.0226409 loss) | |
| I0525 03:27:39.669747 5272 solver.cpp:406] Test net output #84: loss2/loss09 = 0.518391 (* 0.0272727 = 0.0141379 loss) | |
| I0525 03:27:39.669760 5272 solver.cpp:406] Test net output #85: loss2/loss10 = 0.435276 (* 0.0272727 = 0.0118712 loss) | |
| I0525 03:27:39.669775 5272 solver.cpp:406] Test net output #86: loss2/loss11 = 0.345118 (* 0.0272727 = 0.0094123 loss) | |
| I0525 03:27:39.669788 5272 solver.cpp:406] Test net output #87: loss2/loss12 = 0.275516 (* 0.0272727 = 0.00751408 loss) | |
| I0525 03:27:39.669801 5272 solver.cpp:406] Test net output #88: loss2/loss13 = 0.250039 (* 0.0272727 = 0.00681926 loss) | |
| I0525 03:27:39.669816 5272 solver.cpp:406] Test net output #89: loss2/loss14 = 0.211915 (* 0.0272727 = 0.0057795 loss) | |
| I0525 03:27:39.669828 5272 solver.cpp:406] Test net output #90: loss2/loss15 = 0.207491 (* 0.0272727 = 0.00565885 loss) | |
| I0525 03:27:39.669842 5272 solver.cpp:406] Test net output #91: loss2/loss16 = 0.124061 (* 0.0272727 = 0.00338349 loss) | |
| I0525 03:27:39.669857 5272 solver.cpp:406] Test net output #92: loss2/loss17 = 0.0651923 (* 0.0272727 = 0.00177797 loss) | |
| I0525 03:27:39.669870 5272 solver.cpp:406] Test net output #93: loss2/loss18 = 0.0612407 (* 0.0272727 = 0.0016702 loss) | |
| I0525 03:27:39.669884 5272 solver.cpp:406] Test net output #94: loss2/loss19 = 0.0541983 (* 0.0272727 = 0.00147814 loss) | |
| I0525 03:27:39.669898 5272 solver.cpp:406] Test net output #95: loss2/loss20 = 0.0207097 (* 0.0272727 = 0.000564811 loss) | |
| I0525 03:27:39.669912 5272 solver.cpp:406] Test net output #96: loss2/loss21 = 0.0202217 (* 0.0272727 = 0.0005515 loss) | |
| I0525 03:27:39.669929 5272 solver.cpp:406] Test net output #97: loss2/loss22 = 0.0223832 (* 0.0272727 = 0.000610452 loss) | |
| I0525 03:27:39.669942 5272 solver.cpp:406] Test net output #98: loss3/accuracy = 0.0802786 | |
| I0525 03:27:39.669953 5272 solver.cpp:406] Test net output #99: loss3/accuracy01 = 0.1 | |
| I0525 03:27:39.669965 5272 solver.cpp:406] Test net output #100: loss3/accuracy02 = 0.097 | |
| I0525 03:27:39.669976 5272 solver.cpp:406] Test net output #101: loss3/accuracy03 = 0.087 | |
| I0525 03:27:39.669988 5272 solver.cpp:406] Test net output #102: loss3/accuracy04 = 0.175 | |
| I0525 03:27:39.669999 5272 solver.cpp:406] Test net output #103: loss3/accuracy05 = 0.353 | |
| I0525 03:27:39.670011 5272 solver.cpp:406] Test net output #104: loss3/accuracy06 = 0.447 | |
| I0525 03:27:39.670022 5272 solver.cpp:406] Test net output #105: loss3/accuracy07 = 0.66 | |
| I0525 03:27:39.670033 5272 solver.cpp:406] Test net output #106: loss3/accuracy08 = 0.826 | |
| I0525 03:27:39.670045 5272 solver.cpp:406] Test net output #107: loss3/accuracy09 = 0.887 | |
| I0525 03:27:39.670056 5272 solver.cpp:406] Test net output #108: loss3/accuracy10 = 0.904 | |
| I0525 03:27:39.670068 5272 solver.cpp:406] Test net output #109: loss3/accuracy11 = 0.925 | |
| I0525 03:27:39.670079 5272 solver.cpp:406] Test net output #110: loss3/accuracy12 = 0.942 | |
| I0525 03:27:39.670090 5272 solver.cpp:406] Test net output #111: loss3/accuracy13 = 0.952 | |
| I0525 03:27:39.670101 5272 solver.cpp:406] Test net output #112: loss3/accuracy14 = 0.961 | |
| I0525 03:27:39.670114 5272 solver.cpp:406] Test net output #113: loss3/accuracy15 = 0.964 | |
| I0525 03:27:39.670121 5272 solver.cpp:406] Test net output #114: loss3/accuracy16 = 0.982 | |
| I0525 03:27:39.670142 5272 solver.cpp:406] Test net output #115: loss3/accuracy17 = 0.992 | |
| I0525 03:27:39.670156 5272 solver.cpp:406] Test net output #116: loss3/accuracy18 = 0.993 | |
| I0525 03:27:39.670166 5272 solver.cpp:406] Test net output #117: loss3/accuracy19 = 0.994 | |
| I0525 03:27:39.670178 5272 solver.cpp:406] Test net output #118: loss3/accuracy20 = 0.998 | |
| I0525 03:27:39.670189 5272 solver.cpp:406] Test net output #119: loss3/accuracy21 = 0.998 | |
| I0525 03:27:39.670200 5272 solver.cpp:406] Test net output #120: loss3/accuracy22 = 0.998 | |
| I0525 03:27:39.670212 5272 solver.cpp:406] Test net output #121: loss3/accuracy_incl_empty = 0.737228 | |
| I0525 03:27:39.670223 5272 solver.cpp:406] Test net output #122: loss3/accuracy_top3 = 0.246684 | |
| I0525 03:27:39.670238 5272 solver.cpp:406] Test net output #123: loss3/cross_entropy_loss = 3.17301 (* 1 = 3.17301 loss) | |
| I0525 03:27:39.670251 5272 solver.cpp:406] Test net output #124: loss3/cross_entropy_loss_incl_empty = 0.9571 (* 1 = 0.9571 loss) | |
| I0525 03:27:39.670264 5272 solver.cpp:406] Test net output #125: loss3/loss01 = 2.91385 (* 0.0909091 = 0.264895 loss) | |
| I0525 03:27:39.670279 5272 solver.cpp:406] Test net output #126: loss3/loss02 = 2.99934 (* 0.0909091 = 0.272667 loss) | |
| I0525 03:27:39.670291 5272 solver.cpp:406] Test net output #127: loss3/loss03 = 3.10188 (* 0.0909091 = 0.281989 loss) | |
| I0525 03:27:39.670305 5272 solver.cpp:406] Test net output #128: loss3/loss04 = 2.97285 (* 0.0909091 = 0.270259 loss) | |
| I0525 03:27:39.670318 5272 solver.cpp:406] Test net output #129: loss3/loss05 = 2.50756 (* 0.0909091 = 0.22796 loss) | |
| I0525 03:27:39.670331 5272 solver.cpp:406] Test net output #130: loss3/loss06 = 2.14288 (* 0.0909091 = 0.194808 loss) | |
| I0525 03:27:39.670344 5272 solver.cpp:406] Test net output #131: loss3/loss07 = 1.41917 (* 0.0909091 = 0.129016 loss) | |
| I0525 03:27:39.670358 5272 solver.cpp:406] Test net output #132: loss3/loss08 = 0.779182 (* 0.0909091 = 0.0708348 loss) | |
| I0525 03:27:39.670372 5272 solver.cpp:406] Test net output #133: loss3/loss09 = 0.478201 (* 0.0909091 = 0.0434728 loss) | |
| I0525 03:27:39.670385 5272 solver.cpp:406] Test net output #134: loss3/loss10 = 0.402988 (* 0.0909091 = 0.0366353 loss) | |
| I0525 03:27:39.670398 5272 solver.cpp:406] Test net output #135: loss3/loss11 = 0.312749 (* 0.0909091 = 0.0284317 loss) | |
| I0525 03:27:39.670413 5272 solver.cpp:406] Test net output #136: loss3/loss12 = 0.245422 (* 0.0909091 = 0.0223111 loss) | |
| I0525 03:27:39.670425 5272 solver.cpp:406] Test net output #137: loss3/loss13 = 0.22795 (* 0.0909091 = 0.0207227 loss) | |
| I0525 03:27:39.670439 5272 solver.cpp:406] Test net output #138: loss3/loss14 = 0.191202 (* 0.0909091 = 0.017382 loss) | |
| I0525 03:27:39.670452 5272 solver.cpp:406] Test net output #139: loss3/loss15 = 0.184095 (* 0.0909091 = 0.0167359 loss) | |
| I0525 03:27:39.670465 5272 solver.cpp:406] Test net output #140: loss3/loss16 = 0.104678 (* 0.0909091 = 0.00951615 loss) | |
| I0525 03:27:39.670480 5272 solver.cpp:406] Test net output #141: loss3/loss17 = 0.0529746 (* 0.0909091 = 0.00481588 loss) | |
| I0525 03:27:39.670492 5272 solver.cpp:406] Test net output #142: loss3/loss18 = 0.0536157 (* 0.0909091 = 0.00487415 loss) | |
| I0525 03:27:39.670506 5272 solver.cpp:406] Test net output #143: loss3/loss19 = 0.0490098 (* 0.0909091 = 0.00445544 loss) | |
| I0525 03:27:39.670519 5272 solver.cpp:406] Test net output #144: loss3/loss20 = 0.0208882 (* 0.0909091 = 0.00189893 loss) | |
| I0525 03:27:39.670533 5272 solver.cpp:406] Test net output #145: loss3/loss21 = 0.0239523 (* 0.0909091 = 0.00217748 loss) | |
| I0525 03:27:39.670547 5272 solver.cpp:406] Test net output #146: loss3/loss22 = 0.023586 (* 0.0909091 = 0.00214418 loss) | |
| I0525 03:27:39.670558 5272 solver.cpp:406] Test net output #147: total_accuracy = 0 | |
| I0525 03:27:39.670569 5272 solver.cpp:406] Test net output #148: total_accuracy_not_rec = 0 | |
| I0525 03:27:39.670580 5272 solver.cpp:406] Test net output #149: total_confidence = 0.000267173 | |
| I0525 03:27:39.670600 5272 solver.cpp:406] Test net output #150: total_confidence_not_rec = 0.000348047 | |
| I0525 03:27:40.027756 5272 solver.cpp:229] Iteration 15000, loss = 9.99141 | |
| I0525 03:27:40.027820 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.06 | |
| I0525 03:27:40.027839 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0 | |
| I0525 03:27:40.027853 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0.25 | |
| I0525 03:27:40.027865 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0.25 | |
| I0525 03:27:40.027878 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.125 | |
| I0525 03:27:40.027891 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.125 | |
| I0525 03:27:40.027904 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.25 | |
| I0525 03:27:40.027916 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.625 | |
| I0525 03:27:40.027930 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.75 | |
| I0525 03:27:40.027941 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 1 | |
| I0525 03:27:40.027953 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 1 | |
| I0525 03:27:40.027966 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 03:27:40.027978 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 03:27:40.027990 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 03:27:40.028002 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 03:27:40.028014 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 03:27:40.028025 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 03:27:40.028038 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 03:27:40.028049 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 03:27:40.028061 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 03:27:40.028074 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 03:27:40.028086 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 03:27:40.028098 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 03:27:40.028110 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.732955 | |
| I0525 03:27:40.028121 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.26 | |
| I0525 03:27:40.028138 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.2736 (* 0.3 = 0.98208 loss) | |
| I0525 03:27:40.028152 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 0.989012 (* 0.3 = 0.296704 loss) | |
| I0525 03:27:40.028167 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.39907 (* 0.0272727 = 0.0927019 loss) | |
| I0525 03:27:40.028182 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.10783 (* 0.0272727 = 0.0847589 loss) | |
| I0525 03:27:40.028195 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.33076 (* 0.0272727 = 0.0908388 loss) | |
| I0525 03:27:40.028209 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 2.86844 (* 0.0272727 = 0.0782303 loss) | |
| I0525 03:27:40.028223 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 3.05794 (* 0.0272727 = 0.0833984 loss) | |
| I0525 03:27:40.028237 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 3.12607 (* 0.0272727 = 0.0852565 loss) | |
| I0525 03:27:40.028251 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 1.4996 (* 0.0272727 = 0.0408981 loss) | |
| I0525 03:27:40.028265 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 1.4426 (* 0.0272727 = 0.0393437 loss) | |
| I0525 03:27:40.028283 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.239513 (* 0.0272727 = 0.00653216 loss) | |
| I0525 03:27:40.028298 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.117337 (* 0.0272727 = 0.00320009 loss) | |
| I0525 03:27:40.028313 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.104551 (* 0.0272727 = 0.0028514 loss) | |
| I0525 03:27:40.028360 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.121336 (* 0.0272727 = 0.00330917 loss) | |
| I0525 03:27:40.028378 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.0573485 (* 0.0272727 = 0.00156405 loss) | |
| I0525 03:27:40.028391 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.0575126 (* 0.0272727 = 0.00156853 loss) | |
| I0525 03:27:40.028406 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0396513 (* 0.0272727 = 0.0010814 loss) | |
| I0525 03:27:40.028420 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.0275282 (* 0.0272727 = 0.000750768 loss) | |
| I0525 03:27:40.028434 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.0149263 (* 0.0272727 = 0.000407081 loss) | |
| I0525 03:27:40.028448 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0229183 (* 0.0272727 = 0.000625046 loss) | |
| I0525 03:27:40.028462 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.0115301 (* 0.0272727 = 0.000314458 loss) | |
| I0525 03:27:40.028477 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.00699912 (* 0.0272727 = 0.000190885 loss) | |
| I0525 03:27:40.028491 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.00627207 (* 0.0272727 = 0.000171057 loss) | |
| I0525 03:27:40.028506 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.00738677 (* 0.0272727 = 0.000201457 loss) | |
| I0525 03:27:40.028517 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.06 | |
| I0525 03:27:40.028530 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0 | |
| I0525 03:27:40.028542 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0.125 | |
| I0525 03:27:40.028554 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0.125 | |
| I0525 03:27:40.028566 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0.25 | |
| I0525 03:27:40.028578 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.25 | |
| I0525 03:27:40.028590 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.125 | |
| I0525 03:27:40.028602 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.625 | |
| I0525 03:27:40.028614 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.75 | |
| I0525 03:27:40.028626 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 1 | |
| I0525 03:27:40.028638 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 1 | |
| I0525 03:27:40.028650 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 03:27:40.028661 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 03:27:40.028673 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 03:27:40.028684 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 03:27:40.028697 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 03:27:40.028708 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 03:27:40.028719 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 03:27:40.028731 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 03:27:40.028743 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 03:27:40.028758 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 03:27:40.028769 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 03:27:40.028781 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 03:27:40.028792 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.727273 | |
| I0525 03:27:40.028805 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.22 | |
| I0525 03:27:40.028820 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.29526 (* 0.3 = 0.988578 loss) | |
| I0525 03:27:40.028833 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.07101 (* 0.3 = 0.321303 loss) | |
| I0525 03:27:40.028847 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.61301 (* 0.0272727 = 0.0985367 loss) | |
| I0525 03:27:40.028873 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 3.70135 (* 0.0272727 = 0.100946 loss) | |
| I0525 03:27:40.028888 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 2.83592 (* 0.0272727 = 0.0773433 loss) | |
| I0525 03:27:40.028903 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 2.88441 (* 0.0272727 = 0.0786658 loss) | |
| I0525 03:27:40.028916 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 2.9348 (* 0.0272727 = 0.08004 loss) | |
| I0525 03:27:40.028930 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 3.67525 (* 0.0272727 = 0.100234 loss) | |
| I0525 03:27:40.028944 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 1.33968 (* 0.0272727 = 0.0365367 loss) | |
| I0525 03:27:40.028957 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 1.26109 (* 0.0272727 = 0.0343934 loss) | |
| I0525 03:27:40.028971 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.174744 (* 0.0272727 = 0.00476574 loss) | |
| I0525 03:27:40.028985 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.0740329 (* 0.0272727 = 0.00201908 loss) | |
| I0525 03:27:40.029000 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.0630543 (* 0.0272727 = 0.00171966 loss) | |
| I0525 03:27:40.029014 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.0481258 (* 0.0272727 = 0.00131252 loss) | |
| I0525 03:27:40.029028 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.0298549 (* 0.0272727 = 0.000814225 loss) | |
| I0525 03:27:40.029042 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.0249457 (* 0.0272727 = 0.000680338 loss) | |
| I0525 03:27:40.029057 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.0189401 (* 0.0272727 = 0.000516549 loss) | |
| I0525 03:27:40.029070 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.0100057 (* 0.0272727 = 0.000272882 loss) | |
| I0525 03:27:40.029084 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.00585015 (* 0.0272727 = 0.00015955 loss) | |
| I0525 03:27:40.029098 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.00535054 (* 0.0272727 = 0.000145924 loss) | |
| I0525 03:27:40.029112 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.0099426 (* 0.0272727 = 0.000271162 loss) | |
| I0525 03:27:40.029142 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.00334323 (* 0.0272727 = 9.11789e-05 loss) | |
| I0525 03:27:40.029157 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.00429528 (* 0.0272727 = 0.000117144 loss) | |
| I0525 03:27:40.029171 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.00301502 (* 0.0272727 = 8.22278e-05 loss) | |
| I0525 03:27:40.029184 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.04 | |
| I0525 03:27:40.029196 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.125 | |
| I0525 03:27:40.029208 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0.125 | |
| I0525 03:27:40.029220 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0.125 | |
| I0525 03:27:40.029232 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.125 | |
| I0525 03:27:40.029244 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.25 | |
| I0525 03:27:40.029256 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.125 | |
| I0525 03:27:40.029268 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.625 | |
| I0525 03:27:40.029280 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.75 | |
| I0525 03:27:40.029292 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 1 | |
| I0525 03:27:40.029304 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 1 | |
| I0525 03:27:40.029316 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 03:27:40.029331 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 03:27:40.029343 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 03:27:40.029356 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 03:27:40.029378 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 03:27:40.029392 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 03:27:40.029404 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 03:27:40.029417 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 03:27:40.029428 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 03:27:40.029439 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 03:27:40.029451 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 03:27:40.029464 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 03:27:40.029474 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.727273 | |
| I0525 03:27:40.029484 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.22 | |
| I0525 03:27:40.029495 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.23706 (* 1 = 3.23706 loss) | |
| I0525 03:27:40.029508 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 0.972268 (* 1 = 0.972268 loss) | |
| I0525 03:27:40.029522 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 3.45488 (* 0.0909091 = 0.31408 loss) | |
| I0525 03:27:40.029536 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.35645 (* 0.0909091 = 0.305132 loss) | |
| I0525 03:27:40.029551 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.15619 (* 0.0909091 = 0.286926 loss) | |
| I0525 03:27:40.029564 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 2.8836 (* 0.0909091 = 0.262146 loss) | |
| I0525 03:27:40.029578 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 2.85568 (* 0.0909091 = 0.259607 loss) | |
| I0525 03:27:40.029592 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 3.18089 (* 0.0909091 = 0.289172 loss) | |
| I0525 03:27:40.029606 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 1.31532 (* 0.0909091 = 0.119575 loss) | |
| I0525 03:27:40.029620 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 1.07583 (* 0.0909091 = 0.0978026 loss) | |
| I0525 03:27:40.029634 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.244441 (* 0.0909091 = 0.0222219 loss) | |
| I0525 03:27:40.029649 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.116614 (* 0.0909091 = 0.0106013 loss) | |
| I0525 03:27:40.029662 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.0785128 (* 0.0909091 = 0.00713753 loss) | |
| I0525 03:27:40.029676 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.0559512 (* 0.0909091 = 0.00508647 loss) | |
| I0525 03:27:40.029691 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.0417427 (* 0.0909091 = 0.00379479 loss) | |
| I0525 03:27:40.029706 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.0337461 (* 0.0909091 = 0.00306783 loss) | |
| I0525 03:27:40.029719 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.03011 (* 0.0909091 = 0.00273728 loss) | |
| I0525 03:27:40.029733 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.0166098 (* 0.0909091 = 0.00150999 loss) | |
| I0525 03:27:40.029747 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.00840129 (* 0.0909091 = 0.000763754 loss) | |
| I0525 03:27:40.029762 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.00434437 (* 0.0909091 = 0.000394943 loss) | |
| I0525 03:27:40.029775 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00304991 (* 0.0909091 = 0.000277265 loss) | |
| I0525 03:27:40.029789 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00424968 (* 0.0909091 = 0.000386334 loss) | |
| I0525 03:27:40.029806 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00223896 (* 0.0909091 = 0.000203542 loss) | |
| I0525 03:27:40.029820 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.00168685 (* 0.0909091 = 0.00015335 loss) | |
| I0525 03:27:40.029834 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 03:27:40.029855 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 03:27:40.029867 5272 solver.cpp:245] Train net output #149: total_confidence = 7.97902e-06 | |
| I0525 03:27:40.029880 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 1.15929e-05 | |
| I0525 03:27:40.029892 5272 sgd_solver.cpp:106] Iteration 15000, lr = 0.001 | |
| I0525 03:27:47.314586 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 30.8799 > 30) by scale factor 0.971506 | |
| I0525 03:30:12.770532 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 36.4854 > 30) by scale factor 0.822247 | |
| I0525 03:31:53.544445 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 49.1603 > 30) by scale factor 0.610249 | |
| I0525 03:33:45.122551 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 30.3631 > 30) by scale factor 0.98804 | |
| I0525 03:34:04.767937 5272 solver.cpp:229] Iteration 15500, loss = 9.9276 | |
| I0525 03:34:04.768004 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.142857 | |
| I0525 03:34:04.768023 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0 | |
| I0525 03:34:04.768035 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0525 03:34:04.768049 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0.375 | |
| I0525 03:34:04.768061 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.125 | |
| I0525 03:34:04.768074 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.25 | |
| I0525 03:34:04.768086 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.25 | |
| I0525 03:34:04.768100 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.5 | |
| I0525 03:34:04.768111 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.875 | |
| I0525 03:34:04.768124 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 1 | |
| I0525 03:34:04.768136 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 1 | |
| I0525 03:34:04.768149 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 03:34:04.768162 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 03:34:04.768173 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 03:34:04.768185 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 03:34:04.768196 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 03:34:04.768208 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 03:34:04.768220 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 03:34:04.768232 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 03:34:04.768244 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 03:34:04.768256 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 03:34:04.768268 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 03:34:04.768280 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 03:34:04.768292 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.732955 | |
| I0525 03:34:04.768304 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.244898 | |
| I0525 03:34:04.768321 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.25834 (* 0.3 = 0.977501 loss) | |
| I0525 03:34:04.768335 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.10535 (* 0.3 = 0.331604 loss) | |
| I0525 03:34:04.768349 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.3001 (* 0.0272727 = 0.0900027 loss) | |
| I0525 03:34:04.768363 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.08349 (* 0.0272727 = 0.0840951 loss) | |
| I0525 03:34:04.768378 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 2.75727 (* 0.0272727 = 0.0751982 loss) | |
| I0525 03:34:04.768393 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.85069 (* 0.0272727 = 0.105019 loss) | |
| I0525 03:34:04.768406 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 2.90476 (* 0.0272727 = 0.0792207 loss) | |
| I0525 03:34:04.768420 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 2.76213 (* 0.0272727 = 0.0753307 loss) | |
| I0525 03:34:04.768434 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 2.36091 (* 0.0272727 = 0.0643885 loss) | |
| I0525 03:34:04.768447 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 0.724624 (* 0.0272727 = 0.0197625 loss) | |
| I0525 03:34:04.768462 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.144901 (* 0.0272727 = 0.00395185 loss) | |
| I0525 03:34:04.768476 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.141948 (* 0.0272727 = 0.0038713 loss) | |
| I0525 03:34:04.768491 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.137897 (* 0.0272727 = 0.00376082 loss) | |
| I0525 03:34:04.768506 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.0885088 (* 0.0272727 = 0.00241388 loss) | |
| I0525 03:34:04.768553 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.0505395 (* 0.0272727 = 0.00137835 loss) | |
| I0525 03:34:04.768568 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.0356555 (* 0.0272727 = 0.000972422 loss) | |
| I0525 03:34:04.768584 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0222831 (* 0.0272727 = 0.000607721 loss) | |
| I0525 03:34:04.768597 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.0364462 (* 0.0272727 = 0.000993988 loss) | |
| I0525 03:34:04.768615 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.0284699 (* 0.0272727 = 0.000776451 loss) | |
| I0525 03:34:04.768630 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0139512 (* 0.0272727 = 0.000380486 loss) | |
| I0525 03:34:04.768646 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.0154336 (* 0.0272727 = 0.000420917 loss) | |
| I0525 03:34:04.768659 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.00994675 (* 0.0272727 = 0.000271275 loss) | |
| I0525 03:34:04.768673 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.0098096 (* 0.0272727 = 0.000267534 loss) | |
| I0525 03:34:04.768687 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.00799504 (* 0.0272727 = 0.000218047 loss) | |
| I0525 03:34:04.768699 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.0408163 | |
| I0525 03:34:04.768712 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0.125 | |
| I0525 03:34:04.768724 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0 | |
| I0525 03:34:04.768735 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0 | |
| I0525 03:34:04.768749 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0 | |
| I0525 03:34:04.768761 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.375 | |
| I0525 03:34:04.768774 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.375 | |
| I0525 03:34:04.768785 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.5 | |
| I0525 03:34:04.768797 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.875 | |
| I0525 03:34:04.768810 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 1 | |
| I0525 03:34:04.768821 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 1 | |
| I0525 03:34:04.768832 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 03:34:04.768844 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 03:34:04.768856 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 03:34:04.768867 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 03:34:04.768878 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 03:34:04.768890 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 03:34:04.768901 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 03:34:04.768913 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 03:34:04.768924 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 03:34:04.768935 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 03:34:04.768947 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 03:34:04.768959 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 03:34:04.768970 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.721591 | |
| I0525 03:34:04.768981 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.183673 | |
| I0525 03:34:04.768996 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.29373 (* 0.3 = 0.988119 loss) | |
| I0525 03:34:04.769009 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.03251 (* 0.3 = 0.309752 loss) | |
| I0525 03:34:04.769022 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.03227 (* 0.0272727 = 0.0826982 loss) | |
| I0525 03:34:04.769037 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 3.15294 (* 0.0272727 = 0.0859893 loss) | |
| I0525 03:34:04.769062 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.02747 (* 0.0272727 = 0.0825673 loss) | |
| I0525 03:34:04.769075 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.59206 (* 0.0272727 = 0.0979653 loss) | |
| I0525 03:34:04.769089 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 2.52609 (* 0.0272727 = 0.0688933 loss) | |
| I0525 03:34:04.769104 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 2.33103 (* 0.0272727 = 0.0635735 loss) | |
| I0525 03:34:04.769134 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 2.3001 (* 0.0272727 = 0.06273 loss) | |
| I0525 03:34:04.769151 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 0.656524 (* 0.0272727 = 0.0179052 loss) | |
| I0525 03:34:04.769166 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.0744496 (* 0.0272727 = 0.00203044 loss) | |
| I0525 03:34:04.769181 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.0658119 (* 0.0272727 = 0.00179487 loss) | |
| I0525 03:34:04.769194 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.0394265 (* 0.0272727 = 0.00107527 loss) | |
| I0525 03:34:04.769209 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.0314298 (* 0.0272727 = 0.000857176 loss) | |
| I0525 03:34:04.769223 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.0101711 (* 0.0272727 = 0.000277392 loss) | |
| I0525 03:34:04.769237 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.0157271 (* 0.0272727 = 0.00042892 loss) | |
| I0525 03:34:04.769251 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.0230788 (* 0.0272727 = 0.000629423 loss) | |
| I0525 03:34:04.769265 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.00992693 (* 0.0272727 = 0.000270734 loss) | |
| I0525 03:34:04.769279 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.0188802 (* 0.0272727 = 0.000514913 loss) | |
| I0525 03:34:04.769294 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.0167816 (* 0.0272727 = 0.00045768 loss) | |
| I0525 03:34:04.769307 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.0138034 (* 0.0272727 = 0.000376456 loss) | |
| I0525 03:34:04.769321 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.0112452 (* 0.0272727 = 0.000306688 loss) | |
| I0525 03:34:04.769335 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.00701348 (* 0.0272727 = 0.000191277 loss) | |
| I0525 03:34:04.769348 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.00649548 (* 0.0272727 = 0.00017715 loss) | |
| I0525 03:34:04.769361 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.0816327 | |
| I0525 03:34:04.769373 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.125 | |
| I0525 03:34:04.769384 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0 | |
| I0525 03:34:04.769397 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0 | |
| I0525 03:34:04.769408 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0 | |
| I0525 03:34:04.769419 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.25 | |
| I0525 03:34:04.769431 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.25 | |
| I0525 03:34:04.769443 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.5 | |
| I0525 03:34:04.769455 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.875 | |
| I0525 03:34:04.769467 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 1 | |
| I0525 03:34:04.769479 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 1 | |
| I0525 03:34:04.769490 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 03:34:04.769501 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 03:34:04.769512 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 03:34:04.769525 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 03:34:04.769536 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 03:34:04.769558 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 03:34:04.769572 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 03:34:04.769583 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 03:34:04.769595 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 03:34:04.769608 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 03:34:04.769618 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 03:34:04.769630 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 03:34:04.769641 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.732955 | |
| I0525 03:34:04.769654 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.285714 | |
| I0525 03:34:04.769670 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 2.80814 (* 1 = 2.80814 loss) | |
| I0525 03:34:04.769685 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 0.877005 (* 1 = 0.877005 loss) | |
| I0525 03:34:04.769698 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 2.61296 (* 0.0909091 = 0.237542 loss) | |
| I0525 03:34:04.769712 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 2.8794 (* 0.0909091 = 0.261763 loss) | |
| I0525 03:34:04.769726 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 2.77366 (* 0.0909091 = 0.252151 loss) | |
| I0525 03:34:04.769740 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.54035 (* 0.0909091 = 0.32185 loss) | |
| I0525 03:34:04.769753 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 2.38097 (* 0.0909091 = 0.216452 loss) | |
| I0525 03:34:04.769767 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 2.08633 (* 0.0909091 = 0.189667 loss) | |
| I0525 03:34:04.769781 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 2.06382 (* 0.0909091 = 0.18762 loss) | |
| I0525 03:34:04.769798 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.536527 (* 0.0909091 = 0.0487752 loss) | |
| I0525 03:34:04.769811 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.113475 (* 0.0909091 = 0.0103159 loss) | |
| I0525 03:34:04.769825 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.0794687 (* 0.0909091 = 0.00722443 loss) | |
| I0525 03:34:04.769840 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.0626262 (* 0.0909091 = 0.00569329 loss) | |
| I0525 03:34:04.769855 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.0369124 (* 0.0909091 = 0.00335567 loss) | |
| I0525 03:34:04.769868 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.0215954 (* 0.0909091 = 0.00196322 loss) | |
| I0525 03:34:04.769881 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.0150633 (* 0.0909091 = 0.00136939 loss) | |
| I0525 03:34:04.769896 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.0134135 (* 0.0909091 = 0.00121941 loss) | |
| I0525 03:34:04.769909 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.00711239 (* 0.0909091 = 0.000646581 loss) | |
| I0525 03:34:04.769927 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.00650103 (* 0.0909091 = 0.000591003 loss) | |
| I0525 03:34:04.769940 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.00591476 (* 0.0909091 = 0.000537705 loss) | |
| I0525 03:34:04.769954 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00230234 (* 0.0909091 = 0.000209304 loss) | |
| I0525 03:34:04.769968 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00236752 (* 0.0909091 = 0.000215229 loss) | |
| I0525 03:34:04.769982 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00231042 (* 0.0909091 = 0.000210038 loss) | |
| I0525 03:34:04.769995 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.00092201 (* 0.0909091 = 8.38191e-05 loss) | |
| I0525 03:34:04.770009 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 03:34:04.770020 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 03:34:04.770041 5272 solver.cpp:245] Train net output #149: total_confidence = 4.96809e-05 | |
| I0525 03:34:04.770054 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 0.000163431 | |
| I0525 03:34:04.770067 5272 sgd_solver.cpp:106] Iteration 15500, lr = 0.001 | |
| I0525 03:35:36.707347 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 52.9072 > 30) by scale factor 0.567031 | |
| I0525 03:39:35.287448 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 31.995 > 30) by scale factor 0.937647 | |
| I0525 03:40:29.610981 5272 solver.cpp:229] Iteration 16000, loss = 10.0087 | |
| I0525 03:40:29.611110 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0847458 | |
| I0525 03:40:29.611132 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0 | |
| I0525 03:40:29.611145 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0.125 | |
| I0525 03:40:29.611158 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0.25 | |
| I0525 03:40:29.611171 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0 | |
| I0525 03:40:29.611183 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.375 | |
| I0525 03:40:29.611196 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.375 | |
| I0525 03:40:29.611209 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.375 | |
| I0525 03:40:29.611222 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.375 | |
| I0525 03:40:29.611234 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 0.625 | |
| I0525 03:40:29.611248 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 0.875 | |
| I0525 03:40:29.611261 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 0.875 | |
| I0525 03:40:29.611274 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 0.875 | |
| I0525 03:40:29.611286 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 0.875 | |
| I0525 03:40:29.611299 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 03:40:29.611310 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 03:40:29.611321 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 03:40:29.611333 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 03:40:29.611345 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 03:40:29.611356 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 03:40:29.611368 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 03:40:29.611380 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 03:40:29.611392 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 03:40:29.611404 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.6875 | |
| I0525 03:40:29.611416 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.186441 | |
| I0525 03:40:29.611433 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.13995 (* 0.3 = 0.941986 loss) | |
| I0525 03:40:29.611448 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.24203 (* 0.3 = 0.372609 loss) | |
| I0525 03:40:29.611462 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.38016 (* 0.0272727 = 0.0921863 loss) | |
| I0525 03:40:29.611476 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 2.99163 (* 0.0272727 = 0.0815898 loss) | |
| I0525 03:40:29.611490 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 2.99546 (* 0.0272727 = 0.0816943 loss) | |
| I0525 03:40:29.611505 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.01218 (* 0.0272727 = 0.0821502 loss) | |
| I0525 03:40:29.611517 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 2.17431 (* 0.0272727 = 0.0592995 loss) | |
| I0525 03:40:29.611532 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 2.30817 (* 0.0272727 = 0.06295 loss) | |
| I0525 03:40:29.611546 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 2.56759 (* 0.0272727 = 0.0700251 loss) | |
| I0525 03:40:29.611560 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 2.54102 (* 0.0272727 = 0.0693007 loss) | |
| I0525 03:40:29.611573 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 1.50636 (* 0.0272727 = 0.0410824 loss) | |
| I0525 03:40:29.611588 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.648441 (* 0.0272727 = 0.0176847 loss) | |
| I0525 03:40:29.611603 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.673985 (* 0.0272727 = 0.0183814 loss) | |
| I0525 03:40:29.611615 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.659943 (* 0.0272727 = 0.0179984 loss) | |
| I0525 03:40:29.611629 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.406591 (* 0.0272727 = 0.0110888 loss) | |
| I0525 03:40:29.611665 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.134549 (* 0.0272727 = 0.00366951 loss) | |
| I0525 03:40:29.611680 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0984001 (* 0.0272727 = 0.00268364 loss) | |
| I0525 03:40:29.611695 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.0292249 (* 0.0272727 = 0.000797044 loss) | |
| I0525 03:40:29.611708 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.0133283 (* 0.0272727 = 0.000363499 loss) | |
| I0525 03:40:29.611722 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0276383 (* 0.0272727 = 0.000753773 loss) | |
| I0525 03:40:29.611737 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.0117294 (* 0.0272727 = 0.000319894 loss) | |
| I0525 03:40:29.611750 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.0065907 (* 0.0272727 = 0.000179746 loss) | |
| I0525 03:40:29.611764 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.00492645 (* 0.0272727 = 0.000134358 loss) | |
| I0525 03:40:29.611778 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.00552311 (* 0.0272727 = 0.00015063 loss) | |
| I0525 03:40:29.611791 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.118644 | |
| I0525 03:40:29.611804 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0.125 | |
| I0525 03:40:29.611816 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0.25 | |
| I0525 03:40:29.611829 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0.125 | |
| I0525 03:40:29.611840 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0.125 | |
| I0525 03:40:29.611852 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.375 | |
| I0525 03:40:29.611865 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.375 | |
| I0525 03:40:29.611879 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.375 | |
| I0525 03:40:29.611892 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.375 | |
| I0525 03:40:29.611904 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 0.625 | |
| I0525 03:40:29.611917 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 0.875 | |
| I0525 03:40:29.611928 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 0.875 | |
| I0525 03:40:29.611940 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 0.875 | |
| I0525 03:40:29.611953 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 0.875 | |
| I0525 03:40:29.611964 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 03:40:29.611976 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 03:40:29.611987 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 03:40:29.611999 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 03:40:29.612011 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 03:40:29.612022 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 03:40:29.612035 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 03:40:29.612046 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 03:40:29.612057 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 03:40:29.612068 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.704545 | |
| I0525 03:40:29.612081 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.237288 | |
| I0525 03:40:29.612094 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.11685 (* 0.3 = 0.935056 loss) | |
| I0525 03:40:29.612108 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.14148 (* 0.3 = 0.342443 loss) | |
| I0525 03:40:29.612125 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.18168 (* 0.0272727 = 0.0867731 loss) | |
| I0525 03:40:29.612140 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 3.27047 (* 0.0272727 = 0.0891946 loss) | |
| I0525 03:40:29.612165 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 2.80781 (* 0.0272727 = 0.0765766 loss) | |
| I0525 03:40:29.612180 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.03835 (* 0.0272727 = 0.0828641 loss) | |
| I0525 03:40:29.612195 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 2.28662 (* 0.0272727 = 0.0623623 loss) | |
| I0525 03:40:29.612208 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 2.45987 (* 0.0272727 = 0.0670874 loss) | |
| I0525 03:40:29.612221 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 2.68855 (* 0.0272727 = 0.0733241 loss) | |
| I0525 03:40:29.612236 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 2.45544 (* 0.0272727 = 0.0669664 loss) | |
| I0525 03:40:29.612249 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 1.69385 (* 0.0272727 = 0.046196 loss) | |
| I0525 03:40:29.612263 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.686413 (* 0.0272727 = 0.0187203 loss) | |
| I0525 03:40:29.612277 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.51738 (* 0.0272727 = 0.0141104 loss) | |
| I0525 03:40:29.612290 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.664432 (* 0.0272727 = 0.0181209 loss) | |
| I0525 03:40:29.612304 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.421833 (* 0.0272727 = 0.0115045 loss) | |
| I0525 03:40:29.612318 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.0986402 (* 0.0272727 = 0.00269019 loss) | |
| I0525 03:40:29.612332 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.0634175 (* 0.0272727 = 0.00172957 loss) | |
| I0525 03:40:29.612346 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.0645511 (* 0.0272727 = 0.00176048 loss) | |
| I0525 03:40:29.612361 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.0275928 (* 0.0272727 = 0.000752531 loss) | |
| I0525 03:40:29.612375 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.00864016 (* 0.0272727 = 0.000235641 loss) | |
| I0525 03:40:29.612390 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.0239436 (* 0.0272727 = 0.000653007 loss) | |
| I0525 03:40:29.612403 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.00545371 (* 0.0272727 = 0.000148738 loss) | |
| I0525 03:40:29.612417 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.00851153 (* 0.0272727 = 0.000232133 loss) | |
| I0525 03:40:29.612432 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.0135096 (* 0.0272727 = 0.000368445 loss) | |
| I0525 03:40:29.612444 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.169492 | |
| I0525 03:40:29.612457 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.25 | |
| I0525 03:40:29.612468 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0 | |
| I0525 03:40:29.612480 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0.25 | |
| I0525 03:40:29.612494 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.25 | |
| I0525 03:40:29.612506 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.375 | |
| I0525 03:40:29.612519 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.5 | |
| I0525 03:40:29.612530 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.375 | |
| I0525 03:40:29.612542 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.375 | |
| I0525 03:40:29.612553 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 0.625 | |
| I0525 03:40:29.612565 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 0.875 | |
| I0525 03:40:29.612577 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 0.875 | |
| I0525 03:40:29.612589 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 0.875 | |
| I0525 03:40:29.612601 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 0.875 | |
| I0525 03:40:29.612612 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 03:40:29.612624 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 03:40:29.612637 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 03:40:29.612658 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 03:40:29.612670 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 03:40:29.612681 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 03:40:29.612694 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 03:40:29.612705 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 03:40:29.612716 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 03:40:29.612727 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.721591 | |
| I0525 03:40:29.612740 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.271186 | |
| I0525 03:40:29.612753 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 2.91297 (* 1 = 2.91297 loss) | |
| I0525 03:40:29.612768 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.08626 (* 1 = 1.08626 loss) | |
| I0525 03:40:29.612782 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 2.87178 (* 0.0909091 = 0.261071 loss) | |
| I0525 03:40:29.612795 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 2.88061 (* 0.0909091 = 0.261874 loss) | |
| I0525 03:40:29.612809 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 2.44347 (* 0.0909091 = 0.222133 loss) | |
| I0525 03:40:29.612823 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 2.69387 (* 0.0909091 = 0.244898 loss) | |
| I0525 03:40:29.612838 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 1.89877 (* 0.0909091 = 0.172615 loss) | |
| I0525 03:40:29.612851 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 1.83026 (* 0.0909091 = 0.166387 loss) | |
| I0525 03:40:29.612864 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 2.52894 (* 0.0909091 = 0.229904 loss) | |
| I0525 03:40:29.612879 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 2.30378 (* 0.0909091 = 0.209434 loss) | |
| I0525 03:40:29.612891 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 1.31315 (* 0.0909091 = 0.119377 loss) | |
| I0525 03:40:29.612905 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.59627 (* 0.0909091 = 0.0542064 loss) | |
| I0525 03:40:29.612920 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.610379 (* 0.0909091 = 0.055489 loss) | |
| I0525 03:40:29.612936 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.369548 (* 0.0909091 = 0.0335952 loss) | |
| I0525 03:40:29.612951 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.396128 (* 0.0909091 = 0.0360116 loss) | |
| I0525 03:40:29.612965 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.0364827 (* 0.0909091 = 0.00331661 loss) | |
| I0525 03:40:29.612979 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.0172525 (* 0.0909091 = 0.00156841 loss) | |
| I0525 03:40:29.612993 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.0115012 (* 0.0909091 = 0.00104556 loss) | |
| I0525 03:40:29.613008 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.0149426 (* 0.0909091 = 0.00135842 loss) | |
| I0525 03:40:29.613021 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.00593184 (* 0.0909091 = 0.000539259 loss) | |
| I0525 03:40:29.613035 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00313401 (* 0.0909091 = 0.00028491 loss) | |
| I0525 03:40:29.613049 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.0012625 (* 0.0909091 = 0.000114773 loss) | |
| I0525 03:40:29.613064 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.000638181 (* 0.0909091 = 5.80165e-05 loss) | |
| I0525 03:40:29.613077 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.000431056 (* 0.0909091 = 3.91869e-05 loss) | |
| I0525 03:40:29.613090 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 03:40:29.613101 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 03:40:29.613113 5272 solver.cpp:245] Train net output #149: total_confidence = 3.4372e-05 | |
| I0525 03:40:29.613150 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 0.000203559 | |
| I0525 03:40:29.613167 5272 sgd_solver.cpp:106] Iteration 16000, lr = 0.001 | |
| I0525 03:41:05.377734 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 32.1014 > 30) by scale factor 0.934538 | |
| I0525 03:42:25.434659 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 33.3097 > 30) by scale factor 0.900638 | |
| I0525 03:45:13.289178 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 31.2507 > 30) by scale factor 0.959977 | |
| I0525 03:45:36.383708 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 34.2675 > 30) by scale factor 0.875466 | |
| I0525 03:45:41.779907 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 40.026 > 30) by scale factor 0.749513 | |
| I0525 03:46:54.617725 5272 solver.cpp:229] Iteration 16500, loss = 9.95266 | |
| I0525 03:46:54.617871 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.137255 | |
| I0525 03:46:54.617892 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.25 | |
| I0525 03:46:54.617907 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0.125 | |
| I0525 03:46:54.617919 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0.125 | |
| I0525 03:46:54.617933 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.125 | |
| I0525 03:46:54.617944 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.25 | |
| I0525 03:46:54.617957 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.25 | |
| I0525 03:46:54.617969 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.5 | |
| I0525 03:46:54.617981 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.75 | |
| I0525 03:46:54.617995 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 0.875 | |
| I0525 03:46:54.618006 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 1 | |
| I0525 03:46:54.618019 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 03:46:54.618032 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 03:46:54.618046 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 03:46:54.618057 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 03:46:54.618068 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 03:46:54.618080 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 03:46:54.618091 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 03:46:54.618104 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 03:46:54.618115 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 03:46:54.618127 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 03:46:54.618139 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 03:46:54.618151 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 03:46:54.618162 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.744318 | |
| I0525 03:46:54.618175 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.352941 | |
| I0525 03:46:54.618191 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.05289 (* 0.3 = 0.915868 loss) | |
| I0525 03:46:54.618206 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 0.951113 (* 0.3 = 0.285334 loss) | |
| I0525 03:46:54.618219 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 2.58906 (* 0.0272727 = 0.0706107 loss) | |
| I0525 03:46:54.618233 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.02925 (* 0.0272727 = 0.082616 loss) | |
| I0525 03:46:54.618247 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.09303 (* 0.0272727 = 0.0843554 loss) | |
| I0525 03:46:54.618262 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 2.87012 (* 0.0272727 = 0.078276 loss) | |
| I0525 03:46:54.618276 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 2.73307 (* 0.0272727 = 0.0745383 loss) | |
| I0525 03:46:54.618289 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 2.92504 (* 0.0272727 = 0.0797738 loss) | |
| I0525 03:46:54.618304 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 2.14681 (* 0.0272727 = 0.0585494 loss) | |
| I0525 03:46:54.618317 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 0.862504 (* 0.0272727 = 0.0235228 loss) | |
| I0525 03:46:54.618332 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.46301 (* 0.0272727 = 0.0126276 loss) | |
| I0525 03:46:54.618346 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.0802536 (* 0.0272727 = 0.00218874 loss) | |
| I0525 03:46:54.618361 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.0752945 (* 0.0272727 = 0.00205349 loss) | |
| I0525 03:46:54.618376 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.0823297 (* 0.0272727 = 0.00224535 loss) | |
| I0525 03:46:54.618389 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.0323772 (* 0.0272727 = 0.000883014 loss) | |
| I0525 03:46:54.618425 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.025092 (* 0.0272727 = 0.000684328 loss) | |
| I0525 03:46:54.618441 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0317565 (* 0.0272727 = 0.000866085 loss) | |
| I0525 03:46:54.618455 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.00680745 (* 0.0272727 = 0.000185658 loss) | |
| I0525 03:46:54.618468 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.00657653 (* 0.0272727 = 0.00017936 loss) | |
| I0525 03:46:54.618482 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.00475138 (* 0.0272727 = 0.000129583 loss) | |
| I0525 03:46:54.618496 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.00481302 (* 0.0272727 = 0.000131264 loss) | |
| I0525 03:46:54.618511 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.00348588 (* 0.0272727 = 9.50693e-05 loss) | |
| I0525 03:46:54.618525 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.00229253 (* 0.0272727 = 6.25236e-05 loss) | |
| I0525 03:46:54.618538 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.00296761 (* 0.0272727 = 8.09349e-05 loss) | |
| I0525 03:46:54.618551 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.137255 | |
| I0525 03:46:54.618563 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0.25 | |
| I0525 03:46:54.618576 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0.125 | |
| I0525 03:46:54.618587 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0.125 | |
| I0525 03:46:54.618599 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0.25 | |
| I0525 03:46:54.618612 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.125 | |
| I0525 03:46:54.618623 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.25 | |
| I0525 03:46:54.618635 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.5 | |
| I0525 03:46:54.618648 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.75 | |
| I0525 03:46:54.618659 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 0.875 | |
| I0525 03:46:54.618671 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 1 | |
| I0525 03:46:54.618683 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 03:46:54.618695 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 03:46:54.618706 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 03:46:54.618718 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 03:46:54.618731 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 03:46:54.618741 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 03:46:54.618753 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 03:46:54.618765 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 03:46:54.618777 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 03:46:54.618788 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 03:46:54.618800 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 03:46:54.618811 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 03:46:54.618823 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.75 | |
| I0525 03:46:54.618835 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.254902 | |
| I0525 03:46:54.618849 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 2.95707 (* 0.3 = 0.887122 loss) | |
| I0525 03:46:54.618863 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 0.945267 (* 0.3 = 0.28358 loss) | |
| I0525 03:46:54.618881 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 2.54671 (* 0.0272727 = 0.0694558 loss) | |
| I0525 03:46:54.618892 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 2.89973 (* 0.0272727 = 0.0790834 loss) | |
| I0525 03:46:54.618918 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.00472 (* 0.0272727 = 0.0819469 loss) | |
| I0525 03:46:54.618933 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 2.75665 (* 0.0272727 = 0.0751814 loss) | |
| I0525 03:46:54.618947 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 2.81052 (* 0.0272727 = 0.0766505 loss) | |
| I0525 03:46:54.618962 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 2.8664 (* 0.0272727 = 0.0781745 loss) | |
| I0525 03:46:54.618974 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 2.2521 (* 0.0272727 = 0.0614209 loss) | |
| I0525 03:46:54.618988 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 1.08122 (* 0.0272727 = 0.0294879 loss) | |
| I0525 03:46:54.619002 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.569229 (* 0.0272727 = 0.0155244 loss) | |
| I0525 03:46:54.619017 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.0327131 (* 0.0272727 = 0.000892174 loss) | |
| I0525 03:46:54.619031 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.00847852 (* 0.0272727 = 0.000231232 loss) | |
| I0525 03:46:54.619045 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.00721386 (* 0.0272727 = 0.000196742 loss) | |
| I0525 03:46:54.619060 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.0075548 (* 0.0272727 = 0.00020604 loss) | |
| I0525 03:46:54.619072 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.00696494 (* 0.0272727 = 0.000189953 loss) | |
| I0525 03:46:54.619086 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.00632296 (* 0.0272727 = 0.000172444 loss) | |
| I0525 03:46:54.619101 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.0030857 (* 0.0272727 = 8.41554e-05 loss) | |
| I0525 03:46:54.619114 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.00404422 (* 0.0272727 = 0.000110297 loss) | |
| I0525 03:46:54.619128 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.00145885 (* 0.0272727 = 3.97869e-05 loss) | |
| I0525 03:46:54.619143 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.00162843 (* 0.0272727 = 4.44118e-05 loss) | |
| I0525 03:46:54.619156 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.000827683 (* 0.0272727 = 2.25732e-05 loss) | |
| I0525 03:46:54.619170 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.0014765 (* 0.0272727 = 4.02681e-05 loss) | |
| I0525 03:46:54.619184 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.000740876 (* 0.0272727 = 2.02057e-05 loss) | |
| I0525 03:46:54.619196 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.156863 | |
| I0525 03:46:54.619209 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.375 | |
| I0525 03:46:54.619220 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0 | |
| I0525 03:46:54.619232 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0.125 | |
| I0525 03:46:54.619245 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.375 | |
| I0525 03:46:54.619256 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.125 | |
| I0525 03:46:54.619268 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.25 | |
| I0525 03:46:54.619280 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.5 | |
| I0525 03:46:54.619292 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.75 | |
| I0525 03:46:54.619303 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 0.875 | |
| I0525 03:46:54.619315 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 1 | |
| I0525 03:46:54.619328 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 03:46:54.619338 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 03:46:54.619349 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 03:46:54.619361 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 03:46:54.619372 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 03:46:54.619385 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 03:46:54.619405 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 03:46:54.619417 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 03:46:54.619429 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 03:46:54.619441 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 03:46:54.619452 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 03:46:54.619463 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 03:46:54.619475 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.755682 | |
| I0525 03:46:54.619488 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.294118 | |
| I0525 03:46:54.619501 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 2.84986 (* 1 = 2.84986 loss) | |
| I0525 03:46:54.619515 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 0.876946 (* 1 = 0.876946 loss) | |
| I0525 03:46:54.619529 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 2.45544 (* 0.0909091 = 0.223222 loss) | |
| I0525 03:46:54.619544 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 2.90914 (* 0.0909091 = 0.264468 loss) | |
| I0525 03:46:54.619557 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 2.74934 (* 0.0909091 = 0.24994 loss) | |
| I0525 03:46:54.619571 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 2.55501 (* 0.0909091 = 0.232273 loss) | |
| I0525 03:46:54.619585 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 2.56215 (* 0.0909091 = 0.232923 loss) | |
| I0525 03:46:54.619598 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 2.70508 (* 0.0909091 = 0.245917 loss) | |
| I0525 03:46:54.619611 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 1.99877 (* 0.0909091 = 0.181706 loss) | |
| I0525 03:46:54.619626 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.856668 (* 0.0909091 = 0.0778789 loss) | |
| I0525 03:46:54.619639 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.471886 (* 0.0909091 = 0.0428987 loss) | |
| I0525 03:46:54.619649 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.0738205 (* 0.0909091 = 0.00671095 loss) | |
| I0525 03:46:54.619659 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.0239838 (* 0.0909091 = 0.00218034 loss) | |
| I0525 03:46:54.619674 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.0142832 (* 0.0909091 = 0.00129847 loss) | |
| I0525 03:46:54.619688 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.0163333 (* 0.0909091 = 0.00148484 loss) | |
| I0525 03:46:54.619702 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.00940803 (* 0.0909091 = 0.000855275 loss) | |
| I0525 03:46:54.619716 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.0101508 (* 0.0909091 = 0.000922797 loss) | |
| I0525 03:46:54.619729 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.0125232 (* 0.0909091 = 0.00113848 loss) | |
| I0525 03:46:54.619743 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.0125034 (* 0.0909091 = 0.00113667 loss) | |
| I0525 03:46:54.619757 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.00544933 (* 0.0909091 = 0.000495393 loss) | |
| I0525 03:46:54.619771 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00342997 (* 0.0909091 = 0.000311816 loss) | |
| I0525 03:46:54.619784 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.0025867 (* 0.0909091 = 0.000235154 loss) | |
| I0525 03:46:54.619798 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.000747743 (* 0.0909091 = 6.79766e-05 loss) | |
| I0525 03:46:54.619812 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.000796393 (* 0.0909091 = 7.23994e-05 loss) | |
| I0525 03:46:54.619824 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 03:46:54.619835 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 03:46:54.619846 5272 solver.cpp:245] Train net output #149: total_confidence = 2.49174e-05 | |
| I0525 03:46:54.619868 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 0.000139793 | |
| I0525 03:46:54.619881 5272 sgd_solver.cpp:106] Iteration 16500, lr = 0.001 | |
| I0525 03:48:02.751521 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 33.9711 > 30) by scale factor 0.883105 | |
| I0525 03:51:33.928478 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 34.0884 > 30) by scale factor 0.880064 | |
| I0525 03:51:46.240334 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 32.857 > 30) by scale factor 0.913046 | |
| I0525 03:52:44.756243 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 30.7742 > 30) by scale factor 0.974842 | |
| I0525 03:53:15.541491 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 34.6426 > 30) by scale factor 0.865986 | |
| I0525 03:53:19.792511 5272 solver.cpp:229] Iteration 17000, loss = 9.96095 | |
| I0525 03:53:19.792582 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0697674 | |
| I0525 03:53:19.792599 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.25 | |
| I0525 03:53:19.792613 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0525 03:53:19.792626 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0525 03:53:19.792639 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.125 | |
| I0525 03:53:19.792651 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.25 | |
| I0525 03:53:19.792665 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.5 | |
| I0525 03:53:19.792677 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.75 | |
| I0525 03:53:19.792692 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.875 | |
| I0525 03:53:19.792706 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 1 | |
| I0525 03:53:19.792717 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 1 | |
| I0525 03:53:19.792731 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 03:53:19.792742 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 03:53:19.792754 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 03:53:19.792767 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 03:53:19.792778 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 03:53:19.792790 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 03:53:19.792803 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 03:53:19.792814 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 03:53:19.792826 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 03:53:19.792839 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 03:53:19.792850 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 03:53:19.792861 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 03:53:19.792873 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.772727 | |
| I0525 03:53:19.792886 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.255814 | |
| I0525 03:53:19.792901 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 2.98732 (* 0.3 = 0.896196 loss) | |
| I0525 03:53:19.792917 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 0.804036 (* 0.3 = 0.241211 loss) | |
| I0525 03:53:19.792930 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 2.80692 (* 0.0272727 = 0.0765524 loss) | |
| I0525 03:53:19.792944 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.44307 (* 0.0272727 = 0.0939018 loss) | |
| I0525 03:53:19.792958 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.4879 (* 0.0272727 = 0.0951245 loss) | |
| I0525 03:53:19.792973 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 2.81378 (* 0.0272727 = 0.0767393 loss) | |
| I0525 03:53:19.792986 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 2.50198 (* 0.0272727 = 0.0682359 loss) | |
| I0525 03:53:19.793000 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 2.06775 (* 0.0272727 = 0.0563931 loss) | |
| I0525 03:53:19.793015 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 1.24982 (* 0.0272727 = 0.0340859 loss) | |
| I0525 03:53:19.793028 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 0.702248 (* 0.0272727 = 0.0191522 loss) | |
| I0525 03:53:19.793045 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.00603944 (* 0.0272727 = 0.000164712 loss) | |
| I0525 03:53:19.793059 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.00419402 (* 0.0272727 = 0.000114382 loss) | |
| I0525 03:53:19.793073 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.00299061 (* 0.0272727 = 8.1562e-05 loss) | |
| I0525 03:53:19.793088 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.00218774 (* 0.0272727 = 5.96655e-05 loss) | |
| I0525 03:53:19.793156 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.00257254 (* 0.0272727 = 7.01603e-05 loss) | |
| I0525 03:53:19.793172 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.0014997 (* 0.0272727 = 4.0901e-05 loss) | |
| I0525 03:53:19.793187 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0029842 (* 0.0272727 = 8.13874e-05 loss) | |
| I0525 03:53:19.793201 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.00378948 (* 0.0272727 = 0.000103349 loss) | |
| I0525 03:53:19.793215 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.0018549 (* 0.0272727 = 5.05881e-05 loss) | |
| I0525 03:53:19.793229 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.00257865 (* 0.0272727 = 7.03268e-05 loss) | |
| I0525 03:53:19.793243 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.00162324 (* 0.0272727 = 4.42702e-05 loss) | |
| I0525 03:53:19.793257 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.00189218 (* 0.0272727 = 5.1605e-05 loss) | |
| I0525 03:53:19.793272 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.00166128 (* 0.0272727 = 4.53076e-05 loss) | |
| I0525 03:53:19.793287 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.00406098 (* 0.0272727 = 0.000110754 loss) | |
| I0525 03:53:19.793298 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.0697674 | |
| I0525 03:53:19.793311 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0.125 | |
| I0525 03:53:19.793323 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0 | |
| I0525 03:53:19.793334 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0.125 | |
| I0525 03:53:19.793346 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0.125 | |
| I0525 03:53:19.793359 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.25 | |
| I0525 03:53:19.793370 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.5 | |
| I0525 03:53:19.793382 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.75 | |
| I0525 03:53:19.793395 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.875 | |
| I0525 03:53:19.793406 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 1 | |
| I0525 03:53:19.793417 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 1 | |
| I0525 03:53:19.793428 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 03:53:19.793440 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 03:53:19.793452 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 03:53:19.793463 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 03:53:19.793474 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 03:53:19.793486 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 03:53:19.793498 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 03:53:19.793510 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 03:53:19.793521 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 03:53:19.793534 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 03:53:19.793545 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 03:53:19.793556 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 03:53:19.793567 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.772727 | |
| I0525 03:53:19.793581 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.348837 | |
| I0525 03:53:19.793593 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 2.82465 (* 0.3 = 0.847394 loss) | |
| I0525 03:53:19.793607 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 0.775539 (* 0.3 = 0.232662 loss) | |
| I0525 03:53:19.793622 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 2.63012 (* 0.0272727 = 0.0717305 loss) | |
| I0525 03:53:19.793635 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 3.39972 (* 0.0272727 = 0.0927197 loss) | |
| I0525 03:53:19.793661 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 2.95927 (* 0.0272727 = 0.0807074 loss) | |
| I0525 03:53:19.793676 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 2.6357 (* 0.0272727 = 0.0718829 loss) | |
| I0525 03:53:19.793690 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 2.51045 (* 0.0272727 = 0.0684667 loss) | |
| I0525 03:53:19.793704 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 1.90236 (* 0.0272727 = 0.0518826 loss) | |
| I0525 03:53:19.793717 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 1.15075 (* 0.0272727 = 0.0313841 loss) | |
| I0525 03:53:19.793735 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 0.732372 (* 0.0272727 = 0.0199738 loss) | |
| I0525 03:53:19.793750 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.00747531 (* 0.0272727 = 0.000203872 loss) | |
| I0525 03:53:19.793763 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.00712594 (* 0.0272727 = 0.000194344 loss) | |
| I0525 03:53:19.793776 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.00469047 (* 0.0272727 = 0.000127922 loss) | |
| I0525 03:53:19.793792 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.00326161 (* 0.0272727 = 8.89529e-05 loss) | |
| I0525 03:53:19.793805 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.00365549 (* 0.0272727 = 9.96953e-05 loss) | |
| I0525 03:53:19.793818 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.00643849 (* 0.0272727 = 0.000175595 loss) | |
| I0525 03:53:19.793833 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.00476655 (* 0.0272727 = 0.000129997 loss) | |
| I0525 03:53:19.793846 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.00463573 (* 0.0272727 = 0.000126429 loss) | |
| I0525 03:53:19.793860 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.00666577 (* 0.0272727 = 0.000181794 loss) | |
| I0525 03:53:19.793874 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.00297897 (* 0.0272727 = 8.12446e-05 loss) | |
| I0525 03:53:19.793889 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.00544555 (* 0.0272727 = 0.000148515 loss) | |
| I0525 03:53:19.793903 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.0024178 (* 0.0272727 = 6.594e-05 loss) | |
| I0525 03:53:19.793917 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.00335889 (* 0.0272727 = 9.16062e-05 loss) | |
| I0525 03:53:19.793938 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.0020405 (* 0.0272727 = 5.56501e-05 loss) | |
| I0525 03:53:19.793963 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.0930233 | |
| I0525 03:53:19.793982 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0 | |
| I0525 03:53:19.793994 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0.125 | |
| I0525 03:53:19.794006 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0.125 | |
| I0525 03:53:19.794018 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.25 | |
| I0525 03:53:19.794030 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.375 | |
| I0525 03:53:19.794041 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.5 | |
| I0525 03:53:19.794054 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.75 | |
| I0525 03:53:19.794066 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.875 | |
| I0525 03:53:19.794077 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 1 | |
| I0525 03:53:19.794090 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 1 | |
| I0525 03:53:19.794101 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 03:53:19.794109 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 03:53:19.794117 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 03:53:19.794129 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 03:53:19.794140 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 03:53:19.794169 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 03:53:19.794183 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 03:53:19.794194 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 03:53:19.794206 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 03:53:19.794217 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 03:53:19.794229 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 03:53:19.794240 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 03:53:19.794252 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.767045 | |
| I0525 03:53:19.794265 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.27907 | |
| I0525 03:53:19.794278 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 2.80016 (* 1 = 2.80016 loss) | |
| I0525 03:53:19.794292 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 0.748355 (* 1 = 0.748355 loss) | |
| I0525 03:53:19.794306 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 2.70138 (* 0.0909091 = 0.24558 loss) | |
| I0525 03:53:19.794320 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 2.99376 (* 0.0909091 = 0.27216 loss) | |
| I0525 03:53:19.794334 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.15709 (* 0.0909091 = 0.287008 loss) | |
| I0525 03:53:19.794348 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 2.61033 (* 0.0909091 = 0.237303 loss) | |
| I0525 03:53:19.794361 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 2.09067 (* 0.0909091 = 0.190061 loss) | |
| I0525 03:53:19.794375 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 1.76544 (* 0.0909091 = 0.160495 loss) | |
| I0525 03:53:19.794389 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 1.0783 (* 0.0909091 = 0.0980269 loss) | |
| I0525 03:53:19.794402 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.678254 (* 0.0909091 = 0.0616594 loss) | |
| I0525 03:53:19.794416 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.0016475 (* 0.0909091 = 0.000149773 loss) | |
| I0525 03:53:19.794430 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.000643156 (* 0.0909091 = 5.84687e-05 loss) | |
| I0525 03:53:19.794445 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.000470967 (* 0.0909091 = 4.28152e-05 loss) | |
| I0525 03:53:19.794458 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.000478653 (* 0.0909091 = 4.35139e-05 loss) | |
| I0525 03:53:19.794472 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.000354277 (* 0.0909091 = 3.2207e-05 loss) | |
| I0525 03:53:19.794486 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.000326132 (* 0.0909091 = 2.96484e-05 loss) | |
| I0525 03:53:19.794500 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.000401394 (* 0.0909091 = 3.64904e-05 loss) | |
| I0525 03:53:19.794514 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.000336714 (* 0.0909091 = 3.06103e-05 loss) | |
| I0525 03:53:19.794528 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.000439536 (* 0.0909091 = 3.99578e-05 loss) | |
| I0525 03:53:19.794543 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.000441357 (* 0.0909091 = 4.01234e-05 loss) | |
| I0525 03:53:19.794556 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.000709273 (* 0.0909091 = 6.44794e-05 loss) | |
| I0525 03:53:19.794570 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.000464645 (* 0.0909091 = 4.22405e-05 loss) | |
| I0525 03:53:19.794584 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00056146 (* 0.0909091 = 5.10418e-05 loss) | |
| I0525 03:53:19.794598 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.000466338 (* 0.0909091 = 4.23944e-05 loss) | |
| I0525 03:53:19.794610 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 03:53:19.794622 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 03:53:19.794643 5272 solver.cpp:245] Train net output #149: total_confidence = 3.20007e-05 | |
| I0525 03:53:19.794656 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 5.64344e-05 | |
| I0525 03:53:19.794670 5272 sgd_solver.cpp:106] Iteration 17000, lr = 0.001 | |
| I0525 03:57:04.981215 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 31.8268 > 30) by scale factor 0.942603 | |
| I0525 03:57:54.219537 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 38.9306 > 30) by scale factor 0.770602 | |
| I0525 03:59:44.722273 5272 solver.cpp:229] Iteration 17500, loss = 9.85525 | |
| I0525 03:59:44.722414 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0833333 | |
| I0525 03:59:44.722435 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.125 | |
| I0525 03:59:44.722450 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0525 03:59:44.722462 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0.25 | |
| I0525 03:59:44.722476 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0 | |
| I0525 03:59:44.722488 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.25 | |
| I0525 03:59:44.722501 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.375 | |
| I0525 03:59:44.722513 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.625 | |
| I0525 03:59:44.722527 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.75 | |
| I0525 03:59:44.722538 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 1 | |
| I0525 03:59:44.722551 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 1 | |
| I0525 03:59:44.722563 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 03:59:44.722575 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 03:59:44.722587 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 03:59:44.722599 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 03:59:44.722611 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 03:59:44.722623 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 03:59:44.722635 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 03:59:44.722646 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 03:59:44.722659 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 03:59:44.722671 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 03:59:44.722682 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 03:59:44.722694 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 03:59:44.722707 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.744318 | |
| I0525 03:59:44.722718 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.229167 | |
| I0525 03:59:44.722735 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.13784 (* 0.3 = 0.941352 loss) | |
| I0525 03:59:44.722749 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 0.928904 (* 0.3 = 0.278671 loss) | |
| I0525 03:59:44.722764 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 2.84019 (* 0.0272727 = 0.0774598 loss) | |
| I0525 03:59:44.722777 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.08727 (* 0.0272727 = 0.0841983 loss) | |
| I0525 03:59:44.722791 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.30686 (* 0.0272727 = 0.090187 loss) | |
| I0525 03:59:44.722805 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.55626 (* 0.0272727 = 0.0969888 loss) | |
| I0525 03:59:44.722820 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 2.7269 (* 0.0272727 = 0.0743701 loss) | |
| I0525 03:59:44.722833 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 2.59432 (* 0.0272727 = 0.0707541 loss) | |
| I0525 03:59:44.722847 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 1.77876 (* 0.0272727 = 0.0485115 loss) | |
| I0525 03:59:44.722862 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 1.4755 (* 0.0272727 = 0.0402408 loss) | |
| I0525 03:59:44.722878 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.0538676 (* 0.0272727 = 0.00146912 loss) | |
| I0525 03:59:44.722893 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.0453337 (* 0.0272727 = 0.00123637 loss) | |
| I0525 03:59:44.722908 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.0177974 (* 0.0272727 = 0.000485385 loss) | |
| I0525 03:59:44.722923 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.0158009 (* 0.0272727 = 0.000430934 loss) | |
| I0525 03:59:44.722936 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.017356 (* 0.0272727 = 0.000473346 loss) | |
| I0525 03:59:44.722970 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.00948369 (* 0.0272727 = 0.000258646 loss) | |
| I0525 03:59:44.722985 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.00633728 (* 0.0272727 = 0.000172835 loss) | |
| I0525 03:59:44.723000 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.00526755 (* 0.0272727 = 0.000143661 loss) | |
| I0525 03:59:44.723013 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.00478485 (* 0.0272727 = 0.000130496 loss) | |
| I0525 03:59:44.723027 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.00294798 (* 0.0272727 = 8.03995e-05 loss) | |
| I0525 03:59:44.723042 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.00626945 (* 0.0272727 = 0.000170985 loss) | |
| I0525 03:59:44.723055 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.00539131 (* 0.0272727 = 0.000147036 loss) | |
| I0525 03:59:44.723069 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.00288908 (* 0.0272727 = 7.87932e-05 loss) | |
| I0525 03:59:44.723084 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.0035027 (* 0.0272727 = 9.55282e-05 loss) | |
| I0525 03:59:44.723096 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.125 | |
| I0525 03:59:44.723109 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0.375 | |
| I0525 03:59:44.723121 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0.25 | |
| I0525 03:59:44.723132 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0.25 | |
| I0525 03:59:44.723145 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0 | |
| I0525 03:59:44.723156 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.375 | |
| I0525 03:59:44.723168 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.375 | |
| I0525 03:59:44.723179 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.625 | |
| I0525 03:59:44.723191 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.75 | |
| I0525 03:59:44.723204 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 1 | |
| I0525 03:59:44.723217 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 1 | |
| I0525 03:59:44.723227 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 03:59:44.723238 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 03:59:44.723250 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 03:59:44.723261 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 03:59:44.723273 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 03:59:44.723284 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 03:59:44.723296 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 03:59:44.723307 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 03:59:44.723320 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 03:59:44.723330 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 03:59:44.723342 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 03:59:44.723353 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 03:59:44.723366 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.755682 | |
| I0525 03:59:44.723376 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.270833 | |
| I0525 03:59:44.723390 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.2306 (* 0.3 = 0.969181 loss) | |
| I0525 03:59:44.723404 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 0.977939 (* 0.3 = 0.293382 loss) | |
| I0525 03:59:44.723418 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 2.78538 (* 0.0272727 = 0.0759649 loss) | |
| I0525 03:59:44.723436 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 2.98938 (* 0.0272727 = 0.0815286 loss) | |
| I0525 03:59:44.723461 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.18361 (* 0.0272727 = 0.0868258 loss) | |
| I0525 03:59:44.723476 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.62686 (* 0.0272727 = 0.0989143 loss) | |
| I0525 03:59:44.723490 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 2.38687 (* 0.0272727 = 0.0650964 loss) | |
| I0525 03:59:44.723505 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 2.56685 (* 0.0272727 = 0.0700051 loss) | |
| I0525 03:59:44.723518 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 1.99854 (* 0.0272727 = 0.0545057 loss) | |
| I0525 03:59:44.723531 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 1.4656 (* 0.0272727 = 0.0399708 loss) | |
| I0525 03:59:44.723546 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.027803 (* 0.0272727 = 0.000758264 loss) | |
| I0525 03:59:44.723559 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.0140055 (* 0.0272727 = 0.000381968 loss) | |
| I0525 03:59:44.723573 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.00899451 (* 0.0272727 = 0.000245305 loss) | |
| I0525 03:59:44.723587 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.00886107 (* 0.0272727 = 0.000241666 loss) | |
| I0525 03:59:44.723601 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.00504581 (* 0.0272727 = 0.000137613 loss) | |
| I0525 03:59:44.723615 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.00922408 (* 0.0272727 = 0.000251566 loss) | |
| I0525 03:59:44.723628 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.00454956 (* 0.0272727 = 0.000124079 loss) | |
| I0525 03:59:44.723642 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.00492972 (* 0.0272727 = 0.000134447 loss) | |
| I0525 03:59:44.723656 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.00588692 (* 0.0272727 = 0.000160552 loss) | |
| I0525 03:59:44.723670 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.00195813 (* 0.0272727 = 5.34037e-05 loss) | |
| I0525 03:59:44.723685 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.00321498 (* 0.0272727 = 8.76812e-05 loss) | |
| I0525 03:59:44.723698 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.00318902 (* 0.0272727 = 8.69732e-05 loss) | |
| I0525 03:59:44.723711 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.00318535 (* 0.0272727 = 8.68733e-05 loss) | |
| I0525 03:59:44.723726 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.00273894 (* 0.0272727 = 7.46983e-05 loss) | |
| I0525 03:59:44.723737 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.0833333 | |
| I0525 03:59:44.723749 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.25 | |
| I0525 03:59:44.723758 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0 | |
| I0525 03:59:44.723767 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0 | |
| I0525 03:59:44.723778 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.125 | |
| I0525 03:59:44.723790 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.625 | |
| I0525 03:59:44.723803 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.375 | |
| I0525 03:59:44.723814 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.625 | |
| I0525 03:59:44.723826 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.75 | |
| I0525 03:59:44.723839 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 1 | |
| I0525 03:59:44.723850 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 1 | |
| I0525 03:59:44.723861 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 03:59:44.723872 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 03:59:44.723884 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 03:59:44.723896 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 03:59:44.723907 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 03:59:44.723918 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 03:59:44.723943 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 03:59:44.723956 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 03:59:44.723968 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 03:59:44.723979 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 03:59:44.723991 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 03:59:44.724002 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 03:59:44.724015 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.744318 | |
| I0525 03:59:44.724026 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.270833 | |
| I0525 03:59:44.724041 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 2.91138 (* 1 = 2.91138 loss) | |
| I0525 03:59:44.724055 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 0.839294 (* 1 = 0.839294 loss) | |
| I0525 03:59:44.724068 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 2.41788 (* 0.0909091 = 0.219807 loss) | |
| I0525 03:59:44.724082 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 2.83776 (* 0.0909091 = 0.257979 loss) | |
| I0525 03:59:44.724097 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 2.8583 (* 0.0909091 = 0.259845 loss) | |
| I0525 03:59:44.724109 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.33131 (* 0.0909091 = 0.302846 loss) | |
| I0525 03:59:44.724123 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 2.12336 (* 0.0909091 = 0.193033 loss) | |
| I0525 03:59:44.724138 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 2.12498 (* 0.0909091 = 0.19318 loss) | |
| I0525 03:59:44.724151 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 1.77389 (* 0.0909091 = 0.161262 loss) | |
| I0525 03:59:44.724164 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 1.24847 (* 0.0909091 = 0.113497 loss) | |
| I0525 03:59:44.724179 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.0192627 (* 0.0909091 = 0.00175116 loss) | |
| I0525 03:59:44.724192 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.00625155 (* 0.0909091 = 0.000568323 loss) | |
| I0525 03:59:44.724206 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.00500311 (* 0.0909091 = 0.000454828 loss) | |
| I0525 03:59:44.724220 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.00277463 (* 0.0909091 = 0.000252239 loss) | |
| I0525 03:59:44.724233 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.00241169 (* 0.0909091 = 0.000219244 loss) | |
| I0525 03:59:44.724248 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.00187107 (* 0.0909091 = 0.000170098 loss) | |
| I0525 03:59:44.724262 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.00196994 (* 0.0909091 = 0.000179085 loss) | |
| I0525 03:59:44.724277 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.00126634 (* 0.0909091 = 0.000115121 loss) | |
| I0525 03:59:44.724289 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.00153558 (* 0.0909091 = 0.000139599 loss) | |
| I0525 03:59:44.724304 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.00130161 (* 0.0909091 = 0.000118329 loss) | |
| I0525 03:59:44.724318 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00119699 (* 0.0909091 = 0.000108817 loss) | |
| I0525 03:59:44.724331 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00118888 (* 0.0909091 = 0.00010808 loss) | |
| I0525 03:59:44.724345 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.000583546 (* 0.0909091 = 5.30496e-05 loss) | |
| I0525 03:59:44.724359 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.000492477 (* 0.0909091 = 4.47706e-05 loss) | |
| I0525 03:59:44.724372 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 03:59:44.724383 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 03:59:44.724395 5272 solver.cpp:245] Train net output #149: total_confidence = 4.80769e-05 | |
| I0525 03:59:44.724416 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 5.82044e-05 | |
| I0525 03:59:44.724431 5272 sgd_solver.cpp:106] Iteration 17500, lr = 0.001 | |
| I0525 04:00:55.935582 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 40.2513 > 30) by scale factor 0.745318 | |
| I0525 04:01:12.858304 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 37.2357 > 30) by scale factor 0.805678 | |
| I0525 04:04:26.093750 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 33.1223 > 30) by scale factor 0.905734 | |
| I0525 04:06:09.641572 5272 solver.cpp:229] Iteration 18000, loss = 9.86657 | |
| I0525 04:06:09.641696 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0638298 | |
| I0525 04:06:09.641717 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.125 | |
| I0525 04:06:09.641731 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0.125 | |
| I0525 04:06:09.641743 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0.125 | |
| I0525 04:06:09.641755 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.125 | |
| I0525 04:06:09.641768 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.25 | |
| I0525 04:06:09.641782 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.25 | |
| I0525 04:06:09.641793 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.75 | |
| I0525 04:06:09.641806 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.75 | |
| I0525 04:06:09.641819 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 1 | |
| I0525 04:06:09.641831 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 1 | |
| I0525 04:06:09.641844 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 04:06:09.641855 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 04:06:09.641867 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 04:06:09.641882 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 04:06:09.641894 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 04:06:09.641906 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 04:06:09.641918 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 04:06:09.641929 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 04:06:09.641942 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 04:06:09.641953 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 04:06:09.641964 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 04:06:09.641976 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 04:06:09.641988 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.744318 | |
| I0525 04:06:09.642000 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.234043 | |
| I0525 04:06:09.642016 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.34429 (* 0.3 = 1.00329 loss) | |
| I0525 04:06:09.642030 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.00033 (* 0.3 = 0.300099 loss) | |
| I0525 04:06:09.642045 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 2.94846 (* 0.0272727 = 0.0804126 loss) | |
| I0525 04:06:09.642060 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.66943 (* 0.0272727 = 0.100075 loss) | |
| I0525 04:06:09.642073 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.46056 (* 0.0272727 = 0.0943789 loss) | |
| I0525 04:06:09.642087 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.01885 (* 0.0272727 = 0.0823323 loss) | |
| I0525 04:06:09.642102 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 3.07219 (* 0.0272727 = 0.0837869 loss) | |
| I0525 04:06:09.642115 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 3.62537 (* 0.0272727 = 0.0988738 loss) | |
| I0525 04:06:09.642128 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 1.38733 (* 0.0272727 = 0.0378363 loss) | |
| I0525 04:06:09.642143 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 1.32023 (* 0.0272727 = 0.0360063 loss) | |
| I0525 04:06:09.642156 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.101036 (* 0.0272727 = 0.00275553 loss) | |
| I0525 04:06:09.642171 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.0615007 (* 0.0272727 = 0.00167729 loss) | |
| I0525 04:06:09.642185 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.0641018 (* 0.0272727 = 0.00174823 loss) | |
| I0525 04:06:09.642199 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.036175 (* 0.0272727 = 0.00098659 loss) | |
| I0525 04:06:09.642215 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.0259707 (* 0.0272727 = 0.000708291 loss) | |
| I0525 04:06:09.642246 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.026647 (* 0.0272727 = 0.000726735 loss) | |
| I0525 04:06:09.642261 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0186071 (* 0.0272727 = 0.000507467 loss) | |
| I0525 04:06:09.642277 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.00926692 (* 0.0272727 = 0.000252734 loss) | |
| I0525 04:06:09.642290 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.00917478 (* 0.0272727 = 0.000250221 loss) | |
| I0525 04:06:09.642304 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.00811545 (* 0.0272727 = 0.00022133 loss) | |
| I0525 04:06:09.642318 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.00526028 (* 0.0272727 = 0.000143462 loss) | |
| I0525 04:06:09.642331 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.00553701 (* 0.0272727 = 0.000151009 loss) | |
| I0525 04:06:09.642345 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.00336276 (* 0.0272727 = 9.17117e-05 loss) | |
| I0525 04:06:09.642359 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.00503558 (* 0.0272727 = 0.000137334 loss) | |
| I0525 04:06:09.642372 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.12766 | |
| I0525 04:06:09.642385 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0 | |
| I0525 04:06:09.642396 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0 | |
| I0525 04:06:09.642407 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0 | |
| I0525 04:06:09.642419 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0.25 | |
| I0525 04:06:09.642431 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.375 | |
| I0525 04:06:09.642442 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.25 | |
| I0525 04:06:09.642454 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.75 | |
| I0525 04:06:09.642467 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.75 | |
| I0525 04:06:09.642478 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 1 | |
| I0525 04:06:09.642489 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 1 | |
| I0525 04:06:09.642500 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 04:06:09.642511 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 04:06:09.642524 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 04:06:09.642534 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 04:06:09.642545 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 04:06:09.642557 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 04:06:09.642568 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 04:06:09.642580 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 04:06:09.642590 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 04:06:09.642601 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 04:06:09.642613 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 04:06:09.642624 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 04:06:09.642637 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.761364 | |
| I0525 04:06:09.642647 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.319149 | |
| I0525 04:06:09.642662 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.55852 (* 0.3 = 1.06756 loss) | |
| I0525 04:06:09.642674 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.05997 (* 0.3 = 0.317992 loss) | |
| I0525 04:06:09.642688 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.43709 (* 0.0272727 = 0.0937389 loss) | |
| I0525 04:06:09.642702 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 4.03267 (* 0.0272727 = 0.109982 loss) | |
| I0525 04:06:09.642730 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.67203 (* 0.0272727 = 0.100146 loss) | |
| I0525 04:06:09.642745 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.11115 (* 0.0272727 = 0.0848497 loss) | |
| I0525 04:06:09.642760 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 3.353 (* 0.0272727 = 0.0914455 loss) | |
| I0525 04:06:09.642773 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 4.04124 (* 0.0272727 = 0.110216 loss) | |
| I0525 04:06:09.642786 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 1.41236 (* 0.0272727 = 0.0385188 loss) | |
| I0525 04:06:09.642801 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 1.33945 (* 0.0272727 = 0.0365306 loss) | |
| I0525 04:06:09.642812 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.076946 (* 0.0272727 = 0.00209853 loss) | |
| I0525 04:06:09.642825 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.0345699 (* 0.0272727 = 0.000942816 loss) | |
| I0525 04:06:09.642839 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.0216829 (* 0.0272727 = 0.000591352 loss) | |
| I0525 04:06:09.642854 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.0400009 (* 0.0272727 = 0.00109093 loss) | |
| I0525 04:06:09.642868 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.0256295 (* 0.0272727 = 0.000698986 loss) | |
| I0525 04:06:09.642882 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.0245151 (* 0.0272727 = 0.000668594 loss) | |
| I0525 04:06:09.642895 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.0146602 (* 0.0272727 = 0.000399823 loss) | |
| I0525 04:06:09.642910 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.00956319 (* 0.0272727 = 0.000260814 loss) | |
| I0525 04:06:09.642923 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.00697215 (* 0.0272727 = 0.00019015 loss) | |
| I0525 04:06:09.642940 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.00945512 (* 0.0272727 = 0.000257867 loss) | |
| I0525 04:06:09.642954 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.0048763 (* 0.0272727 = 0.00013299 loss) | |
| I0525 04:06:09.642968 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.00932681 (* 0.0272727 = 0.000254368 loss) | |
| I0525 04:06:09.642982 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.00343135 (* 0.0272727 = 9.35822e-05 loss) | |
| I0525 04:06:09.642995 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.00630837 (* 0.0272727 = 0.000172047 loss) | |
| I0525 04:06:09.643007 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.0851064 | |
| I0525 04:06:09.643019 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.25 | |
| I0525 04:06:09.643031 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0 | |
| I0525 04:06:09.643043 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0 | |
| I0525 04:06:09.643054 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.375 | |
| I0525 04:06:09.643065 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.25 | |
| I0525 04:06:09.643077 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.25 | |
| I0525 04:06:09.643090 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.75 | |
| I0525 04:06:09.643100 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.75 | |
| I0525 04:06:09.643112 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 1 | |
| I0525 04:06:09.643123 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 1 | |
| I0525 04:06:09.643134 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 04:06:09.643146 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 04:06:09.643157 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 04:06:09.643168 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 04:06:09.643179 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 04:06:09.643190 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 04:06:09.643213 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 04:06:09.643224 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 04:06:09.643236 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 04:06:09.643247 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 04:06:09.643259 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 04:06:09.643270 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 04:06:09.643281 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.75 | |
| I0525 04:06:09.643293 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.212766 | |
| I0525 04:06:09.643306 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.62987 (* 1 = 3.62987 loss) | |
| I0525 04:06:09.643321 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.08267 (* 1 = 1.08267 loss) | |
| I0525 04:06:09.643334 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 3.01471 (* 0.0909091 = 0.274065 loss) | |
| I0525 04:06:09.643347 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 4.37728 (* 0.0909091 = 0.397935 loss) | |
| I0525 04:06:09.643362 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.62819 (* 0.0909091 = 0.329836 loss) | |
| I0525 04:06:09.643375 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 2.91936 (* 0.0909091 = 0.265396 loss) | |
| I0525 04:06:09.643388 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 3.55817 (* 0.0909091 = 0.32347 loss) | |
| I0525 04:06:09.643402 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 3.52315 (* 0.0909091 = 0.320287 loss) | |
| I0525 04:06:09.643415 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 1.21667 (* 0.0909091 = 0.110607 loss) | |
| I0525 04:06:09.643429 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 1.02342 (* 0.0909091 = 0.0930385 loss) | |
| I0525 04:06:09.643443 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.0809822 (* 0.0909091 = 0.00736202 loss) | |
| I0525 04:06:09.643457 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.0541274 (* 0.0909091 = 0.00492067 loss) | |
| I0525 04:06:09.643471 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.0311399 (* 0.0909091 = 0.0028309 loss) | |
| I0525 04:06:09.643486 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.0116313 (* 0.0909091 = 0.00105739 loss) | |
| I0525 04:06:09.643499 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.0157709 (* 0.0909091 = 0.00143371 loss) | |
| I0525 04:06:09.643513 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.00845612 (* 0.0909091 = 0.000768738 loss) | |
| I0525 04:06:09.643528 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.00931627 (* 0.0909091 = 0.000846933 loss) | |
| I0525 04:06:09.643543 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.00612826 (* 0.0909091 = 0.000557114 loss) | |
| I0525 04:06:09.643556 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.00472019 (* 0.0909091 = 0.000429108 loss) | |
| I0525 04:06:09.643569 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.00234181 (* 0.0909091 = 0.000212892 loss) | |
| I0525 04:06:09.643584 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00185075 (* 0.0909091 = 0.00016825 loss) | |
| I0525 04:06:09.643597 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00208436 (* 0.0909091 = 0.000189487 loss) | |
| I0525 04:06:09.643610 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.000702511 (* 0.0909091 = 6.38647e-05 loss) | |
| I0525 04:06:09.643625 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.000892533 (* 0.0909091 = 8.11394e-05 loss) | |
| I0525 04:06:09.643636 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 04:06:09.643647 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 04:06:09.643658 5272 solver.cpp:245] Train net output #149: total_confidence = 0.000318692 | |
| I0525 04:06:09.643679 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 0.00203058 | |
| I0525 04:06:09.643693 5272 sgd_solver.cpp:106] Iteration 18000, lr = 0.001 | |
| I0525 04:06:53.103301 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 30.3493 > 30) by scale factor 0.98849 | |
| I0525 04:12:34.594841 5272 solver.cpp:229] Iteration 18500, loss = 9.77522 | |
| I0525 04:12:34.594987 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.08 | |
| I0525 04:12:34.595008 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.125 | |
| I0525 04:12:34.595021 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0525 04:12:34.595034 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0.125 | |
| I0525 04:12:34.595049 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.125 | |
| I0525 04:12:34.595062 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.375 | |
| I0525 04:12:34.595074 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.625 | |
| I0525 04:12:34.595088 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.625 | |
| I0525 04:12:34.595099 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.75 | |
| I0525 04:12:34.595113 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 0.75 | |
| I0525 04:12:34.595124 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 0.875 | |
| I0525 04:12:34.595137 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 0.875 | |
| I0525 04:12:34.595151 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 04:12:34.595163 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 04:12:34.595175 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 04:12:34.595186 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 04:12:34.595198 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 04:12:34.595211 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 04:12:34.595222 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 04:12:34.595234 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 04:12:34.595247 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 04:12:34.595257 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 04:12:34.595269 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 04:12:34.595281 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.732955 | |
| I0525 04:12:34.595293 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.34 | |
| I0525 04:12:34.595309 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.16741 (* 0.3 = 0.950222 loss) | |
| I0525 04:12:34.595324 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.02969 (* 0.3 = 0.308907 loss) | |
| I0525 04:12:34.595338 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.03737 (* 0.0272727 = 0.0828374 loss) | |
| I0525 04:12:34.595352 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.51136 (* 0.0272727 = 0.0957642 loss) | |
| I0525 04:12:34.595366 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.32134 (* 0.0272727 = 0.0905819 loss) | |
| I0525 04:12:34.595381 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.22547 (* 0.0272727 = 0.0879675 loss) | |
| I0525 04:12:34.595394 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 2.3253 (* 0.0272727 = 0.0634173 loss) | |
| I0525 04:12:34.595408 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 1.83675 (* 0.0272727 = 0.0500933 loss) | |
| I0525 04:12:34.595422 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 1.86559 (* 0.0272727 = 0.0508797 loss) | |
| I0525 04:12:34.595437 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 1.16717 (* 0.0272727 = 0.0318318 loss) | |
| I0525 04:12:34.595450 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 1.04078 (* 0.0272727 = 0.0283849 loss) | |
| I0525 04:12:34.595465 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.530819 (* 0.0272727 = 0.0144769 loss) | |
| I0525 04:12:34.595479 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.525478 (* 0.0272727 = 0.0143312 loss) | |
| I0525 04:12:34.595494 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.158687 (* 0.0272727 = 0.00432782 loss) | |
| I0525 04:12:34.595509 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.0694457 (* 0.0272727 = 0.00189397 loss) | |
| I0525 04:12:34.595543 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.0769427 (* 0.0272727 = 0.00209844 loss) | |
| I0525 04:12:34.595559 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0511271 (* 0.0272727 = 0.00139438 loss) | |
| I0525 04:12:34.595574 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.0280499 (* 0.0272727 = 0.000764996 loss) | |
| I0525 04:12:34.595588 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.0122903 (* 0.0272727 = 0.000335189 loss) | |
| I0525 04:12:34.595602 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0102983 (* 0.0272727 = 0.000280864 loss) | |
| I0525 04:12:34.595616 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.00747338 (* 0.0272727 = 0.000203819 loss) | |
| I0525 04:12:34.595630 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.00775103 (* 0.0272727 = 0.000211392 loss) | |
| I0525 04:12:34.595643 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.00526831 (* 0.0272727 = 0.000143681 loss) | |
| I0525 04:12:34.595657 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.0128368 (* 0.0272727 = 0.000350095 loss) | |
| I0525 04:12:34.595670 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.18 | |
| I0525 04:12:34.595682 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0.25 | |
| I0525 04:12:34.595695 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0 | |
| I0525 04:12:34.595706 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0 | |
| I0525 04:12:34.595718 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0.375 | |
| I0525 04:12:34.595731 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.375 | |
| I0525 04:12:34.595742 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.5 | |
| I0525 04:12:34.595754 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.625 | |
| I0525 04:12:34.595767 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.75 | |
| I0525 04:12:34.595778 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 0.75 | |
| I0525 04:12:34.595790 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 0.875 | |
| I0525 04:12:34.595803 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 0.875 | |
| I0525 04:12:34.595813 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 04:12:34.595825 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 04:12:34.595837 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 04:12:34.595849 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 04:12:34.595860 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 04:12:34.595872 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 04:12:34.595887 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 04:12:34.595899 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 04:12:34.595911 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 04:12:34.595923 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 04:12:34.595935 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 04:12:34.595947 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.75 | |
| I0525 04:12:34.595958 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.28 | |
| I0525 04:12:34.595973 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.03086 (* 0.3 = 0.909258 loss) | |
| I0525 04:12:34.595986 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.03762 (* 0.3 = 0.311286 loss) | |
| I0525 04:12:34.596006 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.02777 (* 0.0272727 = 0.0825757 loss) | |
| I0525 04:12:34.596034 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 3.12939 (* 0.0272727 = 0.0853469 loss) | |
| I0525 04:12:34.596067 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.26086 (* 0.0272727 = 0.0889324 loss) | |
| I0525 04:12:34.596083 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.37048 (* 0.0272727 = 0.0919223 loss) | |
| I0525 04:12:34.596098 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 2.03878 (* 0.0272727 = 0.055603 loss) | |
| I0525 04:12:34.596112 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 1.70372 (* 0.0272727 = 0.046465 loss) | |
| I0525 04:12:34.596125 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 1.70922 (* 0.0272727 = 0.0466152 loss) | |
| I0525 04:12:34.596139 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 1.17508 (* 0.0272727 = 0.0320476 loss) | |
| I0525 04:12:34.596153 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.909057 (* 0.0272727 = 0.0247925 loss) | |
| I0525 04:12:34.596168 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.611669 (* 0.0272727 = 0.0166819 loss) | |
| I0525 04:12:34.596180 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.603757 (* 0.0272727 = 0.0164661 loss) | |
| I0525 04:12:34.596195 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.208195 (* 0.0272727 = 0.00567804 loss) | |
| I0525 04:12:34.596210 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.181189 (* 0.0272727 = 0.00494151 loss) | |
| I0525 04:12:34.596223 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.149976 (* 0.0272727 = 0.00409025 loss) | |
| I0525 04:12:34.596236 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.0940518 (* 0.0272727 = 0.00256505 loss) | |
| I0525 04:12:34.596251 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.0471108 (* 0.0272727 = 0.00128484 loss) | |
| I0525 04:12:34.596264 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.0277911 (* 0.0272727 = 0.000757939 loss) | |
| I0525 04:12:34.596278 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.0206049 (* 0.0272727 = 0.000561952 loss) | |
| I0525 04:12:34.596292 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.028789 (* 0.0272727 = 0.000785153 loss) | |
| I0525 04:12:34.596307 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.0108661 (* 0.0272727 = 0.000296348 loss) | |
| I0525 04:12:34.596319 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.0216374 (* 0.0272727 = 0.000590111 loss) | |
| I0525 04:12:34.596333 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.0180423 (* 0.0272727 = 0.000492064 loss) | |
| I0525 04:12:34.596346 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.14 | |
| I0525 04:12:34.596359 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.375 | |
| I0525 04:12:34.596370 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0 | |
| I0525 04:12:34.596382 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0.125 | |
| I0525 04:12:34.596395 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.125 | |
| I0525 04:12:34.596406 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.5 | |
| I0525 04:12:34.596418 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.5 | |
| I0525 04:12:34.596431 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.625 | |
| I0525 04:12:34.596442 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.875 | |
| I0525 04:12:34.596453 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 0.75 | |
| I0525 04:12:34.596465 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 0.875 | |
| I0525 04:12:34.596477 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 0.875 | |
| I0525 04:12:34.596489 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 04:12:34.596501 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 04:12:34.596513 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 04:12:34.596524 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 04:12:34.596535 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 04:12:34.596556 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 04:12:34.596570 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 04:12:34.596580 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 04:12:34.596592 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 04:12:34.596604 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 04:12:34.596616 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 04:12:34.596627 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.732955 | |
| I0525 04:12:34.596639 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.34 | |
| I0525 04:12:34.596662 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.0144 (* 1 = 3.0144 loss) | |
| I0525 04:12:34.596690 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.03708 (* 1 = 1.03708 loss) | |
| I0525 04:12:34.596709 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 2.70461 (* 0.0909091 = 0.245874 loss) | |
| I0525 04:12:34.596719 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.05563 (* 0.0909091 = 0.277785 loss) | |
| I0525 04:12:34.596729 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.28489 (* 0.0909091 = 0.298627 loss) | |
| I0525 04:12:34.596743 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 2.98885 (* 0.0909091 = 0.271714 loss) | |
| I0525 04:12:34.596757 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 1.91774 (* 0.0909091 = 0.17434 loss) | |
| I0525 04:12:34.596771 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 1.77225 (* 0.0909091 = 0.161113 loss) | |
| I0525 04:12:34.596784 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 1.43922 (* 0.0909091 = 0.130838 loss) | |
| I0525 04:12:34.596798 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.94987 (* 0.0909091 = 0.0863518 loss) | |
| I0525 04:12:34.596812 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.91769 (* 0.0909091 = 0.0834264 loss) | |
| I0525 04:12:34.596825 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.490146 (* 0.0909091 = 0.0445587 loss) | |
| I0525 04:12:34.596839 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.484407 (* 0.0909091 = 0.044037 loss) | |
| I0525 04:12:34.596853 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.128122 (* 0.0909091 = 0.0116474 loss) | |
| I0525 04:12:34.596868 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.0959597 (* 0.0909091 = 0.00872361 loss) | |
| I0525 04:12:34.596881 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.0480195 (* 0.0909091 = 0.00436541 loss) | |
| I0525 04:12:34.596895 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.0211426 (* 0.0909091 = 0.00192205 loss) | |
| I0525 04:12:34.596909 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.0135416 (* 0.0909091 = 0.00123106 loss) | |
| I0525 04:12:34.596923 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.013089 (* 0.0909091 = 0.00118991 loss) | |
| I0525 04:12:34.596941 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.00712528 (* 0.0909091 = 0.000647753 loss) | |
| I0525 04:12:34.596956 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00629259 (* 0.0909091 = 0.000572054 loss) | |
| I0525 04:12:34.596969 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00380776 (* 0.0909091 = 0.00034616 loss) | |
| I0525 04:12:34.596982 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00170268 (* 0.0909091 = 0.000154789 loss) | |
| I0525 04:12:34.596997 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.00138994 (* 0.0909091 = 0.000126358 loss) | |
| I0525 04:12:34.597008 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 04:12:34.597019 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 04:12:34.597031 5272 solver.cpp:245] Train net output #149: total_confidence = 5.47178e-05 | |
| I0525 04:12:34.597057 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 0.00158301 | |
| I0525 04:12:34.597072 5272 sgd_solver.cpp:106] Iteration 18500, lr = 0.001 | |
| I0525 04:16:39.772830 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 30.709 > 30) by scale factor 0.976911 | |
| I0525 04:16:55.974751 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 31.0794 > 30) by scale factor 0.96527 | |
| I0525 04:18:59.588925 5272 solver.cpp:229] Iteration 19000, loss = 9.86371 | |
| I0525 04:18:59.589085 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0882353 | |
| I0525 04:18:59.589108 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0 | |
| I0525 04:18:59.589121 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0525 04:18:59.589134 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0525 04:18:59.589146 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0 | |
| I0525 04:18:59.589159 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.125 | |
| I0525 04:18:59.589171 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.125 | |
| I0525 04:18:59.589184 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.5 | |
| I0525 04:18:59.589195 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.625 | |
| I0525 04:18:59.589223 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 0.625 | |
| I0525 04:18:59.589236 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 0.625 | |
| I0525 04:18:59.589249 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 0.875 | |
| I0525 04:18:59.589262 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 0.875 | |
| I0525 04:18:59.589274 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 0.875 | |
| I0525 04:18:59.589287 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 0.875 | |
| I0525 04:18:59.589299 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 0.875 | |
| I0525 04:18:59.589311 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 0.875 | |
| I0525 04:18:59.589323 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 04:18:59.589335 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 04:18:59.589347 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 04:18:59.589359 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 04:18:59.589371 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 04:18:59.589382 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 04:18:59.589395 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.642045 | |
| I0525 04:18:59.589406 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.25 | |
| I0525 04:18:59.589423 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.26631 (* 0.3 = 0.979893 loss) | |
| I0525 04:18:59.589437 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.43865 (* 0.3 = 0.431595 loss) | |
| I0525 04:18:59.589452 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.19737 (* 0.0272727 = 0.087201 loss) | |
| I0525 04:18:59.589467 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.39988 (* 0.0272727 = 0.0927241 loss) | |
| I0525 04:18:59.589480 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.79299 (* 0.0272727 = 0.103445 loss) | |
| I0525 04:18:59.589494 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.91754 (* 0.0272727 = 0.106842 loss) | |
| I0525 04:18:59.589509 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 3.15509 (* 0.0272727 = 0.0860479 loss) | |
| I0525 04:18:59.589522 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 4.21535 (* 0.0272727 = 0.114964 loss) | |
| I0525 04:18:59.589536 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 2.62505 (* 0.0272727 = 0.0715922 loss) | |
| I0525 04:18:59.589550 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 1.62388 (* 0.0272727 = 0.0442875 loss) | |
| I0525 04:18:59.589565 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 1.40825 (* 0.0272727 = 0.0384069 loss) | |
| I0525 04:18:59.589579 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 1.38675 (* 0.0272727 = 0.0378204 loss) | |
| I0525 04:18:59.589593 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.643883 (* 0.0272727 = 0.0175605 loss) | |
| I0525 04:18:59.589607 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.922386 (* 0.0272727 = 0.025156 loss) | |
| I0525 04:18:59.589622 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.480812 (* 0.0272727 = 0.0131131 loss) | |
| I0525 04:18:59.589658 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.696563 (* 0.0272727 = 0.0189972 loss) | |
| I0525 04:18:59.589674 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.748137 (* 0.0272727 = 0.0204037 loss) | |
| I0525 04:18:59.589689 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.834522 (* 0.0272727 = 0.0227597 loss) | |
| I0525 04:18:59.589704 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.031992 (* 0.0272727 = 0.000872508 loss) | |
| I0525 04:18:59.589717 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0180784 (* 0.0272727 = 0.000493046 loss) | |
| I0525 04:18:59.589732 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.0155258 (* 0.0272727 = 0.00042343 loss) | |
| I0525 04:18:59.589746 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.0126712 (* 0.0272727 = 0.000345578 loss) | |
| I0525 04:18:59.589761 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.0125072 (* 0.0272727 = 0.000341105 loss) | |
| I0525 04:18:59.589774 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.0190095 (* 0.0272727 = 0.000518441 loss) | |
| I0525 04:18:59.589787 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.0441176 | |
| I0525 04:18:59.589799 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0.125 | |
| I0525 04:18:59.589812 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0.125 | |
| I0525 04:18:59.589824 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0.125 | |
| I0525 04:18:59.589836 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0 | |
| I0525 04:18:59.589848 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.125 | |
| I0525 04:18:59.589859 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.25 | |
| I0525 04:18:59.589871 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.5 | |
| I0525 04:18:59.589886 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.625 | |
| I0525 04:18:59.589898 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 0.625 | |
| I0525 04:18:59.589911 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 0.625 | |
| I0525 04:18:59.589922 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 0.875 | |
| I0525 04:18:59.589934 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 0.875 | |
| I0525 04:18:59.589946 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 0.875 | |
| I0525 04:18:59.589958 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 0.875 | |
| I0525 04:18:59.589970 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 0.875 | |
| I0525 04:18:59.589982 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 0.875 | |
| I0525 04:18:59.589994 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 04:18:59.590006 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 04:18:59.590018 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 04:18:59.590029 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 04:18:59.590040 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 04:18:59.590052 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 04:18:59.590064 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.630682 | |
| I0525 04:18:59.590075 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.25 | |
| I0525 04:18:59.590092 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.22183 (* 0.3 = 0.966549 loss) | |
| I0525 04:18:59.590107 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.35254 (* 0.3 = 0.405762 loss) | |
| I0525 04:18:59.590121 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.11079 (* 0.0272727 = 0.0848398 loss) | |
| I0525 04:18:59.590136 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 3.2504 (* 0.0272727 = 0.0886473 loss) | |
| I0525 04:18:59.590159 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.51762 (* 0.0272727 = 0.095935 loss) | |
| I0525 04:18:59.590174 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.60495 (* 0.0272727 = 0.0983167 loss) | |
| I0525 04:18:59.590188 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 3.54035 (* 0.0272727 = 0.096555 loss) | |
| I0525 04:18:59.590203 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 3.58681 (* 0.0272727 = 0.0978221 loss) | |
| I0525 04:18:59.590215 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 2.61884 (* 0.0272727 = 0.0714229 loss) | |
| I0525 04:18:59.590229 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 1.66121 (* 0.0272727 = 0.0453056 loss) | |
| I0525 04:18:59.590243 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 1.31875 (* 0.0272727 = 0.0359659 loss) | |
| I0525 04:18:59.590257 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 1.51599 (* 0.0272727 = 0.0413452 loss) | |
| I0525 04:18:59.590270 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.628763 (* 0.0272727 = 0.0171481 loss) | |
| I0525 04:18:59.590284 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.654404 (* 0.0272727 = 0.0178474 loss) | |
| I0525 04:18:59.590298 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.492787 (* 0.0272727 = 0.0134397 loss) | |
| I0525 04:18:59.590312 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.786999 (* 0.0272727 = 0.0214636 loss) | |
| I0525 04:18:59.590327 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.656859 (* 0.0272727 = 0.0179143 loss) | |
| I0525 04:18:59.590340 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.776949 (* 0.0272727 = 0.0211895 loss) | |
| I0525 04:18:59.590354 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.0135091 (* 0.0272727 = 0.000368431 loss) | |
| I0525 04:18:59.590368 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.0080268 (* 0.0272727 = 0.000218913 loss) | |
| I0525 04:18:59.590383 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.00940633 (* 0.0272727 = 0.000256536 loss) | |
| I0525 04:18:59.590396 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.00729824 (* 0.0272727 = 0.000199043 loss) | |
| I0525 04:18:59.590410 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.00494928 (* 0.0272727 = 0.00013498 loss) | |
| I0525 04:18:59.590425 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.00607485 (* 0.0272727 = 0.000165678 loss) | |
| I0525 04:18:59.590436 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.117647 | |
| I0525 04:18:59.590448 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.25 | |
| I0525 04:18:59.590463 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0.125 | |
| I0525 04:18:59.590476 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0 | |
| I0525 04:18:59.590487 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0 | |
| I0525 04:18:59.590498 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.125 | |
| I0525 04:18:59.590510 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.125 | |
| I0525 04:18:59.590523 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.375 | |
| I0525 04:18:59.590534 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.625 | |
| I0525 04:18:59.590546 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 0.625 | |
| I0525 04:18:59.590558 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 0.625 | |
| I0525 04:18:59.590569 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 04:18:59.590581 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 0.875 | |
| I0525 04:18:59.590593 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 0.875 | |
| I0525 04:18:59.590605 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 0.875 | |
| I0525 04:18:59.590616 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 0.875 | |
| I0525 04:18:59.590628 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 0.875 | |
| I0525 04:18:59.590651 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 04:18:59.590663 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 04:18:59.590674 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 04:18:59.590687 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 04:18:59.590698 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 04:18:59.590710 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 04:18:59.590721 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.659091 | |
| I0525 04:18:59.590734 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.264706 | |
| I0525 04:18:59.590747 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.17467 (* 1 = 3.17467 loss) | |
| I0525 04:18:59.590761 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.3034 (* 1 = 1.3034 loss) | |
| I0525 04:18:59.590775 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 2.85527 (* 0.0909091 = 0.25957 loss) | |
| I0525 04:18:59.590790 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 2.7749 (* 0.0909091 = 0.252264 loss) | |
| I0525 04:18:59.590802 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.25527 (* 0.0909091 = 0.295934 loss) | |
| I0525 04:18:59.590816 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.24903 (* 0.0909091 = 0.295366 loss) | |
| I0525 04:18:59.590831 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 3.29476 (* 0.0909091 = 0.299524 loss) | |
| I0525 04:18:59.590844 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 3.48059 (* 0.0909091 = 0.316417 loss) | |
| I0525 04:18:59.590857 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 2.6687 (* 0.0909091 = 0.242609 loss) | |
| I0525 04:18:59.590872 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 1.58777 (* 0.0909091 = 0.144343 loss) | |
| I0525 04:18:59.590885 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 1.27067 (* 0.0909091 = 0.115516 loss) | |
| I0525 04:18:59.590899 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 1.29685 (* 0.0909091 = 0.117895 loss) | |
| I0525 04:18:59.590912 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.493306 (* 0.0909091 = 0.044846 loss) | |
| I0525 04:18:59.590929 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.550736 (* 0.0909091 = 0.0500669 loss) | |
| I0525 04:18:59.590944 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.403936 (* 0.0909091 = 0.0367215 loss) | |
| I0525 04:18:59.590957 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.686864 (* 0.0909091 = 0.0624422 loss) | |
| I0525 04:18:59.590971 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.638432 (* 0.0909091 = 0.0580392 loss) | |
| I0525 04:18:59.590984 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.57413 (* 0.0909091 = 0.0521936 loss) | |
| I0525 04:18:59.590999 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.0270174 (* 0.0909091 = 0.00245612 loss) | |
| I0525 04:18:59.591012 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.0192084 (* 0.0909091 = 0.00174621 loss) | |
| I0525 04:18:59.591027 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.0116814 (* 0.0909091 = 0.00106195 loss) | |
| I0525 04:18:59.591040 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00527394 (* 0.0909091 = 0.000479449 loss) | |
| I0525 04:18:59.591054 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00356909 (* 0.0909091 = 0.000324463 loss) | |
| I0525 04:18:59.591068 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.00289446 (* 0.0909091 = 0.000263133 loss) | |
| I0525 04:18:59.591080 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 04:18:59.591092 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 04:18:59.591104 5272 solver.cpp:245] Train net output #149: total_confidence = 2.56861e-07 | |
| I0525 04:18:59.591125 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 1.77086e-06 | |
| I0525 04:18:59.591140 5272 sgd_solver.cpp:106] Iteration 19000, lr = 0.001 | |
| I0525 04:22:20.113984 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 45.9868 > 30) by scale factor 0.652361 | |
| I0525 04:23:02.446341 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 33.603 > 30) by scale factor 0.892777 | |
| I0525 04:24:05.590708 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 32.2828 > 30) by scale factor 0.929286 | |
| I0525 04:24:45.609282 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 30.6862 > 30) by scale factor 0.977639 | |
| I0525 04:25:24.513455 5272 solver.cpp:229] Iteration 19500, loss = 9.75068 | |
| I0525 04:25:24.513592 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0816327 | |
| I0525 04:25:24.513613 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0 | |
| I0525 04:25:24.513628 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0.25 | |
| I0525 04:25:24.513640 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0.125 | |
| I0525 04:25:24.513653 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.125 | |
| I0525 04:25:24.513666 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.125 | |
| I0525 04:25:24.513679 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.25 | |
| I0525 04:25:24.513691 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.625 | |
| I0525 04:25:24.513705 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.75 | |
| I0525 04:25:24.513717 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 1 | |
| I0525 04:25:24.513731 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 1 | |
| I0525 04:25:24.513742 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 04:25:24.513754 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 04:25:24.513767 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 04:25:24.513778 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 04:25:24.513790 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 04:25:24.513803 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 04:25:24.513814 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 04:25:24.513825 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 04:25:24.513839 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 04:25:24.513850 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 04:25:24.513862 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 04:25:24.513877 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 04:25:24.513890 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.738636 | |
| I0525 04:25:24.513902 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.22449 | |
| I0525 04:25:24.513918 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.22795 (* 0.3 = 0.968385 loss) | |
| I0525 04:25:24.513933 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 0.942298 (* 0.3 = 0.282689 loss) | |
| I0525 04:25:24.513948 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.39759 (* 0.0272727 = 0.0926616 loss) | |
| I0525 04:25:24.513962 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.30668 (* 0.0272727 = 0.0901821 loss) | |
| I0525 04:25:24.513977 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.23659 (* 0.0272727 = 0.0882707 loss) | |
| I0525 04:25:24.513990 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.23016 (* 0.0272727 = 0.0880954 loss) | |
| I0525 04:25:24.514004 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 3.29154 (* 0.0272727 = 0.0897692 loss) | |
| I0525 04:25:24.514019 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 3.50149 (* 0.0272727 = 0.0954953 loss) | |
| I0525 04:25:24.514032 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 1.29876 (* 0.0272727 = 0.0354207 loss) | |
| I0525 04:25:24.514046 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 0.896999 (* 0.0272727 = 0.0244636 loss) | |
| I0525 04:25:24.514061 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.197984 (* 0.0272727 = 0.00539957 loss) | |
| I0525 04:25:24.514075 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.116555 (* 0.0272727 = 0.00317878 loss) | |
| I0525 04:25:24.514089 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.0498358 (* 0.0272727 = 0.00135916 loss) | |
| I0525 04:25:24.514104 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.0660184 (* 0.0272727 = 0.0018005 loss) | |
| I0525 04:25:24.514118 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.05327 (* 0.0272727 = 0.00145282 loss) | |
| I0525 04:25:24.514153 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.0359881 (* 0.0272727 = 0.000981494 loss) | |
| I0525 04:25:24.514168 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0251916 (* 0.0272727 = 0.000687044 loss) | |
| I0525 04:25:24.514183 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.031323 (* 0.0272727 = 0.000854265 loss) | |
| I0525 04:25:24.514196 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.0154739 (* 0.0272727 = 0.000422016 loss) | |
| I0525 04:25:24.514210 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0133223 (* 0.0272727 = 0.000363335 loss) | |
| I0525 04:25:24.514225 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.0105633 (* 0.0272727 = 0.000288091 loss) | |
| I0525 04:25:24.514238 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.0106521 (* 0.0272727 = 0.000290512 loss) | |
| I0525 04:25:24.514252 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.0191888 (* 0.0272727 = 0.000523332 loss) | |
| I0525 04:25:24.514266 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.00957829 (* 0.0272727 = 0.000261226 loss) | |
| I0525 04:25:24.514279 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.0408163 | |
| I0525 04:25:24.514292 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0 | |
| I0525 04:25:24.514303 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0 | |
| I0525 04:25:24.514315 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0.375 | |
| I0525 04:25:24.514328 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0 | |
| I0525 04:25:24.514338 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.25 | |
| I0525 04:25:24.514350 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.25 | |
| I0525 04:25:24.514363 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.625 | |
| I0525 04:25:24.514374 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.75 | |
| I0525 04:25:24.514386 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 1 | |
| I0525 04:25:24.514397 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 1 | |
| I0525 04:25:24.514408 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 04:25:24.514420 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 04:25:24.514431 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 04:25:24.514444 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 04:25:24.514456 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 04:25:24.514467 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 04:25:24.514478 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 04:25:24.514489 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 04:25:24.514502 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 04:25:24.514513 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 04:25:24.514525 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 04:25:24.514536 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 04:25:24.514549 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.727273 | |
| I0525 04:25:24.514560 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.22449 | |
| I0525 04:25:24.514575 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.06843 (* 0.3 = 0.92053 loss) | |
| I0525 04:25:24.514588 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 0.9118 (* 0.3 = 0.27354 loss) | |
| I0525 04:25:24.514605 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 2.7041 (* 0.0272727 = 0.0737483 loss) | |
| I0525 04:25:24.514619 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 2.80397 (* 0.0272727 = 0.0764719 loss) | |
| I0525 04:25:24.514643 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 2.85946 (* 0.0272727 = 0.0779854 loss) | |
| I0525 04:25:24.514658 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.27302 (* 0.0272727 = 0.0892643 loss) | |
| I0525 04:25:24.514672 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 3.38045 (* 0.0272727 = 0.0921942 loss) | |
| I0525 04:25:24.514686 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 3.34108 (* 0.0272727 = 0.0911203 loss) | |
| I0525 04:25:24.514700 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 1.46775 (* 0.0272727 = 0.0400297 loss) | |
| I0525 04:25:24.514714 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 1.05023 (* 0.0272727 = 0.0286426 loss) | |
| I0525 04:25:24.514729 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.114665 (* 0.0272727 = 0.00312723 loss) | |
| I0525 04:25:24.514742 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.0252047 (* 0.0272727 = 0.0006874 loss) | |
| I0525 04:25:24.514756 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.0176146 (* 0.0272727 = 0.000480398 loss) | |
| I0525 04:25:24.514770 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.0153371 (* 0.0272727 = 0.000418285 loss) | |
| I0525 04:25:24.514785 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.00847213 (* 0.0272727 = 0.000231058 loss) | |
| I0525 04:25:24.514798 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.0047955 (* 0.0272727 = 0.000130786 loss) | |
| I0525 04:25:24.514812 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.00719247 (* 0.0272727 = 0.000196158 loss) | |
| I0525 04:25:24.514827 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.0040245 (* 0.0272727 = 0.000109759 loss) | |
| I0525 04:25:24.514840 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.00195702 (* 0.0272727 = 5.33734e-05 loss) | |
| I0525 04:25:24.514854 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.00115778 (* 0.0272727 = 3.15758e-05 loss) | |
| I0525 04:25:24.514868 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.0013391 (* 0.0272727 = 3.65209e-05 loss) | |
| I0525 04:25:24.514883 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.000751598 (* 0.0272727 = 2.04981e-05 loss) | |
| I0525 04:25:24.514896 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.000620915 (* 0.0272727 = 1.6934e-05 loss) | |
| I0525 04:25:24.514910 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.000676594 (* 0.0272727 = 1.84526e-05 loss) | |
| I0525 04:25:24.514922 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.163265 | |
| I0525 04:25:24.514937 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0 | |
| I0525 04:25:24.514950 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0 | |
| I0525 04:25:24.514961 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0.125 | |
| I0525 04:25:24.514973 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0 | |
| I0525 04:25:24.514984 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.25 | |
| I0525 04:25:24.514997 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.25 | |
| I0525 04:25:24.515008 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.75 | |
| I0525 04:25:24.515020 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.75 | |
| I0525 04:25:24.515031 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 1 | |
| I0525 04:25:24.515043 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 1 | |
| I0525 04:25:24.515055 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 04:25:24.515066 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 04:25:24.515079 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 04:25:24.515090 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 04:25:24.515099 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 04:25:24.515106 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 04:25:24.515127 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 04:25:24.515141 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 04:25:24.515152 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 04:25:24.515163 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 04:25:24.515175 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 04:25:24.515187 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 04:25:24.515198 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.761364 | |
| I0525 04:25:24.515210 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.285714 | |
| I0525 04:25:24.515224 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 2.92841 (* 1 = 2.92841 loss) | |
| I0525 04:25:24.515239 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 0.885311 (* 1 = 0.885311 loss) | |
| I0525 04:25:24.515252 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 2.77741 (* 0.0909091 = 0.252492 loss) | |
| I0525 04:25:24.515266 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 2.75129 (* 0.0909091 = 0.250117 loss) | |
| I0525 04:25:24.515280 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 2.8153 (* 0.0909091 = 0.255936 loss) | |
| I0525 04:25:24.515295 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 2.98828 (* 0.0909091 = 0.271662 loss) | |
| I0525 04:25:24.515308 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 3.08261 (* 0.0909091 = 0.280237 loss) | |
| I0525 04:25:24.515321 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 3.05782 (* 0.0909091 = 0.277984 loss) | |
| I0525 04:25:24.515336 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 1.12113 (* 0.0909091 = 0.101921 loss) | |
| I0525 04:25:24.515349 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.901134 (* 0.0909091 = 0.0819213 loss) | |
| I0525 04:25:24.515363 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.0784026 (* 0.0909091 = 0.00712751 loss) | |
| I0525 04:25:24.515377 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.0403155 (* 0.0909091 = 0.00366504 loss) | |
| I0525 04:25:24.515391 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.0103662 (* 0.0909091 = 0.000942383 loss) | |
| I0525 04:25:24.515405 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.00974966 (* 0.0909091 = 0.000886333 loss) | |
| I0525 04:25:24.515419 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.0152279 (* 0.0909091 = 0.00138436 loss) | |
| I0525 04:25:24.515432 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.0107611 (* 0.0909091 = 0.000978286 loss) | |
| I0525 04:25:24.515446 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.0100758 (* 0.0909091 = 0.000915979 loss) | |
| I0525 04:25:24.515460 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.00648123 (* 0.0909091 = 0.000589203 loss) | |
| I0525 04:25:24.515473 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.00229293 (* 0.0909091 = 0.000208448 loss) | |
| I0525 04:25:24.515487 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.00254153 (* 0.0909091 = 0.000231048 loss) | |
| I0525 04:25:24.515501 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00149377 (* 0.0909091 = 0.000135797 loss) | |
| I0525 04:25:24.515514 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00116375 (* 0.0909091 = 0.000105796 loss) | |
| I0525 04:25:24.515528 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.000750387 (* 0.0909091 = 6.8217e-05 loss) | |
| I0525 04:25:24.515542 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.000870525 (* 0.0909091 = 7.91386e-05 loss) | |
| I0525 04:25:24.515554 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 04:25:24.515566 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 04:25:24.515578 5272 solver.cpp:245] Train net output #149: total_confidence = 3.86508e-05 | |
| I0525 04:25:24.515599 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 0.000312713 | |
| I0525 04:25:24.515612 5272 sgd_solver.cpp:106] Iteration 19500, lr = 0.001 | |
| I0525 04:29:15.156944 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 30.1318 > 30) by scale factor 0.995625 | |
| I0525 04:31:49.165145 5272 solver.cpp:456] Snapshotting to binary proto file /mnt/snapshots/mixed_lstm20_iter_20000.caffemodel | |
| I0525 04:31:50.776320 5272 sgd_solver.cpp:273] Snapshotting solver state to binary proto file /mnt/snapshots/mixed_lstm20_iter_20000.solverstate | |
| I0525 04:31:51.056249 5272 solver.cpp:338] Iteration 20000, Testing net (#0) | |
| I0525 04:32:49.085144 5272 solver.cpp:393] Test loss: 9.06269 | |
| I0525 04:32:49.085259 5272 solver.cpp:406] Test net output #0: loss1/accuracy = 0.0681274 | |
| I0525 04:32:49.085279 5272 solver.cpp:406] Test net output #1: loss1/accuracy01 = 0.146 | |
| I0525 04:32:49.085294 5272 solver.cpp:406] Test net output #2: loss1/accuracy02 = 0.105 | |
| I0525 04:32:49.085307 5272 solver.cpp:406] Test net output #3: loss1/accuracy03 = 0.09 | |
| I0525 04:32:49.085319 5272 solver.cpp:406] Test net output #4: loss1/accuracy04 = 0.172 | |
| I0525 04:32:49.085331 5272 solver.cpp:406] Test net output #5: loss1/accuracy05 = 0.334 | |
| I0525 04:32:49.085343 5272 solver.cpp:406] Test net output #6: loss1/accuracy06 = 0.476 | |
| I0525 04:32:49.085355 5272 solver.cpp:406] Test net output #7: loss1/accuracy07 = 0.737 | |
| I0525 04:32:49.085367 5272 solver.cpp:406] Test net output #8: loss1/accuracy08 = 0.917 | |
| I0525 04:32:49.085381 5272 solver.cpp:406] Test net output #9: loss1/accuracy09 = 0.98 | |
| I0525 04:32:49.085392 5272 solver.cpp:406] Test net output #10: loss1/accuracy10 = 0.993 | |
| I0525 04:32:49.085403 5272 solver.cpp:406] Test net output #11: loss1/accuracy11 = 1 | |
| I0525 04:32:49.085415 5272 solver.cpp:406] Test net output #12: loss1/accuracy12 = 1 | |
| I0525 04:32:49.085427 5272 solver.cpp:406] Test net output #13: loss1/accuracy13 = 1 | |
| I0525 04:32:49.085438 5272 solver.cpp:406] Test net output #14: loss1/accuracy14 = 1 | |
| I0525 04:32:49.085449 5272 solver.cpp:406] Test net output #15: loss1/accuracy15 = 1 | |
| I0525 04:32:49.085461 5272 solver.cpp:406] Test net output #16: loss1/accuracy16 = 1 | |
| I0525 04:32:49.085472 5272 solver.cpp:406] Test net output #17: loss1/accuracy17 = 1 | |
| I0525 04:32:49.085484 5272 solver.cpp:406] Test net output #18: loss1/accuracy18 = 1 | |
| I0525 04:32:49.085494 5272 solver.cpp:406] Test net output #19: loss1/accuracy19 = 1 | |
| I0525 04:32:49.085506 5272 solver.cpp:406] Test net output #20: loss1/accuracy20 = 1 | |
| I0525 04:32:49.085517 5272 solver.cpp:406] Test net output #21: loss1/accuracy21 = 1 | |
| I0525 04:32:49.085530 5272 solver.cpp:406] Test net output #22: loss1/accuracy22 = 1 | |
| I0525 04:32:49.085541 5272 solver.cpp:406] Test net output #23: loss1/accuracy_incl_empty = 0.766455 | |
| I0525 04:32:49.085552 5272 solver.cpp:406] Test net output #24: loss1/accuracy_top3 = 0.239561 | |
| I0525 04:32:49.085567 5272 solver.cpp:406] Test net output #25: loss1/cross_entropy_loss = 3.38716 (* 0.3 = 1.01615 loss) | |
| I0525 04:32:49.085582 5272 solver.cpp:406] Test net output #26: loss1/cross_entropy_loss_incl_empty = 0.878778 (* 0.3 = 0.263634 loss) | |
| I0525 04:32:49.085597 5272 solver.cpp:406] Test net output #27: loss1/loss01 = 2.8544 (* 0.0272727 = 0.0778471 loss) | |
| I0525 04:32:49.085610 5272 solver.cpp:406] Test net output #28: loss1/loss02 = 3.08968 (* 0.0272727 = 0.084264 loss) | |
| I0525 04:32:49.085623 5272 solver.cpp:406] Test net output #29: loss1/loss03 = 3.16894 (* 0.0272727 = 0.0864256 loss) | |
| I0525 04:32:49.085638 5272 solver.cpp:406] Test net output #30: loss1/loss04 = 3.01095 (* 0.0272727 = 0.0821167 loss) | |
| I0525 04:32:49.085650 5272 solver.cpp:406] Test net output #31: loss1/loss05 = 2.51506 (* 0.0272727 = 0.0685926 loss) | |
| I0525 04:32:49.085664 5272 solver.cpp:406] Test net output #32: loss1/loss06 = 2.0789 (* 0.0272727 = 0.0566972 loss) | |
| I0525 04:32:49.085677 5272 solver.cpp:406] Test net output #33: loss1/loss07 = 1.2292 (* 0.0272727 = 0.0335235 loss) | |
| I0525 04:32:49.085691 5272 solver.cpp:406] Test net output #34: loss1/loss08 = 0.463374 (* 0.0272727 = 0.0126375 loss) | |
| I0525 04:32:49.085705 5272 solver.cpp:406] Test net output #35: loss1/loss09 = 0.121401 (* 0.0272727 = 0.00331094 loss) | |
| I0525 04:32:49.085719 5272 solver.cpp:406] Test net output #36: loss1/loss10 = 0.0719074 (* 0.0272727 = 0.00196111 loss) | |
| I0525 04:32:49.085733 5272 solver.cpp:406] Test net output #37: loss1/loss11 = 0.025424 (* 0.0272727 = 0.000693383 loss) | |
| I0525 04:32:49.085747 5272 solver.cpp:406] Test net output #38: loss1/loss12 = 0.0189049 (* 0.0272727 = 0.000515587 loss) | |
| I0525 04:32:49.085762 5272 solver.cpp:406] Test net output #39: loss1/loss13 = 0.0151439 (* 0.0272727 = 0.000413015 loss) | |
| I0525 04:32:49.085799 5272 solver.cpp:406] Test net output #40: loss1/loss14 = 0.0108729 (* 0.0272727 = 0.000296533 loss) | |
| I0525 04:32:49.085814 5272 solver.cpp:406] Test net output #41: loss1/loss15 = 0.00773051 (* 0.0272727 = 0.000210832 loss) | |
| I0525 04:32:49.085829 5272 solver.cpp:406] Test net output #42: loss1/loss16 = 0.0056384 (* 0.0272727 = 0.000153775 loss) | |
| I0525 04:32:49.085842 5272 solver.cpp:406] Test net output #43: loss1/loss17 = 0.00392531 (* 0.0272727 = 0.000107054 loss) | |
| I0525 04:32:49.085856 5272 solver.cpp:406] Test net output #44: loss1/loss18 = 0.00281712 (* 0.0272727 = 7.68305e-05 loss) | |
| I0525 04:32:49.085870 5272 solver.cpp:406] Test net output #45: loss1/loss19 = 0.00259081 (* 0.0272727 = 7.06584e-05 loss) | |
| I0525 04:32:49.085888 5272 solver.cpp:406] Test net output #46: loss1/loss20 = 0.00238352 (* 0.0272727 = 6.50051e-05 loss) | |
| I0525 04:32:49.085902 5272 solver.cpp:406] Test net output #47: loss1/loss21 = 0.00227323 (* 0.0272727 = 6.19972e-05 loss) | |
| I0525 04:32:49.085916 5272 solver.cpp:406] Test net output #48: loss1/loss22 = 0.00221379 (* 0.0272727 = 6.03762e-05 loss) | |
| I0525 04:32:49.085928 5272 solver.cpp:406] Test net output #49: loss2/accuracy = 0.0669266 | |
| I0525 04:32:49.085940 5272 solver.cpp:406] Test net output #50: loss2/accuracy01 = 0.123 | |
| I0525 04:32:49.085952 5272 solver.cpp:406] Test net output #51: loss2/accuracy02 = 0.105 | |
| I0525 04:32:49.085963 5272 solver.cpp:406] Test net output #52: loss2/accuracy03 = 0.083 | |
| I0525 04:32:49.085974 5272 solver.cpp:406] Test net output #53: loss2/accuracy04 = 0.167 | |
| I0525 04:32:49.085986 5272 solver.cpp:406] Test net output #54: loss2/accuracy05 = 0.341 | |
| I0525 04:32:49.085999 5272 solver.cpp:406] Test net output #55: loss2/accuracy06 = 0.481 | |
| I0525 04:32:49.086009 5272 solver.cpp:406] Test net output #56: loss2/accuracy07 = 0.736 | |
| I0525 04:32:49.086020 5272 solver.cpp:406] Test net output #57: loss2/accuracy08 = 0.918 | |
| I0525 04:32:49.086032 5272 solver.cpp:406] Test net output #58: loss2/accuracy09 = 0.98 | |
| I0525 04:32:49.086043 5272 solver.cpp:406] Test net output #59: loss2/accuracy10 = 0.993 | |
| I0525 04:32:49.086055 5272 solver.cpp:406] Test net output #60: loss2/accuracy11 = 1 | |
| I0525 04:32:49.086066 5272 solver.cpp:406] Test net output #61: loss2/accuracy12 = 1 | |
| I0525 04:32:49.086076 5272 solver.cpp:406] Test net output #62: loss2/accuracy13 = 1 | |
| I0525 04:32:49.086087 5272 solver.cpp:406] Test net output #63: loss2/accuracy14 = 1 | |
| I0525 04:32:49.086098 5272 solver.cpp:406] Test net output #64: loss2/accuracy15 = 1 | |
| I0525 04:32:49.086109 5272 solver.cpp:406] Test net output #65: loss2/accuracy16 = 1 | |
| I0525 04:32:49.086120 5272 solver.cpp:406] Test net output #66: loss2/accuracy17 = 1 | |
| I0525 04:32:49.086132 5272 solver.cpp:406] Test net output #67: loss2/accuracy18 = 1 | |
| I0525 04:32:49.086143 5272 solver.cpp:406] Test net output #68: loss2/accuracy19 = 1 | |
| I0525 04:32:49.086153 5272 solver.cpp:406] Test net output #69: loss2/accuracy20 = 1 | |
| I0525 04:32:49.086164 5272 solver.cpp:406] Test net output #70: loss2/accuracy21 = 1 | |
| I0525 04:32:49.086175 5272 solver.cpp:406] Test net output #71: loss2/accuracy22 = 1 | |
| I0525 04:32:49.086185 5272 solver.cpp:406] Test net output #72: loss2/accuracy_incl_empty = 0.766001 | |
| I0525 04:32:49.086197 5272 solver.cpp:406] Test net output #73: loss2/accuracy_top3 = 0.234893 | |
| I0525 04:32:49.086210 5272 solver.cpp:406] Test net output #74: loss2/cross_entropy_loss = 3.4892 (* 0.3 = 1.04676 loss) | |
| I0525 04:32:49.086223 5272 solver.cpp:406] Test net output #75: loss2/cross_entropy_loss_incl_empty = 0.903918 (* 0.3 = 0.271175 loss) | |
| I0525 04:32:49.086237 5272 solver.cpp:406] Test net output #76: loss2/loss01 = 2.84473 (* 0.0272727 = 0.0775836 loss) | |
| I0525 04:32:49.086251 5272 solver.cpp:406] Test net output #77: loss2/loss02 = 3.0509 (* 0.0272727 = 0.0832063 loss) | |
| I0525 04:32:49.086264 5272 solver.cpp:406] Test net output #78: loss2/loss03 = 3.14582 (* 0.0272727 = 0.0857952 loss) | |
| I0525 04:32:49.086293 5272 solver.cpp:406] Test net output #79: loss2/loss04 = 2.99103 (* 0.0272727 = 0.0815736 loss) | |
| I0525 04:32:49.086308 5272 solver.cpp:406] Test net output #80: loss2/loss05 = 2.4765 (* 0.0272727 = 0.0675408 loss) | |
| I0525 04:32:49.086323 5272 solver.cpp:406] Test net output #81: loss2/loss06 = 2.03532 (* 0.0272727 = 0.0555088 loss) | |
| I0525 04:32:49.086335 5272 solver.cpp:406] Test net output #82: loss2/loss07 = 1.19396 (* 0.0272727 = 0.0325624 loss) | |
| I0525 04:32:49.086349 5272 solver.cpp:406] Test net output #83: loss2/loss08 = 0.445675 (* 0.0272727 = 0.0121548 loss) | |
| I0525 04:32:49.086364 5272 solver.cpp:406] Test net output #84: loss2/loss09 = 0.107036 (* 0.0272727 = 0.00291916 loss) | |
| I0525 04:32:49.086376 5272 solver.cpp:406] Test net output #85: loss2/loss10 = 0.0621045 (* 0.0272727 = 0.00169376 loss) | |
| I0525 04:32:49.086390 5272 solver.cpp:406] Test net output #86: loss2/loss11 = 0.018584 (* 0.0272727 = 0.000506836 loss) | |
| I0525 04:32:49.086403 5272 solver.cpp:406] Test net output #87: loss2/loss12 = 0.013575 (* 0.0272727 = 0.000370226 loss) | |
| I0525 04:32:49.086416 5272 solver.cpp:406] Test net output #88: loss2/loss13 = 0.00972601 (* 0.0272727 = 0.000265255 loss) | |
| I0525 04:32:49.086427 5272 solver.cpp:406] Test net output #89: loss2/loss14 = 0.00740712 (* 0.0272727 = 0.000202012 loss) | |
| I0525 04:32:49.086436 5272 solver.cpp:406] Test net output #90: loss2/loss15 = 0.00544423 (* 0.0272727 = 0.000148479 loss) | |
| I0525 04:32:49.086450 5272 solver.cpp:406] Test net output #91: loss2/loss16 = 0.00405647 (* 0.0272727 = 0.000110631 loss) | |
| I0525 04:32:49.086464 5272 solver.cpp:406] Test net output #92: loss2/loss17 = 0.00259628 (* 0.0272727 = 7.08076e-05 loss) | |
| I0525 04:32:49.086478 5272 solver.cpp:406] Test net output #93: loss2/loss18 = 0.00233311 (* 0.0272727 = 6.36302e-05 loss) | |
| I0525 04:32:49.086491 5272 solver.cpp:406] Test net output #94: loss2/loss19 = 0.00192376 (* 0.0272727 = 5.2466e-05 loss) | |
| I0525 04:32:49.086505 5272 solver.cpp:406] Test net output #95: loss2/loss20 = 0.0017468 (* 0.0272727 = 4.76401e-05 loss) | |
| I0525 04:32:49.086519 5272 solver.cpp:406] Test net output #96: loss2/loss21 = 0.00161749 (* 0.0272727 = 4.41134e-05 loss) | |
| I0525 04:32:49.086532 5272 solver.cpp:406] Test net output #97: loss2/loss22 = 0.00167208 (* 0.0272727 = 4.56023e-05 loss) | |
| I0525 04:32:49.086544 5272 solver.cpp:406] Test net output #98: loss3/accuracy = 0.0837575 | |
| I0525 04:32:49.086556 5272 solver.cpp:406] Test net output #99: loss3/accuracy01 = 0.131 | |
| I0525 04:32:49.086567 5272 solver.cpp:406] Test net output #100: loss3/accuracy02 = 0.101 | |
| I0525 04:32:49.086580 5272 solver.cpp:406] Test net output #101: loss3/accuracy03 = 0.084 | |
| I0525 04:32:49.086591 5272 solver.cpp:406] Test net output #102: loss3/accuracy04 = 0.163 | |
| I0525 04:32:49.086602 5272 solver.cpp:406] Test net output #103: loss3/accuracy05 = 0.335 | |
| I0525 04:32:49.086613 5272 solver.cpp:406] Test net output #104: loss3/accuracy06 = 0.486 | |
| I0525 04:32:49.086624 5272 solver.cpp:406] Test net output #105: loss3/accuracy07 = 0.738 | |
| I0525 04:32:49.086637 5272 solver.cpp:406] Test net output #106: loss3/accuracy08 = 0.916 | |
| I0525 04:32:49.086647 5272 solver.cpp:406] Test net output #107: loss3/accuracy09 = 0.979 | |
| I0525 04:32:49.086658 5272 solver.cpp:406] Test net output #108: loss3/accuracy10 = 0.99 | |
| I0525 04:32:49.086669 5272 solver.cpp:406] Test net output #109: loss3/accuracy11 = 0.999 | |
| I0525 04:32:49.086680 5272 solver.cpp:406] Test net output #110: loss3/accuracy12 = 0.999 | |
| I0525 04:32:49.086691 5272 solver.cpp:406] Test net output #111: loss3/accuracy13 = 1 | |
| I0525 04:32:49.086704 5272 solver.cpp:406] Test net output #112: loss3/accuracy14 = 1 | |
| I0525 04:32:49.086714 5272 solver.cpp:406] Test net output #113: loss3/accuracy15 = 1 | |
| I0525 04:32:49.086725 5272 solver.cpp:406] Test net output #114: loss3/accuracy16 = 1 | |
| I0525 04:32:49.086736 5272 solver.cpp:406] Test net output #115: loss3/accuracy17 = 1 | |
| I0525 04:32:49.086756 5272 solver.cpp:406] Test net output #116: loss3/accuracy18 = 1 | |
| I0525 04:32:49.086768 5272 solver.cpp:406] Test net output #117: loss3/accuracy19 = 1 | |
| I0525 04:32:49.086779 5272 solver.cpp:406] Test net output #118: loss3/accuracy20 = 1 | |
| I0525 04:32:49.086791 5272 solver.cpp:406] Test net output #119: loss3/accuracy21 = 1 | |
| I0525 04:32:49.086802 5272 solver.cpp:406] Test net output #120: loss3/accuracy22 = 1 | |
| I0525 04:32:49.086812 5272 solver.cpp:406] Test net output #121: loss3/accuracy_incl_empty = 0.765546 | |
| I0525 04:32:49.086823 5272 solver.cpp:406] Test net output #122: loss3/accuracy_top3 = 0.266575 | |
| I0525 04:32:49.086838 5272 solver.cpp:406] Test net output #123: loss3/cross_entropy_loss = 3.02285 (* 1 = 3.02285 loss) | |
| I0525 04:32:49.086850 5272 solver.cpp:406] Test net output #124: loss3/cross_entropy_loss_incl_empty = 0.816482 (* 1 = 0.816482 loss) | |
| I0525 04:32:49.086864 5272 solver.cpp:406] Test net output #125: loss3/loss01 = 2.72822 (* 0.0909091 = 0.24802 loss) | |
| I0525 04:32:49.086877 5272 solver.cpp:406] Test net output #126: loss3/loss02 = 2.96743 (* 0.0909091 = 0.269766 loss) | |
| I0525 04:32:49.086891 5272 solver.cpp:406] Test net output #127: loss3/loss03 = 3.05545 (* 0.0909091 = 0.277768 loss) | |
| I0525 04:32:49.086905 5272 solver.cpp:406] Test net output #128: loss3/loss04 = 2.90534 (* 0.0909091 = 0.264122 loss) | |
| I0525 04:32:49.086917 5272 solver.cpp:406] Test net output #129: loss3/loss05 = 2.38122 (* 0.0909091 = 0.216475 loss) | |
| I0525 04:32:49.086933 5272 solver.cpp:406] Test net output #130: loss3/loss06 = 1.93345 (* 0.0909091 = 0.175768 loss) | |
| I0525 04:32:49.086947 5272 solver.cpp:406] Test net output #131: loss3/loss07 = 1.11479 (* 0.0909091 = 0.101344 loss) | |
| I0525 04:32:49.086961 5272 solver.cpp:406] Test net output #132: loss3/loss08 = 0.422952 (* 0.0909091 = 0.0384502 loss) | |
| I0525 04:32:49.086974 5272 solver.cpp:406] Test net output #133: loss3/loss09 = 0.10682 (* 0.0909091 = 0.00971094 loss) | |
| I0525 04:32:49.086988 5272 solver.cpp:406] Test net output #134: loss3/loss10 = 0.0619808 (* 0.0909091 = 0.00563461 loss) | |
| I0525 04:32:49.087002 5272 solver.cpp:406] Test net output #135: loss3/loss11 = 0.018001 (* 0.0909091 = 0.00163646 loss) | |
| I0525 04:32:49.087015 5272 solver.cpp:406] Test net output #136: loss3/loss12 = 0.0124609 (* 0.0909091 = 0.00113281 loss) | |
| I0525 04:32:49.087029 5272 solver.cpp:406] Test net output #137: loss3/loss13 = 0.00980878 (* 0.0909091 = 0.000891707 loss) | |
| I0525 04:32:49.087043 5272 solver.cpp:406] Test net output #138: loss3/loss14 = 0.00705698 (* 0.0909091 = 0.000641543 loss) | |
| I0525 04:32:49.087055 5272 solver.cpp:406] Test net output #139: loss3/loss15 = 0.0053528 (* 0.0909091 = 0.000486618 loss) | |
| I0525 04:32:49.087069 5272 solver.cpp:406] Test net output #140: loss3/loss16 = 0.00369426 (* 0.0909091 = 0.000335842 loss) | |
| I0525 04:32:49.087082 5272 solver.cpp:406] Test net output #141: loss3/loss17 = 0.00271653 (* 0.0909091 = 0.000246957 loss) | |
| I0525 04:32:49.087096 5272 solver.cpp:406] Test net output #142: loss3/loss18 = 0.00195548 (* 0.0909091 = 0.000177771 loss) | |
| I0525 04:32:49.087110 5272 solver.cpp:406] Test net output #143: loss3/loss19 = 0.00152079 (* 0.0909091 = 0.000138254 loss) | |
| I0525 04:32:49.087123 5272 solver.cpp:406] Test net output #144: loss3/loss20 = 0.00137456 (* 0.0909091 = 0.00012496 loss) | |
| I0525 04:32:49.087137 5272 solver.cpp:406] Test net output #145: loss3/loss21 = 0.00110642 (* 0.0909091 = 0.000100584 loss) | |
| I0525 04:32:49.087147 5272 solver.cpp:406] Test net output #146: loss3/loss22 = 0.00104875 (* 0.0909091 = 9.53412e-05 loss) | |
| I0525 04:32:49.087159 5272 solver.cpp:406] Test net output #147: total_accuracy = 0 | |
| I0525 04:32:49.087170 5272 solver.cpp:406] Test net output #148: total_accuracy_not_rec = 0 | |
| I0525 04:32:49.087182 5272 solver.cpp:406] Test net output #149: total_confidence = 0.000255441 | |
| I0525 04:32:49.087193 5272 solver.cpp:406] Test net output #150: total_confidence_not_rec = 0.000359897 | |
| I0525 04:32:49.087215 5272 solver.cpp:338] Iteration 20000, Testing net (#1) | |
| I0525 04:33:47.102599 5272 solver.cpp:393] Test loss: 9.66398 | |
| I0525 04:33:47.102737 5272 solver.cpp:406] Test net output #0: loss1/accuracy = 0.0714552 | |
| I0525 04:33:47.102758 5272 solver.cpp:406] Test net output #1: loss1/accuracy01 = 0.128 | |
| I0525 04:33:47.102772 5272 solver.cpp:406] Test net output #2: loss1/accuracy02 = 0.115 | |
| I0525 04:33:47.102784 5272 solver.cpp:406] Test net output #3: loss1/accuracy03 = 0.104 | |
| I0525 04:33:47.102797 5272 solver.cpp:406] Test net output #4: loss1/accuracy04 = 0.184 | |
| I0525 04:33:47.102809 5272 solver.cpp:406] Test net output #5: loss1/accuracy05 = 0.34 | |
| I0525 04:33:47.102821 5272 solver.cpp:406] Test net output #6: loss1/accuracy06 = 0.451 | |
| I0525 04:33:47.102833 5272 solver.cpp:406] Test net output #7: loss1/accuracy07 = 0.662 | |
| I0525 04:33:47.102845 5272 solver.cpp:406] Test net output #8: loss1/accuracy08 = 0.826 | |
| I0525 04:33:47.102857 5272 solver.cpp:406] Test net output #9: loss1/accuracy09 = 0.888 | |
| I0525 04:33:47.102869 5272 solver.cpp:406] Test net output #10: loss1/accuracy10 = 0.905 | |
| I0525 04:33:47.102885 5272 solver.cpp:406] Test net output #11: loss1/accuracy11 = 0.926 | |
| I0525 04:33:47.102898 5272 solver.cpp:406] Test net output #12: loss1/accuracy12 = 0.945 | |
| I0525 04:33:47.102910 5272 solver.cpp:406] Test net output #13: loss1/accuracy13 = 0.953 | |
| I0525 04:33:47.102923 5272 solver.cpp:406] Test net output #14: loss1/accuracy14 = 0.964 | |
| I0525 04:33:47.102936 5272 solver.cpp:406] Test net output #15: loss1/accuracy15 = 0.967 | |
| I0525 04:33:47.102947 5272 solver.cpp:406] Test net output #16: loss1/accuracy16 = 0.983 | |
| I0525 04:33:47.102958 5272 solver.cpp:406] Test net output #17: loss1/accuracy17 = 0.993 | |
| I0525 04:33:47.102970 5272 solver.cpp:406] Test net output #18: loss1/accuracy18 = 0.994 | |
| I0525 04:33:47.102982 5272 solver.cpp:406] Test net output #19: loss1/accuracy19 = 0.996 | |
| I0525 04:33:47.102994 5272 solver.cpp:406] Test net output #20: loss1/accuracy20 = 1 | |
| I0525 04:33:47.103005 5272 solver.cpp:406] Test net output #21: loss1/accuracy21 = 1 | |
| I0525 04:33:47.103016 5272 solver.cpp:406] Test net output #22: loss1/accuracy22 = 1 | |
| I0525 04:33:47.103027 5272 solver.cpp:406] Test net output #23: loss1/accuracy_incl_empty = 0.736455 | |
| I0525 04:33:47.103039 5272 solver.cpp:406] Test net output #24: loss1/accuracy_top3 = 0.250323 | |
| I0525 04:33:47.103056 5272 solver.cpp:406] Test net output #25: loss1/cross_entropy_loss = 3.38708 (* 0.3 = 1.01612 loss) | |
| I0525 04:33:47.103070 5272 solver.cpp:406] Test net output #26: loss1/cross_entropy_loss_incl_empty = 0.99432 (* 0.3 = 0.298296 loss) | |
| I0525 04:33:47.103085 5272 solver.cpp:406] Test net output #27: loss1/loss01 = 2.96207 (* 0.0272727 = 0.0807838 loss) | |
| I0525 04:33:47.103098 5272 solver.cpp:406] Test net output #28: loss1/loss02 = 3.05106 (* 0.0272727 = 0.0832107 loss) | |
| I0525 04:33:47.103112 5272 solver.cpp:406] Test net output #29: loss1/loss03 = 3.16663 (* 0.0272727 = 0.0863627 loss) | |
| I0525 04:33:47.103127 5272 solver.cpp:406] Test net output #30: loss1/loss04 = 2.99791 (* 0.0272727 = 0.0817613 loss) | |
| I0525 04:33:47.103139 5272 solver.cpp:406] Test net output #31: loss1/loss05 = 2.53561 (* 0.0272727 = 0.069153 loss) | |
| I0525 04:33:47.103153 5272 solver.cpp:406] Test net output #32: loss1/loss06 = 2.20831 (* 0.0272727 = 0.0602266 loss) | |
| I0525 04:33:47.103168 5272 solver.cpp:406] Test net output #33: loss1/loss07 = 1.49257 (* 0.0272727 = 0.0407064 loss) | |
| I0525 04:33:47.103181 5272 solver.cpp:406] Test net output #34: loss1/loss08 = 0.825123 (* 0.0272727 = 0.0225034 loss) | |
| I0525 04:33:47.103194 5272 solver.cpp:406] Test net output #35: loss1/loss09 = 0.50138 (* 0.0272727 = 0.013674 loss) | |
| I0525 04:33:47.103209 5272 solver.cpp:406] Test net output #36: loss1/loss10 = 0.423965 (* 0.0272727 = 0.0115627 loss) | |
| I0525 04:33:47.103222 5272 solver.cpp:406] Test net output #37: loss1/loss11 = 0.327619 (* 0.0272727 = 0.00893507 loss) | |
| I0525 04:33:47.103236 5272 solver.cpp:406] Test net output #38: loss1/loss12 = 0.256884 (* 0.0272727 = 0.00700594 loss) | |
| I0525 04:33:47.103251 5272 solver.cpp:406] Test net output #39: loss1/loss13 = 0.237937 (* 0.0272727 = 0.0064892 loss) | |
| I0525 04:33:47.103286 5272 solver.cpp:406] Test net output #40: loss1/loss14 = 0.189985 (* 0.0272727 = 0.00518141 loss) | |
| I0525 04:33:47.103301 5272 solver.cpp:406] Test net output #41: loss1/loss15 = 0.175711 (* 0.0272727 = 0.00479213 loss) | |
| I0525 04:33:47.103315 5272 solver.cpp:406] Test net output #42: loss1/loss16 = 0.106645 (* 0.0272727 = 0.00290851 loss) | |
| I0525 04:33:47.103329 5272 solver.cpp:406] Test net output #43: loss1/loss17 = 0.0531984 (* 0.0272727 = 0.00145087 loss) | |
| I0525 04:33:47.103343 5272 solver.cpp:406] Test net output #44: loss1/loss18 = 0.0466086 (* 0.0272727 = 0.00127114 loss) | |
| I0525 04:33:47.103356 5272 solver.cpp:406] Test net output #45: loss1/loss19 = 0.0329337 (* 0.0272727 = 0.000898191 loss) | |
| I0525 04:33:47.103371 5272 solver.cpp:406] Test net output #46: loss1/loss20 = 0.00349135 (* 0.0272727 = 9.52186e-05 loss) | |
| I0525 04:33:47.103385 5272 solver.cpp:406] Test net output #47: loss1/loss21 = 0.00317343 (* 0.0272727 = 8.6548e-05 loss) | |
| I0525 04:33:47.103399 5272 solver.cpp:406] Test net output #48: loss1/loss22 = 0.00299223 (* 0.0272727 = 8.16061e-05 loss) | |
| I0525 04:33:47.103411 5272 solver.cpp:406] Test net output #49: loss2/accuracy = 0.0629042 | |
| I0525 04:33:47.103425 5272 solver.cpp:406] Test net output #50: loss2/accuracy01 = 0.109 | |
| I0525 04:33:47.103436 5272 solver.cpp:406] Test net output #51: loss2/accuracy02 = 0.12 | |
| I0525 04:33:47.103447 5272 solver.cpp:406] Test net output #52: loss2/accuracy03 = 0.086 | |
| I0525 04:33:47.103459 5272 solver.cpp:406] Test net output #53: loss2/accuracy04 = 0.183 | |
| I0525 04:33:47.103471 5272 solver.cpp:406] Test net output #54: loss2/accuracy05 = 0.346 | |
| I0525 04:33:47.103482 5272 solver.cpp:406] Test net output #55: loss2/accuracy06 = 0.448 | |
| I0525 04:33:47.103493 5272 solver.cpp:406] Test net output #56: loss2/accuracy07 = 0.66 | |
| I0525 04:33:47.103505 5272 solver.cpp:406] Test net output #57: loss2/accuracy08 = 0.825 | |
| I0525 04:33:47.103516 5272 solver.cpp:406] Test net output #58: loss2/accuracy09 = 0.889 | |
| I0525 04:33:47.103528 5272 solver.cpp:406] Test net output #59: loss2/accuracy10 = 0.904 | |
| I0525 04:33:47.103539 5272 solver.cpp:406] Test net output #60: loss2/accuracy11 = 0.926 | |
| I0525 04:33:47.103550 5272 solver.cpp:406] Test net output #61: loss2/accuracy12 = 0.945 | |
| I0525 04:33:47.103562 5272 solver.cpp:406] Test net output #62: loss2/accuracy13 = 0.953 | |
| I0525 04:33:47.103574 5272 solver.cpp:406] Test net output #63: loss2/accuracy14 = 0.964 | |
| I0525 04:33:47.103585 5272 solver.cpp:406] Test net output #64: loss2/accuracy15 = 0.967 | |
| I0525 04:33:47.103596 5272 solver.cpp:406] Test net output #65: loss2/accuracy16 = 0.983 | |
| I0525 04:33:47.103607 5272 solver.cpp:406] Test net output #66: loss2/accuracy17 = 0.993 | |
| I0525 04:33:47.103620 5272 solver.cpp:406] Test net output #67: loss2/accuracy18 = 0.994 | |
| I0525 04:33:47.103631 5272 solver.cpp:406] Test net output #68: loss2/accuracy19 = 0.996 | |
| I0525 04:33:47.103641 5272 solver.cpp:406] Test net output #69: loss2/accuracy20 = 1 | |
| I0525 04:33:47.103653 5272 solver.cpp:406] Test net output #70: loss2/accuracy21 = 1 | |
| I0525 04:33:47.103664 5272 solver.cpp:406] Test net output #71: loss2/accuracy22 = 1 | |
| I0525 04:33:47.103675 5272 solver.cpp:406] Test net output #72: loss2/accuracy_incl_empty = 0.73491 | |
| I0525 04:33:47.103687 5272 solver.cpp:406] Test net output #73: loss2/accuracy_top3 = 0.233724 | |
| I0525 04:33:47.103700 5272 solver.cpp:406] Test net output #74: loss2/cross_entropy_loss = 3.48286 (* 0.3 = 1.04486 loss) | |
| I0525 04:33:47.103713 5272 solver.cpp:406] Test net output #75: loss2/cross_entropy_loss_incl_empty = 1.01859 (* 0.3 = 0.305577 loss) | |
| I0525 04:33:47.103727 5272 solver.cpp:406] Test net output #76: loss2/loss01 = 2.9382 (* 0.0272727 = 0.0801327 loss) | |
| I0525 04:33:47.103740 5272 solver.cpp:406] Test net output #77: loss2/loss02 = 3.01608 (* 0.0272727 = 0.0822569 loss) | |
| I0525 04:33:47.103770 5272 solver.cpp:406] Test net output #78: loss2/loss03 = 3.13943 (* 0.0272727 = 0.0856208 loss) | |
| I0525 04:33:47.103785 5272 solver.cpp:406] Test net output #79: loss2/loss04 = 2.97076 (* 0.0272727 = 0.0810207 loss) | |
| I0525 04:33:47.103798 5272 solver.cpp:406] Test net output #80: loss2/loss05 = 2.49861 (* 0.0272727 = 0.0681438 loss) | |
| I0525 04:33:47.103811 5272 solver.cpp:406] Test net output #81: loss2/loss06 = 2.16789 (* 0.0272727 = 0.0591243 loss) | |
| I0525 04:33:47.103824 5272 solver.cpp:406] Test net output #82: loss2/loss07 = 1.46665 (* 0.0272727 = 0.0399995 loss) | |
| I0525 04:33:47.103838 5272 solver.cpp:406] Test net output #83: loss2/loss08 = 0.806178 (* 0.0272727 = 0.0219867 loss) | |
| I0525 04:33:47.103852 5272 solver.cpp:406] Test net output #84: loss2/loss09 = 0.490652 (* 0.0272727 = 0.0133814 loss) | |
| I0525 04:33:47.103865 5272 solver.cpp:406] Test net output #85: loss2/loss10 = 0.412118 (* 0.0272727 = 0.0112396 loss) | |
| I0525 04:33:47.103879 5272 solver.cpp:406] Test net output #86: loss2/loss11 = 0.319816 (* 0.0272727 = 0.00872224 loss) | |
| I0525 04:33:47.103893 5272 solver.cpp:406] Test net output #87: loss2/loss12 = 0.25533 (* 0.0272727 = 0.00696355 loss) | |
| I0525 04:33:47.103907 5272 solver.cpp:406] Test net output #88: loss2/loss13 = 0.23316 (* 0.0272727 = 0.0063589 loss) | |
| I0525 04:33:47.103921 5272 solver.cpp:406] Test net output #89: loss2/loss14 = 0.182048 (* 0.0272727 = 0.00496496 loss) | |
| I0525 04:33:47.103937 5272 solver.cpp:406] Test net output #90: loss2/loss15 = 0.178098 (* 0.0272727 = 0.00485721 loss) | |
| I0525 04:33:47.103952 5272 solver.cpp:406] Test net output #91: loss2/loss16 = 0.103419 (* 0.0272727 = 0.00282052 loss) | |
| I0525 04:33:47.103961 5272 solver.cpp:406] Test net output #92: loss2/loss17 = 0.0530165 (* 0.0272727 = 0.00144591 loss) | |
| I0525 04:33:47.103971 5272 solver.cpp:406] Test net output #93: loss2/loss18 = 0.0476508 (* 0.0272727 = 0.00129957 loss) | |
| I0525 04:33:47.103981 5272 solver.cpp:406] Test net output #94: loss2/loss19 = 0.0333936 (* 0.0272727 = 0.000910735 loss) | |
| I0525 04:33:47.103996 5272 solver.cpp:406] Test net output #95: loss2/loss20 = 0.00289656 (* 0.0272727 = 7.89971e-05 loss) | |
| I0525 04:33:47.104010 5272 solver.cpp:406] Test net output #96: loss2/loss21 = 0.00266811 (* 0.0272727 = 7.27667e-05 loss) | |
| I0525 04:33:47.104023 5272 solver.cpp:406] Test net output #97: loss2/loss22 = 0.00270785 (* 0.0272727 = 7.38505e-05 loss) | |
| I0525 04:33:47.104035 5272 solver.cpp:406] Test net output #98: loss3/accuracy = 0.0863838 | |
| I0525 04:33:47.104048 5272 solver.cpp:406] Test net output #99: loss3/accuracy01 = 0.122 | |
| I0525 04:33:47.104059 5272 solver.cpp:406] Test net output #100: loss3/accuracy02 = 0.107 | |
| I0525 04:33:47.104070 5272 solver.cpp:406] Test net output #101: loss3/accuracy03 = 0.096 | |
| I0525 04:33:47.104082 5272 solver.cpp:406] Test net output #102: loss3/accuracy04 = 0.18 | |
| I0525 04:33:47.104094 5272 solver.cpp:406] Test net output #103: loss3/accuracy05 = 0.342 | |
| I0525 04:33:47.104105 5272 solver.cpp:406] Test net output #104: loss3/accuracy06 = 0.461 | |
| I0525 04:33:47.104116 5272 solver.cpp:406] Test net output #105: loss3/accuracy07 = 0.661 | |
| I0525 04:33:47.104128 5272 solver.cpp:406] Test net output #106: loss3/accuracy08 = 0.827 | |
| I0525 04:33:47.104140 5272 solver.cpp:406] Test net output #107: loss3/accuracy09 = 0.892 | |
| I0525 04:33:47.104151 5272 solver.cpp:406] Test net output #108: loss3/accuracy10 = 0.906 | |
| I0525 04:33:47.104162 5272 solver.cpp:406] Test net output #109: loss3/accuracy11 = 0.928 | |
| I0525 04:33:47.104174 5272 solver.cpp:406] Test net output #110: loss3/accuracy12 = 0.947 | |
| I0525 04:33:47.104185 5272 solver.cpp:406] Test net output #111: loss3/accuracy13 = 0.953 | |
| I0525 04:33:47.104197 5272 solver.cpp:406] Test net output #112: loss3/accuracy14 = 0.964 | |
| I0525 04:33:47.104208 5272 solver.cpp:406] Test net output #113: loss3/accuracy15 = 0.967 | |
| I0525 04:33:47.104219 5272 solver.cpp:406] Test net output #114: loss3/accuracy16 = 0.983 | |
| I0525 04:33:47.104240 5272 solver.cpp:406] Test net output #115: loss3/accuracy17 = 0.993 | |
| I0525 04:33:47.104252 5272 solver.cpp:406] Test net output #116: loss3/accuracy18 = 0.994 | |
| I0525 04:33:47.104264 5272 solver.cpp:406] Test net output #117: loss3/accuracy19 = 0.996 | |
| I0525 04:33:47.104275 5272 solver.cpp:406] Test net output #118: loss3/accuracy20 = 1 | |
| I0525 04:33:47.104286 5272 solver.cpp:406] Test net output #119: loss3/accuracy21 = 1 | |
| I0525 04:33:47.104297 5272 solver.cpp:406] Test net output #120: loss3/accuracy22 = 1 | |
| I0525 04:33:47.104308 5272 solver.cpp:406] Test net output #121: loss3/accuracy_incl_empty = 0.737728 | |
| I0525 04:33:47.104320 5272 solver.cpp:406] Test net output #122: loss3/accuracy_top3 = 0.249018 | |
| I0525 04:33:47.104332 5272 solver.cpp:406] Test net output #123: loss3/cross_entropy_loss = 3.05032 (* 1 = 3.05032 loss) | |
| I0525 04:33:47.104346 5272 solver.cpp:406] Test net output #124: loss3/cross_entropy_loss_incl_empty = 0.931632 (* 1 = 0.931632 loss) | |
| I0525 04:33:47.104359 5272 solver.cpp:406] Test net output #125: loss3/loss01 = 2.83186 (* 0.0909091 = 0.257442 loss) | |
| I0525 04:33:47.104372 5272 solver.cpp:406] Test net output #126: loss3/loss02 = 2.91906 (* 0.0909091 = 0.265369 loss) | |
| I0525 04:33:47.104385 5272 solver.cpp:406] Test net output #127: loss3/loss03 = 3.03042 (* 0.0909091 = 0.275493 loss) | |
| I0525 04:33:47.104399 5272 solver.cpp:406] Test net output #128: loss3/loss04 = 2.87507 (* 0.0909091 = 0.26137 loss) | |
| I0525 04:33:47.104413 5272 solver.cpp:406] Test net output #129: loss3/loss05 = 2.39901 (* 0.0909091 = 0.218091 loss) | |
| I0525 04:33:47.104425 5272 solver.cpp:406] Test net output #130: loss3/loss06 = 2.0483 (* 0.0909091 = 0.18621 loss) | |
| I0525 04:33:47.104439 5272 solver.cpp:406] Test net output #131: loss3/loss07 = 1.36443 (* 0.0909091 = 0.124039 loss) | |
| I0525 04:33:47.104452 5272 solver.cpp:406] Test net output #132: loss3/loss08 = 0.761142 (* 0.0909091 = 0.0691948 loss) | |
| I0525 04:33:47.104465 5272 solver.cpp:406] Test net output #133: loss3/loss09 = 0.451978 (* 0.0909091 = 0.0410889 loss) | |
| I0525 04:33:47.104480 5272 solver.cpp:406] Test net output #134: loss3/loss10 = 0.386661 (* 0.0909091 = 0.035151 loss) | |
| I0525 04:33:47.104493 5272 solver.cpp:406] Test net output #135: loss3/loss11 = 0.28967 (* 0.0909091 = 0.0263336 loss) | |
| I0525 04:33:47.104506 5272 solver.cpp:406] Test net output #136: loss3/loss12 = 0.228419 (* 0.0909091 = 0.0207653 loss) | |
| I0525 04:33:47.104519 5272 solver.cpp:406] Test net output #137: loss3/loss13 = 0.210345 (* 0.0909091 = 0.0191223 loss) | |
| I0525 04:33:47.104533 5272 solver.cpp:406] Test net output #138: loss3/loss14 = 0.16126 (* 0.0909091 = 0.01466 loss) | |
| I0525 04:33:47.104547 5272 solver.cpp:406] Test net output #139: loss3/loss15 = 0.151315 (* 0.0909091 = 0.0137559 loss) | |
| I0525 04:33:47.104560 5272 solver.cpp:406] Test net output #140: loss3/loss16 = 0.0887068 (* 0.0909091 = 0.00806425 loss) | |
| I0525 04:33:47.104573 5272 solver.cpp:406] Test net output #141: loss3/loss17 = 0.042288 (* 0.0909091 = 0.00384436 loss) | |
| I0525 04:33:47.104588 5272 solver.cpp:406] Test net output #142: loss3/loss18 = 0.0391222 (* 0.0909091 = 0.00355657 loss) | |
| I0525 04:33:47.104600 5272 solver.cpp:406] Test net output #143: loss3/loss19 = 0.0276054 (* 0.0909091 = 0.00250958 loss) | |
| I0525 04:33:47.104614 5272 solver.cpp:406] Test net output #144: loss3/loss20 = 0.00243301 (* 0.0909091 = 0.000221183 loss) | |
| I0525 04:33:47.104629 5272 solver.cpp:406] Test net output #145: loss3/loss21 = 0.0016541 (* 0.0909091 = 0.000150373 loss) | |
| I0525 04:33:47.104641 5272 solver.cpp:406] Test net output #146: loss3/loss22 = 0.00130346 (* 0.0909091 = 0.000118496 loss) | |
| I0525 04:33:47.104653 5272 solver.cpp:406] Test net output #147: total_accuracy = 0 | |
| I0525 04:33:47.104665 5272 solver.cpp:406] Test net output #148: total_accuracy_not_rec = 0 | |
| I0525 04:33:47.104676 5272 solver.cpp:406] Test net output #149: total_confidence = 0.000255476 | |
| I0525 04:33:47.104692 5272 solver.cpp:406] Test net output #150: total_confidence_not_rec = 0.000321263 | |
| I0525 04:33:47.463388 5272 solver.cpp:229] Iteration 20000, loss = 9.77133 | |
| I0525 04:33:47.463465 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.131148 | |
| I0525 04:33:47.463486 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.125 | |
| I0525 04:33:47.463500 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0525 04:33:47.463513 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0525 04:33:47.463526 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0 | |
| I0525 04:33:47.463538 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0 | |
| I0525 04:33:47.463551 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.25 | |
| I0525 04:33:47.463564 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.625 | |
| I0525 04:33:47.463577 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.875 | |
| I0525 04:33:47.463589 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 0.875 | |
| I0525 04:33:47.463603 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 0.875 | |
| I0525 04:33:47.463614 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 0.875 | |
| I0525 04:33:47.463627 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 0.875 | |
| I0525 04:33:47.463640 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 0.875 | |
| I0525 04:33:47.463652 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 0.875 | |
| I0525 04:33:47.463665 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 0.875 | |
| I0525 04:33:47.463676 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 0.875 | |
| I0525 04:33:47.463690 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 0.875 | |
| I0525 04:33:47.463701 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 0.875 | |
| I0525 04:33:47.463722 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 0.875 | |
| I0525 04:33:47.463737 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 0.875 | |
| I0525 04:33:47.463754 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 04:33:47.463773 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 04:33:47.463785 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.676136 | |
| I0525 04:33:47.463798 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.245902 | |
| I0525 04:33:47.463814 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 2.99764 (* 0.3 = 0.899291 loss) | |
| I0525 04:33:47.463829 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.21107 (* 0.3 = 0.363321 loss) | |
| I0525 04:33:47.463843 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 2.88947 (* 0.0272727 = 0.0788038 loss) | |
| I0525 04:33:47.463858 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.20424 (* 0.0272727 = 0.0873885 loss) | |
| I0525 04:33:47.463872 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.39828 (* 0.0272727 = 0.0926804 loss) | |
| I0525 04:33:47.463886 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.31359 (* 0.0272727 = 0.0903706 loss) | |
| I0525 04:33:47.463901 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 3.44813 (* 0.0272727 = 0.0940398 loss) | |
| I0525 04:33:47.463914 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 2.91147 (* 0.0272727 = 0.0794038 loss) | |
| I0525 04:33:47.463928 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 2.06043 (* 0.0272727 = 0.0561935 loss) | |
| I0525 04:33:47.463943 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 0.696244 (* 0.0272727 = 0.0189885 loss) | |
| I0525 04:33:47.463956 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.380352 (* 0.0272727 = 0.0103732 loss) | |
| I0525 04:33:47.463970 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.388004 (* 0.0272727 = 0.0105819 loss) | |
| I0525 04:33:47.463984 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.401543 (* 0.0272727 = 0.0109512 loss) | |
| I0525 04:33:47.464028 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.376872 (* 0.0272727 = 0.0102783 loss) | |
| I0525 04:33:47.464045 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.470881 (* 0.0272727 = 0.0128422 loss) | |
| I0525 04:33:47.464058 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.396428 (* 0.0272727 = 0.0108117 loss) | |
| I0525 04:33:47.464072 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.547539 (* 0.0272727 = 0.0149329 loss) | |
| I0525 04:33:47.464098 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.582506 (* 0.0272727 = 0.0158865 loss) | |
| I0525 04:33:47.464126 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.529664 (* 0.0272727 = 0.0144454 loss) | |
| I0525 04:33:47.464143 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.594326 (* 0.0272727 = 0.0162089 loss) | |
| I0525 04:33:47.464157 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.762178 (* 0.0272727 = 0.0207867 loss) | |
| I0525 04:33:47.464170 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.701677 (* 0.0272727 = 0.0191366 loss) | |
| I0525 04:33:47.464187 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.0147884 (* 0.0272727 = 0.00040332 loss) | |
| I0525 04:33:47.464210 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.0140148 (* 0.0272727 = 0.000382222 loss) | |
| I0525 04:33:47.464224 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.0983607 | |
| I0525 04:33:47.464242 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0.125 | |
| I0525 04:33:47.464257 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0 | |
| I0525 04:33:47.464270 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0 | |
| I0525 04:33:47.464282 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0 | |
| I0525 04:33:47.464293 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0 | |
| I0525 04:33:47.464306 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.25 | |
| I0525 04:33:47.464318 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.625 | |
| I0525 04:33:47.464330 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.875 | |
| I0525 04:33:47.464342 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 0.875 | |
| I0525 04:33:47.464354 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 0.875 | |
| I0525 04:33:47.464366 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 0.875 | |
| I0525 04:33:47.464378 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 0.875 | |
| I0525 04:33:47.464390 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 0.875 | |
| I0525 04:33:47.464402 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 0.875 | |
| I0525 04:33:47.464414 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 0.875 | |
| I0525 04:33:47.464426 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 0.875 | |
| I0525 04:33:47.464439 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 0.875 | |
| I0525 04:33:47.464450 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 0.875 | |
| I0525 04:33:47.464462 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 0.875 | |
| I0525 04:33:47.464474 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 0.875 | |
| I0525 04:33:47.464486 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 04:33:47.464498 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 04:33:47.464509 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.676136 | |
| I0525 04:33:47.464521 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.245902 | |
| I0525 04:33:47.464535 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.11025 (* 0.3 = 0.933076 loss) | |
| I0525 04:33:47.464550 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.18985 (* 0.3 = 0.356954 loss) | |
| I0525 04:33:47.464576 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 2.89456 (* 0.0272727 = 0.0789426 loss) | |
| I0525 04:33:47.464591 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 2.85149 (* 0.0272727 = 0.077768 loss) | |
| I0525 04:33:47.464606 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.23511 (* 0.0272727 = 0.0882303 loss) | |
| I0525 04:33:47.464619 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.39444 (* 0.0272727 = 0.0925756 loss) | |
| I0525 04:33:47.464633 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 3.45539 (* 0.0272727 = 0.0942378 loss) | |
| I0525 04:33:47.464646 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 3.06186 (* 0.0272727 = 0.0835053 loss) | |
| I0525 04:33:47.464660 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 2.26448 (* 0.0272727 = 0.0617586 loss) | |
| I0525 04:33:47.464674 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 0.631294 (* 0.0272727 = 0.0172171 loss) | |
| I0525 04:33:47.464689 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.445314 (* 0.0272727 = 0.0121449 loss) | |
| I0525 04:33:47.464702 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.35271 (* 0.0272727 = 0.00961936 loss) | |
| I0525 04:33:47.464716 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.410395 (* 0.0272727 = 0.0111926 loss) | |
| I0525 04:33:47.464730 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.502393 (* 0.0272727 = 0.0137016 loss) | |
| I0525 04:33:47.464752 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.671797 (* 0.0272727 = 0.0183217 loss) | |
| I0525 04:33:47.464771 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.542856 (* 0.0272727 = 0.0148052 loss) | |
| I0525 04:33:47.464787 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.598881 (* 0.0272727 = 0.0163331 loss) | |
| I0525 04:33:47.464807 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.728908 (* 0.0272727 = 0.0198793 loss) | |
| I0525 04:33:47.464825 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.56225 (* 0.0272727 = 0.0153341 loss) | |
| I0525 04:33:47.464840 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.82687 (* 0.0272727 = 0.022551 loss) | |
| I0525 04:33:47.464854 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.885772 (* 0.0272727 = 0.0241574 loss) | |
| I0525 04:33:47.464869 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 1.02538 (* 0.0272727 = 0.027965 loss) | |
| I0525 04:33:47.464882 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.0215737 (* 0.0272727 = 0.000588374 loss) | |
| I0525 04:33:47.464896 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.00956966 (* 0.0272727 = 0.000260991 loss) | |
| I0525 04:33:47.464910 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.0819672 | |
| I0525 04:33:47.464922 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0 | |
| I0525 04:33:47.464931 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0.125 | |
| I0525 04:33:47.464942 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0.125 | |
| I0525 04:33:47.464956 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0 | |
| I0525 04:33:47.464967 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.125 | |
| I0525 04:33:47.464978 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.375 | |
| I0525 04:33:47.464990 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.625 | |
| I0525 04:33:47.465003 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.875 | |
| I0525 04:33:47.465014 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 0.875 | |
| I0525 04:33:47.465025 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 0.875 | |
| I0525 04:33:47.465037 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 0.875 | |
| I0525 04:33:47.465049 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 0.875 | |
| I0525 04:33:47.465061 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 0.875 | |
| I0525 04:33:47.465085 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 0.875 | |
| I0525 04:33:47.465097 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 0.875 | |
| I0525 04:33:47.465109 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 0.875 | |
| I0525 04:33:47.465142 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 0.875 | |
| I0525 04:33:47.465157 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 0.875 | |
| I0525 04:33:47.465168 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 0.875 | |
| I0525 04:33:47.465181 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 0.875 | |
| I0525 04:33:47.465193 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 04:33:47.465205 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 04:33:47.465216 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.664773 | |
| I0525 04:33:47.465229 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.262295 | |
| I0525 04:33:47.465243 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 2.95942 (* 1 = 2.95942 loss) | |
| I0525 04:33:47.465257 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.17153 (* 1 = 1.17153 loss) | |
| I0525 04:33:47.465271 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 2.565 (* 0.0909091 = 0.233182 loss) | |
| I0525 04:33:47.465288 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 2.68415 (* 0.0909091 = 0.244014 loss) | |
| I0525 04:33:47.465311 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.2363 (* 0.0909091 = 0.294209 loss) | |
| I0525 04:33:47.465325 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.19628 (* 0.0909091 = 0.290571 loss) | |
| I0525 04:33:47.465348 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 3.04095 (* 0.0909091 = 0.27645 loss) | |
| I0525 04:33:47.465363 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 2.40104 (* 0.0909091 = 0.218276 loss) | |
| I0525 04:33:47.465376 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 1.82544 (* 0.0909091 = 0.165949 loss) | |
| I0525 04:33:47.465390 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.639629 (* 0.0909091 = 0.0581481 loss) | |
| I0525 04:33:47.465404 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.329263 (* 0.0909091 = 0.029933 loss) | |
| I0525 04:33:47.465418 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.293536 (* 0.0909091 = 0.026685 loss) | |
| I0525 04:33:47.465432 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.434204 (* 0.0909091 = 0.039473 loss) | |
| I0525 04:33:47.465446 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.317428 (* 0.0909091 = 0.0288571 loss) | |
| I0525 04:33:47.465461 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.57442 (* 0.0909091 = 0.05222 loss) | |
| I0525 04:33:47.465476 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.665187 (* 0.0909091 = 0.0604715 loss) | |
| I0525 04:33:47.465489 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.674674 (* 0.0909091 = 0.061334 loss) | |
| I0525 04:33:47.465503 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.676936 (* 0.0909091 = 0.0615396 loss) | |
| I0525 04:33:47.465517 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.726908 (* 0.0909091 = 0.0660826 loss) | |
| I0525 04:33:47.465530 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.680123 (* 0.0909091 = 0.0618294 loss) | |
| I0525 04:33:47.465544 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.747721 (* 0.0909091 = 0.0679747 loss) | |
| I0525 04:33:47.465559 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.903039 (* 0.0909091 = 0.0820944 loss) | |
| I0525 04:33:47.465574 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.000866617 (* 0.0909091 = 7.87834e-05 loss) | |
| I0525 04:33:47.465587 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.000338962 (* 0.0909091 = 3.08148e-05 loss) | |
| I0525 04:33:47.465600 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 04:33:47.465625 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 04:33:47.465637 5272 solver.cpp:245] Train net output #149: total_confidence = 4.79402e-07 | |
| I0525 04:33:47.465649 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 4.62061e-06 | |
| I0525 04:33:47.465662 5272 sgd_solver.cpp:106] Iteration 20000, lr = 0.001 | |
| I0525 04:35:17.181689 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 30.4282 > 30) by scale factor 0.985927 | |
| I0525 04:36:00.312917 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 46.3671 > 30) by scale factor 0.647011 | |
| I0525 04:38:00.449288 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 30.9566 > 30) by scale factor 0.969099 | |
| I0525 04:39:10.536027 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 44.3731 > 30) by scale factor 0.676085 | |
| I0525 04:39:16.710968 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 36.7165 > 30) by scale factor 0.817072 | |
| I0525 04:40:12.535034 5272 solver.cpp:229] Iteration 20500, loss = 9.7067 | |
| I0525 04:40:12.535162 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.116667 | |
| I0525 04:40:12.535184 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0 | |
| I0525 04:40:12.535197 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0525 04:40:12.535210 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0.125 | |
| I0525 04:40:12.535224 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.375 | |
| I0525 04:40:12.535238 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.375 | |
| I0525 04:40:12.535250 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.5 | |
| I0525 04:40:12.535262 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.5 | |
| I0525 04:40:12.535275 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.75 | |
| I0525 04:40:12.535287 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 0.75 | |
| I0525 04:40:12.535300 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 0.75 | |
| I0525 04:40:12.535313 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 0.75 | |
| I0525 04:40:12.535326 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 0.75 | |
| I0525 04:40:12.535339 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 0.875 | |
| I0525 04:40:12.535351 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 0.875 | |
| I0525 04:40:12.535363 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 0.875 | |
| I0525 04:40:12.535375 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 0.875 | |
| I0525 04:40:12.535387 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 0.875 | |
| I0525 04:40:12.535399 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 0.875 | |
| I0525 04:40:12.535411 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 0.875 | |
| I0525 04:40:12.535423 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 04:40:12.535435 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 04:40:12.535447 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 04:40:12.535459 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.670455 | |
| I0525 04:40:12.535471 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.2 | |
| I0525 04:40:12.535488 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.01785 (* 0.3 = 0.905354 loss) | |
| I0525 04:40:12.535502 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.22847 (* 0.3 = 0.368542 loss) | |
| I0525 04:40:12.535517 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.24312 (* 0.0272727 = 0.0884487 loss) | |
| I0525 04:40:12.535531 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 2.93556 (* 0.0272727 = 0.0800607 loss) | |
| I0525 04:40:12.535545 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.25044 (* 0.0272727 = 0.0886485 loss) | |
| I0525 04:40:12.535559 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 2.9032 (* 0.0272727 = 0.0791782 loss) | |
| I0525 04:40:12.535573 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 2.2301 (* 0.0272727 = 0.0608209 loss) | |
| I0525 04:40:12.535588 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 1.86725 (* 0.0272727 = 0.0509249 loss) | |
| I0525 04:40:12.535600 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 2.32501 (* 0.0272727 = 0.0634093 loss) | |
| I0525 04:40:12.535614 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 0.778871 (* 0.0272727 = 0.0212419 loss) | |
| I0525 04:40:12.535629 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.890573 (* 0.0272727 = 0.0242884 loss) | |
| I0525 04:40:12.535642 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.828401 (* 0.0272727 = 0.0225928 loss) | |
| I0525 04:40:12.535656 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 1.38788 (* 0.0272727 = 0.0378514 loss) | |
| I0525 04:40:12.535670 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 1.0536 (* 0.0272727 = 0.0287346 loss) | |
| I0525 04:40:12.535703 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.640633 (* 0.0272727 = 0.0174718 loss) | |
| I0525 04:40:12.535719 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.678007 (* 0.0272727 = 0.0184911 loss) | |
| I0525 04:40:12.535733 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 1.02732 (* 0.0272727 = 0.0280178 loss) | |
| I0525 04:40:12.535748 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.865885 (* 0.0272727 = 0.023615 loss) | |
| I0525 04:40:12.535761 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 1.30067 (* 0.0272727 = 0.0354729 loss) | |
| I0525 04:40:12.535775 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 1.38763 (* 0.0272727 = 0.0378443 loss) | |
| I0525 04:40:12.535789 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 1.21311 (* 0.0272727 = 0.0330849 loss) | |
| I0525 04:40:12.535804 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.00473243 (* 0.0272727 = 0.000129066 loss) | |
| I0525 04:40:12.535817 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.00159194 (* 0.0272727 = 4.34165e-05 loss) | |
| I0525 04:40:12.535831 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.000666336 (* 0.0272727 = 1.81728e-05 loss) | |
| I0525 04:40:12.535845 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.0666667 | |
| I0525 04:40:12.535856 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0.125 | |
| I0525 04:40:12.535868 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0.125 | |
| I0525 04:40:12.535883 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0.25 | |
| I0525 04:40:12.535897 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0.25 | |
| I0525 04:40:12.535908 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.375 | |
| I0525 04:40:12.535920 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.375 | |
| I0525 04:40:12.535933 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.5 | |
| I0525 04:40:12.535944 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.75 | |
| I0525 04:40:12.535956 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 0.75 | |
| I0525 04:40:12.535969 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 0.75 | |
| I0525 04:40:12.535980 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 0.75 | |
| I0525 04:40:12.535992 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 0.75 | |
| I0525 04:40:12.536005 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 0.875 | |
| I0525 04:40:12.536016 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 0.875 | |
| I0525 04:40:12.536028 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 0.875 | |
| I0525 04:40:12.536041 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 0.875 | |
| I0525 04:40:12.536052 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 0.875 | |
| I0525 04:40:12.536064 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 0.875 | |
| I0525 04:40:12.536077 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 0.875 | |
| I0525 04:40:12.536087 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 04:40:12.536099 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 04:40:12.536110 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 04:40:12.536123 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.664773 | |
| I0525 04:40:12.536134 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.25 | |
| I0525 04:40:12.536147 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.18994 (* 0.3 = 0.956981 loss) | |
| I0525 04:40:12.536161 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.22881 (* 0.3 = 0.368643 loss) | |
| I0525 04:40:12.536177 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 2.6376 (* 0.0272727 = 0.0719345 loss) | |
| I0525 04:40:12.536192 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 2.97868 (* 0.0272727 = 0.0812366 loss) | |
| I0525 04:40:12.536216 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 2.9217 (* 0.0272727 = 0.0796827 loss) | |
| I0525 04:40:12.536231 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.03985 (* 0.0272727 = 0.0829051 loss) | |
| I0525 04:40:12.536245 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 2.0999 (* 0.0272727 = 0.0572701 loss) | |
| I0525 04:40:12.536259 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 2.28378 (* 0.0272727 = 0.0622848 loss) | |
| I0525 04:40:12.536273 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 2.1726 (* 0.0272727 = 0.0592528 loss) | |
| I0525 04:40:12.536288 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 1.03798 (* 0.0272727 = 0.0283087 loss) | |
| I0525 04:40:12.536300 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 1.01961 (* 0.0272727 = 0.0278076 loss) | |
| I0525 04:40:12.536314 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.95397 (* 0.0272727 = 0.0260174 loss) | |
| I0525 04:40:12.536329 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 1.09445 (* 0.0272727 = 0.0298486 loss) | |
| I0525 04:40:12.536342 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.880937 (* 0.0272727 = 0.0240256 loss) | |
| I0525 04:40:12.536356 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.564397 (* 0.0272727 = 0.0153926 loss) | |
| I0525 04:40:12.536370 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.61983 (* 0.0272727 = 0.0169044 loss) | |
| I0525 04:40:12.536384 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.783707 (* 0.0272727 = 0.0213738 loss) | |
| I0525 04:40:12.536398 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.518647 (* 0.0272727 = 0.0141449 loss) | |
| I0525 04:40:12.536412 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.987281 (* 0.0272727 = 0.0269258 loss) | |
| I0525 04:40:12.536425 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 1.05975 (* 0.0272727 = 0.0289024 loss) | |
| I0525 04:40:12.536439 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.96476 (* 0.0272727 = 0.0263116 loss) | |
| I0525 04:40:12.536453 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.00230762 (* 0.0272727 = 6.2935e-05 loss) | |
| I0525 04:40:12.536468 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.00268712 (* 0.0272727 = 7.32851e-05 loss) | |
| I0525 04:40:12.536481 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.00171611 (* 0.0272727 = 4.68031e-05 loss) | |
| I0525 04:40:12.536494 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.0833333 | |
| I0525 04:40:12.536505 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0 | |
| I0525 04:40:12.536517 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0 | |
| I0525 04:40:12.536528 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0.125 | |
| I0525 04:40:12.536540 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.25 | |
| I0525 04:40:12.536552 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.375 | |
| I0525 04:40:12.536564 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.5 | |
| I0525 04:40:12.536576 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.625 | |
| I0525 04:40:12.536588 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.75 | |
| I0525 04:40:12.536600 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 0.75 | |
| I0525 04:40:12.536612 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 0.75 | |
| I0525 04:40:12.536624 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 0.75 | |
| I0525 04:40:12.536635 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 0.75 | |
| I0525 04:40:12.536648 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 0.875 | |
| I0525 04:40:12.536659 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 0.875 | |
| I0525 04:40:12.536671 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 0.875 | |
| I0525 04:40:12.536682 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 0.875 | |
| I0525 04:40:12.536705 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 0.875 | |
| I0525 04:40:12.536717 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 0.875 | |
| I0525 04:40:12.536730 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 0.875 | |
| I0525 04:40:12.536741 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 04:40:12.536753 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 04:40:12.536764 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 04:40:12.536777 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.676136 | |
| I0525 04:40:12.536788 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.3 | |
| I0525 04:40:12.536803 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.01044 (* 1 = 3.01044 loss) | |
| I0525 04:40:12.536816 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.18061 (* 1 = 1.18061 loss) | |
| I0525 04:40:12.536829 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 2.47921 (* 0.0909091 = 0.225383 loss) | |
| I0525 04:40:12.536844 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.00676 (* 0.0909091 = 0.273342 loss) | |
| I0525 04:40:12.536857 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.0504 (* 0.0909091 = 0.277309 loss) | |
| I0525 04:40:12.536871 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 2.95546 (* 0.0909091 = 0.268678 loss) | |
| I0525 04:40:12.536885 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 1.98036 (* 0.0909091 = 0.180033 loss) | |
| I0525 04:40:12.536900 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 2.02785 (* 0.0909091 = 0.18435 loss) | |
| I0525 04:40:12.536912 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 1.77415 (* 0.0909091 = 0.161287 loss) | |
| I0525 04:40:12.536929 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.792669 (* 0.0909091 = 0.0720608 loss) | |
| I0525 04:40:12.536944 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.876183 (* 0.0909091 = 0.079653 loss) | |
| I0525 04:40:12.536958 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.846718 (* 0.0909091 = 0.0769743 loss) | |
| I0525 04:40:12.536972 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.700301 (* 0.0909091 = 0.0636638 loss) | |
| I0525 04:40:12.536985 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.68302 (* 0.0909091 = 0.0620927 loss) | |
| I0525 04:40:12.537001 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.551978 (* 0.0909091 = 0.0501798 loss) | |
| I0525 04:40:12.537011 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.565866 (* 0.0909091 = 0.0514423 loss) | |
| I0525 04:40:12.537025 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.718369 (* 0.0909091 = 0.0653063 loss) | |
| I0525 04:40:12.537039 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.7799 (* 0.0909091 = 0.0709 loss) | |
| I0525 04:40:12.537053 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.617818 (* 0.0909091 = 0.0561653 loss) | |
| I0525 04:40:12.537067 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.96885 (* 0.0909091 = 0.0880772 loss) | |
| I0525 04:40:12.537081 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 1.08615 (* 0.0909091 = 0.098741 loss) | |
| I0525 04:40:12.537096 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00462998 (* 0.0909091 = 0.000420907 loss) | |
| I0525 04:40:12.537109 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00122286 (* 0.0909091 = 0.000111169 loss) | |
| I0525 04:40:12.537142 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.000808319 (* 0.0909091 = 7.34836e-05 loss) | |
| I0525 04:40:12.537155 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 04:40:12.537168 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 04:40:12.537179 5272 solver.cpp:245] Train net output #149: total_confidence = 0.000137818 | |
| I0525 04:40:12.537202 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 0.00027517 | |
| I0525 04:40:12.537217 5272 sgd_solver.cpp:106] Iteration 20500, lr = 0.001 | |
| I0525 04:43:26.946056 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 30.5656 > 30) by scale factor 0.981495 | |
| I0525 04:46:37.703830 5272 solver.cpp:229] Iteration 21000, loss = 9.69837 | |
| I0525 04:46:37.703990 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0681818 | |
| I0525 04:46:37.704013 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0 | |
| I0525 04:46:37.704028 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0.125 | |
| I0525 04:46:37.704041 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0.125 | |
| I0525 04:46:37.704053 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0 | |
| I0525 04:46:37.704066 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.625 | |
| I0525 04:46:37.704078 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.375 | |
| I0525 04:46:37.704090 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.875 | |
| I0525 04:46:37.704103 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 1 | |
| I0525 04:46:37.704116 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 1 | |
| I0525 04:46:37.704128 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 1 | |
| I0525 04:46:37.704141 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 04:46:37.704154 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 04:46:37.704166 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 04:46:37.704177 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 04:46:37.704190 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 04:46:37.704201 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 04:46:37.704213 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 04:46:37.704226 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 04:46:37.704237 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 04:46:37.704249 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 04:46:37.704260 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 04:46:37.704272 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 04:46:37.704284 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.75 | |
| I0525 04:46:37.704298 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.227273 | |
| I0525 04:46:37.704313 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.21026 (* 0.3 = 0.963079 loss) | |
| I0525 04:46:37.704329 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 0.927103 (* 0.3 = 0.278131 loss) | |
| I0525 04:46:37.704344 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.34841 (* 0.0272727 = 0.0913202 loss) | |
| I0525 04:46:37.704357 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.36648 (* 0.0272727 = 0.091813 loss) | |
| I0525 04:46:37.704371 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.08953 (* 0.0272727 = 0.08426 loss) | |
| I0525 04:46:37.704385 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.81931 (* 0.0272727 = 0.104163 loss) | |
| I0525 04:46:37.704399 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 2.25283 (* 0.0272727 = 0.0614409 loss) | |
| I0525 04:46:37.704414 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 2.50128 (* 0.0272727 = 0.0682166 loss) | |
| I0525 04:46:37.704428 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 0.806326 (* 0.0272727 = 0.0219907 loss) | |
| I0525 04:46:37.704443 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 0.0654782 (* 0.0272727 = 0.00178577 loss) | |
| I0525 04:46:37.704458 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.0437953 (* 0.0272727 = 0.00119442 loss) | |
| I0525 04:46:37.704473 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.0237511 (* 0.0272727 = 0.000647758 loss) | |
| I0525 04:46:37.704488 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.0295489 (* 0.0272727 = 0.000805878 loss) | |
| I0525 04:46:37.704501 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.0268581 (* 0.0272727 = 0.000732494 loss) | |
| I0525 04:46:37.704516 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.0174152 (* 0.0272727 = 0.000474959 loss) | |
| I0525 04:46:37.704552 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.0240333 (* 0.0272727 = 0.000655453 loss) | |
| I0525 04:46:37.704567 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0123189 (* 0.0272727 = 0.000335969 loss) | |
| I0525 04:46:37.704581 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.0077471 (* 0.0272727 = 0.000211285 loss) | |
| I0525 04:46:37.704596 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.0160953 (* 0.0272727 = 0.000438963 loss) | |
| I0525 04:46:37.704609 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.00849851 (* 0.0272727 = 0.000231778 loss) | |
| I0525 04:46:37.704624 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.0111119 (* 0.0272727 = 0.000303051 loss) | |
| I0525 04:46:37.704638 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.00658314 (* 0.0272727 = 0.00017954 loss) | |
| I0525 04:46:37.704653 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.00659746 (* 0.0272727 = 0.000179931 loss) | |
| I0525 04:46:37.704666 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.00511409 (* 0.0272727 = 0.000139475 loss) | |
| I0525 04:46:37.704679 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.0681818 | |
| I0525 04:46:37.704691 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0.125 | |
| I0525 04:46:37.704704 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0.125 | |
| I0525 04:46:37.704715 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0.25 | |
| I0525 04:46:37.704727 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0 | |
| I0525 04:46:37.704740 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.25 | |
| I0525 04:46:37.704751 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.375 | |
| I0525 04:46:37.704763 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.875 | |
| I0525 04:46:37.704776 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 1 | |
| I0525 04:46:37.704787 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 1 | |
| I0525 04:46:37.704798 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 1 | |
| I0525 04:46:37.704810 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 04:46:37.704821 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 04:46:37.704833 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 04:46:37.704844 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 04:46:37.704856 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 04:46:37.704869 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 04:46:37.704884 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 04:46:37.704895 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 04:46:37.704906 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 04:46:37.704918 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 04:46:37.704929 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 04:46:37.704941 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 04:46:37.704952 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.761364 | |
| I0525 04:46:37.704964 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.204545 | |
| I0525 04:46:37.704979 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.19877 (* 0.3 = 0.959631 loss) | |
| I0525 04:46:37.704989 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 0.874753 (* 0.3 = 0.262426 loss) | |
| I0525 04:46:37.705008 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.04544 (* 0.0272727 = 0.0830575 loss) | |
| I0525 04:46:37.705021 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 3.176 (* 0.0272727 = 0.0866181 loss) | |
| I0525 04:46:37.705046 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.04488 (* 0.0272727 = 0.0830422 loss) | |
| I0525 04:46:37.705061 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.78814 (* 0.0272727 = 0.103313 loss) | |
| I0525 04:46:37.705075 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 2.98152 (* 0.0272727 = 0.0813142 loss) | |
| I0525 04:46:37.705090 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 2.46513 (* 0.0272727 = 0.0672308 loss) | |
| I0525 04:46:37.705102 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 0.792969 (* 0.0272727 = 0.0216264 loss) | |
| I0525 04:46:37.705129 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 0.087227 (* 0.0272727 = 0.00237892 loss) | |
| I0525 04:46:37.705147 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.0256489 (* 0.0272727 = 0.000699516 loss) | |
| I0525 04:46:37.705162 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.0297102 (* 0.0272727 = 0.000810277 loss) | |
| I0525 04:46:37.705175 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.0193213 (* 0.0272727 = 0.000526944 loss) | |
| I0525 04:46:37.705189 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.00876074 (* 0.0272727 = 0.000238929 loss) | |
| I0525 04:46:37.705204 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.00725171 (* 0.0272727 = 0.000197774 loss) | |
| I0525 04:46:37.705217 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.00767833 (* 0.0272727 = 0.000209409 loss) | |
| I0525 04:46:37.705231 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.0109744 (* 0.0272727 = 0.000299303 loss) | |
| I0525 04:46:37.705245 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.00755705 (* 0.0272727 = 0.000206101 loss) | |
| I0525 04:46:37.705260 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.00389646 (* 0.0272727 = 0.000106267 loss) | |
| I0525 04:46:37.705273 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.00747994 (* 0.0272727 = 0.000203998 loss) | |
| I0525 04:46:37.705287 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.00434774 (* 0.0272727 = 0.000118575 loss) | |
| I0525 04:46:37.705302 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.00410322 (* 0.0272727 = 0.000111906 loss) | |
| I0525 04:46:37.705315 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.00305338 (* 0.0272727 = 8.32739e-05 loss) | |
| I0525 04:46:37.705329 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.00384496 (* 0.0272727 = 0.000104863 loss) | |
| I0525 04:46:37.705341 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.0454545 | |
| I0525 04:46:37.705353 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.125 | |
| I0525 04:46:37.705365 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0.25 | |
| I0525 04:46:37.705377 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0.125 | |
| I0525 04:46:37.705389 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0 | |
| I0525 04:46:37.705401 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.25 | |
| I0525 04:46:37.705413 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.375 | |
| I0525 04:46:37.705425 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.875 | |
| I0525 04:46:37.705436 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 1 | |
| I0525 04:46:37.705448 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 1 | |
| I0525 04:46:37.705459 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 1 | |
| I0525 04:46:37.705471 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 04:46:37.705483 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 04:46:37.705494 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 04:46:37.705507 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 04:46:37.705518 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 04:46:37.705529 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 04:46:37.705551 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 04:46:37.705564 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 04:46:37.705576 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 04:46:37.705588 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 04:46:37.705600 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 04:46:37.705611 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 04:46:37.705623 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.761364 | |
| I0525 04:46:37.705636 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.204545 | |
| I0525 04:46:37.705649 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.06587 (* 1 = 3.06587 loss) | |
| I0525 04:46:37.705663 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 0.810092 (* 1 = 0.810092 loss) | |
| I0525 04:46:37.705677 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 2.91463 (* 0.0909091 = 0.264967 loss) | |
| I0525 04:46:37.705692 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 2.99078 (* 0.0909091 = 0.271889 loss) | |
| I0525 04:46:37.705705 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 2.91583 (* 0.0909091 = 0.265075 loss) | |
| I0525 04:46:37.705719 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.50675 (* 0.0909091 = 0.318795 loss) | |
| I0525 04:46:37.705734 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 2.50299 (* 0.0909091 = 0.227544 loss) | |
| I0525 04:46:37.705744 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 2.22914 (* 0.0909091 = 0.202649 loss) | |
| I0525 04:46:37.705757 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 0.589085 (* 0.0909091 = 0.0535532 loss) | |
| I0525 04:46:37.705771 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.0697591 (* 0.0909091 = 0.00634174 loss) | |
| I0525 04:46:37.705785 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.0314684 (* 0.0909091 = 0.00286076 loss) | |
| I0525 04:46:37.705799 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.0136882 (* 0.0909091 = 0.00124438 loss) | |
| I0525 04:46:37.705813 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.00937546 (* 0.0909091 = 0.000852315 loss) | |
| I0525 04:46:37.705827 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.00902094 (* 0.0909091 = 0.000820086 loss) | |
| I0525 04:46:37.705842 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.00440815 (* 0.0909091 = 0.000400741 loss) | |
| I0525 04:46:37.705855 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.00596475 (* 0.0909091 = 0.00054225 loss) | |
| I0525 04:46:37.705869 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.00431966 (* 0.0909091 = 0.000392697 loss) | |
| I0525 04:46:37.705883 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.00409816 (* 0.0909091 = 0.00037256 loss) | |
| I0525 04:46:37.705896 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.00219154 (* 0.0909091 = 0.000199231 loss) | |
| I0525 04:46:37.705910 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.00198977 (* 0.0909091 = 0.000180888 loss) | |
| I0525 04:46:37.705924 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00170016 (* 0.0909091 = 0.00015456 loss) | |
| I0525 04:46:37.705941 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00145705 (* 0.0909091 = 0.000132459 loss) | |
| I0525 04:46:37.705955 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.000985738 (* 0.0909091 = 8.96125e-05 loss) | |
| I0525 04:46:37.705970 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.00116641 (* 0.0909091 = 0.000106037 loss) | |
| I0525 04:46:37.705981 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 04:46:37.705993 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 04:46:37.706004 5272 solver.cpp:245] Train net output #149: total_confidence = 0.000343258 | |
| I0525 04:46:37.706027 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 0.000922688 | |
| I0525 04:46:37.706040 5272 sgd_solver.cpp:106] Iteration 21000, lr = 0.001 | |
| I0525 04:49:05.994966 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 42.3085 > 30) by scale factor 0.709078 | |
| I0525 04:49:28.350611 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 35.6114 > 30) by scale factor 0.842428 | |
| I0525 04:50:59.216051 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 41.9117 > 30) by scale factor 0.71579 | |
| I0525 04:51:45.416169 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 43.021 > 30) by scale factor 0.697334 | |
| I0525 04:53:02.799557 5272 solver.cpp:229] Iteration 21500, loss = 9.68776 | |
| I0525 04:53:02.799707 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0945946 | |
| I0525 04:53:02.799728 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.25 | |
| I0525 04:53:02.799742 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0525 04:53:02.799756 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0525 04:53:02.799767 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0 | |
| I0525 04:53:02.799779 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0 | |
| I0525 04:53:02.799792 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.25 | |
| I0525 04:53:02.799804 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.25 | |
| I0525 04:53:02.799818 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.375 | |
| I0525 04:53:02.799829 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 0.625 | |
| I0525 04:53:02.799842 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 0.625 | |
| I0525 04:53:02.799855 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 0.75 | |
| I0525 04:53:02.799868 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 0.75 | |
| I0525 04:53:02.799885 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 0.75 | |
| I0525 04:53:02.799896 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 0.75 | |
| I0525 04:53:02.799909 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 0.75 | |
| I0525 04:53:02.799921 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 0.875 | |
| I0525 04:53:02.799933 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 0.875 | |
| I0525 04:53:02.799947 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 04:53:02.799957 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 04:53:02.799969 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 04:53:02.799981 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 04:53:02.799993 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 04:53:02.800005 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.590909 | |
| I0525 04:53:02.800017 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.189189 | |
| I0525 04:53:02.800034 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.05676 (* 0.3 = 0.917029 loss) | |
| I0525 04:53:02.800048 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.53411 (* 0.3 = 0.460232 loss) | |
| I0525 04:53:02.800062 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.50438 (* 0.0272727 = 0.095574 loss) | |
| I0525 04:53:02.800076 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.68488 (* 0.0272727 = 0.100497 loss) | |
| I0525 04:53:02.800091 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.22525 (* 0.0272727 = 0.0879613 loss) | |
| I0525 04:53:02.800106 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 2.83075 (* 0.0272727 = 0.0772022 loss) | |
| I0525 04:53:02.800119 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 2.94681 (* 0.0272727 = 0.0803675 loss) | |
| I0525 04:53:02.800133 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 2.86366 (* 0.0272727 = 0.0780997 loss) | |
| I0525 04:53:02.800148 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 2.57267 (* 0.0272727 = 0.0701636 loss) | |
| I0525 04:53:02.800163 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 2.32217 (* 0.0272727 = 0.0633319 loss) | |
| I0525 04:53:02.800176 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 1.44343 (* 0.0272727 = 0.0393663 loss) | |
| I0525 04:53:02.800190 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 1.71323 (* 0.0272727 = 0.0467244 loss) | |
| I0525 04:53:02.800204 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.882942 (* 0.0272727 = 0.0240802 loss) | |
| I0525 04:53:02.800218 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 1.19151 (* 0.0272727 = 0.0324959 loss) | |
| I0525 04:53:02.800256 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 1.06502 (* 0.0272727 = 0.029046 loss) | |
| I0525 04:53:02.800271 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 1.13025 (* 0.0272727 = 0.0308249 loss) | |
| I0525 04:53:02.800284 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 1.39899 (* 0.0272727 = 0.0381543 loss) | |
| I0525 04:53:02.800297 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 1.03353 (* 0.0272727 = 0.0281872 loss) | |
| I0525 04:53:02.800312 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 1.29911 (* 0.0272727 = 0.0354304 loss) | |
| I0525 04:53:02.800325 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0533758 (* 0.0272727 = 0.0014557 loss) | |
| I0525 04:53:02.800340 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.00925695 (* 0.0272727 = 0.000252462 loss) | |
| I0525 04:53:02.800354 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.0232706 (* 0.0272727 = 0.000634653 loss) | |
| I0525 04:53:02.800369 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.021859 (* 0.0272727 = 0.000596154 loss) | |
| I0525 04:53:02.800384 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.0263539 (* 0.0272727 = 0.000718742 loss) | |
| I0525 04:53:02.800395 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.162162 | |
| I0525 04:53:02.800407 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0 | |
| I0525 04:53:02.800420 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0 | |
| I0525 04:53:02.800431 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0.125 | |
| I0525 04:53:02.800443 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0 | |
| I0525 04:53:02.800454 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.25 | |
| I0525 04:53:02.800467 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.375 | |
| I0525 04:53:02.800478 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.25 | |
| I0525 04:53:02.800490 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.5 | |
| I0525 04:53:02.800503 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 0.625 | |
| I0525 04:53:02.800514 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 0.625 | |
| I0525 04:53:02.800526 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 0.75 | |
| I0525 04:53:02.800539 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 0.75 | |
| I0525 04:53:02.800550 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 0.75 | |
| I0525 04:53:02.800562 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 0.75 | |
| I0525 04:53:02.800575 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 0.75 | |
| I0525 04:53:02.800586 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 0.875 | |
| I0525 04:53:02.800598 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 0.875 | |
| I0525 04:53:02.800611 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 04:53:02.800622 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 04:53:02.800633 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 04:53:02.800645 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 04:53:02.800657 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 04:53:02.800669 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.625 | |
| I0525 04:53:02.800680 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.22973 | |
| I0525 04:53:02.800695 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.01866 (* 0.3 = 0.905598 loss) | |
| I0525 04:53:02.800709 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.46509 (* 0.3 = 0.439528 loss) | |
| I0525 04:53:02.800726 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.59095 (* 0.0272727 = 0.0979351 loss) | |
| I0525 04:53:02.800740 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 3.65614 (* 0.0272727 = 0.0997128 loss) | |
| I0525 04:53:02.800766 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.19446 (* 0.0272727 = 0.0871216 loss) | |
| I0525 04:53:02.800781 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.58929 (* 0.0272727 = 0.0978896 loss) | |
| I0525 04:53:02.800796 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 2.5329 (* 0.0272727 = 0.0690791 loss) | |
| I0525 04:53:02.800808 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 2.96185 (* 0.0272727 = 0.0807777 loss) | |
| I0525 04:53:02.800822 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 2.86447 (* 0.0272727 = 0.0781218 loss) | |
| I0525 04:53:02.800837 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 2.65774 (* 0.0272727 = 0.0724838 loss) | |
| I0525 04:53:02.800849 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 1.44962 (* 0.0272727 = 0.039535 loss) | |
| I0525 04:53:02.800863 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 1.74077 (* 0.0272727 = 0.0474756 loss) | |
| I0525 04:53:02.800878 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.71616 (* 0.0272727 = 0.0195316 loss) | |
| I0525 04:53:02.800891 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.992351 (* 0.0272727 = 0.0270641 loss) | |
| I0525 04:53:02.800905 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 1.1657 (* 0.0272727 = 0.0317919 loss) | |
| I0525 04:53:02.800920 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.94821 (* 0.0272727 = 0.0258603 loss) | |
| I0525 04:53:02.800936 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 1.50791 (* 0.0272727 = 0.0411249 loss) | |
| I0525 04:53:02.800951 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.936513 (* 0.0272727 = 0.0255413 loss) | |
| I0525 04:53:02.800964 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 1.13222 (* 0.0272727 = 0.0308787 loss) | |
| I0525 04:53:02.800978 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.0385646 (* 0.0272727 = 0.00105176 loss) | |
| I0525 04:53:02.800992 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.0227015 (* 0.0272727 = 0.000619133 loss) | |
| I0525 04:53:02.801007 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.014601 (* 0.0272727 = 0.00039821 loss) | |
| I0525 04:53:02.801020 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.020092 (* 0.0272727 = 0.000547965 loss) | |
| I0525 04:53:02.801034 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.0109967 (* 0.0272727 = 0.00029991 loss) | |
| I0525 04:53:02.801048 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.108108 | |
| I0525 04:53:02.801059 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0 | |
| I0525 04:53:02.801071 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0.375 | |
| I0525 04:53:02.801084 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0 | |
| I0525 04:53:02.801095 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.125 | |
| I0525 04:53:02.801107 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.125 | |
| I0525 04:53:02.801131 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.375 | |
| I0525 04:53:02.801146 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.25 | |
| I0525 04:53:02.801158 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.5 | |
| I0525 04:53:02.801170 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 0.625 | |
| I0525 04:53:02.801182 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 0.625 | |
| I0525 04:53:02.801194 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 0.75 | |
| I0525 04:53:02.801206 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 0.875 | |
| I0525 04:53:02.801218 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 0.75 | |
| I0525 04:53:02.801229 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 0.75 | |
| I0525 04:53:02.801241 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 0.75 | |
| I0525 04:53:02.801254 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 0.875 | |
| I0525 04:53:02.801277 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 0.875 | |
| I0525 04:53:02.801290 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 04:53:02.801302 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 04:53:02.801314 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 04:53:02.801326 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 04:53:02.801337 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 04:53:02.801349 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.602273 | |
| I0525 04:53:02.801362 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.256757 | |
| I0525 04:53:02.801378 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 2.93915 (* 1 = 2.93915 loss) | |
| I0525 04:53:02.801391 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.41913 (* 1 = 1.41913 loss) | |
| I0525 04:53:02.801405 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 3.08415 (* 0.0909091 = 0.280377 loss) | |
| I0525 04:53:02.801419 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.0482 (* 0.0909091 = 0.277109 loss) | |
| I0525 04:53:02.801434 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 2.9293 (* 0.0909091 = 0.2663 loss) | |
| I0525 04:53:02.801447 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.38845 (* 0.0909091 = 0.308041 loss) | |
| I0525 04:53:02.801461 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 2.76032 (* 0.0909091 = 0.250938 loss) | |
| I0525 04:53:02.801476 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 2.51969 (* 0.0909091 = 0.229063 loss) | |
| I0525 04:53:02.801488 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 2.58664 (* 0.0909091 = 0.235149 loss) | |
| I0525 04:53:02.801502 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 1.89863 (* 0.0909091 = 0.172603 loss) | |
| I0525 04:53:02.801517 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 1.7684 (* 0.0909091 = 0.160764 loss) | |
| I0525 04:53:02.801530 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 1.47611 (* 0.0909091 = 0.134192 loss) | |
| I0525 04:53:02.801543 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.832566 (* 0.0909091 = 0.0756878 loss) | |
| I0525 04:53:02.801558 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.849825 (* 0.0909091 = 0.0772568 loss) | |
| I0525 04:53:02.801571 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.787854 (* 0.0909091 = 0.0716231 loss) | |
| I0525 04:53:02.801585 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.782514 (* 0.0909091 = 0.0711376 loss) | |
| I0525 04:53:02.801599 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.935624 (* 0.0909091 = 0.0850568 loss) | |
| I0525 04:53:02.801614 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.61301 (* 0.0909091 = 0.0557282 loss) | |
| I0525 04:53:02.801627 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 1.00012 (* 0.0909091 = 0.0909201 loss) | |
| I0525 04:53:02.801641 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.0091183 (* 0.0909091 = 0.000828937 loss) | |
| I0525 04:53:02.801656 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00363059 (* 0.0909091 = 0.000330054 loss) | |
| I0525 04:53:02.801669 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00321613 (* 0.0909091 = 0.000292375 loss) | |
| I0525 04:53:02.801683 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00123788 (* 0.0909091 = 0.000112534 loss) | |
| I0525 04:53:02.801697 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.000677914 (* 0.0909091 = 6.16285e-05 loss) | |
| I0525 04:53:02.801709 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 04:53:02.801720 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 04:53:02.801731 5272 solver.cpp:245] Train net output #149: total_confidence = 1.08685e-07 | |
| I0525 04:53:02.801753 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 2.05321e-06 | |
| I0525 04:53:02.801770 5272 sgd_solver.cpp:106] Iteration 21500, lr = 0.001 | |
| I0525 04:57:20.314046 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 31.9544 > 30) by scale factor 0.938837 | |
| I0525 04:59:23.458575 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 33.0836 > 30) by scale factor 0.906793 | |
| I0525 04:59:27.304214 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 32.1085 > 30) by scale factor 0.934333 | |
| I0525 04:59:27.710850 5272 solver.cpp:229] Iteration 22000, loss = 9.6773 | |
| I0525 04:59:27.710909 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0677966 | |
| I0525 04:59:27.710928 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0 | |
| I0525 04:59:27.710942 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0525 04:59:27.710955 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0525 04:59:27.710968 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0 | |
| I0525 04:59:27.710980 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.125 | |
| I0525 04:59:27.710993 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0 | |
| I0525 04:59:27.711004 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.5 | |
| I0525 04:59:27.711017 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 0.75 | |
| I0525 04:59:27.711030 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 0.875 | |
| I0525 04:59:27.711042 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 0.875 | |
| I0525 04:59:27.711055 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 0.875 | |
| I0525 04:59:27.711067 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 0.875 | |
| I0525 04:59:27.711081 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 0.875 | |
| I0525 04:59:27.711092 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 0.875 | |
| I0525 04:59:27.711104 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 04:59:27.711117 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 04:59:27.711128 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 04:59:27.711140 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 04:59:27.711151 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 04:59:27.711163 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 04:59:27.711175 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 04:59:27.711187 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 04:59:27.711199 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.676136 | |
| I0525 04:59:27.711211 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.20339 | |
| I0525 04:59:27.711227 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.53925 (* 0.3 = 1.06178 loss) | |
| I0525 04:59:27.711241 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 1.31659 (* 0.3 = 0.394978 loss) | |
| I0525 04:59:27.711256 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.38175 (* 0.0272727 = 0.0922296 loss) | |
| I0525 04:59:27.711271 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.57231 (* 0.0272727 = 0.0974266 loss) | |
| I0525 04:59:27.711284 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.68043 (* 0.0272727 = 0.100375 loss) | |
| I0525 04:59:27.711298 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.23006 (* 0.0272727 = 0.0880927 loss) | |
| I0525 04:59:27.711313 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 3.80679 (* 0.0272727 = 0.103821 loss) | |
| I0525 04:59:27.711326 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 3.81571 (* 0.0272727 = 0.104065 loss) | |
| I0525 04:59:27.711340 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 2.41608 (* 0.0272727 = 0.0658932 loss) | |
| I0525 04:59:27.711354 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 1.38785 (* 0.0272727 = 0.0378505 loss) | |
| I0525 04:59:27.711369 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.566975 (* 0.0272727 = 0.0154629 loss) | |
| I0525 04:59:27.711382 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.487841 (* 0.0272727 = 0.0133047 loss) | |
| I0525 04:59:27.711396 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.534627 (* 0.0272727 = 0.0145807 loss) | |
| I0525 04:59:27.711447 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.709563 (* 0.0272727 = 0.0193517 loss) | |
| I0525 04:59:27.711462 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.534905 (* 0.0272727 = 0.0145883 loss) | |
| I0525 04:59:27.711477 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.676085 (* 0.0272727 = 0.0184387 loss) | |
| I0525 04:59:27.711491 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.0711489 (* 0.0272727 = 0.00194042 loss) | |
| I0525 04:59:27.711505 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.035535 (* 0.0272727 = 0.000969137 loss) | |
| I0525 04:59:27.711519 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.01721 (* 0.0272727 = 0.000469364 loss) | |
| I0525 04:59:27.711534 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.0158687 (* 0.0272727 = 0.000432783 loss) | |
| I0525 04:59:27.711547 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.0067653 (* 0.0272727 = 0.000184508 loss) | |
| I0525 04:59:27.711561 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.00304532 (* 0.0272727 = 8.30543e-05 loss) | |
| I0525 04:59:27.711575 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.00573927 (* 0.0272727 = 0.000156525 loss) | |
| I0525 04:59:27.711588 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.00419135 (* 0.0272727 = 0.00011431 loss) | |
| I0525 04:59:27.711601 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.0677966 | |
| I0525 04:59:27.711613 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0.125 | |
| I0525 04:59:27.711626 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0 | |
| I0525 04:59:27.711637 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0.125 | |
| I0525 04:59:27.711649 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0 | |
| I0525 04:59:27.711660 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.125 | |
| I0525 04:59:27.711673 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0 | |
| I0525 04:59:27.711685 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.5 | |
| I0525 04:59:27.711697 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 0.75 | |
| I0525 04:59:27.711709 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 0.875 | |
| I0525 04:59:27.711721 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 0.875 | |
| I0525 04:59:27.711732 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 0.875 | |
| I0525 04:59:27.711745 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 0.875 | |
| I0525 04:59:27.711760 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 0.875 | |
| I0525 04:59:27.711771 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 0.875 | |
| I0525 04:59:27.711783 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 04:59:27.711796 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 04:59:27.711807 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 04:59:27.711818 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 04:59:27.711830 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 04:59:27.711841 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 04:59:27.711853 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 04:59:27.711865 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 04:59:27.711879 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.664773 | |
| I0525 04:59:27.711891 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.152542 | |
| I0525 04:59:27.711906 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.46262 (* 0.3 = 1.03879 loss) | |
| I0525 04:59:27.711920 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 1.35938 (* 0.3 = 0.407815 loss) | |
| I0525 04:59:27.711933 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.13133 (* 0.0272727 = 0.0853998 loss) | |
| I0525 04:59:27.711958 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 3.49872 (* 0.0272727 = 0.0954195 loss) | |
| I0525 04:59:27.711973 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.31344 (* 0.0272727 = 0.0903664 loss) | |
| I0525 04:59:27.711987 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.63836 (* 0.0272727 = 0.099228 loss) | |
| I0525 04:59:27.712002 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 3.57897 (* 0.0272727 = 0.0976083 loss) | |
| I0525 04:59:27.712014 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 3.81665 (* 0.0272727 = 0.10409 loss) | |
| I0525 04:59:27.712028 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 2.70241 (* 0.0272727 = 0.0737022 loss) | |
| I0525 04:59:27.712041 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 1.241 (* 0.0272727 = 0.0338456 loss) | |
| I0525 04:59:27.712055 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.828625 (* 0.0272727 = 0.0225989 loss) | |
| I0525 04:59:27.712069 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.695958 (* 0.0272727 = 0.0189807 loss) | |
| I0525 04:59:27.712082 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.747721 (* 0.0272727 = 0.0203924 loss) | |
| I0525 04:59:27.712096 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.56435 (* 0.0272727 = 0.0153914 loss) | |
| I0525 04:59:27.712110 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.450707 (* 0.0272727 = 0.012292 loss) | |
| I0525 04:59:27.712124 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.610814 (* 0.0272727 = 0.0166586 loss) | |
| I0525 04:59:27.712138 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.0709232 (* 0.0272727 = 0.00193427 loss) | |
| I0525 04:59:27.712152 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.0515115 (* 0.0272727 = 0.00140486 loss) | |
| I0525 04:59:27.712167 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.0288127 (* 0.0272727 = 0.000785802 loss) | |
| I0525 04:59:27.712180 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.0201693 (* 0.0272727 = 0.000550072 loss) | |
| I0525 04:59:27.712194 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.0165472 (* 0.0272727 = 0.000451287 loss) | |
| I0525 04:59:27.712208 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.00708455 (* 0.0272727 = 0.000193215 loss) | |
| I0525 04:59:27.712221 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.00729991 (* 0.0272727 = 0.000199088 loss) | |
| I0525 04:59:27.712232 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.00551168 (* 0.0272727 = 0.000150318 loss) | |
| I0525 04:59:27.712240 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.101695 | |
| I0525 04:59:27.712249 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.125 | |
| I0525 04:59:27.712261 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0.25 | |
| I0525 04:59:27.712273 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0 | |
| I0525 04:59:27.712285 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0 | |
| I0525 04:59:27.712297 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.125 | |
| I0525 04:59:27.712308 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.25 | |
| I0525 04:59:27.712321 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.5 | |
| I0525 04:59:27.712332 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 0.75 | |
| I0525 04:59:27.712344 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 0.875 | |
| I0525 04:59:27.712357 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 0.875 | |
| I0525 04:59:27.712368 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 0.875 | |
| I0525 04:59:27.712379 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 0.875 | |
| I0525 04:59:27.712391 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 0.875 | |
| I0525 04:59:27.712404 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 0.875 | |
| I0525 04:59:27.712424 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 04:59:27.712437 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 04:59:27.712450 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 04:59:27.712460 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 04:59:27.712472 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 04:59:27.712483 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 04:59:27.712496 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 04:59:27.712507 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 04:59:27.712518 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.676136 | |
| I0525 04:59:27.712530 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.186441 | |
| I0525 04:59:27.712544 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.42441 (* 1 = 3.42441 loss) | |
| I0525 04:59:27.712558 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 1.33442 (* 1 = 1.33442 loss) | |
| I0525 04:59:27.712571 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 2.70014 (* 0.0909091 = 0.245467 loss) | |
| I0525 04:59:27.712585 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.09941 (* 0.0909091 = 0.281764 loss) | |
| I0525 04:59:27.712599 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.70807 (* 0.0909091 = 0.337098 loss) | |
| I0525 04:59:27.712613 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.37623 (* 0.0909091 = 0.30693 loss) | |
| I0525 04:59:27.712627 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 4.11733 (* 0.0909091 = 0.374303 loss) | |
| I0525 04:59:27.712641 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 3.88257 (* 0.0909091 = 0.352961 loss) | |
| I0525 04:59:27.712654 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 2.32389 (* 0.0909091 = 0.211263 loss) | |
| I0525 04:59:27.712668 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 1.15855 (* 0.0909091 = 0.105323 loss) | |
| I0525 04:59:27.712682 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.525891 (* 0.0909091 = 0.0478083 loss) | |
| I0525 04:59:27.712695 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.522159 (* 0.0909091 = 0.047469 loss) | |
| I0525 04:59:27.712709 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.742047 (* 0.0909091 = 0.0674588 loss) | |
| I0525 04:59:27.712723 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.479795 (* 0.0909091 = 0.0436178 loss) | |
| I0525 04:59:27.712736 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.417701 (* 0.0909091 = 0.0379728 loss) | |
| I0525 04:59:27.712750 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.600073 (* 0.0909091 = 0.0545521 loss) | |
| I0525 04:59:27.712764 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.0661752 (* 0.0909091 = 0.00601593 loss) | |
| I0525 04:59:27.712779 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.0216227 (* 0.0909091 = 0.0019657 loss) | |
| I0525 04:59:27.712793 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.0146891 (* 0.0909091 = 0.00133537 loss) | |
| I0525 04:59:27.712810 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.0040037 (* 0.0909091 = 0.000363972 loss) | |
| I0525 04:59:27.712826 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.00456805 (* 0.0909091 = 0.000415277 loss) | |
| I0525 04:59:27.712839 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.00261393 (* 0.0909091 = 0.00023763 loss) | |
| I0525 04:59:27.712853 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.00178649 (* 0.0909091 = 0.000162409 loss) | |
| I0525 04:59:27.712867 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.0012882 (* 0.0909091 = 0.000117109 loss) | |
| I0525 04:59:27.712879 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 04:59:27.712900 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 04:59:27.712913 5272 solver.cpp:245] Train net output #149: total_confidence = 1.89541e-06 | |
| I0525 04:59:27.712927 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 7.59691e-05 | |
| I0525 04:59:27.712942 5272 sgd_solver.cpp:106] Iteration 22000, lr = 0.001 | |
| I0525 05:05:52.771066 5272 solver.cpp:229] Iteration 22500, loss = 9.66745 | |
| I0525 05:05:52.771252 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.025641 | |
| I0525 05:05:52.771275 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.125 | |
| I0525 05:05:52.771291 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0525 05:05:52.771302 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0525 05:05:52.771316 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.25 | |
| I0525 05:05:52.771327 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.375 | |
| I0525 05:05:52.771340 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.625 | |
| I0525 05:05:52.771353 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.875 | |
| I0525 05:05:52.771365 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 1 | |
| I0525 05:05:52.771378 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 1 | |
| I0525 05:05:52.771390 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 1 | |
| I0525 05:05:52.771402 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 05:05:52.771415 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 05:05:52.771430 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 05:05:52.771440 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 05:05:52.771452 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 05:05:52.771464 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 05:05:52.771476 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 05:05:52.771488 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 05:05:52.771500 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 05:05:52.771513 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 05:05:52.771524 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 05:05:52.771538 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 05:05:52.771548 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.772727 | |
| I0525 05:05:52.771561 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.128205 | |
| I0525 05:05:52.771579 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 3.39485 (* 0.3 = 1.01846 loss) | |
| I0525 05:05:52.771594 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 0.858025 (* 0.3 = 0.257408 loss) | |
| I0525 05:05:52.771607 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 3.09767 (* 0.0272727 = 0.0844819 loss) | |
| I0525 05:05:52.771621 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 3.50265 (* 0.0272727 = 0.0955269 loss) | |
| I0525 05:05:52.771636 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 3.30974 (* 0.0272727 = 0.0902655 loss) | |
| I0525 05:05:52.771651 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 3.34645 (* 0.0272727 = 0.0912669 loss) | |
| I0525 05:05:52.771666 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 2.17042 (* 0.0272727 = 0.0591932 loss) | |
| I0525 05:05:52.771679 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 1.72553 (* 0.0272727 = 0.0470599 loss) | |
| I0525 05:05:52.771693 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 0.743822 (* 0.0272727 = 0.020286 loss) | |
| I0525 05:05:52.771708 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 0.047318 (* 0.0272727 = 0.00129049 loss) | |
| I0525 05:05:52.771723 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.00618761 (* 0.0272727 = 0.000168753 loss) | |
| I0525 05:05:52.771736 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.00725301 (* 0.0272727 = 0.000197809 loss) | |
| I0525 05:05:52.771751 5272 solver.cpp:245] Train net output #37: loss1/loss11 = 0.00543072 (* 0.0272727 = 0.00014811 loss) | |
| I0525 05:05:52.771765 5272 solver.cpp:245] Train net output #38: loss1/loss12 = 0.00255894 (* 0.0272727 = 6.97892e-05 loss) | |
| I0525 05:05:52.771780 5272 solver.cpp:245] Train net output #39: loss1/loss13 = 0.00233785 (* 0.0272727 = 6.37594e-05 loss) | |
| I0525 05:05:52.771807 5272 solver.cpp:245] Train net output #40: loss1/loss14 = 0.00213642 (* 0.0272727 = 5.82661e-05 loss) | |
| I0525 05:05:52.771822 5272 solver.cpp:245] Train net output #41: loss1/loss15 = 0.00276107 (* 0.0272727 = 7.53018e-05 loss) | |
| I0525 05:05:52.771836 5272 solver.cpp:245] Train net output #42: loss1/loss16 = 0.00191073 (* 0.0272727 = 5.21107e-05 loss) | |
| I0525 05:05:52.771852 5272 solver.cpp:245] Train net output #43: loss1/loss17 = 0.00142779 (* 0.0272727 = 3.89398e-05 loss) | |
| I0525 05:05:52.771865 5272 solver.cpp:245] Train net output #44: loss1/loss18 = 0.00116772 (* 0.0272727 = 3.18468e-05 loss) | |
| I0525 05:05:52.771883 5272 solver.cpp:245] Train net output #45: loss1/loss19 = 0.00112325 (* 0.0272727 = 3.0634e-05 loss) | |
| I0525 05:05:52.771898 5272 solver.cpp:245] Train net output #46: loss1/loss20 = 0.000756945 (* 0.0272727 = 2.0644e-05 loss) | |
| I0525 05:05:52.771911 5272 solver.cpp:245] Train net output #47: loss1/loss21 = 0.000585398 (* 0.0272727 = 1.59654e-05 loss) | |
| I0525 05:05:52.771925 5272 solver.cpp:245] Train net output #48: loss1/loss22 = 0.000817819 (* 0.0272727 = 2.23042e-05 loss) | |
| I0525 05:05:52.771940 5272 solver.cpp:245] Train net output #49: loss2/accuracy = 0.0512821 | |
| I0525 05:05:52.771971 5272 solver.cpp:245] Train net output #50: loss2/accuracy01 = 0.125 | |
| I0525 05:05:52.771984 5272 solver.cpp:245] Train net output #51: loss2/accuracy02 = 0 | |
| I0525 05:05:52.771996 5272 solver.cpp:245] Train net output #52: loss2/accuracy03 = 0 | |
| I0525 05:05:52.772008 5272 solver.cpp:245] Train net output #53: loss2/accuracy04 = 0.25 | |
| I0525 05:05:52.772020 5272 solver.cpp:245] Train net output #54: loss2/accuracy05 = 0.375 | |
| I0525 05:05:52.772033 5272 solver.cpp:245] Train net output #55: loss2/accuracy06 = 0.625 | |
| I0525 05:05:52.772045 5272 solver.cpp:245] Train net output #56: loss2/accuracy07 = 0.875 | |
| I0525 05:05:52.772058 5272 solver.cpp:245] Train net output #57: loss2/accuracy08 = 1 | |
| I0525 05:05:52.772069 5272 solver.cpp:245] Train net output #58: loss2/accuracy09 = 1 | |
| I0525 05:05:52.772081 5272 solver.cpp:245] Train net output #59: loss2/accuracy10 = 1 | |
| I0525 05:05:52.772094 5272 solver.cpp:245] Train net output #60: loss2/accuracy11 = 1 | |
| I0525 05:05:52.772105 5272 solver.cpp:245] Train net output #61: loss2/accuracy12 = 1 | |
| I0525 05:05:52.772116 5272 solver.cpp:245] Train net output #62: loss2/accuracy13 = 1 | |
| I0525 05:05:52.772128 5272 solver.cpp:245] Train net output #63: loss2/accuracy14 = 1 | |
| I0525 05:05:52.772140 5272 solver.cpp:245] Train net output #64: loss2/accuracy15 = 1 | |
| I0525 05:05:52.772152 5272 solver.cpp:245] Train net output #65: loss2/accuracy16 = 1 | |
| I0525 05:05:52.772164 5272 solver.cpp:245] Train net output #66: loss2/accuracy17 = 1 | |
| I0525 05:05:52.772176 5272 solver.cpp:245] Train net output #67: loss2/accuracy18 = 1 | |
| I0525 05:05:52.772187 5272 solver.cpp:245] Train net output #68: loss2/accuracy19 = 1 | |
| I0525 05:05:52.772199 5272 solver.cpp:245] Train net output #69: loss2/accuracy20 = 1 | |
| I0525 05:05:52.772212 5272 solver.cpp:245] Train net output #70: loss2/accuracy21 = 1 | |
| I0525 05:05:52.772223 5272 solver.cpp:245] Train net output #71: loss2/accuracy22 = 1 | |
| I0525 05:05:52.772235 5272 solver.cpp:245] Train net output #72: loss2/accuracy_incl_empty = 0.789773 | |
| I0525 05:05:52.772246 5272 solver.cpp:245] Train net output #73: loss2/accuracy_top3 = 0.153846 | |
| I0525 05:05:52.772266 5272 solver.cpp:245] Train net output #74: loss2/cross_entropy_loss = 3.34064 (* 0.3 = 1.00219 loss) | |
| I0525 05:05:52.772281 5272 solver.cpp:245] Train net output #75: loss2/cross_entropy_loss_incl_empty = 0.795669 (* 0.3 = 0.238701 loss) | |
| I0525 05:05:52.772295 5272 solver.cpp:245] Train net output #76: loss2/loss01 = 3.10648 (* 0.0272727 = 0.0847223 loss) | |
| I0525 05:05:52.772310 5272 solver.cpp:245] Train net output #77: loss2/loss02 = 3.60074 (* 0.0272727 = 0.098202 loss) | |
| I0525 05:05:52.772336 5272 solver.cpp:245] Train net output #78: loss2/loss03 = 3.48501 (* 0.0272727 = 0.0950457 loss) | |
| I0525 05:05:52.772351 5272 solver.cpp:245] Train net output #79: loss2/loss04 = 3.1105 (* 0.0272727 = 0.0848317 loss) | |
| I0525 05:05:52.772364 5272 solver.cpp:245] Train net output #80: loss2/loss05 = 2.10976 (* 0.0272727 = 0.057539 loss) | |
| I0525 05:05:52.772378 5272 solver.cpp:245] Train net output #81: loss2/loss06 = 1.71483 (* 0.0272727 = 0.0467682 loss) | |
| I0525 05:05:52.772392 5272 solver.cpp:245] Train net output #82: loss2/loss07 = 0.717032 (* 0.0272727 = 0.0195554 loss) | |
| I0525 05:05:52.772408 5272 solver.cpp:245] Train net output #83: loss2/loss08 = 0.0208824 (* 0.0272727 = 0.00056952 loss) | |
| I0525 05:05:52.772421 5272 solver.cpp:245] Train net output #84: loss2/loss09 = 0.00340411 (* 0.0272727 = 9.28394e-05 loss) | |
| I0525 05:05:52.772435 5272 solver.cpp:245] Train net output #85: loss2/loss10 = 0.00269401 (* 0.0272727 = 7.3473e-05 loss) | |
| I0525 05:05:52.772450 5272 solver.cpp:245] Train net output #86: loss2/loss11 = 0.00172615 (* 0.0272727 = 4.70767e-05 loss) | |
| I0525 05:05:52.772464 5272 solver.cpp:245] Train net output #87: loss2/loss12 = 0.0015986 (* 0.0272727 = 4.35982e-05 loss) | |
| I0525 05:05:52.772480 5272 solver.cpp:245] Train net output #88: loss2/loss13 = 0.00102282 (* 0.0272727 = 2.7895e-05 loss) | |
| I0525 05:05:52.772493 5272 solver.cpp:245] Train net output #89: loss2/loss14 = 0.00153417 (* 0.0272727 = 4.18409e-05 loss) | |
| I0525 05:05:52.772507 5272 solver.cpp:245] Train net output #90: loss2/loss15 = 0.00158768 (* 0.0272727 = 4.33005e-05 loss) | |
| I0525 05:05:52.772518 5272 solver.cpp:245] Train net output #91: loss2/loss16 = 0.000801379 (* 0.0272727 = 2.18558e-05 loss) | |
| I0525 05:05:52.772528 5272 solver.cpp:245] Train net output #92: loss2/loss17 = 0.00073574 (* 0.0272727 = 2.00656e-05 loss) | |
| I0525 05:05:52.772538 5272 solver.cpp:245] Train net output #93: loss2/loss18 = 0.000514287 (* 0.0272727 = 1.4026e-05 loss) | |
| I0525 05:05:52.772553 5272 solver.cpp:245] Train net output #94: loss2/loss19 = 0.000798053 (* 0.0272727 = 2.17651e-05 loss) | |
| I0525 05:05:52.772567 5272 solver.cpp:245] Train net output #95: loss2/loss20 = 0.000662163 (* 0.0272727 = 1.8059e-05 loss) | |
| I0525 05:05:52.772581 5272 solver.cpp:245] Train net output #96: loss2/loss21 = 0.000623151 (* 0.0272727 = 1.6995e-05 loss) | |
| I0525 05:05:52.772594 5272 solver.cpp:245] Train net output #97: loss2/loss22 = 0.00074224 (* 0.0272727 = 2.02429e-05 loss) | |
| I0525 05:05:52.772608 5272 solver.cpp:245] Train net output #98: loss3/accuracy = 0.0512821 | |
| I0525 05:05:52.772619 5272 solver.cpp:245] Train net output #99: loss3/accuracy01 = 0.125 | |
| I0525 05:05:52.772632 5272 solver.cpp:245] Train net output #100: loss3/accuracy02 = 0.125 | |
| I0525 05:05:52.772644 5272 solver.cpp:245] Train net output #101: loss3/accuracy03 = 0.125 | |
| I0525 05:05:52.772656 5272 solver.cpp:245] Train net output #102: loss3/accuracy04 = 0.25 | |
| I0525 05:05:52.772668 5272 solver.cpp:245] Train net output #103: loss3/accuracy05 = 0.375 | |
| I0525 05:05:52.772680 5272 solver.cpp:245] Train net output #104: loss3/accuracy06 = 0.625 | |
| I0525 05:05:52.772692 5272 solver.cpp:245] Train net output #105: loss3/accuracy07 = 0.875 | |
| I0525 05:05:52.772704 5272 solver.cpp:245] Train net output #106: loss3/accuracy08 = 1 | |
| I0525 05:05:52.772716 5272 solver.cpp:245] Train net output #107: loss3/accuracy09 = 1 | |
| I0525 05:05:52.772728 5272 solver.cpp:245] Train net output #108: loss3/accuracy10 = 1 | |
| I0525 05:05:52.772740 5272 solver.cpp:245] Train net output #109: loss3/accuracy11 = 1 | |
| I0525 05:05:52.772752 5272 solver.cpp:245] Train net output #110: loss3/accuracy12 = 1 | |
| I0525 05:05:52.772763 5272 solver.cpp:245] Train net output #111: loss3/accuracy13 = 1 | |
| I0525 05:05:52.772775 5272 solver.cpp:245] Train net output #112: loss3/accuracy14 = 1 | |
| I0525 05:05:52.772786 5272 solver.cpp:245] Train net output #113: loss3/accuracy15 = 1 | |
| I0525 05:05:52.772799 5272 solver.cpp:245] Train net output #114: loss3/accuracy16 = 1 | |
| I0525 05:05:52.772819 5272 solver.cpp:245] Train net output #115: loss3/accuracy17 = 1 | |
| I0525 05:05:52.772831 5272 solver.cpp:245] Train net output #116: loss3/accuracy18 = 1 | |
| I0525 05:05:52.772843 5272 solver.cpp:245] Train net output #117: loss3/accuracy19 = 1 | |
| I0525 05:05:52.772855 5272 solver.cpp:245] Train net output #118: loss3/accuracy20 = 1 | |
| I0525 05:05:52.772867 5272 solver.cpp:245] Train net output #119: loss3/accuracy21 = 1 | |
| I0525 05:05:52.772879 5272 solver.cpp:245] Train net output #120: loss3/accuracy22 = 1 | |
| I0525 05:05:52.772891 5272 solver.cpp:245] Train net output #121: loss3/accuracy_incl_empty = 0.789773 | |
| I0525 05:05:52.772903 5272 solver.cpp:245] Train net output #122: loss3/accuracy_top3 = 0.282051 | |
| I0525 05:05:52.772917 5272 solver.cpp:245] Train net output #123: loss3/cross_entropy_loss = 3.14293 (* 1 = 3.14293 loss) | |
| I0525 05:05:52.772934 5272 solver.cpp:245] Train net output #124: loss3/cross_entropy_loss_incl_empty = 0.73963 (* 1 = 0.73963 loss) | |
| I0525 05:05:52.772948 5272 solver.cpp:245] Train net output #125: loss3/loss01 = 3.15797 (* 0.0909091 = 0.287088 loss) | |
| I0525 05:05:52.772964 5272 solver.cpp:245] Train net output #126: loss3/loss02 = 3.38184 (* 0.0909091 = 0.30744 loss) | |
| I0525 05:05:52.772977 5272 solver.cpp:245] Train net output #127: loss3/loss03 = 3.0569 (* 0.0909091 = 0.2779 loss) | |
| I0525 05:05:52.772991 5272 solver.cpp:245] Train net output #128: loss3/loss04 = 3.0533 (* 0.0909091 = 0.277573 loss) | |
| I0525 05:05:52.773005 5272 solver.cpp:245] Train net output #129: loss3/loss05 = 2.09699 (* 0.0909091 = 0.190636 loss) | |
| I0525 05:05:52.773020 5272 solver.cpp:245] Train net output #130: loss3/loss06 = 1.79242 (* 0.0909091 = 0.162947 loss) | |
| I0525 05:05:52.773032 5272 solver.cpp:245] Train net output #131: loss3/loss07 = 0.487128 (* 0.0909091 = 0.0442844 loss) | |
| I0525 05:05:52.773047 5272 solver.cpp:245] Train net output #132: loss3/loss08 = 0.0106811 (* 0.0909091 = 0.000971013 loss) | |
| I0525 05:05:52.773061 5272 solver.cpp:245] Train net output #133: loss3/loss09 = 0.00200731 (* 0.0909091 = 0.000182483 loss) | |
| I0525 05:05:52.773075 5272 solver.cpp:245] Train net output #134: loss3/loss10 = 0.00164066 (* 0.0909091 = 0.000149151 loss) | |
| I0525 05:05:52.773089 5272 solver.cpp:245] Train net output #135: loss3/loss11 = 0.00133145 (* 0.0909091 = 0.000121041 loss) | |
| I0525 05:05:52.773103 5272 solver.cpp:245] Train net output #136: loss3/loss12 = 0.0008459 (* 0.0909091 = 7.69e-05 loss) | |
| I0525 05:05:52.773129 5272 solver.cpp:245] Train net output #137: loss3/loss13 = 0.000960478 (* 0.0909091 = 8.73161e-05 loss) | |
| I0525 05:05:52.773147 5272 solver.cpp:245] Train net output #138: loss3/loss14 = 0.000782418 (* 0.0909091 = 7.11289e-05 loss) | |
| I0525 05:05:52.773162 5272 solver.cpp:245] Train net output #139: loss3/loss15 = 0.000765727 (* 0.0909091 = 6.96115e-05 loss) | |
| I0525 05:05:52.773176 5272 solver.cpp:245] Train net output #140: loss3/loss16 = 0.000790156 (* 0.0909091 = 7.18324e-05 loss) | |
| I0525 05:05:52.773190 5272 solver.cpp:245] Train net output #141: loss3/loss17 = 0.000697583 (* 0.0909091 = 6.34167e-05 loss) | |
| I0525 05:05:52.773205 5272 solver.cpp:245] Train net output #142: loss3/loss18 = 0.000769554 (* 0.0909091 = 6.99595e-05 loss) | |
| I0525 05:05:52.773218 5272 solver.cpp:245] Train net output #143: loss3/loss19 = 0.000939737 (* 0.0909091 = 8.54306e-05 loss) | |
| I0525 05:05:52.773232 5272 solver.cpp:245] Train net output #144: loss3/loss20 = 0.000655659 (* 0.0909091 = 5.96054e-05 loss) | |
| I0525 05:05:52.773243 5272 solver.cpp:245] Train net output #145: loss3/loss21 = 0.000603992 (* 0.0909091 = 5.49084e-05 loss) | |
| I0525 05:05:52.773258 5272 solver.cpp:245] Train net output #146: loss3/loss22 = 0.000866675 (* 0.0909091 = 7.87887e-05 loss) | |
| I0525 05:05:52.773272 5272 solver.cpp:245] Train net output #147: total_accuracy = 0 | |
| I0525 05:05:52.773284 5272 solver.cpp:245] Train net output #148: total_accuracy_not_rec = 0 | |
| I0525 05:05:52.773306 5272 solver.cpp:245] Train net output #149: total_confidence = 0.000205044 | |
| I0525 05:05:52.773325 5272 solver.cpp:245] Train net output #150: total_confidence_not_rec = 0.000596169 | |
| I0525 05:05:52.773339 5272 sgd_solver.cpp:106] Iteration 22500, lr = 0.001 | |
| I0525 05:07:33.204154 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 40.8948 > 30) by scale factor 0.73359 | |
| I0525 05:10:22.586864 5272 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 30.8209 > 30) by scale factor 0.973366 | |
| I0525 05:12:17.753682 5272 solver.cpp:229] Iteration 23000, loss = 9.64775 | |
| I0525 05:12:17.753782 5272 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0731707 | |
| I0525 05:12:17.753803 5272 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.125 | |
| I0525 05:12:17.753815 5272 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0.375 | |
| I0525 05:12:17.753829 5272 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0525 05:12:17.753841 5272 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.25 | |
| I0525 05:12:17.753854 5272 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.375 | |
| I0525 05:12:17.753866 5272 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.75 | |
| I0525 05:12:17.753878 5272 solver.cpp:245] Train net output #7: loss1/accuracy07 = 0.625 | |
| I0525 05:12:17.753891 5272 solver.cpp:245] Train net output #8: loss1/accuracy08 = 1 | |
| I0525 05:12:17.753904 5272 solver.cpp:245] Train net output #9: loss1/accuracy09 = 1 | |
| I0525 05:12:17.753916 5272 solver.cpp:245] Train net output #10: loss1/accuracy10 = 1 | |
| I0525 05:12:17.753929 5272 solver.cpp:245] Train net output #11: loss1/accuracy11 = 1 | |
| I0525 05:12:17.753942 5272 solver.cpp:245] Train net output #12: loss1/accuracy12 = 1 | |
| I0525 05:12:17.753953 5272 solver.cpp:245] Train net output #13: loss1/accuracy13 = 1 | |
| I0525 05:12:17.753965 5272 solver.cpp:245] Train net output #14: loss1/accuracy14 = 1 | |
| I0525 05:12:17.753978 5272 solver.cpp:245] Train net output #15: loss1/accuracy15 = 1 | |
| I0525 05:12:17.753988 5272 solver.cpp:245] Train net output #16: loss1/accuracy16 = 1 | |
| I0525 05:12:17.754000 5272 solver.cpp:245] Train net output #17: loss1/accuracy17 = 1 | |
| I0525 05:12:17.754012 5272 solver.cpp:245] Train net output #18: loss1/accuracy18 = 1 | |
| I0525 05:12:17.754024 5272 solver.cpp:245] Train net output #19: loss1/accuracy19 = 1 | |
| I0525 05:12:17.754036 5272 solver.cpp:245] Train net output #20: loss1/accuracy20 = 1 | |
| I0525 05:12:17.754047 5272 solver.cpp:245] Train net output #21: loss1/accuracy21 = 1 | |
| I0525 05:12:17.754060 5272 solver.cpp:245] Train net output #22: loss1/accuracy22 = 1 | |
| I0525 05:12:17.754072 5272 solver.cpp:245] Train net output #23: loss1/accuracy_incl_empty = 0.772727 | |
| I0525 05:12:17.754084 5272 solver.cpp:245] Train net output #24: loss1/accuracy_top3 = 0.341463 | |
| I0525 05:12:17.754101 5272 solver.cpp:245] Train net output #25: loss1/cross_entropy_loss = 2.84617 (* 0.3 = 0.85385 loss) | |
| I0525 05:12:17.754115 5272 solver.cpp:245] Train net output #26: loss1/cross_entropy_loss_incl_empty = 0.759457 (* 0.3 = 0.227837 loss) | |
| I0525 05:12:17.754130 5272 solver.cpp:245] Train net output #27: loss1/loss01 = 2.69638 (* 0.0272727 = 0.0735375 loss) | |
| I0525 05:12:17.754144 5272 solver.cpp:245] Train net output #28: loss1/loss02 = 2.48426 (* 0.0272727 = 0.0677525 loss) | |
| I0525 05:12:17.754158 5272 solver.cpp:245] Train net output #29: loss1/loss03 = 2.74282 (* 0.0272727 = 0.0748043 loss) | |
| I0525 05:12:17.754173 5272 solver.cpp:245] Train net output #30: loss1/loss04 = 2.5797 (* 0.0272727 = 0.0703554 loss) | |
| I0525 05:12:17.754187 5272 solver.cpp:245] Train net output #31: loss1/loss05 = 1.91836 (* 0.0272727 = 0.0523188 loss) | |
| I0525 05:12:17.754201 5272 solver.cpp:245] Train net output #32: loss1/loss06 = 1.32071 (* 0.0272727 = 0.0360194 loss) | |
| I0525 05:12:17.754215 5272 solver.cpp:245] Train net output #33: loss1/loss07 = 1.44006 (* 0.0272727 = 0.0392745 loss) | |
| I0525 05:12:17.754230 5272 solver.cpp:245] Train net output #34: loss1/loss08 = 0.0979319 (* 0.0272727 = 0.00267087 loss) | |
| I0525 05:12:17.754245 5272 solver.cpp:245] Train net output #35: loss1/loss09 = 0.0234728 (* 0.0272727 = 0.000640167 loss) | |
| I0525 05:12:17.754258 5272 solver.cpp:245] Train net output #36: loss1/loss10 = 0.0087309 (* 0.0272727 = 0.000238115 loss) | |
| I0525 05:12:17.754273 |
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