Stas stas-sl
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| I0506 00:21:17.931069 15760 solver.cpp:280] Solving mixed_lstm | |
| I0506 00:21:17.931088 15760 solver.cpp:281] Learning Rate Policy: fixed | |
| I0506 00:21:18.209065 15760 solver.cpp:229] Iteration 0, loss = 27.5695 | |
| I0506 00:21:18.209156 15760 solver.cpp:245] Train net output #0: loss1/accuracy = 0 | |
| I0506 00:21:18.209175 15760 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0 | |
| I0506 00:21:18.209188 15760 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0506 00:21:18.209200 15760 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0506 00:21:18.209211 15760 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0 | |
| I0506 00:21:18.209223 15760 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.125 | |
| I0506 00:21:18.209236 15760 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0 |
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| I0506 00:21:17.931069 15760 solver.cpp:280] Solving mixed_lstm | |
| I0506 00:21:17.931088 15760 solver.cpp:281] Learning Rate Policy: fixed | |
| I0506 00:21:18.209065 15760 solver.cpp:229] Iteration 0, loss = 27.5695 | |
| I0506 00:21:18.209156 15760 solver.cpp:245] Train net output #0: loss1/accuracy = 0 | |
| I0506 00:21:18.209175 15760 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0 | |
| I0506 00:21:18.209188 15760 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0506 00:21:18.209200 15760 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0506 00:21:18.209211 15760 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0 | |
| I0506 00:21:18.209223 15760 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.125 | |
| I0506 00:21:18.209236 15760 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0 |
stas-sl
/ mixed_14_3
Last active
May 4, 2016 08:27
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| I0430 14:38:39.975833 15443 solver.cpp:280] Solving mixed_lstm | |
| I0430 14:38:39.975847 15443 solver.cpp:281] Learning Rate Policy: fixed | |
| I0430 14:38:40.358908 15443 solver.cpp:229] Iteration 0, loss = 5.42065 | |
| I0430 14:38:40.358966 15443 solver.cpp:245] Train net output #0: loss1/accuracy = 0.510638 | |
| I0430 14:38:40.358986 15443 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.75 | |
| I0430 14:38:40.358999 15443 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0.375 | |
| I0430 14:38:40.359011 15443 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0.375 | |
| I0430 14:38:40.359024 15443 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.375 | |
| I0430 14:38:40.359035 15443 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.375 | |
| I0430 14:38:40.359047 15443 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.625 |
stas-sl
/ mixed_14_2
Created
April 30, 2016 06:26
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| I0429 09:32:51.715076 8162 solver.cpp:280] Solving mixed_lstm | |
| I0429 09:32:51.715093 8162 solver.cpp:281] Learning Rate Policy: fixed | |
| I0429 09:32:52.102222 8162 solver.cpp:229] Iteration 0, loss = 4.62979 | |
| I0429 09:32:52.102285 8162 solver.cpp:245] Train net output #0: loss1/accuracy = 0.4 | |
| I0429 09:32:52.102303 8162 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.125 | |
| I0429 09:32:52.102318 8162 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0.5 | |
| I0429 09:32:52.102329 8162 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0.375 | |
| I0429 09:32:52.102342 8162 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.25 | |
| I0429 09:32:52.102355 8162 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.5 | |
| I0429 09:32:52.102366 8162 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.5 |
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| I0428 23:20:07.606009 6470 solver.cpp:280] Solving mixed_lstm | |
| I0428 23:20:07.606020 6470 solver.cpp:281] Learning Rate Policy: fixed | |
| I0428 23:20:07.969547 6470 solver.cpp:229] Iteration 0, loss = 27.5204 | |
| I0428 23:20:07.969617 6470 solver.cpp:245] Train net output #0: loss1/accuracy = 0 | |
| I0428 23:20:07.969635 6470 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0 | |
| I0428 23:20:07.969650 6470 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0 | |
| I0428 23:20:07.969666 6470 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0 | |
| I0428 23:20:07.969679 6470 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0 | |
| I0428 23:20:07.969691 6470 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0.125 | |
| I0428 23:20:07.969703 6470 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0 |
stas-sl
/ mixed_lstm11_bn
Last active
April 27, 2016 06:45
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| I0425 10:06:42.668747 22523 solver.cpp:280] Solving mixed_lstm | |
| I0425 10:06:42.668761 22523 solver.cpp:281] Learning Rate Policy: step | |
| I0425 10:06:42.687485 22523 solver.cpp:338] Iteration 0, Testing net (#0) | |
| I0425 10:07:34.893544 22523 solver.cpp:393] Test loss: 1.17466 | |
| I0425 10:07:34.894027 22523 solver.cpp:406] Test net output #0: loss1/accuracy = 0.822526 | |
| I0425 10:07:34.894048 22523 solver.cpp:406] Test net output #1: loss1/accuracy01 = 0.92 | |
| I0425 10:07:34.894062 22523 solver.cpp:406] Test net output #2: loss1/accuracy02 = 0.723 | |
| I0425 10:07:34.894073 22523 solver.cpp:406] Test net output #3: loss1/accuracy03 = 0.567 | |
| I0425 10:07:34.894085 22523 solver.cpp:406] Test net output #4: loss1/accuracy04 = 0.553 | |
| I0425 10:07:34.894098 22523 solver.cpp:406] Test net output #5: loss1/accuracy05 = 0.616 |
stas-sl
/ mixed_lstm10_bn_2
Created
April 22, 2016 21:04
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| I0421 23:25:34.773021 32397 solver.cpp:280] Solving mixed_lstm | |
| I0421 23:25:34.773036 32397 solver.cpp:281] Learning Rate Policy: fixed | |
| I0421 23:25:35.594626 32397 solver.cpp:229] Iteration 0, loss = 2.77223 | |
| I0421 23:25:35.594671 32397 solver.cpp:245] Train net output #0: loss1/accuracy = 0.528302 | |
| I0421 23:25:35.594687 32397 solver.cpp:245] Train net output #1: loss1/accuracy01 = 0.875 | |
| I0421 23:25:35.594701 32397 solver.cpp:245] Train net output #2: loss1/accuracy02 = 0.625 | |
| I0421 23:25:35.594712 32397 solver.cpp:245] Train net output #3: loss1/accuracy03 = 0.25 | |
| I0421 23:25:35.594724 32397 solver.cpp:245] Train net output #4: loss1/accuracy04 = 0.375 | |
| I0421 23:25:35.594737 32397 solver.cpp:245] Train net output #5: loss1/accuracy05 = 0 | |
| I0421 23:25:35.594748 32397 solver.cpp:245] Train net output #6: loss1/accuracy06 = 0.625 |
stas-sl
/ mixed_lstm10_bn
Last active
April 19, 2016 15:17
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| I0407 23:54:15.468787 3443 solver.cpp:280] Solving mixed_lstm | |
| I0407 23:54:15.468801 3443 solver.cpp:281] Learning Rate Policy: poly | |
| I0407 23:54:16.245584 3443 solver.cpp:229] Iteration 0, loss = 13.8505 | |
| I0407 23:54:16.245641 3443 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0208333 | |
| I0407 23:54:16.245658 3443 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.00568182 | |
| I0407 23:54:16.245672 3443 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.0416667 | |
| I0407 23:54:16.245688 3443 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 4.34597 (* 0.3 = 1.30379 loss) | |
| I0407 23:54:16.245735 3443 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 4.31917 (* 0.3 = 1.29575 loss) | |
| I0407 23:54:16.245749 3443 solver.cpp:245] Train net output #5: loss2/accuracy = 0 | |
| I0407 23:54:16.245761 3443 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0 |
stas-sl
/ firenet150x50_len22_6_trainval
Last active
April 8, 2016 06:23
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| I0407 15:14:50.542440 1004 solver.cpp:280] Solving | |
| I0407 15:14:50.542451 1004 solver.cpp:281] Learning Rate Policy: poly | |
| I0407 15:14:50.601984 1004 solver.cpp:229] Iteration 0, loss = 4.3042 | |
| I0407 15:14:50.602022 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 15:14:50.602041 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:14:50.602053 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:14:50.602068 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 15:14:50.602082 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0 | |
| I0407 15:14:50.602092 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0 | |
| I0407 15:14:50.602120 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0 |
stas-sl
/ firenet150x50_len22_5_trainval
Last active
April 7, 2016 12:11
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| I0407 12:20:09.825912 32304 solver.cpp:280] Solving | |
| I0407 12:20:09.825924 32304 solver.cpp:281] Learning Rate Policy: poly | |
| I0407 12:20:10.069551 32304 solver.cpp:229] Iteration 0, loss = 4.30406 | |
| I0407 12:20:10.069617 32304 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 12:20:10.069638 32304 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 12:20:10.069651 32304 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 12:20:10.069664 32304 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 12:20:10.069674 32304 solver.cpp:245] Train net output #4: loss/accuracy05 = 0 | |
| I0407 12:20:10.069711 32304 solver.cpp:245] Train net output #5: loss/accuracy06 = 0 | |
| I0407 12:20:10.069725 32304 solver.cpp:245] Train net output #6: loss/accuracy07 = 0 |