log_12312.txt

I1113 13:59:14.466996 15355 solver.cpp:337] Iteration 0, Testing net (#0)
I1113 13:59:14.481719 15355 net.cpp:693] Ignoring source layer prob
I1113 13:59:44.028913 15355 solver.cpp:404]     Test net output #0: accuracy = 0.013875
I1113 13:59:44.168041 15355 solver.cpp:228] Iteration 0, loss = 4.52858
I1113 13:59:44.168081 15355 solver.cpp:244]     Train net output #0: loss = 4.52858 (* 1 = 4.52858 loss)
I1113 13:59:44.168093 15355 sgd_solver.cpp:106] Iteration 0, lr = 0.001
I1113 14:03:18.589840 15355 solver.cpp:228] Iteration 1000, loss = 0.235305
I1113 14:03:18.589912 15355 solver.cpp:244]     Train net output #0: loss = 0.235305 (* 1 = 0.235305 loss)
I1113 14:03:18.589920 15355 sgd_solver.cpp:106] Iteration 1000, lr = 0.001
I1113 14:06:52.377185 15355 solver.cpp:228] Iteration 2000, loss = 0.0354668
I1113 14:06:52.377305 15355 solver.cpp:244]     Train net output #0: loss = 0.0354666 (* 1 = 0.0354666 loss)
I1113 14:06:52.377315 15355 sgd_solver.cpp:106] Iteration 2000, lr = 0.001
I1113 14:10:17.346045 15355 solver.cpp:228] Iteration 3000, loss = 0.0729819
I1113 14:10:17.346158 15355 solver.cpp:244]     Train net output #0: loss = 0.0729819 (* 1 = 0.0729819 loss)
I1113 14:10:17.346166 15355 sgd_solver.cpp:106] Iteration 3000, lr = 0.001
I1113 14:13:51.757073 15355 solver.cpp:228] Iteration 4000, loss = 0.0275689
I1113 14:13:51.757141 15355 solver.cpp:244]     Train net output #0: loss = 0.027569 (* 1 = 0.027569 loss)
I1113 14:13:51.757158 15355 sgd_solver.cpp:106] Iteration 4000, lr = 0.001
I1113 14:17:24.839128 15355 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_5000.caffemodel
I1113 14:17:25.801959 15355 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_5000.solverstate
I1113 14:17:25.831944 15355 solver.cpp:337] Iteration 5000, Testing net (#0)
I1113 14:17:25.831974 15355 net.cpp:693] Ignoring source layer prob
I1113 14:17:56.449120 15355 solver.cpp:404]     Test net output #0: accuracy = 0.96575
I1113 14:17:56.579897 15355 solver.cpp:228] Iteration 5000, loss = 0.0172594
I1113 14:17:56.579943 15355 solver.cpp:244]     Train net output #0: loss = 0.0172593 (* 1 = 0.0172593 loss)
I1113 14:17:56.579952 15355 sgd_solver.cpp:106] Iteration 5000, lr = 0.001
I1113 14:21:26.672283 15355 solver.cpp:228] Iteration 6000, loss = 0.0264688
I1113 14:21:26.672425 15355 solver.cpp:244]     Train net output #0: loss = 0.0264687 (* 1 = 0.0264687 loss)
I1113 14:21:26.672436 15355 sgd_solver.cpp:106] Iteration 6000, lr = 0.001
I1113 14:24:47.573354 15355 solver.cpp:228] Iteration 7000, loss = 0.0779026
I1113 14:24:47.573468 15355 solver.cpp:244]     Train net output #0: loss = 0.0779027 (* 1 = 0.0779027 loss)
I1113 14:24:47.573485 15355 sgd_solver.cpp:106] Iteration 7000, lr = 0.001
I1113 14:27:10.243358 15355 solver.cpp:228] Iteration 8000, loss = 0.0142168
I1113 14:27:10.243476 15355 solver.cpp:244]     Train net output #0: loss = 0.0142166 (* 1 = 0.0142166 loss)
I1113 14:27:10.243485 15355 sgd_solver.cpp:106] Iteration 8000, lr = 0.001
I1113 14:29:33.488984 15355 solver.cpp:228] Iteration 9000, loss = 0.0463145
I1113 14:29:33.489152 15355 solver.cpp:244]     Train net output #0: loss = 0.0463141 (* 1 = 0.0463141 loss)
I1113 14:29:33.489166 15355 sgd_solver.cpp:106] Iteration 9000, lr = 0.001
I1113 14:31:58.653976 15355 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_10000.caffemodel
I1113 14:31:59.002169 15355 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_10000.solverstate
I1113 14:31:59.032902 15355 solver.cpp:337] Iteration 10000, Testing net (#0)
I1113 14:31:59.032932 15355 net.cpp:693] Ignoring source layer prob
I1113 14:32:14.980231 15355 solver.cpp:404]     Test net output #0: accuracy = 0.970375
I1113 14:32:15.048615 15355 solver.cpp:228] Iteration 10000, loss = 0.199158
I1113 14:32:15.048663 15355 solver.cpp:244]     Train net output #0: loss = 0.199158 (* 1 = 0.199158 loss)
I1113 14:32:15.048671 15355 sgd_solver.cpp:106] Iteration 10000, lr = 0.001
I1113 14:34:40.779438 15355 solver.cpp:228] Iteration 11000, loss = 0.137944
I1113 14:34:40.779587 15355 solver.cpp:244]     Train net output #0: loss = 0.137943 (* 1 = 0.137943 loss)
I1113 14:34:40.779599 15355 sgd_solver.cpp:106] Iteration 11000, lr = 0.001
I1113 14:37:05.481401 15355 solver.cpp:228] Iteration 12000, loss = 0.0383468
I1113 14:37:05.481559 15355 solver.cpp:244]     Train net output #0: loss = 0.0383462 (* 1 = 0.0383462 loss)
I1113 14:37:05.481572 15355 sgd_solver.cpp:106] Iteration 12000, lr = 0.001
I1113 14:39:31.297600 15355 solver.cpp:228] Iteration 13000, loss = 0.037655
I1113 14:39:31.297683 15355 solver.cpp:244]     Train net output #0: loss = 0.0376545 (* 1 = 0.0376545 loss)
I1113 14:39:31.297694 15355 sgd_solver.cpp:106] Iteration 13000, lr = 0.001
I1113 14:41:52.632163 15355 solver.cpp:228] Iteration 14000, loss = 0.0350755
I1113 14:41:52.632272 15355 solver.cpp:244]     Train net output #0: loss = 0.0350752 (* 1 = 0.0350752 loss)
I1113 14:41:52.632288 15355 sgd_solver.cpp:106] Iteration 14000, lr = 0.001
I1113 14:44:11.553197 15355 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_15000.caffemodel
I1113 14:44:14.022374 15355 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_15000.solverstate
I1113 14:44:14.051734 15355 solver.cpp:337] Iteration 15000, Testing net (#0)
I1113 14:44:14.051764 15355 net.cpp:693] Ignoring source layer prob
I1113 14:44:29.390152 15355 solver.cpp:404]     Test net output #0: accuracy = 0.9875
I1113 14:44:29.455154 15355 solver.cpp:228] Iteration 15000, loss = 0.0756778
I1113 14:44:29.455194 15355 solver.cpp:244]     Train net output #0: loss = 0.0756776 (* 1 = 0.0756776 loss)
I1113 14:44:29.455210 15355 sgd_solver.cpp:106] Iteration 15000, lr = 0.001
I1113 14:46:53.090965 15355 solver.cpp:228] Iteration 16000, loss = 0.045877
I1113 14:46:53.091142 15355 solver.cpp:244]     Train net output #0: loss = 0.0458767 (* 1 = 0.0458767 loss)
I1113 14:46:53.091155 15355 sgd_solver.cpp:106] Iteration 16000, lr = 0.001
I1113 14:49:14.056412 15355 solver.cpp:228] Iteration 17000, loss = 0.0107027
I1113 14:49:14.056587 15355 solver.cpp:244]     Train net output #0: loss = 0.0107023 (* 1 = 0.0107023 loss)
I1113 14:49:14.056607 15355 sgd_solver.cpp:106] Iteration 17000, lr = 0.001
I1113 14:51:33.361199 15355 solver.cpp:228] Iteration 18000, loss = 0.164821
I1113 14:51:33.361326 15355 solver.cpp:244]     Train net output #0: loss = 0.16482 (* 1 = 0.16482 loss)
I1113 14:51:33.361340 15355 sgd_solver.cpp:106] Iteration 18000, lr = 0.001
I1113 14:53:54.505609 15355 solver.cpp:228] Iteration 19000, loss = 0.0220261
I1113 14:53:54.505791 15355 solver.cpp:244]     Train net output #0: loss = 0.0220258 (* 1 = 0.0220258 loss)
I1113 14:53:54.505815 15355 sgd_solver.cpp:106] Iteration 19000, lr = 0.001
I1113 14:56:14.749822 15355 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_20000.caffemodel
I1113 14:56:14.886792 15355 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_20000.solverstate
I1113 14:56:14.915223 15355 solver.cpp:337] Iteration 20000, Testing net (#0)
I1113 14:56:14.915267 15355 net.cpp:693] Ignoring source layer prob
I1113 14:56:30.412019 15355 solver.cpp:404]     Test net output #0: accuracy = 0.984375
I1113 14:56:30.477948 15355 solver.cpp:228] Iteration 20000, loss = 0.0825481
I1113 14:56:30.477996 15355 solver.cpp:244]     Train net output #0: loss = 0.0825478 (* 1 = 0.0825478 loss)
I1113 14:56:30.478004 15355 sgd_solver.cpp:106] Iteration 20000, lr = 0.001
I1113 14:58:49.728137 15355 solver.cpp:228] Iteration 21000, loss = 0.0391386
I1113 14:58:49.728269 15355 solver.cpp:244]     Train net output #0: loss = 0.0391381 (* 1 = 0.0391381 loss)
I1113 14:58:49.728277 15355 sgd_solver.cpp:106] Iteration 21000, lr = 0.001
I1113 15:01:08.848606 15355 solver.cpp:228] Iteration 22000, loss = 0.00148871
I1113 15:01:08.848736 15355 solver.cpp:244]     Train net output #0: loss = 0.00148812 (* 1 = 0.00148812 loss)
I1113 15:01:08.848743 15355 sgd_solver.cpp:106] Iteration 22000, lr = 0.001
I1113 15:03:28.010241 15355 solver.cpp:228] Iteration 23000, loss = 0.064207
I1113 15:03:28.010351 15355 solver.cpp:244]     Train net output #0: loss = 0.0642063 (* 1 = 0.0642063 loss)
I1113 15:03:28.010360 15355 sgd_solver.cpp:106] Iteration 23000, lr = 0.001
I1113 15:05:49.544870 15355 solver.cpp:228] Iteration 24000, loss = 0.00705606
I1113 15:05:49.544975 15355 solver.cpp:244]     Train net output #0: loss = 0.00705541 (* 1 = 0.00705541 loss)
I1113 15:05:49.544982 15355 sgd_solver.cpp:106] Iteration 24000, lr = 0.001
I1113 15:08:09.076315 15355 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_25000.caffemodel
I1113 15:08:10.779561 15355 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_25000.solverstate
I1113 15:08:10.808876 15355 solver.cpp:337] Iteration 25000, Testing net (#0)
I1113 15:08:10.808905 15355 net.cpp:693] Ignoring source layer prob
I1113 15:08:26.134369 15355 solver.cpp:404]     Test net output #0: accuracy = 0.986875
I1113 15:08:26.199717 15355 solver.cpp:228] Iteration 25000, loss = 0.0064166
I1113 15:08:26.199746 15355 solver.cpp:244]     Train net output #0: loss = 0.00641606 (* 1 = 0.00641606 loss)
I1113 15:08:26.199754 15355 sgd_solver.cpp:106] Iteration 25000, lr = 0.001
I1113 15:10:45.348054 15355 solver.cpp:228] Iteration 26000, loss = 0.00986812
I1113 15:10:45.348208 15355 solver.cpp:244]     Train net output #0: loss = 0.00986761 (* 1 = 0.00986761 loss)
I1113 15:10:45.348227 15355 sgd_solver.cpp:106] Iteration 26000, lr = 0.001
I1113 15:13:05.813032 15355 solver.cpp:228] Iteration 27000, loss = 0.0512098
I1113 15:13:05.813194 15355 solver.cpp:244]     Train net output #0: loss = 0.0512093 (* 1 = 0.0512093 loss)
I1113 15:13:05.813222 15355 sgd_solver.cpp:106] Iteration 27000, lr = 0.001
I1113 15:15:26.957317 15355 solver.cpp:228] Iteration 28000, loss = 0.465829
I1113 15:15:26.957469 15355 solver.cpp:244]     Train net output #0: loss = 0.465829 (* 1 = 0.465829 loss)
I1113 15:15:26.957487 15355 sgd_solver.cpp:106] Iteration 28000, lr = 0.001
I1113 15:17:48.049712 15355 solver.cpp:228] Iteration 29000, loss = 0.0146872
I1113 15:17:48.049885 15355 solver.cpp:244]     Train net output #0: loss = 0.0146867 (* 1 = 0.0146867 loss)
I1113 15:17:48.049906 15355 sgd_solver.cpp:106] Iteration 29000, lr = 0.001
I1113 15:20:09.071808 15355 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_30000.caffemodel
I1113 15:20:11.207233 15355 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_30000.solverstate
I1113 15:20:11.236838 15355 solver.cpp:337] Iteration 30000, Testing net (#0)
I1113 15:20:11.236868 15355 net.cpp:693] Ignoring source layer prob
I1113 15:20:26.787417 15355 solver.cpp:404]     Test net output #0: accuracy = 0.989625
I1113 15:20:26.858049 15355 solver.cpp:228] Iteration 30000, loss = 0.0116437
I1113 15:20:26.858090 15355 solver.cpp:244]     Train net output #0: loss = 0.0116432 (* 1 = 0.0116432 loss)
I1113 15:20:26.858106 15355 sgd_solver.cpp:106] Iteration 30000, lr = 0.001
I1113 15:22:48.006767 15355 solver.cpp:228] Iteration 31000, loss = 0.0126018
I1113 15:22:48.006844 15355 solver.cpp:244]     Train net output #0: loss = 0.0126013 (* 1 = 0.0126013 loss)
I1113 15:22:48.006855 15355 sgd_solver.cpp:106] Iteration 31000, lr = 0.001
I1113 15:25:09.156078 15355 solver.cpp:228] Iteration 32000, loss = 0.00926994
I1113 15:25:09.156214 15355 solver.cpp:244]     Train net output #0: loss = 0.00926919 (* 1 = 0.00926919 loss)
I1113 15:25:09.156229 15355 sgd_solver.cpp:106] Iteration 32000, lr = 0.001
I1113 15:27:30.260159 15355 solver.cpp:228] Iteration 33000, loss = 0.0277641
I1113 15:27:30.260320 15355 solver.cpp:244]     Train net output #0: loss = 0.0277634 (* 1 = 0.0277634 loss)
I1113 15:27:30.260339 15355 sgd_solver.cpp:106] Iteration 33000, lr = 0.001
I1113 15:29:51.360169 15355 solver.cpp:228] Iteration 34000, loss = 0.0601766
I1113 15:29:51.360324 15355 solver.cpp:244]     Train net output #0: loss = 0.0601758 (* 1 = 0.0601758 loss)
I1113 15:29:51.360343 15355 sgd_solver.cpp:106] Iteration 34000, lr = 0.001
I1113 15:32:12.377017 15355 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_35000.caffemodel
I1113 15:32:14.523319 15355 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_35000.solverstate
I1113 15:32:14.552575 15355 solver.cpp:337] Iteration 35000, Testing net (#0)
I1113 15:32:14.552605 15355 net.cpp:693] Ignoring source layer prob
I1113 15:32:30.123780 15355 solver.cpp:404]     Test net output #0: accuracy = 0.986125
I1113 15:32:30.191820 15355 solver.cpp:228] Iteration 35000, loss = 0.0567674
I1113 15:32:30.191856 15355 solver.cpp:244]     Train net output #0: loss = 0.0567665 (* 1 = 0.0567665 loss)
I1113 15:32:30.191864 15355 sgd_solver.cpp:106] Iteration 35000, lr = 0.001
I1113 15:34:51.341053 15355 solver.cpp:228] Iteration 36000, loss = 0.00517517
I1113 15:34:51.341187 15355 solver.cpp:244]     Train net output #0: loss = 0.00517403 (* 1 = 0.00517403 loss)
I1113 15:34:51.341213 15355 sgd_solver.cpp:106] Iteration 36000, lr = 0.001
I1113 15:37:12.394320 15355 solver.cpp:228] Iteration 37000, loss = 0.017422
I1113 15:37:12.394456 15355 solver.cpp:244]     Train net output #0: loss = 0.0174209 (* 1 = 0.0174209 loss)
I1113 15:37:12.394469 15355 sgd_solver.cpp:106] Iteration 37000, lr = 0.001
I1113 15:39:33.513031 15355 solver.cpp:228] Iteration 38000, loss = 0.0651009
I1113 15:39:33.513171 15355 solver.cpp:244]     Train net output #0: loss = 0.0650997 (* 1 = 0.0650997 loss)
I1113 15:39:33.513185 15355 sgd_solver.cpp:106] Iteration 38000, lr = 0.001
I1113 15:41:54.617285 15355 solver.cpp:228] Iteration 39000, loss = 0.0156377
I1113 15:41:54.617357 15355 solver.cpp:244]     Train net output #0: loss = 0.0156366 (* 1 = 0.0156366 loss)
I1113 15:41:54.617367 15355 sgd_solver.cpp:106] Iteration 39000, lr = 0.001
I1113 15:44:15.540421 15355 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_40000.caffemodel
I1113 15:44:16.898535 15355 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_40000.solverstate
I1113 15:44:16.928228 15355 solver.cpp:337] Iteration 40000, Testing net (#0)
I1113 15:44:16.928282 15355 net.cpp:693] Ignoring source layer prob
I1113 15:44:32.474795 15355 solver.cpp:404]     Test net output #0: accuracy = 0.987625
I1113 15:44:32.542927 15355 solver.cpp:228] Iteration 40000, loss = 0.00513282
I1113 15:44:32.542965 15355 solver.cpp:244]     Train net output #0: loss = 0.00513165 (* 1 = 0.00513165 loss)
I1113 15:44:32.542973 15355 sgd_solver.cpp:106] Iteration 40000, lr = 0.001
I1113 15:46:53.571667 15355 solver.cpp:228] Iteration 41000, loss = 0.0159081
I1113 15:46:53.571738 15355 solver.cpp:244]     Train net output #0: loss = 0.0159069 (* 1 = 0.0159069 loss)
I1113 15:46:53.571748 15355 sgd_solver.cpp:106] Iteration 41000, lr = 0.001
I1113 15:49:13.378293 15355 solver.cpp:228] Iteration 42000, loss = 0.0932506
I1113 15:49:13.378432 15355 solver.cpp:244]     Train net output #0: loss = 0.0932494 (* 1 = 0.0932494 loss)
I1113 15:49:13.378444 15355 sgd_solver.cpp:106] Iteration 42000, lr = 0.001
I1113 15:51:31.343227 15355 solver.cpp:228] Iteration 43000, loss = 0.0294495
I1113 15:51:31.343289 15355 solver.cpp:244]     Train net output #0: loss = 0.0294482 (* 1 = 0.0294482 loss)
I1113 15:51:31.343297 15355 sgd_solver.cpp:106] Iteration 43000, lr = 0.001
I1113 15:53:49.252375 15355 solver.cpp:228] Iteration 44000, loss = 0.0268161
I1113 15:53:49.252504 15355 solver.cpp:244]     Train net output #0: loss = 0.0268149 (* 1 = 0.0268149 loss)
I1113 15:53:49.252517 15355 sgd_solver.cpp:106] Iteration 44000, lr = 0.001
I1113 15:56:07.019610 15355 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_45000.caffemodel
I1113 15:56:09.702158 15355 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_45000.solverstate
I1113 15:56:09.731627 15355 solver.cpp:337] Iteration 45000, Testing net (#0)
I1113 15:56:09.731658 15355 net.cpp:693] Ignoring source layer prob
I1113 15:56:24.923984 15355 solver.cpp:404]     Test net output #0: accuracy = 0.986125
I1113 15:56:24.988979 15355 solver.cpp:228] Iteration 45000, loss = 0.0667244
I1113 15:56:24.989018 15355 solver.cpp:244]     Train net output #0: loss = 0.0667232 (* 1 = 0.0667232 loss)
I1113 15:56:24.989027 15355 sgd_solver.cpp:106] Iteration 45000, lr = 0.001
I1113 15:58:42.900693 15355 solver.cpp:228] Iteration 46000, loss = 0.148047
I1113 15:58:42.900816 15355 solver.cpp:244]     Train net output #0: loss = 0.148045 (* 1 = 0.148045 loss)
I1113 15:58:42.900823 15355 sgd_solver.cpp:106] Iteration 46000, lr = 0.001
I1113 16:01:00.805279 15355 solver.cpp:228] Iteration 47000, loss = 0.0075711
I1113 16:01:00.805393 15355 solver.cpp:244]     Train net output #0: loss = 0.00756987 (* 1 = 0.00756987 loss)
I1113 16:01:00.805410 15355 sgd_solver.cpp:106] Iteration 47000, lr = 0.001
I1113 16:03:18.706336 15355 solver.cpp:228] Iteration 48000, loss = 0.188174
I1113 16:03:18.706447 15355 solver.cpp:244]     Train net output #0: loss = 0.188172 (* 1 = 0.188172 loss)
I1113 16:03:18.706454 15355 sgd_solver.cpp:106] Iteration 48000, lr = 0.001
I1113 16:05:37.900684 15355 solver.cpp:228] Iteration 49000, loss = 0.0677421
I1113 16:05:37.900838 15355 solver.cpp:244]     Train net output #0: loss = 0.0677409 (* 1 = 0.0677409 loss)
I1113 16:05:37.900857 15355 sgd_solver.cpp:106] Iteration 49000, lr = 0.001
I1113 16:07:56.808817 15355 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_50000.caffemodel
I1113 16:07:57.912847 15355 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_50000.solverstate
I1113 16:07:57.942046 15355 solver.cpp:337] Iteration 50000, Testing net (#0)
I1113 16:07:57.942083 15355 net.cpp:693] Ignoring source layer prob
I1113 16:08:13.358683 15355 solver.cpp:404]     Test net output #0: accuracy = 0.983125
I1113 16:08:13.423692 15355 solver.cpp:228] Iteration 50000, loss = 0.0210407
I1113 16:08:13.423730 15355 solver.cpp:244]     Train net output #0: loss = 0.0210395 (* 1 = 0.0210395 loss)
I1113 16:08:13.423738 15355 sgd_solver.cpp:106] Iteration 50000, lr = 0.001
I1113 16:10:34.251031 15355 solver.cpp:228] Iteration 51000, loss = 0.327201
I1113 16:10:34.251233 15355 solver.cpp:244]     Train net output #0: loss = 0.3272 (* 1 = 0.3272 loss)
I1113 16:10:34.251245 15355 sgd_solver.cpp:106] Iteration 51000, lr = 0.001
I1113 16:12:54.861960 15355 solver.cpp:228] Iteration 52000, loss = 0.00669153
I1113 16:12:54.862074 15355 solver.cpp:244]     Train net output #0: loss = 0.00669031 (* 1 = 0.00669031 loss)
I1113 16:12:54.862093 15355 sgd_solver.cpp:106] Iteration 52000, lr = 0.001
I1113 16:15:15.763520 15355 solver.cpp:228] Iteration 53000, loss = 0.00253344
I1113 16:15:15.763659 15355 solver.cpp:244]     Train net output #0: loss = 0.00253222 (* 1 = 0.00253222 loss)
I1113 16:15:15.763674 15355 sgd_solver.cpp:106] Iteration 53000, lr = 0.001
I1113 16:17:37.501140 15355 solver.cpp:228] Iteration 54000, loss = 0.0866769
I1113 16:17:37.501286 15355 solver.cpp:244]     Train net output #0: loss = 0.0866757 (* 1 = 0.0866757 loss)
I1113 16:17:37.501312 15355 sgd_solver.cpp:106] Iteration 54000, lr = 0.001
I1113 16:19:57.356968 15355 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_55000.caffemodel
I1113 16:19:57.624414 15355 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_55000.solverstate
I1113 16:19:57.654213 15355 solver.cpp:337] Iteration 55000, Testing net (#0)
I1113 16:19:57.654244 15355 net.cpp:693] Ignoring source layer prob
I1113 16:20:13.063666 15355 solver.cpp:404]     Test net output #0: accuracy = 0.98275
I1113 16:20:13.128733 15355 solver.cpp:228] Iteration 55000, loss = 0.0664568
I1113 16:20:13.128777 15355 solver.cpp:244]     Train net output #0: loss = 0.0664557 (* 1 = 0.0664557 loss)
I1113 16:20:13.128784 15355 sgd_solver.cpp:106] Iteration 55000, lr = 0.001
I1113 16:22:36.804399 15355 solver.cpp:228] Iteration 56000, loss = 0.0057919
I1113 16:22:36.804553 15355 solver.cpp:244]     Train net output #0: loss = 0.00579074 (* 1 = 0.00579074 loss)
I1113 16:22:36.804564 15355 sgd_solver.cpp:106] Iteration 56000, lr = 0.001
I1113 16:25:03.481040 15355 solver.cpp:228] Iteration 57000, loss = 0.0152796
I1113 16:25:03.481176 15355 solver.cpp:244]     Train net output #0: loss = 0.0152785 (* 1 = 0.0152785 loss)
I1113 16:25:03.481196 15355 sgd_solver.cpp:106] Iteration 57000, lr = 0.001
I1113 16:27:24.563259 15355 solver.cpp:228] Iteration 58000, loss = 0.0772121
I1113 16:27:24.563422 15355 solver.cpp:244]     Train net output #0: loss = 0.077211 (* 1 = 0.077211 loss)
I1113 16:27:24.563442 15355 sgd_solver.cpp:106] Iteration 58000, lr = 0.001
I1113 16:29:43.280666 15355 solver.cpp:228] Iteration 59000, loss = 0.111372
I1113 16:29:43.280747 15355 solver.cpp:244]     Train net output #0: loss = 0.111371 (* 1 = 0.111371 loss)
I1113 16:29:43.280755 15355 sgd_solver.cpp:106] Iteration 59000, lr = 0.001
I1113 16:32:01.657596 15355 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_60000.caffemodel
I1113 16:32:02.423228 15355 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_60000.solverstate
I1113 16:32:02.452814 15355 solver.cpp:337] Iteration 60000, Testing net (#0)
I1113 16:32:02.452852 15355 net.cpp:693] Ignoring source layer prob
I1113 16:32:17.728283 15355 solver.cpp:404]     Test net output #0: accuracy = 0.978875
I1113 16:32:17.797955 15355 solver.cpp:228] Iteration 60000, loss = 0.0288639
I1113 16:32:17.798074 15355 solver.cpp:244]     Train net output #0: loss = 0.0288627 (* 1 = 0.0288627 loss)
I1113 16:32:17.798110 15355 sgd_solver.cpp:106] Iteration 60000, lr = 0.001
I1113 16:34:36.380797 15355 solver.cpp:228] Iteration 61000, loss = 0.0107724
I1113 16:34:36.380862 15355 solver.cpp:244]     Train net output #0: loss = 0.0107713 (* 1 = 0.0107713 loss)
I1113 16:34:36.380870 15355 sgd_solver.cpp:106] Iteration 61000, lr = 0.001
I1113 16:36:58.686427 15355 solver.cpp:228] Iteration 62000, loss = 0.0155679
I1113 16:36:58.691663 15355 solver.cpp:244]     Train net output #0: loss = 0.0155668 (* 1 = 0.0155668 loss)
I1113 16:36:58.691684 15355 sgd_solver.cpp:106] Iteration 62000, lr = 0.001
I1113 16:39:25.624583 15355 solver.cpp:228] Iteration 63000, loss = 0.00297875
I1113 16:39:25.624701 15355 solver.cpp:244]     Train net output #0: loss = 0.0029777 (* 1 = 0.0029777 loss)
I1113 16:39:25.624713 15355 sgd_solver.cpp:106] Iteration 63000, lr = 0.001
I1113 16:41:53.154335 15355 solver.cpp:228] Iteration 64000, loss = 0.0100556
I1113 16:41:53.159268 15355 solver.cpp:244]     Train net output #0: loss = 0.0100546 (* 1 = 0.0100546 loss)
I1113 16:41:53.159299 15355 sgd_solver.cpp:106] Iteration 64000, lr = 0.001
I1113 16:44:20.968334 15355 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_65000.caffemodel
I1113 16:44:22.738435 15355 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_65000.solverstate
I1113 16:44:22.850697 15355 solver.cpp:337] Iteration 65000, Testing net (#0)
I1113 16:44:22.850756 15355 net.cpp:693] Ignoring source layer prob
I1113 16:44:40.381198 15355 solver.cpp:404]     Test net output #0: accuracy = 0.989375
I1113 16:44:40.451123 15355 solver.cpp:228] Iteration 65000, loss = 0.0642334
I1113 16:44:40.451181 15355 solver.cpp:244]     Train net output #0: loss = 0.0642323 (* 1 = 0.0642323 loss)
I1113 16:44:40.451195 15355 sgd_solver.cpp:106] Iteration 65000, lr = 0.001
I1113 16:47:08.497979 15355 solver.cpp:228] Iteration 66000, loss = 0.0153502
I1113 16:47:08.502102 15355 solver.cpp:244]     Train net output #0: loss = 0.0153492 (* 1 = 0.0153492 loss)
I1113 16:47:08.502138 15355 sgd_solver.cpp:106] Iteration 66000, lr = 0.001
I1113 16:49:37.541126 15355 solver.cpp:228] Iteration 67000, loss = 0.00426621
I1113 16:49:37.546131 15355 solver.cpp:244]     Train net output #0: loss = 0.00426521 (* 1 = 0.00426521 loss)
I1113 16:49:37.546155 15355 sgd_solver.cpp:106] Iteration 67000, lr = 0.001
I1113 16:52:07.399021 15355 solver.cpp:228] Iteration 68000, loss = 0.0137149
I1113 16:52:07.399130 15355 solver.cpp:244]     Train net output #0: loss = 0.013714 (* 1 = 0.013714 loss)
I1113 16:52:07.399142 15355 sgd_solver.cpp:106] Iteration 68000, lr = 0.001
I1113 16:54:39.922348 15355 solver.cpp:228] Iteration 69000, loss = 0.0133742
I1113 16:54:39.922490 15355 solver.cpp:244]     Train net output #0: loss = 0.0133733 (* 1 = 0.0133733 loss)
I1113 16:54:39.922510 15355 sgd_solver.cpp:106] Iteration 69000, lr = 0.001
I1113 16:57:04.147399 15355 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_70000.caffemodel
I1113 16:57:04.267649 15355 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_70000.solverstate
I1113 16:57:04.297317 15355 solver.cpp:337] Iteration 70000, Testing net (#0)
I1113 16:57:04.297345 15355 net.cpp:693] Ignoring source layer prob
I1113 16:57:20.011585 15355 solver.cpp:404]     Test net output #0: accuracy = 0.977
I1113 16:57:20.078639 15355 solver.cpp:228] Iteration 70000, loss = 0.0527891
I1113 16:57:20.078678 15355 solver.cpp:244]     Train net output #0: loss = 0.0527882 (* 1 = 0.0527882 loss)
I1113 16:57:20.078686 15355 sgd_solver.cpp:106] Iteration 70000, lr = 0.001
I1113 16:59:42.911979 15355 solver.cpp:228] Iteration 71000, loss = 0.173767
I1113 16:59:42.912163 15355 solver.cpp:244]     Train net output #0: loss = 0.173766 (* 1 = 0.173766 loss)
I1113 16:59:42.912184 15355 sgd_solver.cpp:106] Iteration 71000, lr = 0.001
I1113 17:02:06.477825 15355 solver.cpp:228] Iteration 72000, loss = 0.00520182
I1113 17:02:06.477988 15355 solver.cpp:244]     Train net output #0: loss = 0.0052005 (* 1 = 0.0052005 loss)
I1113 17:02:06.478001 15355 sgd_solver.cpp:106] Iteration 72000, lr = 0.001
I1113 17:04:29.930799 15355 solver.cpp:228] Iteration 73000, loss = 0.018188
I1113 17:04:29.930956 15355 solver.cpp:244]     Train net output #0: loss = 0.0181866 (* 1 = 0.0181866 loss)
I1113 17:04:29.930976 15355 sgd_solver.cpp:106] Iteration 73000, lr = 0.001
I1113 17:06:52.840124 15355 solver.cpp:228] Iteration 74000, loss = 0.0377433
I1113 17:06:52.840307 15355 solver.cpp:244]     Train net output #0: loss = 0.0377419 (* 1 = 0.0377419 loss)
I1113 17:06:52.840320 15355 sgd_solver.cpp:106] Iteration 74000, lr = 0.001
I1113 17:09:15.821522 15355 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_75000.caffemodel
I1113 17:09:15.969254 15355 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_75000.solverstate
I1113 17:09:15.998827 15355 solver.cpp:337] Iteration 75000, Testing net (#0)
I1113 17:09:15.998863 15355 net.cpp:693] Ignoring source layer prob
I1113 17:09:31.746443 15355 solver.cpp:404]     Test net output #0: accuracy = 0.988875
I1113 17:09:31.813645 15355 solver.cpp:228] Iteration 75000, loss = 0.0922469
I1113 17:09:31.813690 15355 solver.cpp:244]     Train net output #0: loss = 0.0922454 (* 1 = 0.0922454 loss)
I1113 17:09:31.813707 15355 sgd_solver.cpp:106] Iteration 75000, lr = 0.0001
I1113 17:11:54.445129 15355 solver.cpp:228] Iteration 76000, loss = 0.0034454
I1113 17:11:54.445211 15355 solver.cpp:244]     Train net output #0: loss = 0.00344384 (* 1 = 0.00344384 loss)
I1113 17:11:54.445224 15355 sgd_solver.cpp:106] Iteration 76000, lr = 0.0001
I1113 17:14:17.044863 15355 solver.cpp:228] Iteration 77000, loss = 0.000401679
I1113 17:14:17.045042 15355 solver.cpp:244]     Train net output #0: loss = 0.000400054 (* 1 = 0.000400054 loss)
I1113 17:14:17.045054 15355 sgd_solver.cpp:106] Iteration 77000, lr = 0.0001
I1113 17:16:41.392307 15355 solver.cpp:228] Iteration 78000, loss = 0.0022555
I1113 17:16:41.392478 15355 solver.cpp:244]     Train net output #0: loss = 0.00225394 (* 1 = 0.00225394 loss)
I1113 17:16:41.392506 15355 sgd_solver.cpp:106] Iteration 78000, lr = 0.0001
I1113 17:19:06.424460 15355 solver.cpp:228] Iteration 79000, loss = 0.00848161
I1113 17:19:06.424598 15355 solver.cpp:244]     Train net output #0: loss = 0.00848006 (* 1 = 0.00848006 loss)
I1113 17:19:06.424625 15355 sgd_solver.cpp:106] Iteration 79000, lr = 0.0001
I1113 17:21:30.486796 15355 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_80000.caffemodel
I1113 17:21:43.042233 15355 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_80000.solverstate
I1113 17:21:43.072580 15355 solver.cpp:337] Iteration 80000, Testing net (#0)
I1113 17:21:43.072615 15355 net.cpp:693] Ignoring source layer prob
I1113 17:21:58.777573 15355 solver.cpp:404]     Test net output #0: accuracy = 0.998
I1113 17:21:58.845463 15355 solver.cpp:228] Iteration 80000, loss = 0.00126039
I1113 17:21:58.845500 15355 solver.cpp:244]     Train net output #0: loss = 0.00125885 (* 1 = 0.00125885 loss)
I1113 17:21:58.845509 15355 sgd_solver.cpp:106] Iteration 80000, lr = 0.0001
I1113 17:24:22.571882 15355 solver.cpp:228] Iteration 81000, loss = 0.00402699
I1113 17:24:22.572058 15355 solver.cpp:244]     Train net output #0: loss = 0.00402546 (* 1 = 0.00402546 loss)
I1113 17:24:22.572079 15355 sgd_solver.cpp:106] Iteration 81000, lr = 0.0001
I1113 17:26:46.522867 15355 solver.cpp:228] Iteration 82000, loss = 0.0113391
I1113 17:26:46.523049 15355 solver.cpp:244]     Train net output #0: loss = 0.0113376 (* 1 = 0.0113376 loss)
I1113 17:26:46.523071 15355 sgd_solver.cpp:106] Iteration 82000, lr = 0.0001
I1113 17:29:10.010884 15355 solver.cpp:228] Iteration 83000, loss = 0.00274811
I1113 17:29:10.011042 15355 solver.cpp:244]     Train net output #0: loss = 0.00274655 (* 1 = 0.00274655 loss)
I1113 17:29:10.011070 15355 sgd_solver.cpp:106] Iteration 83000, lr = 0.0001
I1113 17:31:33.593456 15355 solver.cpp:228] Iteration 84000, loss = 0.00133633
I1113 17:31:33.593559 15355 solver.cpp:244]     Train net output #0: loss = 0.00133475 (* 1 = 0.00133475 loss)
I1113 17:31:33.593572 15355 sgd_solver.cpp:106] Iteration 84000, lr = 0.0001
I1113 17:33:56.782923 15355 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_85000.caffemodel
I1113 17:33:56.902390 15355 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_85000.solverstate
I1113 17:33:56.931681 15355 solver.cpp:337] Iteration 85000, Testing net (#0)
I1113 17:33:56.931710 15355 net.cpp:693] Ignoring source layer prob
I1113 17:34:12.659081 15355 solver.cpp:404]     Test net output #0: accuracy = 0.996875
I1113 17:34:12.726058 15355 solver.cpp:228] Iteration 85000, loss = 0.00508406
I1113 17:34:12.726096 15355 solver.cpp:244]     Train net output #0: loss = 0.0050825 (* 1 = 0.0050825 loss)
I1113 17:34:12.726104 15355 sgd_solver.cpp:106] Iteration 85000, lr = 0.0001
I1113 17:36:37.015369 15355 solver.cpp:228] Iteration 86000, loss = 0.00237828
I1113 17:36:37.015547 15355 solver.cpp:244]     Train net output #0: loss = 0.00237675 (* 1 = 0.00237675 loss)
I1113 17:36:37.015559 15355 sgd_solver.cpp:106] Iteration 86000, lr = 0.0001
I1113 17:39:07.032739 15355 solver.cpp:228] Iteration 87000, loss = 0.00264231
I1113 17:39:07.032871 15355 solver.cpp:244]     Train net output #0: loss = 0.00264075 (* 1 = 0.00264075 loss)
I1113 17:39:07.032884 15355 sgd_solver.cpp:106] Iteration 87000, lr = 0.0001
I1113 17:41:34.510818 15355 solver.cpp:228] Iteration 88000, loss = 0.00506829
I1113 17:41:34.510893 15355 solver.cpp:244]     Train net output #0: loss = 0.00506673 (* 1 = 0.00506673 loss)
I1113 17:41:34.510903 15355 sgd_solver.cpp:106] Iteration 88000, lr = 0.0001
I1113 17:44:02.801892 15355 solver.cpp:228] Iteration 89000, loss = 0.0152819
I1113 17:44:02.802023 15355 solver.cpp:244]     Train net output #0: loss = 0.0152802 (* 1 = 0.0152802 loss)
I1113 17:44:02.802033 15355 sgd_solver.cpp:106] Iteration 89000, lr = 0.0001
I1113 17:46:31.447391 15355 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_90000.caffemodel
I1113 17:46:31.981390 15355 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_90000.solverstate
I1113 17:46:32.045997 15355 solver.cpp:337] Iteration 90000, Testing net (#0)
I1113 17:46:32.046073 15355 net.cpp:693] Ignoring source layer prob
I1113 17:46:48.953544 15355 solver.cpp:404]     Test net output #0: accuracy = 0.997125
I1113 17:46:49.021392 15355 solver.cpp:228] Iteration 90000, loss = 0.00272234
I1113 17:46:49.021440 15355 solver.cpp:244]     Train net output #0: loss = 0.00272066 (* 1 = 0.00272066 loss)
I1113 17:46:49.021451 15355 sgd_solver.cpp:106] Iteration 90000, lr = 0.0001