diff --git "a/training.log" "b/training.log" --- "a/training.log" +++ "b/training.log" @@ -1,4581 +1,4688 @@ -2019-08-19 22:14:25,525 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:14:25,525 Model: "SequenceTagger( +2023-04-06 02:11:15,541 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:11:15,542 Model: "SequenceTagger( (embeddings): StackedEmbeddings( - (list_embedding_0): BytePairEmbeddings(model=bpe-en-100000-50) + (list_embedding_0): BytePairEmbeddings(model=0-bpe-en-100000-50) (list_embedding_1): FlairEmbeddings( (lm): LanguageModel( - (drop): Dropout(p=0.05) + (drop): Dropout(p=0.05, inplace=False) (encoder): Embedding(300, 100) (rnn): LSTM(100, 2048) - (decoder): Linear(in_features=2048, out_features=300, bias=True) ) ) (list_embedding_2): FlairEmbeddings( (lm): LanguageModel( - (drop): Dropout(p=0.05) + (drop): Dropout(p=0.05, inplace=False) (encoder): Embedding(300, 100) (rnn): LSTM(100, 2048) - (decoder): Linear(in_features=2048, out_features=300, bias=True) ) ) ) (word_dropout): WordDropout(p=0.05) (locked_dropout): LockedDropout(p=0.5) (embedding2nn): Linear(in_features=4196, out_features=4196, bias=True) - (rnn): LSTM(4196, 256, bidirectional=True) - (linear): Linear(in_features=512, out_features=5196, bias=True) + (rnn): LSTM(4196, 256, batch_first=True, bidirectional=True) + (linear): Linear(in_features=512, out_features=4852, bias=True) + (loss_function): CrossEntropyLoss() )" -2019-08-19 22:14:25,526 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:14:25,526 Corpus: "Corpus: 75187 train + 9603 dev + 9479 test sentences" -2019-08-19 22:14:25,526 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:14:25,526 Parameters: -2019-08-19 22:14:25,526 - learning_rate: "0.1" -2019-08-19 22:14:25,526 - mini_batch_size: "32" -2019-08-19 22:14:25,526 - patience: "3" -2019-08-19 22:14:25,526 - anneal_factor: "0.5" -2019-08-19 22:14:25,526 - max_epochs: "150" -2019-08-19 22:14:25,526 - shuffle: "True" -2019-08-19 22:14:25,526 - train_with_dev: "True" -2019-08-19 22:14:25,526 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:14:25,526 Model training base path: "resources/taggers/release-frame-1" -2019-08-19 22:14:25,526 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:14:25,526 Device: cuda:0 -2019-08-19 22:14:25,526 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:14:25,526 Embeddings storage mode: cpu -2019-08-19 22:14:25,536 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:14:25,593 epoch 1 - iter 0/2650 - loss 8.59099674 - samples/sec: 166389.25 -2019-08-19 22:14:41,412 epoch 1 - iter 265/2650 - loss 1.66716476 - samples/sec: 542.39 -2019-08-19 22:14:57,304 epoch 1 - iter 530/2650 - loss 1.41986128 - samples/sec: 546.97 -2019-08-19 22:15:13,172 epoch 1 - iter 795/2650 - loss 1.29885042 - samples/sec: 539.89 -2019-08-19 22:15:27,665 epoch 1 - iter 1060/2650 - loss 1.22151241 - samples/sec: 589.69 -2019-08-19 22:15:41,800 epoch 1 - iter 1325/2650 - loss 1.16634340 - samples/sec: 604.46 -2019-08-19 22:15:56,521 epoch 1 - iter 1590/2650 - loss 1.12070837 - samples/sec: 603.95 -2019-08-19 22:16:11,121 epoch 1 - iter 1855/2650 - loss 1.08378805 - samples/sec: 589.69 -2019-08-19 22:16:25,602 epoch 1 - iter 2120/2650 - loss 1.05318826 - samples/sec: 592.19 -2019-08-19 22:16:41,221 epoch 1 - iter 2385/2650 - loss 1.02645120 - samples/sec: 547.22 -2019-08-19 22:16:56,841 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:16:56,842 EPOCH 1 done: loss 1.0040 - lr 0.1000 -2019-08-19 22:16:56,842 BAD EPOCHS (no improvement): 0 -2019-08-19 22:16:56,843 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:16:56,905 epoch 2 - iter 0/2650 - loss 0.71326655 - samples/sec: 148954.06 -2019-08-19 22:17:12,582 epoch 2 - iter 265/2650 - loss 0.77831452 - samples/sec: 546.90 -2019-08-19 22:17:28,405 epoch 2 - iter 530/2650 - loss 0.76580608 - samples/sec: 542.87 -2019-08-19 22:17:44,101 epoch 2 - iter 795/2650 - loss 0.76070495 - samples/sec: 544.23 -2019-08-19 22:17:59,544 epoch 2 - iter 1060/2650 - loss 0.74993231 - samples/sec: 553.48 -2019-08-19 22:18:15,125 epoch 2 - iter 1325/2650 - loss 0.74157147 - samples/sec: 548.44 -2019-08-19 22:18:30,711 epoch 2 - iter 1590/2650 - loss 0.73339017 - samples/sec: 548.45 -2019-08-19 22:18:46,295 epoch 2 - iter 1855/2650 - loss 0.72485553 - samples/sec: 548.30 -2019-08-19 22:19:01,909 epoch 2 - iter 2120/2650 - loss 0.71856758 - samples/sec: 547.40 -2019-08-19 22:19:17,512 epoch 2 - iter 2385/2650 - loss 0.71269892 - samples/sec: 547.79 -2019-08-19 22:19:32,969 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:19:32,970 EPOCH 2 done: loss 0.7062 - lr 0.1000 -2019-08-19 22:19:32,970 BAD EPOCHS (no improvement): 0 -2019-08-19 22:19:32,970 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:19:33,022 epoch 3 - iter 0/2650 - loss 0.66013449 - samples/sec: 175833.98 -2019-08-19 22:19:48,351 epoch 3 - iter 265/2650 - loss 0.63813129 - samples/sec: 557.47 -2019-08-19 22:20:03,834 epoch 3 - iter 530/2650 - loss 0.63119037 - samples/sec: 551.82 -2019-08-19 22:20:19,722 epoch 3 - iter 795/2650 - loss 0.62395838 - samples/sec: 537.89 -2019-08-19 22:20:35,561 epoch 3 - iter 1060/2650 - loss 0.62048624 - samples/sec: 539.56 -2019-08-19 22:20:51,399 epoch 3 - iter 1325/2650 - loss 0.61665931 - samples/sec: 539.55 -2019-08-19 22:21:06,953 epoch 3 - iter 1590/2650 - loss 0.61261192 - samples/sec: 549.38 -2019-08-19 22:21:22,532 epoch 3 - iter 1855/2650 - loss 0.61051426 - samples/sec: 548.45 -2019-08-19 22:21:38,132 epoch 3 - iter 2120/2650 - loss 0.60595954 - samples/sec: 547.99 -2019-08-19 22:21:53,714 epoch 3 - iter 2385/2650 - loss 0.60129196 - samples/sec: 548.60 -2019-08-19 22:22:09,217 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:22:09,217 EPOCH 3 done: loss 0.5969 - lr 0.1000 -2019-08-19 22:22:09,217 BAD EPOCHS (no improvement): 0 -2019-08-19 22:22:09,218 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:22:09,274 epoch 4 - iter 0/2650 - loss 0.73410964 - samples/sec: 171117.84 -2019-08-19 22:22:24,695 epoch 4 - iter 265/2650 - loss 0.54467585 - samples/sec: 554.12 -2019-08-19 22:22:40,296 epoch 4 - iter 530/2650 - loss 0.54817504 - samples/sec: 547.49 -2019-08-19 22:22:56,036 epoch 4 - iter 795/2650 - loss 0.54523838 - samples/sec: 543.01 -2019-08-19 22:23:11,794 epoch 4 - iter 1060/2650 - loss 0.54426981 - samples/sec: 542.35 -2019-08-19 22:23:27,530 epoch 4 - iter 1325/2650 - loss 0.53856475 - samples/sec: 543.08 -2019-08-19 22:23:42,964 epoch 4 - iter 1590/2650 - loss 0.53494872 - samples/sec: 554.00 -2019-08-19 22:23:58,885 epoch 4 - iter 1855/2650 - loss 0.53370361 - samples/sec: 536.57 -2019-08-19 22:24:14,419 epoch 4 - iter 2120/2650 - loss 0.53064447 - samples/sec: 550.28 -2019-08-19 22:24:29,732 epoch 4 - iter 2385/2650 - loss 0.52907321 - samples/sec: 558.20 -2019-08-19 22:24:45,113 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:24:45,113 EPOCH 4 done: loss 0.5266 - lr 0.1000 -2019-08-19 22:24:45,113 BAD EPOCHS (no improvement): 0 -2019-08-19 22:24:45,114 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:24:45,176 epoch 5 - iter 0/2650 - loss 0.55943245 - samples/sec: 151349.33 -2019-08-19 22:25:00,894 epoch 5 - iter 265/2650 - loss 0.49666332 - samples/sec: 543.47 -2019-08-19 22:25:16,211 epoch 5 - iter 530/2650 - loss 0.49070507 - samples/sec: 557.88 -2019-08-19 22:25:31,824 epoch 5 - iter 795/2650 - loss 0.48832441 - samples/sec: 547.32 -2019-08-19 22:25:47,319 epoch 5 - iter 1060/2650 - loss 0.48710133 - samples/sec: 551.75 -2019-08-19 22:26:02,681 epoch 5 - iter 1325/2650 - loss 0.48713623 - samples/sec: 556.41 -2019-08-19 22:26:18,493 epoch 5 - iter 1590/2650 - loss 0.48673440 - samples/sec: 540.37 -2019-08-19 22:26:34,114 epoch 5 - iter 1855/2650 - loss 0.48525438 - samples/sec: 547.05 -2019-08-19 22:26:49,821 epoch 5 - iter 2120/2650 - loss 0.48228533 - samples/sec: 544.24 -2019-08-19 22:27:05,325 epoch 5 - iter 2385/2650 - loss 0.48073424 - samples/sec: 551.34 -2019-08-19 22:27:20,884 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:27:20,885 EPOCH 5 done: loss 0.4787 - lr 0.1000 -2019-08-19 22:27:20,885 BAD EPOCHS (no improvement): 0 -2019-08-19 22:27:20,886 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:27:20,942 epoch 6 - iter 0/2650 - loss 0.63221174 - samples/sec: 163445.48 -2019-08-19 22:27:36,518 epoch 6 - iter 265/2650 - loss 0.46398676 - samples/sec: 548.59 -2019-08-19 22:27:51,977 epoch 6 - iter 530/2650 - loss 0.45532704 - samples/sec: 552.70 -2019-08-19 22:28:07,627 epoch 6 - iter 795/2650 - loss 0.45312193 - samples/sec: 546.06 -2019-08-19 22:28:23,235 epoch 6 - iter 1060/2650 - loss 0.45119635 - samples/sec: 547.72 -2019-08-19 22:28:38,804 epoch 6 - iter 1325/2650 - loss 0.44928052 - samples/sec: 549.00 -2019-08-19 22:28:54,387 epoch 6 - iter 1590/2650 - loss 0.44701395 - samples/sec: 548.37 -2019-08-19 22:29:10,303 epoch 6 - iter 1855/2650 - loss 0.44617447 - samples/sec: 536.74 -2019-08-19 22:29:26,053 epoch 6 - iter 2120/2650 - loss 0.44550759 - samples/sec: 542.59 -2019-08-19 22:29:41,594 epoch 6 - iter 2385/2650 - loss 0.44379488 - samples/sec: 550.15 -2019-08-19 22:29:57,204 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:29:57,205 EPOCH 6 done: loss 0.4413 - lr 0.1000 -2019-08-19 22:29:57,205 BAD EPOCHS (no improvement): 0 -2019-08-19 22:29:57,206 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:29:57,269 epoch 7 - iter 0/2650 - loss 0.36317006 - samples/sec: 143673.62 -2019-08-19 22:30:12,635 epoch 7 - iter 265/2650 - loss 0.43064775 - samples/sec: 556.15 -2019-08-19 22:30:28,292 epoch 7 - iter 530/2650 - loss 0.42807218 - samples/sec: 545.74 -2019-08-19 22:30:43,947 epoch 7 - iter 795/2650 - loss 0.42837209 - samples/sec: 545.79 -2019-08-19 22:30:59,517 epoch 7 - iter 1060/2650 - loss 0.42643854 - samples/sec: 548.97 -2019-08-19 22:31:15,198 epoch 7 - iter 1325/2650 - loss 0.42466972 - samples/sec: 545.01 -2019-08-19 22:31:29,822 epoch 7 - iter 1590/2650 - loss 0.42211032 - samples/sec: 584.25 -2019-08-19 22:31:44,510 epoch 7 - iter 1855/2650 - loss 0.41876253 - samples/sec: 581.63 -2019-08-19 22:32:00,277 epoch 7 - iter 2120/2650 - loss 0.41826226 - samples/sec: 542.03 -2019-08-19 22:32:15,866 epoch 7 - iter 2385/2650 - loss 0.41550759 - samples/sec: 548.33 -2019-08-19 22:32:31,511 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:32:31,512 EPOCH 7 done: loss 0.4140 - lr 0.1000 -2019-08-19 22:32:31,512 BAD EPOCHS (no improvement): 0 -2019-08-19 22:32:31,513 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:32:31,574 epoch 8 - iter 0/2650 - loss 0.33519208 - samples/sec: 150001.89 -2019-08-19 22:32:46,993 epoch 8 - iter 265/2650 - loss 0.39565657 - samples/sec: 554.23 -2019-08-19 22:33:02,443 epoch 8 - iter 530/2650 - loss 0.39586843 - samples/sec: 553.17 -2019-08-19 22:33:17,978 epoch 8 - iter 795/2650 - loss 0.39527225 - samples/sec: 549.95 -2019-08-19 22:33:33,775 epoch 8 - iter 1060/2650 - loss 0.39428597 - samples/sec: 541.09 -2019-08-19 22:33:49,308 epoch 8 - iter 1325/2650 - loss 0.39356758 - samples/sec: 550.31 -2019-08-19 22:34:05,063 epoch 8 - iter 1590/2650 - loss 0.39483248 - samples/sec: 542.44 -2019-08-19 22:34:20,923 epoch 8 - iter 1855/2650 - loss 0.39392606 - samples/sec: 538.68 -2019-08-19 22:34:36,796 epoch 8 - iter 2120/2650 - loss 0.39315668 - samples/sec: 538.34 -2019-08-19 22:34:52,501 epoch 8 - iter 2385/2650 - loss 0.39171238 - samples/sec: 544.32 -2019-08-19 22:35:07,947 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:35:07,948 EPOCH 8 done: loss 0.3896 - lr 0.1000 -2019-08-19 22:35:07,948 BAD EPOCHS (no improvement): 0 -2019-08-19 22:35:07,948 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:35:08,023 epoch 9 - iter 0/2650 - loss 0.32004815 - samples/sec: 121257.79 -2019-08-19 22:35:23,533 epoch 9 - iter 265/2650 - loss 0.37751624 - samples/sec: 550.99 -2019-08-19 22:35:39,352 epoch 9 - iter 530/2650 - loss 0.37577435 - samples/sec: 540.10 -2019-08-19 22:35:55,116 epoch 9 - iter 795/2650 - loss 0.37468442 - samples/sec: 542.02 -2019-08-19 22:36:10,489 epoch 9 - iter 1060/2650 - loss 0.37479434 - samples/sec: 556.16 -2019-08-19 22:36:26,140 epoch 9 - iter 1325/2650 - loss 0.37333183 - samples/sec: 546.07 -2019-08-19 22:36:41,793 epoch 9 - iter 1590/2650 - loss 0.37138403 - samples/sec: 545.93 -2019-08-19 22:36:57,509 epoch 9 - iter 1855/2650 - loss 0.37088640 - samples/sec: 543.62 -2019-08-19 22:37:13,160 epoch 9 - iter 2120/2650 - loss 0.37074380 - samples/sec: 545.93 -2019-08-19 22:37:28,750 epoch 9 - iter 2385/2650 - loss 0.36915331 - samples/sec: 548.37 -2019-08-19 22:37:44,105 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:37:44,106 EPOCH 9 done: loss 0.3678 - lr 0.1000 -2019-08-19 22:37:44,106 BAD EPOCHS (no improvement): 0 -2019-08-19 22:37:44,107 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:37:44,173 epoch 10 - iter 0/2650 - loss 0.31227595 - samples/sec: 139415.56 -2019-08-19 22:37:59,745 epoch 10 - iter 265/2650 - loss 0.35325827 - samples/sec: 548.61 -2019-08-19 22:38:15,423 epoch 10 - iter 530/2650 - loss 0.35618448 - samples/sec: 544.95 -2019-08-19 22:38:30,982 epoch 10 - iter 795/2650 - loss 0.35304262 - samples/sec: 549.19 -2019-08-19 22:38:46,711 epoch 10 - iter 1060/2650 - loss 0.35399282 - samples/sec: 543.47 -2019-08-19 22:39:02,313 epoch 10 - iter 1325/2650 - loss 0.35415561 - samples/sec: 547.77 -2019-08-19 22:39:17,678 epoch 10 - iter 1590/2650 - loss 0.35292525 - samples/sec: 556.35 -2019-08-19 22:39:33,263 epoch 10 - iter 1855/2650 - loss 0.35142478 - samples/sec: 548.27 -2019-08-19 22:39:47,921 epoch 10 - iter 2120/2650 - loss 0.35047687 - samples/sec: 582.92 -2019-08-19 22:40:02,128 epoch 10 - iter 2385/2650 - loss 0.35021392 - samples/sec: 601.45 -2019-08-19 22:40:17,059 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:40:17,060 EPOCH 10 done: loss 0.3501 - lr 0.1000 -2019-08-19 22:40:17,060 BAD EPOCHS (no improvement): 0 -2019-08-19 22:40:17,060 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:40:17,117 epoch 11 - iter 0/2650 - loss 0.25498712 - samples/sec: 164742.30 -2019-08-19 22:40:32,628 epoch 11 - iter 265/2650 - loss 0.34525151 - samples/sec: 550.93 -2019-08-19 22:40:48,101 epoch 11 - iter 530/2650 - loss 0.34518316 - samples/sec: 552.24 -2019-08-19 22:41:03,878 epoch 11 - iter 795/2650 - loss 0.34172974 - samples/sec: 541.59 -2019-08-19 22:41:19,654 epoch 11 - iter 1060/2650 - loss 0.34100357 - samples/sec: 541.88 -2019-08-19 22:41:35,265 epoch 11 - iter 1325/2650 - loss 0.34019736 - samples/sec: 547.51 -2019-08-19 22:41:50,802 epoch 11 - iter 1590/2650 - loss 0.34044711 - samples/sec: 550.04 -2019-08-19 22:42:06,345 epoch 11 - iter 1855/2650 - loss 0.33906932 - samples/sec: 549.80 -2019-08-19 22:42:22,263 epoch 11 - iter 2120/2650 - loss 0.33910658 - samples/sec: 536.75 -2019-08-19 22:42:38,010 epoch 11 - iter 2385/2650 - loss 0.33932851 - samples/sec: 542.78 -2019-08-19 22:42:53,366 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:42:53,367 EPOCH 11 done: loss 0.3393 - lr 0.1000 -2019-08-19 22:42:53,367 BAD EPOCHS (no improvement): 0 -2019-08-19 22:42:53,368 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:42:53,434 epoch 12 - iter 0/2650 - loss 0.37560481 - samples/sec: 140623.81 -2019-08-19 22:43:09,067 epoch 12 - iter 265/2650 - loss 0.33473621 - samples/sec: 546.52 -2019-08-19 22:43:24,506 epoch 12 - iter 530/2650 - loss 0.33441279 - samples/sec: 553.52 -2019-08-19 22:43:40,296 epoch 12 - iter 795/2650 - loss 0.33135085 - samples/sec: 541.03 -2019-08-19 22:43:55,966 epoch 12 - iter 1060/2650 - loss 0.33122202 - samples/sec: 545.57 -2019-08-19 22:44:11,373 epoch 12 - iter 1325/2650 - loss 0.33057416 - samples/sec: 554.98 -2019-08-19 22:44:27,008 epoch 12 - iter 1590/2650 - loss 0.32995708 - samples/sec: 546.56 -2019-08-19 22:44:42,766 epoch 12 - iter 1855/2650 - loss 0.32821617 - samples/sec: 542.18 -2019-08-19 22:44:58,433 epoch 12 - iter 2120/2650 - loss 0.32715545 - samples/sec: 545.38 -2019-08-19 22:45:14,059 epoch 12 - iter 2385/2650 - loss 0.32560495 - samples/sec: 547.09 -2019-08-19 22:45:29,602 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:45:29,602 EPOCH 12 done: loss 0.3244 - lr 0.1000 -2019-08-19 22:45:29,602 BAD EPOCHS (no improvement): 0 -2019-08-19 22:45:29,603 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:45:29,658 epoch 13 - iter 0/2650 - loss 0.40027055 - samples/sec: 166600.46 -2019-08-19 22:45:45,107 epoch 13 - iter 265/2650 - loss 0.31595895 - samples/sec: 553.22 -2019-08-19 22:46:00,665 epoch 13 - iter 530/2650 - loss 0.31806686 - samples/sec: 549.24 -2019-08-19 22:46:16,415 epoch 13 - iter 795/2650 - loss 0.31615453 - samples/sec: 542.45 -2019-08-19 22:46:32,259 epoch 13 - iter 1060/2650 - loss 0.31794199 - samples/sec: 539.46 -2019-08-19 22:46:47,820 epoch 13 - iter 1325/2650 - loss 0.31559066 - samples/sec: 549.30 -2019-08-19 22:47:03,333 epoch 13 - iter 1590/2650 - loss 0.31472953 - samples/sec: 550.97 -2019-08-19 22:47:18,953 epoch 13 - iter 1855/2650 - loss 0.31486845 - samples/sec: 546.99 -2019-08-19 22:47:34,627 epoch 13 - iter 2120/2650 - loss 0.31325423 - samples/sec: 545.18 -2019-08-19 22:47:50,434 epoch 13 - iter 2385/2650 - loss 0.31331975 - samples/sec: 540.69 -2019-08-19 22:48:05,802 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:48:05,802 EPOCH 13 done: loss 0.3125 - lr 0.1000 -2019-08-19 22:48:05,803 BAD EPOCHS (no improvement): 0 -2019-08-19 22:48:05,804 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:48:05,857 epoch 14 - iter 0/2650 - loss 0.31171232 - samples/sec: 173455.27 -2019-08-19 22:48:21,554 epoch 14 - iter 265/2650 - loss 0.31021067 - samples/sec: 544.36 -2019-08-19 22:48:37,140 epoch 14 - iter 530/2650 - loss 0.30865761 - samples/sec: 548.36 -2019-08-19 22:48:52,654 epoch 14 - iter 795/2650 - loss 0.30609431 - samples/sec: 550.67 -2019-08-19 22:49:08,355 epoch 14 - iter 1060/2650 - loss 0.30612310 - samples/sec: 544.33 -2019-08-19 22:49:24,046 epoch 14 - iter 1325/2650 - loss 0.30534654 - samples/sec: 544.70 -2019-08-19 22:49:39,321 epoch 14 - iter 1590/2650 - loss 0.30470693 - samples/sec: 559.62 -2019-08-19 22:49:54,699 epoch 14 - iter 1855/2650 - loss 0.30451178 - samples/sec: 555.76 -2019-08-19 22:50:10,455 epoch 14 - iter 2120/2650 - loss 0.30375481 - samples/sec: 542.50 -2019-08-19 22:50:26,173 epoch 14 - iter 2385/2650 - loss 0.30409149 - samples/sec: 543.73 -2019-08-19 22:50:41,990 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:50:41,990 EPOCH 14 done: loss 0.3041 - lr 0.1000 -2019-08-19 22:50:41,990 BAD EPOCHS (no improvement): 0 -2019-08-19 22:50:41,991 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:50:42,061 epoch 15 - iter 0/2650 - loss 0.26974624 - samples/sec: 128232.42 -2019-08-19 22:50:57,665 epoch 15 - iter 265/2650 - loss 0.30113069 - samples/sec: 547.66 -2019-08-19 22:51:13,021 epoch 15 - iter 530/2650 - loss 0.29724519 - samples/sec: 556.52 -2019-08-19 22:51:28,807 epoch 15 - iter 795/2650 - loss 0.29551158 - samples/sec: 541.22 -2019-08-19 22:51:44,400 epoch 15 - iter 1060/2650 - loss 0.29572058 - samples/sec: 548.07 -2019-08-19 22:52:00,282 epoch 15 - iter 1325/2650 - loss 0.29625220 - samples/sec: 538.09 -2019-08-19 22:52:15,886 epoch 15 - iter 1590/2650 - loss 0.29645694 - samples/sec: 547.82 -2019-08-19 22:52:31,528 epoch 15 - iter 1855/2650 - loss 0.29607825 - samples/sec: 546.23 -2019-08-19 22:52:47,129 epoch 15 - iter 2120/2650 - loss 0.29543583 - samples/sec: 547.78 -2019-08-19 22:53:02,934 epoch 15 - iter 2385/2650 - loss 0.29466721 - samples/sec: 540.76 -2019-08-19 22:53:17,095 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:53:17,096 EPOCH 15 done: loss 0.2948 - lr 0.1000 -2019-08-19 22:53:17,096 BAD EPOCHS (no improvement): 0 -2019-08-19 22:53:17,097 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:53:17,154 epoch 16 - iter 0/2650 - loss 0.32539731 - samples/sec: 156406.15 -2019-08-19 22:53:32,202 epoch 16 - iter 265/2650 - loss 0.29628976 - samples/sec: 567.86 -2019-08-19 22:53:48,023 epoch 16 - iter 530/2650 - loss 0.28914000 - samples/sec: 540.05 -2019-08-19 22:54:03,846 epoch 16 - iter 795/2650 - loss 0.28855277 - samples/sec: 539.98 -2019-08-19 22:54:19,444 epoch 16 - iter 1060/2650 - loss 0.28792533 - samples/sec: 547.89 -2019-08-19 22:54:34,945 epoch 16 - iter 1325/2650 - loss 0.28712722 - samples/sec: 551.52 -2019-08-19 22:54:50,164 epoch 16 - iter 1590/2650 - loss 0.28790468 - samples/sec: 561.55 -2019-08-19 22:55:05,794 epoch 16 - iter 1855/2650 - loss 0.28790515 - samples/sec: 546.72 -2019-08-19 22:55:21,327 epoch 16 - iter 2120/2650 - loss 0.28790196 - samples/sec: 550.18 -2019-08-19 22:55:37,013 epoch 16 - iter 2385/2650 - loss 0.28687749 - samples/sec: 544.81 -2019-08-19 22:55:52,577 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:55:52,578 EPOCH 16 done: loss 0.2862 - lr 0.1000 -2019-08-19 22:55:52,578 BAD EPOCHS (no improvement): 0 -2019-08-19 22:55:52,579 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:55:52,630 epoch 17 - iter 0/2650 - loss 0.29281208 - samples/sec: 185293.79 -2019-08-19 22:56:07,765 epoch 17 - iter 265/2650 - loss 0.28761848 - samples/sec: 564.74 -2019-08-19 22:56:23,325 epoch 17 - iter 530/2650 - loss 0.28707239 - samples/sec: 549.24 -2019-08-19 22:56:39,011 epoch 17 - iter 795/2650 - loss 0.28197558 - samples/sec: 544.75 -2019-08-19 22:56:54,655 epoch 17 - iter 1060/2650 - loss 0.28149227 - samples/sec: 546.24 -2019-08-19 22:57:10,171 epoch 17 - iter 1325/2650 - loss 0.28075268 - samples/sec: 551.00 -2019-08-19 22:57:25,799 epoch 17 - iter 1590/2650 - loss 0.28031181 - samples/sec: 546.88 -2019-08-19 22:57:41,612 epoch 17 - iter 1855/2650 - loss 0.27885337 - samples/sec: 540.44 -2019-08-19 22:57:57,323 epoch 17 - iter 2120/2650 - loss 0.27892241 - samples/sec: 543.85 -2019-08-19 22:58:13,271 epoch 17 - iter 2385/2650 - loss 0.27883772 - samples/sec: 535.90 -2019-08-19 22:58:28,844 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:58:28,844 EPOCH 17 done: loss 0.2791 - lr 0.1000 -2019-08-19 22:58:28,845 BAD EPOCHS (no improvement): 0 -2019-08-19 22:58:28,846 ---------------------------------------------------------------------------------------------------- -2019-08-19 22:58:28,910 epoch 18 - iter 0/2650 - loss 0.36196372 - samples/sec: 141051.54 -2019-08-19 22:58:44,344 epoch 18 - iter 265/2650 - loss 0.26994119 - samples/sec: 553.88 -2019-08-19 22:58:59,984 epoch 18 - iter 530/2650 - loss 0.27388498 - samples/sec: 546.34 -2019-08-19 22:59:15,718 epoch 18 - iter 795/2650 - loss 0.27343169 - samples/sec: 542.99 -2019-08-19 22:59:31,503 epoch 18 - iter 1060/2650 - loss 0.27211975 - samples/sec: 541.42 -2019-08-19 22:59:47,376 epoch 18 - iter 1325/2650 - loss 0.27284622 - samples/sec: 538.56 -2019-08-19 23:00:02,740 epoch 18 - iter 1590/2650 - loss 0.27267814 - samples/sec: 556.48 -2019-08-19 23:00:18,569 epoch 18 - iter 1855/2650 - loss 0.27193196 - samples/sec: 539.75 -2019-08-19 23:00:34,215 epoch 18 - iter 2120/2650 - loss 0.27163399 - samples/sec: 546.15 -2019-08-19 23:00:49,974 epoch 18 - iter 2385/2650 - loss 0.27103466 - samples/sec: 542.24 -2019-08-19 23:01:05,395 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:01:05,396 EPOCH 18 done: loss 0.2706 - lr 0.1000 -2019-08-19 23:01:05,396 BAD EPOCHS (no improvement): 0 -2019-08-19 23:01:05,397 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:01:05,478 epoch 19 - iter 0/2650 - loss 0.44605967 - samples/sec: 110029.85 -2019-08-19 23:01:21,188 epoch 19 - iter 265/2650 - loss 0.27579880 - samples/sec: 543.87 -2019-08-19 23:01:36,844 epoch 19 - iter 530/2650 - loss 0.27479105 - samples/sec: 545.84 -2019-08-19 23:01:52,491 epoch 19 - iter 795/2650 - loss 0.27288013 - samples/sec: 546.26 -2019-08-19 23:02:08,263 epoch 19 - iter 1060/2650 - loss 0.27074773 - samples/sec: 541.77 -2019-08-19 23:02:23,910 epoch 19 - iter 1325/2650 - loss 0.26891832 - samples/sec: 546.32 -2019-08-19 23:02:39,612 epoch 19 - iter 1590/2650 - loss 0.26914633 - samples/sec: 544.25 -2019-08-19 23:02:54,960 epoch 19 - iter 1855/2650 - loss 0.26778476 - samples/sec: 556.90 -2019-08-19 23:03:10,479 epoch 19 - iter 2120/2650 - loss 0.26706822 - samples/sec: 550.66 -2019-08-19 23:03:26,235 epoch 19 - iter 2385/2650 - loss 0.26696577 - samples/sec: 542.31 -2019-08-19 23:03:41,875 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:03:41,876 EPOCH 19 done: loss 0.2667 - lr 0.1000 -2019-08-19 23:03:41,876 BAD EPOCHS (no improvement): 0 -2019-08-19 23:03:41,877 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:03:41,938 epoch 20 - iter 0/2650 - loss 0.25083759 - samples/sec: 152760.55 -2019-08-19 23:03:57,386 epoch 20 - iter 265/2650 - loss 0.25438140 - samples/sec: 553.23 -2019-08-19 23:04:12,867 epoch 20 - iter 530/2650 - loss 0.25417518 - samples/sec: 552.02 -2019-08-19 23:04:28,404 epoch 20 - iter 795/2650 - loss 0.25683633 - samples/sec: 550.09 -2019-08-19 23:04:44,207 epoch 20 - iter 1060/2650 - loss 0.25804393 - samples/sec: 540.55 -2019-08-19 23:04:59,948 epoch 20 - iter 1325/2650 - loss 0.25740624 - samples/sec: 543.01 -2019-08-19 23:05:15,705 epoch 20 - iter 1590/2650 - loss 0.25873520 - samples/sec: 542.38 -2019-08-19 23:05:31,261 epoch 20 - iter 1855/2650 - loss 0.25834428 - samples/sec: 549.69 -2019-08-19 23:05:46,991 epoch 20 - iter 2120/2650 - loss 0.25848088 - samples/sec: 543.20 -2019-08-19 23:06:02,553 epoch 20 - iter 2385/2650 - loss 0.25866347 - samples/sec: 549.06 -2019-08-19 23:06:18,028 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:06:18,029 EPOCH 20 done: loss 0.2593 - lr 0.1000 -2019-08-19 23:06:18,029 BAD EPOCHS (no improvement): 0 -2019-08-19 23:06:18,030 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:06:18,089 epoch 21 - iter 0/2650 - loss 0.29758686 - samples/sec: 155865.37 -2019-08-19 23:06:33,576 epoch 21 - iter 265/2650 - loss 0.26903810 - samples/sec: 551.87 -2019-08-19 23:06:49,132 epoch 21 - iter 530/2650 - loss 0.26203848 - samples/sec: 549.33 -2019-08-19 23:07:04,816 epoch 21 - iter 795/2650 - loss 0.25924950 - samples/sec: 545.15 -2019-08-19 23:07:20,361 epoch 21 - iter 1060/2650 - loss 0.25589746 - samples/sec: 549.86 -2019-08-19 23:07:36,033 epoch 21 - iter 1325/2650 - loss 0.25551541 - samples/sec: 545.42 -2019-08-19 23:07:51,805 epoch 21 - iter 1590/2650 - loss 0.25563869 - samples/sec: 541.86 -2019-08-19 23:08:07,284 epoch 21 - iter 1855/2650 - loss 0.25579299 - samples/sec: 552.16 -2019-08-19 23:08:23,067 epoch 21 - iter 2120/2650 - loss 0.25571547 - samples/sec: 541.39 -2019-08-19 23:08:38,637 epoch 21 - iter 2385/2650 - loss 0.25513835 - samples/sec: 548.75 -2019-08-19 23:08:54,222 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:08:54,223 EPOCH 21 done: loss 0.2545 - lr 0.1000 -2019-08-19 23:08:54,223 BAD EPOCHS (no improvement): 0 -2019-08-19 23:08:54,224 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:08:54,289 epoch 22 - iter 0/2650 - loss 0.21395457 - samples/sec: 141178.63 -2019-08-19 23:09:09,780 epoch 22 - iter 265/2650 - loss 0.24386116 - samples/sec: 551.80 -2019-08-19 23:09:25,399 epoch 22 - iter 530/2650 - loss 0.24441336 - samples/sec: 547.16 -2019-08-19 23:09:41,199 epoch 22 - iter 795/2650 - loss 0.24841173 - samples/sec: 540.73 -2019-08-19 23:09:56,855 epoch 22 - iter 1060/2650 - loss 0.24916057 - samples/sec: 545.68 -2019-08-19 23:10:12,857 epoch 22 - iter 1325/2650 - loss 0.24848286 - samples/sec: 534.04 -2019-08-19 23:10:28,289 epoch 22 - iter 1590/2650 - loss 0.24819781 - samples/sec: 553.83 -2019-08-19 23:10:44,009 epoch 22 - iter 1855/2650 - loss 0.24882885 - samples/sec: 543.63 -2019-08-19 23:10:59,925 epoch 22 - iter 2120/2650 - loss 0.24823141 - samples/sec: 536.83 -2019-08-19 23:11:15,394 epoch 22 - iter 2385/2650 - loss 0.24767650 - samples/sec: 552.35 -2019-08-19 23:11:30,540 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:11:30,541 EPOCH 22 done: loss 0.2477 - lr 0.1000 -2019-08-19 23:11:30,541 BAD EPOCHS (no improvement): 0 -2019-08-19 23:11:30,542 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:11:30,623 epoch 23 - iter 0/2650 - loss 0.32961702 - samples/sec: 110887.78 -2019-08-19 23:11:46,281 epoch 23 - iter 265/2650 - loss 0.24561315 - samples/sec: 545.88 -2019-08-19 23:12:01,896 epoch 23 - iter 530/2650 - loss 0.24569767 - samples/sec: 547.27 -2019-08-19 23:12:17,622 epoch 23 - iter 795/2650 - loss 0.24614646 - samples/sec: 543.38 -2019-08-19 23:12:33,098 epoch 23 - iter 1060/2650 - loss 0.24538210 - samples/sec: 552.17 -2019-08-19 23:12:48,877 epoch 23 - iter 1325/2650 - loss 0.24573371 - samples/sec: 541.81 -2019-08-19 23:13:04,544 epoch 23 - iter 1590/2650 - loss 0.24533843 - samples/sec: 545.51 -2019-08-19 23:13:20,239 epoch 23 - iter 1855/2650 - loss 0.24477333 - samples/sec: 544.83 -2019-08-19 23:13:35,857 epoch 23 - iter 2120/2650 - loss 0.24478856 - samples/sec: 547.13 -2019-08-19 23:13:51,326 epoch 23 - iter 2385/2650 - loss 0.24425356 - samples/sec: 552.53 -2019-08-19 23:14:06,949 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:14:06,950 EPOCH 23 done: loss 0.2443 - lr 0.1000 -2019-08-19 23:14:06,950 BAD EPOCHS (no improvement): 0 -2019-08-19 23:14:06,951 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:14:07,014 epoch 24 - iter 0/2650 - loss 0.22940646 - samples/sec: 145996.03 -2019-08-19 23:14:22,684 epoch 24 - iter 265/2650 - loss 0.24241804 - samples/sec: 545.42 -2019-08-19 23:14:38,112 epoch 24 - iter 530/2650 - loss 0.24192584 - samples/sec: 554.01 -2019-08-19 23:14:53,887 epoch 24 - iter 795/2650 - loss 0.24196244 - samples/sec: 541.77 -2019-08-19 23:15:09,698 epoch 24 - iter 1060/2650 - loss 0.24202560 - samples/sec: 540.41 -2019-08-19 23:15:25,188 epoch 24 - iter 1325/2650 - loss 0.24212966 - samples/sec: 551.77 -2019-08-19 23:15:40,697 epoch 24 - iter 1590/2650 - loss 0.24224858 - samples/sec: 551.17 -2019-08-19 23:15:56,429 epoch 24 - iter 1855/2650 - loss 0.24258081 - samples/sec: 543.21 -2019-08-19 23:16:12,124 epoch 24 - iter 2120/2650 - loss 0.24169834 - samples/sec: 544.42 -2019-08-19 23:16:27,874 epoch 24 - iter 2385/2650 - loss 0.24149838 - samples/sec: 542.50 -2019-08-19 23:16:43,357 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:16:43,358 EPOCH 24 done: loss 0.2409 - lr 0.1000 -2019-08-19 23:16:43,358 BAD EPOCHS (no improvement): 0 -2019-08-19 23:16:43,359 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:16:43,416 epoch 25 - iter 0/2650 - loss 0.15281026 - samples/sec: 162737.28 -2019-08-19 23:16:58,804 epoch 25 - iter 265/2650 - loss 0.24365239 - samples/sec: 555.48 -2019-08-19 23:17:14,360 epoch 25 - iter 530/2650 - loss 0.23803211 - samples/sec: 549.43 -2019-08-19 23:17:29,826 epoch 25 - iter 795/2650 - loss 0.24004381 - samples/sec: 552.64 -2019-08-19 23:17:45,531 epoch 25 - iter 1060/2650 - loss 0.23949026 - samples/sec: 544.12 -2019-08-19 23:18:01,707 epoch 25 - iter 1325/2650 - loss 0.24007054 - samples/sec: 528.12 -2019-08-19 23:18:17,281 epoch 25 - iter 1590/2650 - loss 0.23990514 - samples/sec: 548.87 -2019-08-19 23:18:32,935 epoch 25 - iter 1855/2650 - loss 0.23850645 - samples/sec: 545.95 -2019-08-19 23:18:48,787 epoch 25 - iter 2120/2650 - loss 0.23713523 - samples/sec: 539.13 -2019-08-19 23:19:04,338 epoch 25 - iter 2385/2650 - loss 0.23645622 - samples/sec: 549.41 -2019-08-19 23:19:19,853 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:19:19,853 EPOCH 25 done: loss 0.2358 - lr 0.1000 -2019-08-19 23:19:19,853 BAD EPOCHS (no improvement): 0 -2019-08-19 23:19:19,865 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:19:19,918 epoch 26 - iter 0/2650 - loss 0.25280866 - samples/sec: 169846.37 -2019-08-19 23:19:35,520 epoch 26 - iter 265/2650 - loss 0.23254140 - samples/sec: 547.79 -2019-08-19 23:19:51,013 epoch 26 - iter 530/2650 - loss 0.23291683 - samples/sec: 551.59 -2019-08-19 23:20:06,578 epoch 26 - iter 795/2650 - loss 0.23140503 - samples/sec: 548.97 -2019-08-19 23:20:22,135 epoch 26 - iter 1060/2650 - loss 0.23307124 - samples/sec: 549.31 -2019-08-19 23:20:37,849 epoch 26 - iter 1325/2650 - loss 0.23289432 - samples/sec: 543.79 -2019-08-19 23:20:53,381 epoch 26 - iter 1590/2650 - loss 0.23285426 - samples/sec: 550.47 -2019-08-19 23:21:08,908 epoch 26 - iter 1855/2650 - loss 0.23267722 - samples/sec: 550.49 -2019-08-19 23:21:24,560 epoch 26 - iter 2120/2650 - loss 0.23147020 - samples/sec: 545.95 -2019-08-19 23:21:39,126 epoch 26 - iter 2385/2650 - loss 0.23136001 - samples/sec: 586.47 -2019-08-19 23:21:53,714 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:21:53,715 EPOCH 26 done: loss 0.2313 - lr 0.1000 -2019-08-19 23:21:53,715 BAD EPOCHS (no improvement): 0 -2019-08-19 23:21:53,716 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:21:53,768 epoch 27 - iter 0/2650 - loss 0.19893721 - samples/sec: 170989.50 -2019-08-19 23:22:08,007 epoch 27 - iter 265/2650 - loss 0.22608071 - samples/sec: 600.09 -2019-08-19 23:22:22,336 epoch 27 - iter 530/2650 - loss 0.22911216 - samples/sec: 596.25 -2019-08-19 23:22:36,504 epoch 27 - iter 795/2650 - loss 0.23148031 - samples/sec: 602.98 -2019-08-19 23:22:50,890 epoch 27 - iter 1060/2650 - loss 0.23018177 - samples/sec: 593.72 -2019-08-19 23:23:05,451 epoch 27 - iter 1325/2650 - loss 0.23101070 - samples/sec: 586.68 -2019-08-19 23:23:19,810 epoch 27 - iter 1590/2650 - loss 0.23078214 - samples/sec: 595.00 -2019-08-19 23:23:34,320 epoch 27 - iter 1855/2650 - loss 0.23087411 - samples/sec: 588.70 -2019-08-19 23:23:48,953 epoch 27 - iter 2120/2650 - loss 0.22997535 - samples/sec: 583.49 -2019-08-19 23:24:04,063 epoch 27 - iter 2385/2650 - loss 0.22988326 - samples/sec: 565.36 -2019-08-19 23:24:19,715 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:24:19,720 EPOCH 27 done: loss 0.2296 - lr 0.1000 -2019-08-19 23:24:19,721 BAD EPOCHS (no improvement): 0 -2019-08-19 23:24:19,721 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:24:19,786 epoch 28 - iter 0/2650 - loss 0.16799319 - samples/sec: 139839.27 -2019-08-19 23:24:35,416 epoch 28 - iter 265/2650 - loss 0.22863118 - samples/sec: 551.08 -2019-08-19 23:24:51,046 epoch 28 - iter 530/2650 - loss 0.23042438 - samples/sec: 551.40 -2019-08-19 23:25:07,171 epoch 28 - iter 795/2650 - loss 0.22825822 - samples/sec: 535.42 -2019-08-19 23:25:23,109 epoch 28 - iter 1060/2650 - loss 0.22958359 - samples/sec: 540.92 -2019-08-19 23:25:39,152 epoch 28 - iter 1325/2650 - loss 0.22838478 - samples/sec: 538.65 -2019-08-19 23:25:54,749 epoch 28 - iter 1590/2650 - loss 0.22753342 - samples/sec: 554.20 -2019-08-19 23:26:10,474 epoch 28 - iter 1855/2650 - loss 0.22668582 - samples/sec: 549.36 -2019-08-19 23:26:26,343 epoch 28 - iter 2120/2650 - loss 0.22743414 - samples/sec: 544.30 -2019-08-19 23:26:42,034 epoch 28 - iter 2385/2650 - loss 0.22676640 - samples/sec: 549.67 -2019-08-19 23:26:57,388 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:26:57,390 EPOCH 28 done: loss 0.2264 - lr 0.1000 -2019-08-19 23:26:57,390 BAD EPOCHS (no improvement): 0 -2019-08-19 23:26:57,391 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:26:57,459 epoch 29 - iter 0/2650 - loss 0.14094543 - samples/sec: 134222.79 -2019-08-19 23:27:13,226 epoch 29 - iter 265/2650 - loss 0.22493393 - samples/sec: 547.16 -2019-08-19 23:27:28,854 epoch 29 - iter 530/2650 - loss 0.22503695 - samples/sec: 547.34 -2019-08-19 23:27:44,628 epoch 29 - iter 795/2650 - loss 0.22391316 - samples/sec: 548.36 -2019-08-19 23:28:00,218 epoch 29 - iter 1060/2650 - loss 0.22264189 - samples/sec: 548.73 -2019-08-19 23:28:15,990 epoch 29 - iter 1325/2650 - loss 0.22262765 - samples/sec: 546.06 -2019-08-19 23:28:31,859 epoch 29 - iter 1590/2650 - loss 0.22272510 - samples/sec: 542.80 -2019-08-19 23:28:47,466 epoch 29 - iter 1855/2650 - loss 0.22293072 - samples/sec: 549.46 -2019-08-19 23:29:03,216 epoch 29 - iter 2120/2650 - loss 0.22346011 - samples/sec: 544.38 -2019-08-19 23:29:19,204 epoch 29 - iter 2385/2650 - loss 0.22328265 - samples/sec: 537.65 -2019-08-19 23:29:34,816 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:29:34,816 EPOCH 29 done: loss 0.2229 - lr 0.1000 -2019-08-19 23:29:34,817 BAD EPOCHS (no improvement): 0 -2019-08-19 23:29:34,819 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:29:34,880 epoch 30 - iter 0/2650 - loss 0.18331525 - samples/sec: 151440.19 -2019-08-19 23:29:50,391 epoch 30 - iter 265/2650 - loss 0.21686775 - samples/sec: 556.16 -2019-08-19 23:30:06,243 epoch 30 - iter 530/2650 - loss 0.22085530 - samples/sec: 546.88 -2019-08-19 23:30:21,941 epoch 30 - iter 795/2650 - loss 0.21849414 - samples/sec: 548.06 -2019-08-19 23:30:37,700 epoch 30 - iter 1060/2650 - loss 0.21868353 - samples/sec: 547.15 -2019-08-19 23:30:53,482 epoch 30 - iter 1325/2650 - loss 0.21961606 - samples/sec: 545.51 -2019-08-19 23:31:09,394 epoch 30 - iter 1590/2650 - loss 0.22088999 - samples/sec: 541.80 -2019-08-19 23:31:25,333 epoch 30 - iter 1855/2650 - loss 0.22086541 - samples/sec: 543.54 -2019-08-19 23:31:41,055 epoch 30 - iter 2120/2650 - loss 0.22033209 - samples/sec: 545.03 -2019-08-19 23:31:56,851 epoch 30 - iter 2385/2650 - loss 0.21995697 - samples/sec: 543.13 -2019-08-19 23:32:12,423 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:32:12,424 EPOCH 30 done: loss 0.2203 - lr 0.1000 -2019-08-19 23:32:12,424 BAD EPOCHS (no improvement): 0 -2019-08-19 23:32:12,425 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:32:12,475 epoch 31 - iter 0/2650 - loss 0.12523431 - samples/sec: 188200.83 -2019-08-19 23:32:27,799 epoch 31 - iter 265/2650 - loss 0.21382740 - samples/sec: 561.49 -2019-08-19 23:32:43,427 epoch 31 - iter 530/2650 - loss 0.22013704 - samples/sec: 553.23 -2019-08-19 23:32:59,225 epoch 31 - iter 795/2650 - loss 0.21953608 - samples/sec: 545.08 -2019-08-19 23:33:14,718 epoch 31 - iter 1060/2650 - loss 0.21923459 - samples/sec: 555.21 -2019-08-19 23:33:30,511 epoch 31 - iter 1325/2650 - loss 0.21956447 - samples/sec: 545.03 -2019-08-19 23:33:46,238 epoch 31 - iter 1590/2650 - loss 0.21933896 - samples/sec: 545.06 -2019-08-19 23:34:02,560 epoch 31 - iter 1855/2650 - loss 0.21926979 - samples/sec: 527.74 -2019-08-19 23:34:18,284 epoch 31 - iter 2120/2650 - loss 0.21886710 - samples/sec: 547.19 -2019-08-19 23:34:33,857 epoch 31 - iter 2385/2650 - loss 0.21777516 - samples/sec: 551.72 -2019-08-19 23:34:49,619 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:34:49,619 EPOCH 31 done: loss 0.2173 - lr 0.1000 -2019-08-19 23:34:49,619 BAD EPOCHS (no improvement): 0 -2019-08-19 23:34:49,621 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:34:49,679 epoch 32 - iter 0/2650 - loss 0.33263162 - samples/sec: 155885.86 -2019-08-19 23:35:05,297 epoch 32 - iter 265/2650 - loss 0.21510753 - samples/sec: 552.14 -2019-08-19 23:35:20,704 epoch 32 - iter 530/2650 - loss 0.21264153 - samples/sec: 557.19 -2019-08-19 23:35:36,351 epoch 32 - iter 795/2650 - loss 0.21428363 - samples/sec: 552.74 -2019-08-19 23:35:52,060 epoch 32 - iter 1060/2650 - loss 0.21510281 - samples/sec: 550.01 -2019-08-19 23:36:07,796 epoch 32 - iter 1325/2650 - loss 0.21499013 - samples/sec: 546.64 -2019-08-19 23:36:23,488 epoch 32 - iter 1590/2650 - loss 0.21469857 - samples/sec: 547.89 -2019-08-19 23:36:39,333 epoch 32 - iter 1855/2650 - loss 0.21487844 - samples/sec: 542.88 -2019-08-19 23:36:55,193 epoch 32 - iter 2120/2650 - loss 0.21472236 - samples/sec: 542.45 -2019-08-19 23:37:10,960 epoch 32 - iter 2385/2650 - loss 0.21469535 - samples/sec: 543.15 -2019-08-19 23:37:26,798 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:37:26,799 EPOCH 32 done: loss 0.2145 - lr 0.1000 -2019-08-19 23:37:26,799 BAD EPOCHS (no improvement): 0 -2019-08-19 23:37:26,800 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:37:26,868 epoch 33 - iter 0/2650 - loss 0.16787463 - samples/sec: 136436.76 -2019-08-19 23:37:42,264 epoch 33 - iter 265/2650 - loss 0.20941108 - samples/sec: 557.02 -2019-08-19 23:37:57,958 epoch 33 - iter 530/2650 - loss 0.21320815 - samples/sec: 548.96 -2019-08-19 23:38:13,827 epoch 33 - iter 795/2650 - loss 0.21294681 - samples/sec: 547.17 -2019-08-19 23:38:29,442 epoch 33 - iter 1060/2650 - loss 0.21212244 - samples/sec: 551.07 -2019-08-19 23:38:45,337 epoch 33 - iter 1325/2650 - loss 0.21122514 - samples/sec: 542.99 -2019-08-19 23:39:03,865 epoch 33 - iter 1590/2650 - loss 0.21242551 - samples/sec: 547.32 -2019-08-19 23:39:19,558 epoch 33 - iter 1855/2650 - loss 0.21218765 - samples/sec: 544.69 -2019-08-19 23:39:35,326 epoch 33 - iter 2120/2650 - loss 0.21148963 - samples/sec: 543.42 -2019-08-19 23:39:51,362 epoch 33 - iter 2385/2650 - loss 0.21198712 - samples/sec: 537.27 -2019-08-19 23:40:07,026 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:40:07,026 EPOCH 33 done: loss 0.2118 - lr 0.1000 -2019-08-19 23:40:07,026 BAD EPOCHS (no improvement): 0 -2019-08-19 23:40:07,027 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:40:07,084 epoch 34 - iter 0/2650 - loss 0.35110649 - samples/sec: 165455.01 -2019-08-19 23:40:22,508 epoch 34 - iter 265/2650 - loss 0.20202972 - samples/sec: 557.90 -2019-08-19 23:40:38,257 epoch 34 - iter 530/2650 - loss 0.20441395 - samples/sec: 546.21 -2019-08-19 23:40:53,994 epoch 34 - iter 795/2650 - loss 0.20552068 - samples/sec: 545.70 -2019-08-19 23:41:09,947 epoch 34 - iter 1060/2650 - loss 0.20537495 - samples/sec: 540.02 -2019-08-19 23:41:25,863 epoch 34 - iter 1325/2650 - loss 0.20622048 - samples/sec: 541.15 -2019-08-19 23:41:41,441 epoch 34 - iter 1590/2650 - loss 0.20694618 - samples/sec: 551.10 -2019-08-19 23:41:57,056 epoch 34 - iter 1855/2650 - loss 0.20773251 - samples/sec: 552.50 -2019-08-19 23:42:12,672 epoch 34 - iter 2120/2650 - loss 0.20919587 - samples/sec: 549.53 -2019-08-19 23:42:28,516 epoch 34 - iter 2385/2650 - loss 0.20927029 - samples/sec: 543.49 -2019-08-19 23:42:44,342 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:42:44,354 EPOCH 34 done: loss 0.2096 - lr 0.1000 -2019-08-19 23:42:44,354 BAD EPOCHS (no improvement): 0 -2019-08-19 23:42:44,355 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:42:44,444 epoch 35 - iter 0/2650 - loss 0.20653157 - samples/sec: 100752.93 -2019-08-19 23:42:59,990 epoch 35 - iter 265/2650 - loss 0.20655111 - samples/sec: 553.50 -2019-08-19 23:43:15,434 epoch 35 - iter 530/2650 - loss 0.20700099 - samples/sec: 555.14 -2019-08-19 23:43:31,198 epoch 35 - iter 795/2650 - loss 0.20706704 - samples/sec: 545.82 -2019-08-19 23:43:47,059 epoch 35 - iter 1060/2650 - loss 0.20596267 - samples/sec: 539.82 -2019-08-19 23:44:02,745 epoch 35 - iter 1325/2650 - loss 0.20410404 - samples/sec: 548.64 -2019-08-19 23:44:18,358 epoch 35 - iter 1590/2650 - loss 0.20374661 - samples/sec: 547.43 -2019-08-19 23:44:33,858 epoch 35 - iter 1855/2650 - loss 0.20435928 - samples/sec: 551.46 -2019-08-19 23:44:49,492 epoch 35 - iter 2120/2650 - loss 0.20382092 - samples/sec: 546.67 -2019-08-19 23:45:05,123 epoch 35 - iter 2385/2650 - loss 0.20400133 - samples/sec: 546.68 -2019-08-19 23:45:20,662 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:45:20,663 EPOCH 35 done: loss 0.2041 - lr 0.1000 -2019-08-19 23:45:20,663 BAD EPOCHS (no improvement): 0 -2019-08-19 23:45:20,664 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:45:20,723 epoch 36 - iter 0/2650 - loss 0.49937969 - samples/sec: 158398.27 -2019-08-19 23:45:36,266 epoch 36 - iter 265/2650 - loss 0.20720920 - samples/sec: 550.01 -2019-08-19 23:45:51,978 epoch 36 - iter 530/2650 - loss 0.20657344 - samples/sec: 544.05 -2019-08-19 23:46:07,390 epoch 36 - iter 795/2650 - loss 0.20587755 - samples/sec: 554.58 -2019-08-19 23:46:23,211 epoch 36 - iter 1060/2650 - loss 0.20443431 - samples/sec: 539.96 -2019-08-19 23:46:38,897 epoch 36 - iter 1325/2650 - loss 0.20400690 - samples/sec: 544.68 -2019-08-19 23:46:54,412 epoch 36 - iter 1590/2650 - loss 0.20293882 - samples/sec: 551.06 -2019-08-19 23:47:10,114 epoch 36 - iter 1855/2650 - loss 0.20276132 - samples/sec: 544.35 -2019-08-19 23:47:25,610 epoch 36 - iter 2120/2650 - loss 0.20258175 - samples/sec: 551.46 -2019-08-19 23:47:41,179 epoch 36 - iter 2385/2650 - loss 0.20314885 - samples/sec: 548.89 -2019-08-19 23:47:56,673 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:47:56,673 EPOCH 36 done: loss 0.2027 - lr 0.1000 -2019-08-19 23:47:56,674 BAD EPOCHS (no improvement): 0 -2019-08-19 23:47:56,674 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:47:56,741 epoch 37 - iter 0/2650 - loss 0.12280576 - samples/sec: 142819.79 -2019-08-19 23:48:12,291 epoch 37 - iter 265/2650 - loss 0.20127852 - samples/sec: 549.70 -2019-08-19 23:48:27,720 epoch 37 - iter 530/2650 - loss 0.20055160 - samples/sec: 554.03 -2019-08-19 23:48:43,353 epoch 37 - iter 795/2650 - loss 0.20041645 - samples/sec: 546.60 -2019-08-19 23:48:59,130 epoch 37 - iter 1060/2650 - loss 0.20205601 - samples/sec: 541.58 -2019-08-19 23:49:14,996 epoch 37 - iter 1325/2650 - loss 0.20155492 - samples/sec: 538.47 -2019-08-19 23:49:30,545 epoch 37 - iter 1590/2650 - loss 0.20241153 - samples/sec: 549.75 -2019-08-19 23:49:46,200 epoch 37 - iter 1855/2650 - loss 0.20172859 - samples/sec: 545.95 -2019-08-19 23:50:01,701 epoch 37 - iter 2120/2650 - loss 0.20202693 - samples/sec: 551.41 -2019-08-19 23:50:17,575 epoch 37 - iter 2385/2650 - loss 0.20199569 - samples/sec: 538.26 -2019-08-19 23:50:33,098 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:50:33,098 EPOCH 37 done: loss 0.2013 - lr 0.1000 -2019-08-19 23:50:33,098 BAD EPOCHS (no improvement): 0 -2019-08-19 23:50:33,099 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:50:33,155 epoch 38 - iter 0/2650 - loss 0.16063198 - samples/sec: 161429.21 -2019-08-19 23:50:47,609 epoch 38 - iter 265/2650 - loss 0.19651906 - samples/sec: 591.16 -2019-08-19 23:51:02,060 epoch 38 - iter 530/2650 - loss 0.19794597 - samples/sec: 591.20 -2019-08-19 23:51:16,571 epoch 38 - iter 795/2650 - loss 0.19868490 - samples/sec: 588.87 -2019-08-19 23:51:31,997 epoch 38 - iter 1060/2650 - loss 0.19746446 - samples/sec: 554.05 -2019-08-19 23:51:47,566 epoch 38 - iter 1325/2650 - loss 0.19699823 - samples/sec: 548.77 -2019-08-19 23:52:03,101 epoch 38 - iter 1590/2650 - loss 0.19768063 - samples/sec: 550.25 -2019-08-19 23:52:18,727 epoch 38 - iter 1855/2650 - loss 0.19837417 - samples/sec: 546.94 -2019-08-19 23:52:34,275 epoch 38 - iter 2120/2650 - loss 0.19827845 - samples/sec: 549.85 -2019-08-19 23:52:49,917 epoch 38 - iter 2385/2650 - loss 0.19795650 - samples/sec: 546.29 -2019-08-19 23:53:05,717 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:53:05,718 EPOCH 38 done: loss 0.1983 - lr 0.1000 -2019-08-19 23:53:05,718 BAD EPOCHS (no improvement): 0 -2019-08-19 23:53:05,719 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:53:05,778 epoch 39 - iter 0/2650 - loss 0.24760196 - samples/sec: 159995.76 -2019-08-19 23:53:21,318 epoch 39 - iter 265/2650 - loss 0.19286030 - samples/sec: 550.07 -2019-08-19 23:53:36,858 epoch 39 - iter 530/2650 - loss 0.19837060 - samples/sec: 550.14 -2019-08-19 23:53:52,551 epoch 39 - iter 795/2650 - loss 0.19992106 - samples/sec: 544.49 -2019-08-19 23:54:08,399 epoch 39 - iter 1060/2650 - loss 0.20048287 - samples/sec: 539.11 -2019-08-19 23:54:23,995 epoch 39 - iter 1325/2650 - loss 0.19948974 - samples/sec: 547.88 -2019-08-19 23:54:39,573 epoch 39 - iter 1590/2650 - loss 0.19806667 - samples/sec: 549.07 -2019-08-19 23:54:55,160 epoch 39 - iter 1855/2650 - loss 0.19792523 - samples/sec: 548.44 -2019-08-19 23:55:10,909 epoch 39 - iter 2120/2650 - loss 0.19919935 - samples/sec: 542.63 -2019-08-19 23:55:26,583 epoch 39 - iter 2385/2650 - loss 0.19843704 - samples/sec: 545.12 -2019-08-19 23:55:41,991 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:55:41,991 EPOCH 39 done: loss 0.1984 - lr 0.1000 -2019-08-19 23:55:41,991 BAD EPOCHS (no improvement): 1 -2019-08-19 23:55:41,992 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:55:42,055 epoch 40 - iter 0/2650 - loss 0.14787883 - samples/sec: 144028.52 -2019-08-19 23:55:57,650 epoch 40 - iter 265/2650 - loss 0.19220925 - samples/sec: 548.13 -2019-08-19 23:56:13,188 epoch 40 - iter 530/2650 - loss 0.19150406 - samples/sec: 550.10 -2019-08-19 23:56:28,576 epoch 40 - iter 795/2650 - loss 0.19432227 - samples/sec: 555.54 -2019-08-19 23:56:43,359 epoch 40 - iter 1060/2650 - loss 0.19353466 - samples/sec: 577.88 -2019-08-19 23:56:59,354 epoch 40 - iter 1325/2650 - loss 0.19364972 - samples/sec: 534.09 -2019-08-19 23:57:14,905 epoch 40 - iter 1590/2650 - loss 0.19391282 - samples/sec: 549.71 -2019-08-19 23:57:30,623 epoch 40 - iter 1855/2650 - loss 0.19412825 - samples/sec: 543.78 -2019-08-19 23:57:46,015 epoch 40 - iter 2120/2650 - loss 0.19435192 - samples/sec: 555.35 -2019-08-19 23:58:01,671 epoch 40 - iter 2385/2650 - loss 0.19445802 - samples/sec: 545.84 -2019-08-19 23:58:17,302 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:58:17,302 EPOCH 40 done: loss 0.1950 - lr 0.1000 -2019-08-19 23:58:17,302 BAD EPOCHS (no improvement): 0 -2019-08-19 23:58:17,303 ---------------------------------------------------------------------------------------------------- -2019-08-19 23:58:17,365 epoch 41 - iter 0/2650 - loss 0.23086514 - samples/sec: 145709.54 -2019-08-19 23:58:33,000 epoch 41 - iter 265/2650 - loss 0.19661124 - samples/sec: 546.66 -2019-08-19 23:58:47,440 epoch 41 - iter 530/2650 - loss 0.19493437 - samples/sec: 591.83 -2019-08-19 23:59:02,905 epoch 41 - iter 795/2650 - loss 0.19531445 - samples/sec: 552.71 -2019-08-19 23:59:18,530 epoch 41 - iter 1060/2650 - loss 0.19470108 - samples/sec: 546.92 -2019-08-19 23:59:34,335 epoch 41 - iter 1325/2650 - loss 0.19330854 - samples/sec: 540.53 -2019-08-19 23:59:49,778 epoch 41 - iter 1590/2650 - loss 0.19372585 - samples/sec: 553.50 -2019-08-20 00:00:05,333 epoch 41 - iter 1855/2650 - loss 0.19294975 - samples/sec: 549.82 -2019-08-20 00:00:21,021 epoch 41 - iter 2120/2650 - loss 0.19298053 - samples/sec: 544.72 -2019-08-20 00:00:36,895 epoch 41 - iter 2385/2650 - loss 0.19235461 - samples/sec: 538.26 -2019-08-20 00:00:52,347 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:00:52,347 EPOCH 41 done: loss 0.1921 - lr 0.1000 -2019-08-20 00:00:52,348 BAD EPOCHS (no improvement): 0 -2019-08-20 00:00:52,349 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:00:52,402 epoch 42 - iter 0/2650 - loss 0.10013852 - samples/sec: 177351.66 -2019-08-20 00:01:08,125 epoch 42 - iter 265/2650 - loss 0.18573013 - samples/sec: 543.64 -2019-08-20 00:01:23,777 epoch 42 - iter 530/2650 - loss 0.18781238 - samples/sec: 546.06 -2019-08-20 00:01:39,175 epoch 42 - iter 795/2650 - loss 0.18808984 - samples/sec: 555.09 -2019-08-20 00:01:54,664 epoch 42 - iter 1060/2650 - loss 0.18881902 - samples/sec: 551.75 -2019-08-20 00:02:10,571 epoch 42 - iter 1325/2650 - loss 0.18996250 - samples/sec: 537.01 -2019-08-20 00:02:26,347 epoch 42 - iter 1590/2650 - loss 0.18923649 - samples/sec: 541.75 -2019-08-20 00:02:42,066 epoch 42 - iter 1855/2650 - loss 0.18993912 - samples/sec: 543.78 -2019-08-20 00:02:57,682 epoch 42 - iter 2120/2650 - loss 0.19044208 - samples/sec: 547.34 -2019-08-20 00:03:13,082 epoch 42 - iter 2385/2650 - loss 0.19030543 - samples/sec: 554.95 -2019-08-20 00:03:28,722 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:03:28,723 EPOCH 42 done: loss 0.1908 - lr 0.1000 -2019-08-20 00:03:28,723 BAD EPOCHS (no improvement): 0 -2019-08-20 00:03:28,724 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:03:28,779 epoch 43 - iter 0/2650 - loss 0.15492092 - samples/sec: 171519.70 -2019-08-20 00:03:44,442 epoch 43 - iter 265/2650 - loss 0.18742334 - samples/sec: 545.80 -2019-08-20 00:04:00,312 epoch 43 - iter 530/2650 - loss 0.18900585 - samples/sec: 538.59 -2019-08-20 00:04:15,759 epoch 43 - iter 795/2650 - loss 0.18914298 - samples/sec: 553.30 -2019-08-20 00:04:31,386 epoch 43 - iter 1060/2650 - loss 0.18905504 - samples/sec: 546.83 -2019-08-20 00:04:47,052 epoch 43 - iter 1325/2650 - loss 0.18869046 - samples/sec: 545.48 -2019-08-20 00:05:02,536 epoch 43 - iter 1590/2650 - loss 0.18996170 - samples/sec: 551.97 -2019-08-20 00:05:18,104 epoch 43 - iter 1855/2650 - loss 0.18930023 - samples/sec: 549.10 -2019-08-20 00:05:33,566 epoch 43 - iter 2120/2650 - loss 0.18971582 - samples/sec: 552.78 -2019-08-20 00:05:49,327 epoch 43 - iter 2385/2650 - loss 0.18935833 - samples/sec: 542.26 -2019-08-20 00:06:04,948 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:06:04,949 EPOCH 43 done: loss 0.1892 - lr 0.1000 -2019-08-20 00:06:04,949 BAD EPOCHS (no improvement): 0 -2019-08-20 00:06:04,949 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:06:05,010 epoch 44 - iter 0/2650 - loss 0.16975994 - samples/sec: 156027.42 -2019-08-20 00:06:20,700 epoch 44 - iter 265/2650 - loss 0.18727340 - samples/sec: 544.59 -2019-08-20 00:06:36,464 epoch 44 - iter 530/2650 - loss 0.18395524 - samples/sec: 542.22 -2019-08-20 00:06:51,924 epoch 44 - iter 795/2650 - loss 0.18692889 - samples/sec: 552.89 -2019-08-20 00:07:07,552 epoch 44 - iter 1060/2650 - loss 0.18595139 - samples/sec: 546.93 -2019-08-20 00:07:23,110 epoch 44 - iter 1325/2650 - loss 0.18540281 - samples/sec: 549.27 -2019-08-20 00:07:38,987 epoch 44 - iter 1590/2650 - loss 0.18554785 - samples/sec: 538.16 -2019-08-20 00:07:54,590 epoch 44 - iter 1855/2650 - loss 0.18586202 - samples/sec: 547.88 -2019-08-20 00:08:10,066 epoch 44 - iter 2120/2650 - loss 0.18679668 - samples/sec: 552.32 -2019-08-20 00:08:25,657 epoch 44 - iter 2385/2650 - loss 0.18663593 - samples/sec: 548.19 -2019-08-20 00:08:41,191 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:08:41,191 EPOCH 44 done: loss 0.1869 - lr 0.1000 -2019-08-20 00:08:41,191 BAD EPOCHS (no improvement): 0 -2019-08-20 00:08:41,192 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:08:41,253 epoch 45 - iter 0/2650 - loss 0.10272710 - samples/sec: 150179.23 -2019-08-20 00:08:56,995 epoch 45 - iter 265/2650 - loss 0.18951790 - samples/sec: 542.75 -2019-08-20 00:09:12,513 epoch 45 - iter 530/2650 - loss 0.19105754 - samples/sec: 550.81 -2019-08-20 00:09:28,227 epoch 45 - iter 795/2650 - loss 0.19145854 - samples/sec: 543.83 -2019-08-20 00:09:43,734 epoch 45 - iter 1060/2650 - loss 0.18741153 - samples/sec: 551.14 -2019-08-20 00:09:59,518 epoch 45 - iter 1325/2650 - loss 0.18696050 - samples/sec: 541.38 -2019-08-20 00:10:15,279 epoch 45 - iter 1590/2650 - loss 0.18732248 - samples/sec: 542.11 -2019-08-20 00:10:30,860 epoch 45 - iter 1855/2650 - loss 0.18685083 - samples/sec: 548.59 -2019-08-20 00:10:46,492 epoch 45 - iter 2120/2650 - loss 0.18688114 - samples/sec: 546.83 -2019-08-20 00:11:02,094 epoch 45 - iter 2385/2650 - loss 0.18612070 - samples/sec: 547.72 -2019-08-20 00:11:17,548 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:11:17,549 EPOCH 45 done: loss 0.1862 - lr 0.1000 -2019-08-20 00:11:17,549 BAD EPOCHS (no improvement): 0 -2019-08-20 00:11:17,550 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:11:17,613 epoch 46 - iter 0/2650 - loss 0.16157024 - samples/sec: 147989.09 -2019-08-20 00:11:33,263 epoch 46 - iter 265/2650 - loss 0.19075566 - samples/sec: 545.97 -2019-08-20 00:11:48,554 epoch 46 - iter 530/2650 - loss 0.18653810 - samples/sec: 559.22 -2019-08-20 00:12:03,870 epoch 46 - iter 795/2650 - loss 0.18674590 - samples/sec: 558.16 -2019-08-20 00:12:19,658 epoch 46 - iter 1060/2650 - loss 0.18595535 - samples/sec: 541.16 -2019-08-20 00:12:35,359 epoch 46 - iter 1325/2650 - loss 0.18508470 - samples/sec: 544.20 -2019-08-20 00:12:51,211 epoch 46 - iter 1590/2650 - loss 0.18567912 - samples/sec: 538.89 -2019-08-20 00:13:07,073 epoch 46 - iter 1855/2650 - loss 0.18642753 - samples/sec: 538.84 -2019-08-20 00:13:22,616 epoch 46 - iter 2120/2650 - loss 0.18663571 - samples/sec: 549.92 -2019-08-20 00:13:38,115 epoch 46 - iter 2385/2650 - loss 0.18622236 - samples/sec: 551.41 -2019-08-20 00:13:53,737 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:13:53,737 EPOCH 46 done: loss 0.1860 - lr 0.1000 -2019-08-20 00:13:53,737 BAD EPOCHS (no improvement): 0 -2019-08-20 00:13:53,738 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:13:53,795 epoch 47 - iter 0/2650 - loss 0.24551518 - samples/sec: 163687.69 -2019-08-20 00:14:09,460 epoch 47 - iter 265/2650 - loss 0.18550519 - samples/sec: 545.38 -2019-08-20 00:14:24,835 epoch 47 - iter 530/2650 - loss 0.18517429 - samples/sec: 556.05 -2019-08-20 00:14:40,467 epoch 47 - iter 795/2650 - loss 0.18518436 - samples/sec: 546.71 -2019-08-20 00:14:55,933 epoch 47 - iter 1060/2650 - loss 0.18504280 - samples/sec: 552.67 -2019-08-20 00:15:11,625 epoch 47 - iter 1325/2650 - loss 0.18429551 - samples/sec: 544.99 -2019-08-20 00:15:26,229 epoch 47 - iter 1590/2650 - loss 0.18334557 - samples/sec: 584.88 -2019-08-20 00:15:40,905 epoch 47 - iter 1855/2650 - loss 0.18338995 - samples/sec: 582.06 -2019-08-20 00:15:55,290 epoch 47 - iter 2120/2650 - loss 0.18335034 - samples/sec: 593.93 -2019-08-20 00:16:09,686 epoch 47 - iter 2385/2650 - loss 0.18312884 - samples/sec: 593.42 -2019-08-20 00:16:24,077 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:16:24,077 EPOCH 47 done: loss 0.1823 - lr 0.1000 -2019-08-20 00:16:24,077 BAD EPOCHS (no improvement): 0 -2019-08-20 00:16:24,078 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:16:24,130 epoch 48 - iter 0/2650 - loss 0.20818339 - samples/sec: 171834.59 -2019-08-20 00:16:38,578 epoch 48 - iter 265/2650 - loss 0.18674498 - samples/sec: 591.16 -2019-08-20 00:16:52,923 epoch 48 - iter 530/2650 - loss 0.18486447 - samples/sec: 595.68 -2019-08-20 00:17:07,732 epoch 48 - iter 795/2650 - loss 0.18256051 - samples/sec: 576.89 -2019-08-20 00:17:23,570 epoch 48 - iter 1060/2650 - loss 0.18074785 - samples/sec: 539.51 -2019-08-20 00:17:39,229 epoch 48 - iter 1325/2650 - loss 0.18093633 - samples/sec: 545.73 -2019-08-20 00:17:54,745 epoch 48 - iter 1590/2650 - loss 0.18139948 - samples/sec: 550.79 -2019-08-20 00:18:10,274 epoch 48 - iter 1855/2650 - loss 0.18106720 - samples/sec: 550.54 -2019-08-20 00:18:25,737 epoch 48 - iter 2120/2650 - loss 0.18087845 - samples/sec: 552.84 -2019-08-20 00:18:41,484 epoch 48 - iter 2385/2650 - loss 0.18117624 - samples/sec: 542.74 -2019-08-20 00:18:57,077 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:18:57,078 EPOCH 48 done: loss 0.1807 - lr 0.1000 -2019-08-20 00:18:57,078 BAD EPOCHS (no improvement): 0 -2019-08-20 00:18:57,079 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:18:57,134 epoch 49 - iter 0/2650 - loss 0.17064032 - samples/sec: 173859.71 -2019-08-20 00:19:12,833 epoch 49 - iter 265/2650 - loss 0.18082704 - samples/sec: 544.53 -2019-08-20 00:19:28,436 epoch 49 - iter 530/2650 - loss 0.18068858 - samples/sec: 547.86 -2019-08-20 00:19:43,839 epoch 49 - iter 795/2650 - loss 0.18148276 - samples/sec: 554.96 -2019-08-20 00:19:59,537 epoch 49 - iter 1060/2650 - loss 0.18000424 - samples/sec: 544.38 -2019-08-20 00:20:15,325 epoch 49 - iter 1325/2650 - loss 0.18037715 - samples/sec: 541.13 -2019-08-20 00:20:31,280 epoch 49 - iter 1590/2650 - loss 0.18061975 - samples/sec: 535.47 -2019-08-20 00:20:46,859 epoch 49 - iter 1855/2650 - loss 0.17985931 - samples/sec: 548.75 -2019-08-20 00:21:02,366 epoch 49 - iter 2120/2650 - loss 0.18034141 - samples/sec: 551.15 -2019-08-20 00:21:18,026 epoch 49 - iter 2385/2650 - loss 0.18014014 - samples/sec: 545.70 -2019-08-20 00:21:33,481 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:21:33,481 EPOCH 49 done: loss 0.1805 - lr 0.1000 -2019-08-20 00:21:33,481 BAD EPOCHS (no improvement): 0 -2019-08-20 00:21:33,482 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:21:33,536 epoch 50 - iter 0/2650 - loss 0.12022720 - samples/sec: 175716.71 -2019-08-20 00:21:49,187 epoch 50 - iter 265/2650 - loss 0.17929744 - samples/sec: 545.87 -2019-08-20 00:22:04,605 epoch 50 - iter 530/2650 - loss 0.17976369 - samples/sec: 554.48 -2019-08-20 00:22:20,331 epoch 50 - iter 795/2650 - loss 0.18068269 - samples/sec: 543.49 -2019-08-20 00:22:35,679 epoch 50 - iter 1060/2650 - loss 0.18185405 - samples/sec: 556.90 -2019-08-20 00:22:51,476 epoch 50 - iter 1325/2650 - loss 0.18158468 - samples/sec: 540.84 -2019-08-20 00:23:07,015 epoch 50 - iter 1590/2650 - loss 0.18120589 - samples/sec: 549.89 -2019-08-20 00:23:22,651 epoch 50 - iter 1855/2650 - loss 0.18092781 - samples/sec: 546.81 -2019-08-20 00:23:38,259 epoch 50 - iter 2120/2650 - loss 0.18080500 - samples/sec: 547.60 -2019-08-20 00:23:53,927 epoch 50 - iter 2385/2650 - loss 0.17997464 - samples/sec: 545.54 -2019-08-20 00:24:09,559 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:24:09,560 EPOCH 50 done: loss 0.1793 - lr 0.1000 -2019-08-20 00:24:09,560 BAD EPOCHS (no improvement): 0 -2019-08-20 00:24:09,561 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:24:09,616 epoch 51 - iter 0/2650 - loss 0.18118468 - samples/sec: 169179.86 -2019-08-20 00:24:25,143 epoch 51 - iter 265/2650 - loss 0.18001101 - samples/sec: 550.29 -2019-08-20 00:24:40,929 epoch 51 - iter 530/2650 - loss 0.17948648 - samples/sec: 541.43 -2019-08-20 00:24:54,994 epoch 51 - iter 795/2650 - loss 0.17783865 - samples/sec: 607.57 -2019-08-20 00:25:09,431 epoch 51 - iter 1060/2650 - loss 0.17678009 - samples/sec: 591.65 -2019-08-20 00:25:25,220 epoch 51 - iter 1325/2650 - loss 0.17619883 - samples/sec: 541.23 -2019-08-20 00:25:40,906 epoch 51 - iter 1590/2650 - loss 0.17641101 - samples/sec: 544.65 -2019-08-20 00:25:56,455 epoch 51 - iter 1855/2650 - loss 0.17744221 - samples/sec: 549.82 -2019-08-20 00:26:12,353 epoch 51 - iter 2120/2650 - loss 0.17727450 - samples/sec: 537.56 -2019-08-20 00:26:27,843 epoch 51 - iter 2385/2650 - loss 0.17690437 - samples/sec: 551.78 -2019-08-20 00:26:43,336 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:26:43,336 EPOCH 51 done: loss 0.1775 - lr 0.1000 -2019-08-20 00:26:43,337 BAD EPOCHS (no improvement): 0 -2019-08-20 00:26:43,337 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:26:43,397 epoch 52 - iter 0/2650 - loss 0.16438434 - samples/sec: 153430.07 -2019-08-20 00:26:58,798 epoch 52 - iter 265/2650 - loss 0.18147174 - samples/sec: 554.82 -2019-08-20 00:27:14,742 epoch 52 - iter 530/2650 - loss 0.17801281 - samples/sec: 536.15 -2019-08-20 00:27:30,261 epoch 52 - iter 795/2650 - loss 0.17914631 - samples/sec: 550.78 -2019-08-20 00:27:45,740 epoch 52 - iter 1060/2650 - loss 0.17834845 - samples/sec: 552.14 -2019-08-20 00:28:01,299 epoch 52 - iter 1325/2650 - loss 0.17784619 - samples/sec: 549.21 -2019-08-20 00:28:17,221 epoch 52 - iter 1590/2650 - loss 0.17884573 - samples/sec: 536.57 -2019-08-20 00:28:32,972 epoch 52 - iter 1855/2650 - loss 0.17746894 - samples/sec: 542.63 -2019-08-20 00:28:48,311 epoch 52 - iter 2120/2650 - loss 0.17664190 - samples/sec: 557.32 -2019-08-20 00:29:03,719 epoch 52 - iter 2385/2650 - loss 0.17585326 - samples/sec: 554.86 -2019-08-20 00:29:19,140 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:29:19,141 EPOCH 52 done: loss 0.1752 - lr 0.1000 -2019-08-20 00:29:19,141 BAD EPOCHS (no improvement): 0 -2019-08-20 00:29:19,141 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:29:19,199 epoch 53 - iter 0/2650 - loss 0.14526375 - samples/sec: 159563.66 -2019-08-20 00:29:34,737 epoch 53 - iter 265/2650 - loss 0.17747556 - samples/sec: 549.87 -2019-08-20 00:29:50,362 epoch 53 - iter 530/2650 - loss 0.17713675 - samples/sec: 546.95 -2019-08-20 00:30:06,021 epoch 53 - iter 795/2650 - loss 0.17858360 - samples/sec: 545.87 -2019-08-20 00:30:21,560 epoch 53 - iter 1060/2650 - loss 0.17648463 - samples/sec: 549.93 -2019-08-20 00:30:37,085 epoch 53 - iter 1325/2650 - loss 0.17694560 - samples/sec: 550.44 -2019-08-20 00:30:52,622 epoch 53 - iter 1590/2650 - loss 0.17717760 - samples/sec: 550.02 -2019-08-20 00:31:07,997 epoch 53 - iter 1855/2650 - loss 0.17646329 - samples/sec: 555.93 -2019-08-20 00:31:23,717 epoch 53 - iter 2120/2650 - loss 0.17630070 - samples/sec: 543.73 -2019-08-20 00:31:39,523 epoch 53 - iter 2385/2650 - loss 0.17618083 - samples/sec: 540.67 -2019-08-20 00:31:55,154 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:31:55,155 EPOCH 53 done: loss 0.1759 - lr 0.1000 -2019-08-20 00:31:55,155 BAD EPOCHS (no improvement): 1 -2019-08-20 00:31:55,155 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:31:55,210 epoch 54 - iter 0/2650 - loss 0.16237158 - samples/sec: 170054.26 -2019-08-20 00:32:10,912 epoch 54 - iter 265/2650 - loss 0.17215948 - samples/sec: 544.06 -2019-08-20 00:32:26,530 epoch 54 - iter 530/2650 - loss 0.17308067 - samples/sec: 547.45 -2019-08-20 00:32:42,101 epoch 54 - iter 795/2650 - loss 0.17137985 - samples/sec: 548.88 -2019-08-20 00:32:57,604 epoch 54 - iter 1060/2650 - loss 0.17096500 - samples/sec: 551.26 -2019-08-20 00:33:13,116 epoch 54 - iter 1325/2650 - loss 0.17142410 - samples/sec: 550.91 -2019-08-20 00:33:28,918 epoch 54 - iter 1590/2650 - loss 0.17243561 - samples/sec: 540.66 -2019-08-20 00:33:44,632 epoch 54 - iter 1855/2650 - loss 0.17146680 - samples/sec: 543.84 -2019-08-20 00:34:00,221 epoch 54 - iter 2120/2650 - loss 0.17193210 - samples/sec: 548.33 -2019-08-20 00:34:16,012 epoch 54 - iter 2385/2650 - loss 0.17217037 - samples/sec: 541.15 -2019-08-20 00:34:31,725 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:34:31,726 EPOCH 54 done: loss 0.1726 - lr 0.1000 -2019-08-20 00:34:31,726 BAD EPOCHS (no improvement): 0 -2019-08-20 00:34:31,726 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:34:31,784 epoch 55 - iter 0/2650 - loss 0.19842897 - samples/sec: 160805.20 -2019-08-20 00:34:47,442 epoch 55 - iter 265/2650 - loss 0.17509412 - samples/sec: 545.61 -2019-08-20 00:35:03,111 epoch 55 - iter 530/2650 - loss 0.17311767 - samples/sec: 545.47 -2019-08-20 00:35:18,708 epoch 55 - iter 795/2650 - loss 0.17410467 - samples/sec: 548.08 -2019-08-20 00:35:34,336 epoch 55 - iter 1060/2650 - loss 0.17370049 - samples/sec: 546.84 -2019-08-20 00:35:48,612 epoch 55 - iter 1325/2650 - loss 0.17336950 - samples/sec: 598.45 -2019-08-20 00:36:03,275 epoch 55 - iter 1590/2650 - loss 0.17393896 - samples/sec: 582.40 -2019-08-20 00:36:17,567 epoch 55 - iter 1855/2650 - loss 0.17262960 - samples/sec: 597.86 -2019-08-20 00:36:31,976 epoch 55 - iter 2120/2650 - loss 0.17213970 - samples/sec: 592.88 -2019-08-20 00:36:47,651 epoch 55 - iter 2385/2650 - loss 0.17235774 - samples/sec: 545.20 -2019-08-20 00:37:03,146 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:37:03,146 EPOCH 55 done: loss 0.1720 - lr 0.1000 -2019-08-20 00:37:03,147 BAD EPOCHS (no improvement): 0 -2019-08-20 00:37:03,147 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:37:03,198 epoch 56 - iter 0/2650 - loss 0.16385296 - samples/sec: 186580.73 -2019-08-20 00:37:17,687 epoch 56 - iter 265/2650 - loss 0.17444487 - samples/sec: 589.63 -2019-08-20 00:37:32,039 epoch 56 - iter 530/2650 - loss 0.17174113 - samples/sec: 595.32 -2019-08-20 00:37:46,361 epoch 56 - iter 795/2650 - loss 0.17294190 - samples/sec: 596.57 -2019-08-20 00:38:00,668 epoch 56 - iter 1060/2650 - loss 0.17312463 - samples/sec: 597.09 -2019-08-20 00:38:16,306 epoch 56 - iter 1325/2650 - loss 0.17303782 - samples/sec: 546.77 -2019-08-20 00:38:31,936 epoch 56 - iter 1590/2650 - loss 0.17225536 - samples/sec: 546.78 -2019-08-20 00:38:47,566 epoch 56 - iter 1855/2650 - loss 0.17214963 - samples/sec: 547.01 -2019-08-20 00:39:03,224 epoch 56 - iter 2120/2650 - loss 0.17153237 - samples/sec: 545.90 -2019-08-20 00:39:19,204 epoch 56 - iter 2385/2650 - loss 0.17127074 - samples/sec: 534.74 -2019-08-20 00:39:34,757 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:39:34,757 EPOCH 56 done: loss 0.1711 - lr 0.1000 -2019-08-20 00:39:34,757 BAD EPOCHS (no improvement): 0 -2019-08-20 00:39:34,758 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:39:34,809 epoch 57 - iter 0/2650 - loss 0.19273978 - samples/sec: 182420.90 -2019-08-20 00:39:50,275 epoch 57 - iter 265/2650 - loss 0.16836555 - samples/sec: 552.31 -2019-08-20 00:40:05,808 epoch 57 - iter 530/2650 - loss 0.16970871 - samples/sec: 550.24 -2019-08-20 00:40:21,409 epoch 57 - iter 795/2650 - loss 0.16844341 - samples/sec: 547.79 -2019-08-20 00:40:37,302 epoch 57 - iter 1060/2650 - loss 0.16867528 - samples/sec: 537.66 -2019-08-20 00:40:52,960 epoch 57 - iter 1325/2650 - loss 0.16823485 - samples/sec: 545.57 -2019-08-20 00:41:08,718 epoch 57 - iter 1590/2650 - loss 0.16968210 - samples/sec: 542.09 -2019-08-20 00:41:24,414 epoch 57 - iter 1855/2650 - loss 0.16934053 - samples/sec: 544.45 -2019-08-20 00:41:39,907 epoch 57 - iter 2120/2650 - loss 0.16870016 - samples/sec: 551.71 -2019-08-20 00:41:55,628 epoch 57 - iter 2385/2650 - loss 0.16804868 - samples/sec: 543.39 -2019-08-20 00:42:11,261 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:42:11,261 EPOCH 57 done: loss 0.1678 - lr 0.1000 -2019-08-20 00:42:11,261 BAD EPOCHS (no improvement): 0 -2019-08-20 00:42:11,262 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:42:11,331 epoch 58 - iter 0/2650 - loss 0.16558382 - samples/sec: 132122.22 -2019-08-20 00:42:27,063 epoch 58 - iter 265/2650 - loss 0.16896552 - samples/sec: 543.02 -2019-08-20 00:42:42,722 epoch 58 - iter 530/2650 - loss 0.16878129 - samples/sec: 546.18 -2019-08-20 00:42:58,321 epoch 58 - iter 795/2650 - loss 0.16731893 - samples/sec: 547.79 -2019-08-20 00:43:13,788 epoch 58 - iter 1060/2650 - loss 0.16769354 - samples/sec: 552.49 -2019-08-20 00:43:29,685 epoch 58 - iter 1325/2650 - loss 0.16895886 - samples/sec: 537.27 -2019-08-20 00:43:45,493 epoch 58 - iter 1590/2650 - loss 0.16767046 - samples/sec: 540.43 -2019-08-20 00:44:01,024 epoch 58 - iter 1855/2650 - loss 0.16881694 - samples/sec: 550.29 -2019-08-20 00:44:16,734 epoch 58 - iter 2120/2650 - loss 0.16867819 - samples/sec: 543.95 -2019-08-20 00:44:32,251 epoch 58 - iter 2385/2650 - loss 0.16846610 - samples/sec: 550.41 -2019-08-20 00:44:47,681 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:44:47,682 EPOCH 58 done: loss 0.1686 - lr 0.1000 -2019-08-20 00:44:47,682 BAD EPOCHS (no improvement): 1 -2019-08-20 00:44:47,683 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:44:47,742 epoch 59 - iter 0/2650 - loss 0.21995698 - samples/sec: 160948.55 -2019-08-20 00:45:03,435 epoch 59 - iter 265/2650 - loss 0.16389459 - samples/sec: 544.25 -2019-08-20 00:45:18,906 epoch 59 - iter 530/2650 - loss 0.16745237 - samples/sec: 552.43 -2019-08-20 00:45:34,506 epoch 59 - iter 795/2650 - loss 0.16513767 - samples/sec: 547.67 -2019-08-20 00:45:50,143 epoch 59 - iter 1060/2650 - loss 0.16555205 - samples/sec: 546.21 -2019-08-20 00:46:05,906 epoch 59 - iter 1325/2650 - loss 0.16630389 - samples/sec: 542.08 -2019-08-20 00:46:21,579 epoch 59 - iter 1590/2650 - loss 0.16595267 - samples/sec: 545.14 -2019-08-20 00:46:37,225 epoch 59 - iter 1855/2650 - loss 0.16632060 - samples/sec: 546.25 -2019-08-20 00:46:52,797 epoch 59 - iter 2120/2650 - loss 0.16613691 - samples/sec: 548.82 -2019-08-20 00:47:08,264 epoch 59 - iter 2385/2650 - loss 0.16563141 - samples/sec: 552.57 -2019-08-20 00:47:23,935 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:47:23,936 EPOCH 59 done: loss 0.1663 - lr 0.1000 -2019-08-20 00:47:23,936 BAD EPOCHS (no improvement): 0 -2019-08-20 00:47:23,937 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:47:23,996 epoch 60 - iter 0/2650 - loss 0.15647285 - samples/sec: 153682.65 -2019-08-20 00:47:39,898 epoch 60 - iter 265/2650 - loss 0.16249622 - samples/sec: 537.09 -2019-08-20 00:47:55,713 epoch 60 - iter 530/2650 - loss 0.16152983 - samples/sec: 540.39 -2019-08-20 00:48:11,486 epoch 60 - iter 795/2650 - loss 0.16461942 - samples/sec: 541.92 -2019-08-20 00:48:26,957 epoch 60 - iter 1060/2650 - loss 0.16386237 - samples/sec: 552.46 -2019-08-20 00:48:42,430 epoch 60 - iter 1325/2650 - loss 0.16451866 - samples/sec: 554.78 -2019-08-20 00:48:58,137 epoch 60 - iter 1590/2650 - loss 0.16413363 - samples/sec: 543.96 -2019-08-20 00:49:13,740 epoch 60 - iter 1855/2650 - loss 0.16399683 - samples/sec: 547.74 -2019-08-20 00:49:29,342 epoch 60 - iter 2120/2650 - loss 0.16479471 - samples/sec: 548.07 -2019-08-20 00:49:45,044 epoch 60 - iter 2385/2650 - loss 0.16590240 - samples/sec: 544.42 -2019-08-20 00:50:00,571 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:50:00,571 EPOCH 60 done: loss 0.1660 - lr 0.1000 -2019-08-20 00:50:00,572 BAD EPOCHS (no improvement): 0 -2019-08-20 00:50:00,572 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:50:00,631 epoch 61 - iter 0/2650 - loss 0.16566333 - samples/sec: 152176.25 -2019-08-20 00:50:16,391 epoch 61 - iter 265/2650 - loss 0.15939569 - samples/sec: 542.08 -2019-08-20 00:50:32,178 epoch 61 - iter 530/2650 - loss 0.16096455 - samples/sec: 541.25 -2019-08-20 00:50:47,747 epoch 61 - iter 795/2650 - loss 0.16193996 - samples/sec: 549.00 -2019-08-20 00:51:03,558 epoch 61 - iter 1060/2650 - loss 0.16205794 - samples/sec: 540.53 -2019-08-20 00:51:19,060 epoch 61 - iter 1325/2650 - loss 0.16264928 - samples/sec: 551.29 -2019-08-20 00:51:34,881 epoch 61 - iter 1590/2650 - loss 0.16338731 - samples/sec: 539.97 -2019-08-20 00:51:50,515 epoch 61 - iter 1855/2650 - loss 0.16394431 - samples/sec: 546.75 -2019-08-20 00:52:06,213 epoch 61 - iter 2120/2650 - loss 0.16372591 - samples/sec: 544.44 -2019-08-20 00:52:21,881 epoch 61 - iter 2385/2650 - loss 0.16381066 - samples/sec: 545.60 -2019-08-20 00:52:37,311 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:52:37,312 EPOCH 61 done: loss 0.1638 - lr 0.1000 -2019-08-20 00:52:37,312 BAD EPOCHS (no improvement): 0 -2019-08-20 00:52:37,313 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:52:37,374 epoch 62 - iter 0/2650 - loss 0.12478349 - samples/sec: 151855.29 -2019-08-20 00:52:53,117 epoch 62 - iter 265/2650 - loss 0.16228499 - samples/sec: 542.61 -2019-08-20 00:53:08,759 epoch 62 - iter 530/2650 - loss 0.16591574 - samples/sec: 546.36 -2019-08-20 00:53:24,323 epoch 62 - iter 795/2650 - loss 0.16630126 - samples/sec: 549.25 -2019-08-20 00:53:39,938 epoch 62 - iter 1060/2650 - loss 0.16657359 - samples/sec: 547.37 -2019-08-20 00:53:55,535 epoch 62 - iter 1325/2650 - loss 0.16449843 - samples/sec: 548.01 -2019-08-20 00:54:10,939 epoch 62 - iter 1590/2650 - loss 0.16489503 - samples/sec: 554.70 -2019-08-20 00:54:26,453 epoch 62 - iter 1855/2650 - loss 0.16511341 - samples/sec: 550.83 -2019-08-20 00:54:42,152 epoch 62 - iter 2120/2650 - loss 0.16416922 - samples/sec: 544.52 -2019-08-20 00:54:57,949 epoch 62 - iter 2385/2650 - loss 0.16442208 - samples/sec: 540.98 -2019-08-20 00:55:13,569 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:55:13,570 EPOCH 62 done: loss 0.1644 - lr 0.1000 -2019-08-20 00:55:13,570 BAD EPOCHS (no improvement): 1 -2019-08-20 00:55:13,571 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:55:13,630 epoch 63 - iter 0/2650 - loss 0.09939575 - samples/sec: 157076.16 -2019-08-20 00:55:29,411 epoch 63 - iter 265/2650 - loss 0.16187153 - samples/sec: 543.52 -2019-08-20 00:55:45,046 epoch 63 - iter 530/2650 - loss 0.16367082 - samples/sec: 546.48 -2019-08-20 00:56:00,440 epoch 63 - iter 795/2650 - loss 0.16288289 - samples/sec: 555.34 -2019-08-20 00:56:15,968 epoch 63 - iter 1060/2650 - loss 0.16346731 - samples/sec: 550.39 -2019-08-20 00:56:31,556 epoch 63 - iter 1325/2650 - loss 0.16361037 - samples/sec: 548.30 -2019-08-20 00:56:47,158 epoch 63 - iter 1590/2650 - loss 0.16347986 - samples/sec: 547.73 -2019-08-20 00:57:02,947 epoch 63 - iter 1855/2650 - loss 0.16277845 - samples/sec: 541.14 -2019-08-20 00:57:18,529 epoch 63 - iter 2120/2650 - loss 0.16208126 - samples/sec: 548.58 -2019-08-20 00:57:34,240 epoch 63 - iter 2385/2650 - loss 0.16187398 - samples/sec: 544.01 -2019-08-20 00:57:49,926 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:57:49,927 EPOCH 63 done: loss 0.1614 - lr 0.1000 -2019-08-20 00:57:49,927 BAD EPOCHS (no improvement): 0 -2019-08-20 00:57:49,928 ---------------------------------------------------------------------------------------------------- -2019-08-20 00:57:49,986 epoch 64 - iter 0/2650 - loss 0.23570958 - samples/sec: 157938.27 -2019-08-20 00:58:05,527 epoch 64 - iter 265/2650 - loss 0.16565028 - samples/sec: 549.81 -2019-08-20 00:58:20,774 epoch 64 - iter 530/2650 - loss 0.16399347 - samples/sec: 560.50 -2019-08-20 00:58:36,380 epoch 64 - iter 795/2650 - loss 0.16285309 - samples/sec: 547.87 -2019-08-20 00:58:51,998 epoch 64 - iter 1060/2650 - loss 0.16308848 - samples/sec: 547.36 -2019-08-20 00:59:07,748 epoch 64 - iter 1325/2650 - loss 0.16198057 - samples/sec: 542.35 -2019-08-20 00:59:23,419 epoch 64 - iter 1590/2650 - loss 0.16195543 - samples/sec: 545.19 -2019-08-20 00:59:39,274 epoch 64 - iter 1855/2650 - loss 0.16194092 - samples/sec: 538.84 -2019-08-20 00:59:54,714 epoch 64 - iter 2120/2650 - loss 0.16178186 - samples/sec: 553.93 -2019-08-20 01:00:09,886 epoch 64 - iter 2385/2650 - loss 0.16197717 - samples/sec: 563.21 -2019-08-20 01:00:25,430 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:00:25,431 EPOCH 64 done: loss 0.1621 - lr 0.1000 -2019-08-20 01:00:25,431 BAD EPOCHS (no improvement): 1 -2019-08-20 01:00:25,433 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:00:25,487 epoch 65 - iter 0/2650 - loss 0.12983660 - samples/sec: 170199.92 -2019-08-20 01:00:40,979 epoch 65 - iter 265/2650 - loss 0.15662380 - samples/sec: 551.49 -2019-08-20 01:00:56,443 epoch 65 - iter 530/2650 - loss 0.15746519 - samples/sec: 552.59 -2019-08-20 01:01:11,969 epoch 65 - iter 795/2650 - loss 0.15942268 - samples/sec: 550.73 -2019-08-20 01:01:27,726 epoch 65 - iter 1060/2650 - loss 0.15995640 - samples/sec: 542.34 -2019-08-20 01:01:43,385 epoch 65 - iter 1325/2650 - loss 0.16086322 - samples/sec: 545.77 -2019-08-20 01:01:58,849 epoch 65 - iter 1590/2650 - loss 0.16022735 - samples/sec: 553.05 -2019-08-20 01:02:14,656 epoch 65 - iter 1855/2650 - loss 0.16027487 - samples/sec: 540.58 -2019-08-20 01:02:30,291 epoch 65 - iter 2120/2650 - loss 0.16058755 - samples/sec: 546.76 -2019-08-20 01:02:45,996 epoch 65 - iter 2385/2650 - loss 0.16032055 - samples/sec: 544.10 -2019-08-20 01:03:01,569 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:03:01,570 EPOCH 65 done: loss 0.1598 - lr 0.1000 -2019-08-20 01:03:01,570 BAD EPOCHS (no improvement): 0 -2019-08-20 01:03:01,571 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:03:01,640 epoch 66 - iter 0/2650 - loss 0.19647236 - samples/sec: 133165.97 -2019-08-20 01:03:17,393 epoch 66 - iter 265/2650 - loss 0.16372049 - samples/sec: 542.31 -2019-08-20 01:03:32,832 epoch 66 - iter 530/2650 - loss 0.16167454 - samples/sec: 553.50 -2019-08-20 01:03:48,504 epoch 66 - iter 795/2650 - loss 0.16185346 - samples/sec: 545.40 -2019-08-20 01:04:03,827 epoch 66 - iter 1060/2650 - loss 0.16100319 - samples/sec: 557.80 -2019-08-20 01:04:19,541 epoch 66 - iter 1325/2650 - loss 0.15978168 - samples/sec: 543.76 -2019-08-20 01:04:35,086 epoch 66 - iter 1590/2650 - loss 0.16011765 - samples/sec: 549.69 -2019-08-20 01:04:50,808 epoch 66 - iter 1855/2650 - loss 0.15992827 - samples/sec: 543.43 -2019-08-20 01:05:06,391 epoch 66 - iter 2120/2650 - loss 0.16048040 - samples/sec: 548.80 -2019-08-20 01:05:21,992 epoch 66 - iter 2385/2650 - loss 0.16049776 - samples/sec: 547.91 -2019-08-20 01:05:37,761 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:05:37,761 EPOCH 66 done: loss 0.1605 - lr 0.1000 -2019-08-20 01:05:37,761 BAD EPOCHS (no improvement): 1 -2019-08-20 01:05:37,763 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:05:37,824 epoch 67 - iter 0/2650 - loss 0.11604624 - samples/sec: 152194.48 -2019-08-20 01:05:53,321 epoch 67 - iter 265/2650 - loss 0.16005195 - samples/sec: 551.47 -2019-08-20 01:06:08,973 epoch 67 - iter 530/2650 - loss 0.16022655 - samples/sec: 545.81 -2019-08-20 01:06:24,460 epoch 67 - iter 795/2650 - loss 0.15937072 - samples/sec: 552.09 -2019-08-20 01:06:40,024 epoch 67 - iter 1060/2650 - loss 0.15928141 - samples/sec: 549.19 -2019-08-20 01:06:55,861 epoch 67 - iter 1325/2650 - loss 0.15934004 - samples/sec: 539.64 -2019-08-20 01:07:11,814 epoch 67 - iter 1590/2650 - loss 0.15974317 - samples/sec: 535.49 -2019-08-20 01:07:27,432 epoch 67 - iter 1855/2650 - loss 0.15922718 - samples/sec: 547.09 -2019-08-20 01:07:43,109 epoch 67 - iter 2120/2650 - loss 0.15925940 - samples/sec: 545.27 -2019-08-20 01:07:58,679 epoch 67 - iter 2385/2650 - loss 0.15891131 - samples/sec: 548.94 -2019-08-20 01:08:14,200 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:08:14,200 EPOCH 67 done: loss 0.1585 - lr 0.1000 -2019-08-20 01:08:14,201 BAD EPOCHS (no improvement): 0 -2019-08-20 01:08:14,202 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:08:14,262 epoch 68 - iter 0/2650 - loss 0.12822534 - samples/sec: 152162.58 -2019-08-20 01:08:29,874 epoch 68 - iter 265/2650 - loss 0.15454575 - samples/sec: 547.28 -2019-08-20 01:08:45,456 epoch 68 - iter 530/2650 - loss 0.15778074 - samples/sec: 548.34 -2019-08-20 01:09:01,223 epoch 68 - iter 795/2650 - loss 0.15740512 - samples/sec: 542.14 -2019-08-20 01:09:16,874 epoch 68 - iter 1060/2650 - loss 0.15813451 - samples/sec: 546.13 -2019-08-20 01:09:32,228 epoch 68 - iter 1325/2650 - loss 0.15664546 - samples/sec: 556.88 -2019-08-20 01:09:47,731 epoch 68 - iter 1590/2650 - loss 0.15673308 - samples/sec: 551.17 -2019-08-20 01:10:03,489 epoch 68 - iter 1855/2650 - loss 0.15651596 - samples/sec: 542.18 -2019-08-20 01:10:19,205 epoch 68 - iter 2120/2650 - loss 0.15657311 - samples/sec: 543.83 -2019-08-20 01:10:34,783 epoch 68 - iter 2385/2650 - loss 0.15726901 - samples/sec: 548.68 -2019-08-20 01:10:50,161 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:10:50,162 EPOCH 68 done: loss 0.1575 - lr 0.1000 -2019-08-20 01:10:50,162 BAD EPOCHS (no improvement): 0 -2019-08-20 01:10:50,163 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:10:50,222 epoch 69 - iter 0/2650 - loss 0.10856034 - samples/sec: 155428.09 -2019-08-20 01:11:05,881 epoch 69 - iter 265/2650 - loss 0.16049600 - samples/sec: 545.61 -2019-08-20 01:11:21,591 epoch 69 - iter 530/2650 - loss 0.15805749 - samples/sec: 543.75 -2019-08-20 01:11:37,291 epoch 69 - iter 795/2650 - loss 0.15778062 - samples/sec: 544.35 -2019-08-20 01:11:52,887 epoch 69 - iter 1060/2650 - loss 0.15701510 - samples/sec: 548.01 -2019-08-20 01:12:08,619 epoch 69 - iter 1325/2650 - loss 0.15743576 - samples/sec: 543.26 -2019-08-20 01:12:24,537 epoch 69 - iter 1590/2650 - loss 0.15663787 - samples/sec: 536.75 -2019-08-20 01:12:40,236 epoch 69 - iter 1855/2650 - loss 0.15656121 - samples/sec: 545.68 -2019-08-20 01:12:55,603 epoch 69 - iter 2120/2650 - loss 0.15650452 - samples/sec: 556.37 -2019-08-20 01:13:11,087 epoch 69 - iter 2385/2650 - loss 0.15665051 - samples/sec: 552.04 -2019-08-20 01:13:26,491 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:13:26,491 EPOCH 69 done: loss 0.1564 - lr 0.1000 -2019-08-20 01:13:26,492 BAD EPOCHS (no improvement): 0 -2019-08-20 01:13:26,493 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:13:26,557 epoch 70 - iter 0/2650 - loss 0.09800376 - samples/sec: 142627.93 -2019-08-20 01:13:42,174 epoch 70 - iter 265/2650 - loss 0.15643673 - samples/sec: 548.01 -2019-08-20 01:13:57,916 epoch 70 - iter 530/2650 - loss 0.15530982 - samples/sec: 542.71 -2019-08-20 01:14:13,734 epoch 70 - iter 795/2650 - loss 0.15384866 - samples/sec: 540.31 -2019-08-20 01:14:29,360 epoch 70 - iter 1060/2650 - loss 0.15467861 - samples/sec: 547.12 -2019-08-20 01:14:45,045 epoch 70 - iter 1325/2650 - loss 0.15519881 - samples/sec: 544.79 -2019-08-20 01:15:00,667 epoch 70 - iter 1590/2650 - loss 0.15498933 - samples/sec: 547.04 -2019-08-20 01:15:16,101 epoch 70 - iter 1855/2650 - loss 0.15504247 - samples/sec: 554.32 -2019-08-20 01:15:31,861 epoch 70 - iter 2120/2650 - loss 0.15536868 - samples/sec: 542.39 -2019-08-20 01:15:47,584 epoch 70 - iter 2385/2650 - loss 0.15597666 - samples/sec: 543.60 -2019-08-20 01:16:03,152 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:16:03,152 EPOCH 70 done: loss 0.1556 - lr 0.1000 -2019-08-20 01:16:03,152 BAD EPOCHS (no improvement): 0 -2019-08-20 01:16:03,153 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:16:03,214 epoch 71 - iter 0/2650 - loss 0.14027870 - samples/sec: 153298.47 -2019-08-20 01:16:18,702 epoch 71 - iter 265/2650 - loss 0.14580149 - samples/sec: 551.58 -2019-08-20 01:16:34,436 epoch 71 - iter 530/2650 - loss 0.15013033 - samples/sec: 542.95 -2019-08-20 01:16:50,163 epoch 71 - iter 795/2650 - loss 0.15264292 - samples/sec: 543.43 -2019-08-20 01:17:05,868 epoch 71 - iter 1060/2650 - loss 0.15216024 - samples/sec: 544.28 -2019-08-20 01:17:21,354 epoch 71 - iter 1325/2650 - loss 0.15329271 - samples/sec: 551.88 -2019-08-20 01:17:36,992 epoch 71 - iter 1590/2650 - loss 0.15268048 - samples/sec: 546.43 -2019-08-20 01:17:52,635 epoch 71 - iter 1855/2650 - loss 0.15243980 - samples/sec: 546.22 -2019-08-20 01:18:08,565 epoch 71 - iter 2120/2650 - loss 0.15237977 - samples/sec: 536.46 -2019-08-20 01:18:24,174 epoch 71 - iter 2385/2650 - loss 0.15272157 - samples/sec: 547.64 -2019-08-20 01:18:39,650 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:18:39,651 EPOCH 71 done: loss 0.1532 - lr 0.1000 -2019-08-20 01:18:39,651 BAD EPOCHS (no improvement): 0 -2019-08-20 01:18:39,652 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:18:39,711 epoch 72 - iter 0/2650 - loss 0.11012738 - samples/sec: 159265.72 -2019-08-20 01:18:55,134 epoch 72 - iter 265/2650 - loss 0.15124292 - samples/sec: 554.12 -2019-08-20 01:19:10,685 epoch 72 - iter 530/2650 - loss 0.15340171 - samples/sec: 549.48 -2019-08-20 01:19:26,385 epoch 72 - iter 795/2650 - loss 0.15431311 - samples/sec: 544.31 -2019-08-20 01:19:41,827 epoch 72 - iter 1060/2650 - loss 0.15428408 - samples/sec: 553.56 -2019-08-20 01:19:57,399 epoch 72 - iter 1325/2650 - loss 0.15349106 - samples/sec: 548.87 -2019-08-20 01:20:13,155 epoch 72 - iter 1590/2650 - loss 0.15409248 - samples/sec: 542.32 -2019-08-20 01:20:28,998 epoch 72 - iter 1855/2650 - loss 0.15427287 - samples/sec: 539.34 -2019-08-20 01:20:44,732 epoch 72 - iter 2120/2650 - loss 0.15363515 - samples/sec: 543.05 -2019-08-20 01:21:00,127 epoch 72 - iter 2385/2650 - loss 0.15339191 - samples/sec: 555.37 -2019-08-20 01:21:15,702 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:21:15,702 EPOCH 72 done: loss 0.1533 - lr 0.1000 -2019-08-20 01:21:15,702 BAD EPOCHS (no improvement): 1 -2019-08-20 01:21:15,703 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:21:15,761 epoch 73 - iter 0/2650 - loss 0.15018545 - samples/sec: 163789.45 -2019-08-20 01:21:31,378 epoch 73 - iter 265/2650 - loss 0.14972714 - samples/sec: 547.21 -2019-08-20 01:21:45,935 epoch 73 - iter 530/2650 - loss 0.15170976 - samples/sec: 586.71 -2019-08-20 01:22:00,420 epoch 73 - iter 795/2650 - loss 0.15293631 - samples/sec: 589.74 -2019-08-20 01:22:14,771 epoch 73 - iter 1060/2650 - loss 0.15510769 - samples/sec: 595.36 -2019-08-20 01:22:29,482 epoch 73 - iter 1325/2650 - loss 0.15461914 - samples/sec: 580.82 -2019-08-20 01:22:45,183 epoch 73 - iter 1590/2650 - loss 0.15383019 - samples/sec: 544.26 -2019-08-20 01:23:01,001 epoch 73 - iter 1855/2650 - loss 0.15408187 - samples/sec: 540.15 -2019-08-20 01:23:16,675 epoch 73 - iter 2120/2650 - loss 0.15372509 - samples/sec: 545.17 -2019-08-20 01:23:32,218 epoch 73 - iter 2385/2650 - loss 0.15291161 - samples/sec: 549.98 -2019-08-20 01:23:47,768 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:23:47,768 EPOCH 73 done: loss 0.1537 - lr 0.1000 -2019-08-20 01:23:47,769 BAD EPOCHS (no improvement): 2 -2019-08-20 01:23:47,769 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:23:47,824 epoch 74 - iter 0/2650 - loss 0.17457779 - samples/sec: 169753.96 -2019-08-20 01:24:03,382 epoch 74 - iter 265/2650 - loss 0.15417234 - samples/sec: 549.23 -2019-08-20 01:24:19,005 epoch 74 - iter 530/2650 - loss 0.15496662 - samples/sec: 546.89 -2019-08-20 01:24:34,470 epoch 74 - iter 795/2650 - loss 0.15450976 - samples/sec: 552.55 -2019-08-20 01:24:50,220 epoch 74 - iter 1060/2650 - loss 0.15324036 - samples/sec: 542.71 -2019-08-20 01:25:05,953 epoch 74 - iter 1325/2650 - loss 0.15262507 - samples/sec: 543.14 -2019-08-20 01:25:21,807 epoch 74 - iter 1590/2650 - loss 0.15236635 - samples/sec: 539.00 -2019-08-20 01:25:37,256 epoch 74 - iter 1855/2650 - loss 0.15240067 - samples/sec: 553.36 -2019-08-20 01:25:53,125 epoch 74 - iter 2120/2650 - loss 0.15200655 - samples/sec: 538.50 -2019-08-20 01:26:08,773 epoch 74 - iter 2385/2650 - loss 0.15255549 - samples/sec: 547.36 -2019-08-20 01:26:24,110 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:26:24,111 EPOCH 74 done: loss 0.1525 - lr 0.1000 -2019-08-20 01:26:24,111 BAD EPOCHS (no improvement): 0 -2019-08-20 01:26:24,112 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:26:24,165 epoch 75 - iter 0/2650 - loss 0.13264412 - samples/sec: 175320.02 -2019-08-20 01:26:39,419 epoch 75 - iter 265/2650 - loss 0.14755341 - samples/sec: 560.01 -2019-08-20 01:26:54,834 epoch 75 - iter 530/2650 - loss 0.14821508 - samples/sec: 554.37 -2019-08-20 01:27:10,464 epoch 75 - iter 795/2650 - loss 0.14828205 - samples/sec: 547.03 -2019-08-20 01:27:25,865 epoch 75 - iter 1060/2650 - loss 0.14947462 - samples/sec: 555.10 -2019-08-20 01:27:41,475 epoch 75 - iter 1325/2650 - loss 0.14968667 - samples/sec: 547.58 -2019-08-20 01:27:57,216 epoch 75 - iter 1590/2650 - loss 0.15017290 - samples/sec: 542.83 -2019-08-20 01:28:12,716 epoch 75 - iter 1855/2650 - loss 0.15054800 - samples/sec: 551.27 -2019-08-20 01:28:28,508 epoch 75 - iter 2120/2650 - loss 0.15128522 - samples/sec: 541.04 -2019-08-20 01:28:44,469 epoch 75 - iter 2385/2650 - loss 0.15122724 - samples/sec: 535.40 -2019-08-20 01:29:00,134 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:29:00,135 EPOCH 75 done: loss 0.1518 - lr 0.1000 -2019-08-20 01:29:00,135 BAD EPOCHS (no improvement): 0 -2019-08-20 01:29:00,136 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:29:00,201 epoch 76 - iter 0/2650 - loss 0.15041780 - samples/sec: 144043.68 -2019-08-20 01:29:15,781 epoch 76 - iter 265/2650 - loss 0.14764286 - samples/sec: 548.45 -2019-08-20 01:29:31,402 epoch 76 - iter 530/2650 - loss 0.14740801 - samples/sec: 546.94 -2019-08-20 01:29:46,851 epoch 76 - iter 795/2650 - loss 0.14856867 - samples/sec: 553.21 -2019-08-20 01:30:02,289 epoch 76 - iter 1060/2650 - loss 0.15028278 - samples/sec: 553.75 -2019-08-20 01:30:17,850 epoch 76 - iter 1325/2650 - loss 0.15105525 - samples/sec: 549.24 -2019-08-20 01:30:33,486 epoch 76 - iter 1590/2650 - loss 0.15089405 - samples/sec: 546.40 -2019-08-20 01:30:48,900 epoch 76 - iter 1855/2650 - loss 0.15039985 - samples/sec: 554.29 -2019-08-20 01:31:04,482 epoch 76 - iter 2120/2650 - loss 0.15019907 - samples/sec: 548.23 -2019-08-20 01:31:20,031 epoch 76 - iter 2385/2650 - loss 0.15080556 - samples/sec: 549.70 -2019-08-20 01:31:35,853 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:31:35,853 EPOCH 76 done: loss 0.1508 - lr 0.1000 -2019-08-20 01:31:35,854 BAD EPOCHS (no improvement): 0 -2019-08-20 01:31:35,855 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:31:35,917 epoch 77 - iter 0/2650 - loss 0.18086848 - samples/sec: 149758.73 -2019-08-20 01:31:51,497 epoch 77 - iter 265/2650 - loss 0.15495933 - samples/sec: 548.52 -2019-08-20 01:32:07,118 epoch 77 - iter 530/2650 - loss 0.15174496 - samples/sec: 546.96 -2019-08-20 01:32:22,676 epoch 77 - iter 795/2650 - loss 0.15089368 - samples/sec: 549.57 -2019-08-20 01:32:38,424 epoch 77 - iter 1060/2650 - loss 0.15032296 - samples/sec: 542.71 -2019-08-20 01:32:54,045 epoch 77 - iter 1325/2650 - loss 0.14990123 - samples/sec: 547.06 -2019-08-20 01:33:09,376 epoch 77 - iter 1590/2650 - loss 0.15024136 - samples/sec: 557.43 -2019-08-20 01:33:25,158 epoch 77 - iter 1855/2650 - loss 0.14964479 - samples/sec: 541.42 -2019-08-20 01:33:40,858 epoch 77 - iter 2120/2650 - loss 0.14879959 - samples/sec: 544.13 -2019-08-20 01:33:56,355 epoch 77 - iter 2385/2650 - loss 0.14834548 - samples/sec: 551.72 -2019-08-20 01:34:11,828 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:34:11,829 EPOCH 77 done: loss 0.1485 - lr 0.1000 -2019-08-20 01:34:11,829 BAD EPOCHS (no improvement): 0 -2019-08-20 01:34:11,830 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:34:11,899 epoch 78 - iter 0/2650 - loss 0.12832874 - samples/sec: 131050.27 -2019-08-20 01:34:27,727 epoch 78 - iter 265/2650 - loss 0.15185968 - samples/sec: 539.80 -2019-08-20 01:34:43,421 epoch 78 - iter 530/2650 - loss 0.14993355 - samples/sec: 544.46 -2019-08-20 01:34:59,112 epoch 78 - iter 795/2650 - loss 0.14914473 - samples/sec: 544.65 -2019-08-20 01:35:14,743 epoch 78 - iter 1060/2650 - loss 0.14879546 - samples/sec: 546.88 -2019-08-20 01:35:30,555 epoch 78 - iter 1325/2650 - loss 0.14753495 - samples/sec: 542.50 -2019-08-20 01:35:45,930 epoch 78 - iter 1590/2650 - loss 0.14704302 - samples/sec: 555.85 -2019-08-20 01:36:01,665 epoch 78 - iter 1855/2650 - loss 0.14839689 - samples/sec: 543.23 -2019-08-20 01:36:17,228 epoch 78 - iter 2120/2650 - loss 0.14930053 - samples/sec: 549.30 -2019-08-20 01:36:33,135 epoch 78 - iter 2385/2650 - loss 0.15014487 - samples/sec: 537.31 -2019-08-20 01:36:48,603 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:36:48,604 EPOCH 78 done: loss 0.1499 - lr 0.1000 -2019-08-20 01:36:48,604 BAD EPOCHS (no improvement): 1 -2019-08-20 01:36:48,605 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:36:48,661 epoch 79 - iter 0/2650 - loss 0.11755203 - samples/sec: 164315.34 -2019-08-20 01:37:04,098 epoch 79 - iter 265/2650 - loss 0.14628362 - samples/sec: 553.62 -2019-08-20 01:37:19,735 epoch 79 - iter 530/2650 - loss 0.14525924 - samples/sec: 546.59 -2019-08-20 01:37:35,576 epoch 79 - iter 795/2650 - loss 0.14562949 - samples/sec: 539.30 -2019-08-20 01:37:50,983 epoch 79 - iter 1060/2650 - loss 0.14642007 - samples/sec: 555.01 -2019-08-20 01:38:06,741 epoch 79 - iter 1325/2650 - loss 0.14631415 - samples/sec: 542.31 -2019-08-20 01:38:22,320 epoch 79 - iter 1590/2650 - loss 0.14632840 - samples/sec: 548.56 -2019-08-20 01:38:37,914 epoch 79 - iter 1855/2650 - loss 0.14693330 - samples/sec: 548.03 -2019-08-20 01:38:53,687 epoch 79 - iter 2120/2650 - loss 0.14758881 - samples/sec: 541.59 -2019-08-20 01:39:09,514 epoch 79 - iter 2385/2650 - loss 0.14794170 - samples/sec: 540.05 -2019-08-20 01:39:25,056 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:39:25,056 EPOCH 79 done: loss 0.1474 - lr 0.1000 -2019-08-20 01:39:25,056 BAD EPOCHS (no improvement): 0 -2019-08-20 01:39:25,057 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:39:25,106 epoch 80 - iter 0/2650 - loss 0.14438860 - samples/sec: 191661.09 -2019-08-20 01:39:40,544 epoch 80 - iter 265/2650 - loss 0.14999757 - samples/sec: 553.54 -2019-08-20 01:39:56,036 epoch 80 - iter 530/2650 - loss 0.15018324 - samples/sec: 551.59 -2019-08-20 01:40:11,612 epoch 80 - iter 795/2650 - loss 0.14960164 - samples/sec: 548.54 -2019-08-20 01:40:27,318 epoch 80 - iter 1060/2650 - loss 0.14917964 - samples/sec: 544.10 -2019-08-20 01:40:42,756 epoch 80 - iter 1325/2650 - loss 0.14930554 - samples/sec: 553.71 -2019-08-20 01:40:58,338 epoch 80 - iter 1590/2650 - loss 0.14885902 - samples/sec: 548.38 -2019-08-20 01:41:13,898 epoch 80 - iter 1855/2650 - loss 0.14877045 - samples/sec: 549.12 -2019-08-20 01:41:29,561 epoch 80 - iter 2120/2650 - loss 0.14856622 - samples/sec: 545.49 -2019-08-20 01:41:45,372 epoch 80 - iter 2385/2650 - loss 0.14849238 - samples/sec: 540.60 -2019-08-20 01:42:01,034 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:42:01,034 EPOCH 80 done: loss 0.1483 - lr 0.1000 -2019-08-20 01:42:01,035 BAD EPOCHS (no improvement): 1 -2019-08-20 01:42:01,035 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:42:01,086 epoch 81 - iter 0/2650 - loss 0.07728260 - samples/sec: 189093.32 -2019-08-20 01:42:16,529 epoch 81 - iter 265/2650 - loss 0.14921977 - samples/sec: 553.41 -2019-08-20 01:42:32,208 epoch 81 - iter 530/2650 - loss 0.14676964 - samples/sec: 544.98 -2019-08-20 01:42:47,866 epoch 81 - iter 795/2650 - loss 0.14728005 - samples/sec: 545.72 -2019-08-20 01:43:03,360 epoch 81 - iter 1060/2650 - loss 0.14647041 - samples/sec: 551.73 -2019-08-20 01:43:18,820 epoch 81 - iter 1325/2650 - loss 0.14631000 - samples/sec: 552.88 -2019-08-20 01:43:34,419 epoch 81 - iter 1590/2650 - loss 0.14695549 - samples/sec: 547.94 -2019-08-20 01:43:50,312 epoch 81 - iter 1855/2650 - loss 0.14672229 - samples/sec: 537.67 -2019-08-20 01:44:05,808 epoch 81 - iter 2120/2650 - loss 0.14695081 - samples/sec: 551.48 -2019-08-20 01:44:21,657 epoch 81 - iter 2385/2650 - loss 0.14655963 - samples/sec: 539.29 -2019-08-20 01:44:37,359 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:44:37,359 EPOCH 81 done: loss 0.1462 - lr 0.1000 -2019-08-20 01:44:37,359 BAD EPOCHS (no improvement): 0 -2019-08-20 01:44:37,360 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:44:37,435 epoch 82 - iter 0/2650 - loss 0.17745636 - samples/sec: 122026.16 -2019-08-20 01:44:52,956 epoch 82 - iter 265/2650 - loss 0.15070948 - samples/sec: 550.54 -2019-08-20 01:45:08,450 epoch 82 - iter 530/2650 - loss 0.14599486 - samples/sec: 551.68 -2019-08-20 01:45:23,963 epoch 82 - iter 795/2650 - loss 0.14670635 - samples/sec: 550.79 -2019-08-20 01:45:39,459 epoch 82 - iter 1060/2650 - loss 0.14518797 - samples/sec: 551.57 -2019-08-20 01:45:55,041 epoch 82 - iter 1325/2650 - loss 0.14689451 - samples/sec: 548.66 -2019-08-20 01:46:10,585 epoch 82 - iter 1590/2650 - loss 0.14771087 - samples/sec: 549.80 -2019-08-20 01:46:26,184 epoch 82 - iter 1855/2650 - loss 0.14720490 - samples/sec: 547.75 -2019-08-20 01:46:42,182 epoch 82 - iter 2120/2650 - loss 0.14675928 - samples/sec: 534.04 -2019-08-20 01:46:57,807 epoch 82 - iter 2385/2650 - loss 0.14660368 - samples/sec: 547.00 -2019-08-20 01:47:13,436 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:47:13,437 EPOCH 82 done: loss 0.1467 - lr 0.1000 -2019-08-20 01:47:13,437 BAD EPOCHS (no improvement): 1 -2019-08-20 01:47:13,438 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:47:13,504 epoch 83 - iter 0/2650 - loss 0.07807794 - samples/sec: 140751.80 -2019-08-20 01:47:29,010 epoch 83 - iter 265/2650 - loss 0.14076378 - samples/sec: 551.16 -2019-08-20 01:47:44,728 epoch 83 - iter 530/2650 - loss 0.14423420 - samples/sec: 543.67 -2019-08-20 01:48:00,350 epoch 83 - iter 795/2650 - loss 0.14416530 - samples/sec: 546.92 -2019-08-20 01:48:16,220 epoch 83 - iter 1060/2650 - loss 0.14472766 - samples/sec: 538.55 -2019-08-20 01:48:31,638 epoch 83 - iter 1325/2650 - loss 0.14500710 - samples/sec: 554.62 -2019-08-20 01:48:47,208 epoch 83 - iter 1590/2650 - loss 0.14526226 - samples/sec: 549.00 -2019-08-20 01:49:02,864 epoch 83 - iter 1855/2650 - loss 0.14543611 - samples/sec: 545.97 -2019-08-20 01:49:18,537 epoch 83 - iter 2120/2650 - loss 0.14548152 - samples/sec: 545.12 -2019-08-20 01:49:34,222 epoch 83 - iter 2385/2650 - loss 0.14585739 - samples/sec: 544.85 -2019-08-20 01:49:49,709 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:49:49,709 EPOCH 83 done: loss 0.1463 - lr 0.1000 -2019-08-20 01:49:49,709 BAD EPOCHS (no improvement): 2 -2019-08-20 01:49:49,710 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:49:49,778 epoch 84 - iter 0/2650 - loss 0.10489204 - samples/sec: 137198.30 -2019-08-20 01:50:05,314 epoch 84 - iter 265/2650 - loss 0.14124670 - samples/sec: 550.10 -2019-08-20 01:50:20,822 epoch 84 - iter 530/2650 - loss 0.14094164 - samples/sec: 551.03 -2019-08-20 01:50:36,471 epoch 84 - iter 795/2650 - loss 0.14250968 - samples/sec: 545.98 -2019-08-20 01:50:52,283 epoch 84 - iter 1060/2650 - loss 0.14391847 - samples/sec: 540.40 -2019-08-20 01:51:07,910 epoch 84 - iter 1325/2650 - loss 0.14471870 - samples/sec: 547.08 -2019-08-20 01:51:23,436 epoch 84 - iter 1590/2650 - loss 0.14535990 - samples/sec: 550.71 -2019-08-20 01:51:39,249 epoch 84 - iter 1855/2650 - loss 0.14525451 - samples/sec: 540.29 -2019-08-20 01:51:54,877 epoch 84 - iter 2120/2650 - loss 0.14532785 - samples/sec: 546.84 -2019-08-20 01:52:10,634 epoch 84 - iter 2385/2650 - loss 0.14527481 - samples/sec: 542.35 -2019-08-20 01:52:26,177 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:52:26,177 EPOCH 84 done: loss 0.1449 - lr 0.1000 -2019-08-20 01:52:26,177 BAD EPOCHS (no improvement): 0 -2019-08-20 01:52:26,178 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:52:26,251 epoch 85 - iter 0/2650 - loss 0.19854258 - samples/sec: 125075.86 -2019-08-20 01:52:41,888 epoch 85 - iter 265/2650 - loss 0.14809410 - samples/sec: 546.49 -2019-08-20 01:52:57,473 epoch 85 - iter 530/2650 - loss 0.14773119 - samples/sec: 548.30 -2019-08-20 01:53:13,068 epoch 85 - iter 795/2650 - loss 0.14799715 - samples/sec: 548.01 -2019-08-20 01:53:28,884 epoch 85 - iter 1060/2650 - loss 0.14690642 - samples/sec: 540.27 -2019-08-20 01:53:44,478 epoch 85 - iter 1325/2650 - loss 0.14613394 - samples/sec: 548.27 -2019-08-20 01:54:00,102 epoch 85 - iter 1590/2650 - loss 0.14556337 - samples/sec: 547.13 -2019-08-20 01:54:15,552 epoch 85 - iter 1855/2650 - loss 0.14617080 - samples/sec: 553.28 -2019-08-20 01:54:31,201 epoch 85 - iter 2120/2650 - loss 0.14592336 - samples/sec: 546.03 -2019-08-20 01:54:46,805 epoch 85 - iter 2385/2650 - loss 0.14611967 - samples/sec: 547.50 -2019-08-20 01:55:02,401 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:55:02,402 EPOCH 85 done: loss 0.1463 - lr 0.1000 -2019-08-20 01:55:02,402 BAD EPOCHS (no improvement): 1 -2019-08-20 01:55:02,403 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:55:02,457 epoch 86 - iter 0/2650 - loss 0.12176257 - samples/sec: 175434.16 -2019-08-20 01:55:18,043 epoch 86 - iter 265/2650 - loss 0.14384648 - samples/sec: 548.39 -2019-08-20 01:55:33,723 epoch 86 - iter 530/2650 - loss 0.14203855 - samples/sec: 544.90 -2019-08-20 01:55:49,224 epoch 86 - iter 795/2650 - loss 0.14240345 - samples/sec: 551.41 -2019-08-20 01:56:04,941 epoch 86 - iter 1060/2650 - loss 0.14292069 - samples/sec: 543.59 -2019-08-20 01:56:20,606 epoch 86 - iter 1325/2650 - loss 0.14404967 - samples/sec: 545.68 -2019-08-20 01:56:36,341 epoch 86 - iter 1590/2650 - loss 0.14396342 - samples/sec: 543.15 -2019-08-20 01:56:51,874 epoch 86 - iter 1855/2650 - loss 0.14437895 - samples/sec: 550.23 -2019-08-20 01:57:07,428 epoch 86 - iter 2120/2650 - loss 0.14457307 - samples/sec: 549.44 -2019-08-20 01:57:23,109 epoch 86 - iter 2385/2650 - loss 0.14457559 - samples/sec: 544.86 -2019-08-20 01:57:38,852 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:57:38,853 EPOCH 86 done: loss 0.1449 - lr 0.1000 -2019-08-20 01:57:38,853 BAD EPOCHS (no improvement): 0 -2019-08-20 01:57:38,854 ---------------------------------------------------------------------------------------------------- -2019-08-20 01:57:38,907 epoch 87 - iter 0/2650 - loss 0.13294466 - samples/sec: 174561.96 -2019-08-20 01:57:54,324 epoch 87 - iter 265/2650 - loss 0.14343736 - samples/sec: 554.43 -2019-08-20 01:58:09,721 epoch 87 - iter 530/2650 - loss 0.14530685 - samples/sec: 555.05 -2019-08-20 01:58:25,353 epoch 87 - iter 795/2650 - loss 0.14334516 - samples/sec: 546.69 -2019-08-20 01:58:41,244 epoch 87 - iter 1060/2650 - loss 0.14224637 - samples/sec: 537.32 -2019-08-20 01:58:56,861 epoch 87 - iter 1325/2650 - loss 0.14425284 - samples/sec: 547.39 -2019-08-20 01:59:12,441 epoch 87 - iter 1590/2650 - loss 0.14378158 - samples/sec: 548.64 -2019-08-20 01:59:28,013 epoch 87 - iter 1855/2650 - loss 0.14291525 - samples/sec: 548.89 -2019-08-20 01:59:42,802 epoch 87 - iter 2120/2650 - loss 0.14314052 - samples/sec: 577.69 -2019-08-20 01:59:57,580 epoch 87 - iter 2385/2650 - loss 0.14284438 - samples/sec: 577.86 -2019-08-20 02:00:11,897 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:00:11,897 EPOCH 87 done: loss 0.1428 - lr 0.1000 -2019-08-20 02:00:11,897 BAD EPOCHS (no improvement): 0 -2019-08-20 02:00:11,898 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:00:11,978 epoch 88 - iter 0/2650 - loss 0.07325857 - samples/sec: 109321.34 -2019-08-20 02:00:26,759 epoch 88 - iter 265/2650 - loss 0.14477092 - samples/sec: 578.14 -2019-08-20 02:00:42,068 epoch 88 - iter 530/2650 - loss 0.14515659 - samples/sec: 558.15 -2019-08-20 02:00:57,561 epoch 88 - iter 795/2650 - loss 0.14421206 - samples/sec: 551.70 -2019-08-20 02:01:13,008 epoch 88 - iter 1060/2650 - loss 0.14359218 - samples/sec: 553.07 -2019-08-20 02:01:28,698 epoch 88 - iter 1325/2650 - loss 0.14248406 - samples/sec: 544.74 -2019-08-20 02:01:44,283 epoch 88 - iter 1590/2650 - loss 0.14276864 - samples/sec: 548.53 -2019-08-20 02:01:59,841 epoch 88 - iter 1855/2650 - loss 0.14338301 - samples/sec: 549.42 -2019-08-20 02:02:15,676 epoch 88 - iter 2120/2650 - loss 0.14308578 - samples/sec: 539.53 -2019-08-20 02:02:31,284 epoch 88 - iter 2385/2650 - loss 0.14304342 - samples/sec: 547.44 -2019-08-20 02:02:46,762 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:02:46,763 EPOCH 88 done: loss 0.1433 - lr 0.1000 -2019-08-20 02:02:46,763 BAD EPOCHS (no improvement): 1 -2019-08-20 02:02:46,764 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:02:46,820 epoch 89 - iter 0/2650 - loss 0.15750135 - samples/sec: 167177.58 -2019-08-20 02:03:02,451 epoch 89 - iter 265/2650 - loss 0.14078916 - samples/sec: 546.73 -2019-08-20 02:03:17,938 epoch 89 - iter 530/2650 - loss 0.14422071 - samples/sec: 551.86 -2019-08-20 02:03:33,618 epoch 89 - iter 795/2650 - loss 0.14290008 - samples/sec: 544.99 -2019-08-20 02:03:49,227 epoch 89 - iter 1060/2650 - loss 0.14242177 - samples/sec: 547.26 -2019-08-20 02:04:05,060 epoch 89 - iter 1325/2650 - loss 0.14099142 - samples/sec: 539.89 -2019-08-20 02:04:20,532 epoch 89 - iter 1590/2650 - loss 0.14152445 - samples/sec: 552.50 -2019-08-20 02:04:36,087 epoch 89 - iter 1855/2650 - loss 0.14125877 - samples/sec: 549.39 -2019-08-20 02:04:51,802 epoch 89 - iter 2120/2650 - loss 0.14162308 - samples/sec: 543.82 -2019-08-20 02:05:07,488 epoch 89 - iter 2385/2650 - loss 0.14214033 - samples/sec: 544.75 -2019-08-20 02:05:23,105 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:05:23,105 EPOCH 89 done: loss 0.1418 - lr 0.1000 -2019-08-20 02:05:23,106 BAD EPOCHS (no improvement): 0 -2019-08-20 02:05:23,106 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:05:23,162 epoch 90 - iter 0/2650 - loss 0.28454143 - samples/sec: 169612.29 -2019-08-20 02:05:38,327 epoch 90 - iter 265/2650 - loss 0.14063395 - samples/sec: 563.71 -2019-08-20 02:05:53,911 epoch 90 - iter 530/2650 - loss 0.14088862 - samples/sec: 548.38 -2019-08-20 02:06:09,694 epoch 90 - iter 795/2650 - loss 0.14215493 - samples/sec: 541.32 -2019-08-20 02:06:25,342 epoch 90 - iter 1060/2650 - loss 0.14128219 - samples/sec: 546.18 -2019-08-20 02:06:41,125 epoch 90 - iter 1325/2650 - loss 0.14109845 - samples/sec: 541.54 -2019-08-20 02:06:56,589 epoch 90 - iter 1590/2650 - loss 0.14127191 - samples/sec: 552.71 -2019-08-20 02:07:12,093 epoch 90 - iter 1855/2650 - loss 0.14153282 - samples/sec: 551.24 -2019-08-20 02:07:27,661 epoch 90 - iter 2120/2650 - loss 0.14053424 - samples/sec: 548.89 -2019-08-20 02:07:42,520 epoch 90 - iter 2385/2650 - loss 0.14064759 - samples/sec: 575.01 -2019-08-20 02:07:56,900 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:07:56,900 EPOCH 90 done: loss 0.1405 - lr 0.1000 -2019-08-20 02:07:56,900 BAD EPOCHS (no improvement): 0 -2019-08-20 02:07:56,901 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:07:56,958 epoch 91 - iter 0/2650 - loss 0.12264702 - samples/sec: 157261.60 -2019-08-20 02:08:11,954 epoch 91 - iter 265/2650 - loss 0.14840940 - samples/sec: 569.87 -2019-08-20 02:08:27,491 epoch 91 - iter 530/2650 - loss 0.14279459 - samples/sec: 550.09 -2019-08-20 02:08:43,149 epoch 91 - iter 795/2650 - loss 0.14094967 - samples/sec: 545.72 -2019-08-20 02:08:58,737 epoch 91 - iter 1060/2650 - loss 0.14033158 - samples/sec: 548.14 -2019-08-20 02:09:14,155 epoch 91 - iter 1325/2650 - loss 0.14049028 - samples/sec: 554.50 -2019-08-20 02:09:29,704 epoch 91 - iter 1590/2650 - loss 0.14041727 - samples/sec: 549.65 -2019-08-20 02:09:45,266 epoch 91 - iter 1855/2650 - loss 0.14047932 - samples/sec: 549.18 -2019-08-20 02:10:01,181 epoch 91 - iter 2120/2650 - loss 0.14101448 - samples/sec: 536.79 -2019-08-20 02:10:16,932 epoch 91 - iter 2385/2650 - loss 0.14113563 - samples/sec: 542.53 -2019-08-20 02:10:32,593 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:10:32,594 EPOCH 91 done: loss 0.1409 - lr 0.1000 -2019-08-20 02:10:32,594 BAD EPOCHS (no improvement): 1 -2019-08-20 02:10:32,595 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:10:32,652 epoch 92 - iter 0/2650 - loss 0.13696256 - samples/sec: 165996.31 -2019-08-20 02:10:48,294 epoch 92 - iter 265/2650 - loss 0.13859172 - samples/sec: 546.31 -2019-08-20 02:11:04,078 epoch 92 - iter 530/2650 - loss 0.14027631 - samples/sec: 541.33 -2019-08-20 02:11:19,538 epoch 92 - iter 795/2650 - loss 0.13936589 - samples/sec: 553.19 -2019-08-20 02:11:35,230 epoch 92 - iter 1060/2650 - loss 0.14137269 - samples/sec: 544.25 -2019-08-20 02:11:50,727 epoch 92 - iter 1325/2650 - loss 0.14003265 - samples/sec: 551.65 -2019-08-20 02:12:06,225 epoch 92 - iter 1590/2650 - loss 0.13952688 - samples/sec: 551.87 -2019-08-20 02:12:21,752 epoch 92 - iter 1855/2650 - loss 0.13928382 - samples/sec: 550.46 -2019-08-20 02:12:37,379 epoch 92 - iter 2120/2650 - loss 0.13928154 - samples/sec: 546.79 -2019-08-20 02:12:53,114 epoch 92 - iter 2385/2650 - loss 0.13906167 - samples/sec: 542.98 -2019-08-20 02:13:08,689 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:13:08,689 EPOCH 92 done: loss 0.1392 - lr 0.1000 -2019-08-20 02:13:08,689 BAD EPOCHS (no improvement): 0 -2019-08-20 02:13:08,690 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:13:08,754 epoch 93 - iter 0/2650 - loss 0.10136921 - samples/sec: 144711.79 -2019-08-20 02:13:24,346 epoch 93 - iter 265/2650 - loss 0.14179029 - samples/sec: 547.99 -2019-08-20 02:13:39,755 epoch 93 - iter 530/2650 - loss 0.13877319 - samples/sec: 554.80 -2019-08-20 02:13:55,258 epoch 93 - iter 795/2650 - loss 0.13950052 - samples/sec: 551.22 -2019-08-20 02:14:11,168 epoch 93 - iter 1060/2650 - loss 0.13988965 - samples/sec: 536.98 -2019-08-20 02:14:26,883 epoch 93 - iter 1325/2650 - loss 0.13896959 - samples/sec: 544.00 -2019-08-20 02:14:42,580 epoch 93 - iter 1590/2650 - loss 0.14010349 - samples/sec: 544.50 -2019-08-20 02:14:58,002 epoch 93 - iter 1855/2650 - loss 0.13933922 - samples/sec: 554.27 -2019-08-20 02:15:13,528 epoch 93 - iter 2120/2650 - loss 0.13920819 - samples/sec: 550.44 -2019-08-20 02:15:29,469 epoch 93 - iter 2385/2650 - loss 0.13898481 - samples/sec: 535.92 -2019-08-20 02:15:44,828 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:15:44,829 EPOCH 93 done: loss 0.1396 - lr 0.1000 -2019-08-20 02:15:44,829 BAD EPOCHS (no improvement): 1 -2019-08-20 02:15:44,830 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:15:44,896 epoch 94 - iter 0/2650 - loss 0.10312391 - samples/sec: 141941.49 -2019-08-20 02:16:00,414 epoch 94 - iter 265/2650 - loss 0.14085947 - samples/sec: 550.58 -2019-08-20 02:16:16,163 epoch 94 - iter 530/2650 - loss 0.13776318 - samples/sec: 542.64 -2019-08-20 02:16:31,712 epoch 94 - iter 795/2650 - loss 0.13874695 - samples/sec: 549.64 -2019-08-20 02:16:47,535 epoch 94 - iter 1060/2650 - loss 0.13888893 - samples/sec: 539.97 -2019-08-20 02:17:03,038 epoch 94 - iter 1325/2650 - loss 0.13840225 - samples/sec: 551.43 -2019-08-20 02:17:18,618 epoch 94 - iter 1590/2650 - loss 0.13847752 - samples/sec: 548.57 -2019-08-20 02:17:34,122 epoch 94 - iter 1855/2650 - loss 0.13856534 - samples/sec: 551.25 -2019-08-20 02:17:49,617 epoch 94 - iter 2120/2650 - loss 0.13820072 - samples/sec: 551.53 -2019-08-20 02:18:05,587 epoch 94 - iter 2385/2650 - loss 0.13790226 - samples/sec: 534.96 -2019-08-20 02:18:21,084 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:18:21,085 EPOCH 94 done: loss 0.1385 - lr 0.1000 -2019-08-20 02:18:21,085 BAD EPOCHS (no improvement): 0 -2019-08-20 02:18:21,086 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:18:21,149 epoch 95 - iter 0/2650 - loss 0.22659291 - samples/sec: 145944.51 -2019-08-20 02:18:36,599 epoch 95 - iter 265/2650 - loss 0.13771195 - samples/sec: 553.32 -2019-08-20 02:18:52,049 epoch 95 - iter 530/2650 - loss 0.13732790 - samples/sec: 553.17 -2019-08-20 02:19:07,819 epoch 95 - iter 795/2650 - loss 0.13773914 - samples/sec: 541.86 -2019-08-20 02:19:23,270 epoch 95 - iter 1060/2650 - loss 0.13845656 - samples/sec: 553.10 -2019-08-20 02:19:39,140 epoch 95 - iter 1325/2650 - loss 0.13734552 - samples/sec: 538.54 -2019-08-20 02:19:54,617 epoch 95 - iter 1590/2650 - loss 0.13843019 - samples/sec: 552.60 -2019-08-20 02:20:10,019 epoch 95 - iter 1855/2650 - loss 0.13829012 - samples/sec: 555.04 -2019-08-20 02:20:25,559 epoch 95 - iter 2120/2650 - loss 0.13841871 - samples/sec: 550.01 -2019-08-20 02:20:41,543 epoch 95 - iter 2385/2650 - loss 0.13853765 - samples/sec: 534.50 -2019-08-20 02:20:57,180 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:20:57,180 EPOCH 95 done: loss 0.1386 - lr 0.1000 -2019-08-20 02:20:57,180 BAD EPOCHS (no improvement): 1 -2019-08-20 02:20:57,181 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:20:57,243 epoch 96 - iter 0/2650 - loss 0.14462325 - samples/sec: 148935.97 -2019-08-20 02:21:13,055 epoch 96 - iter 265/2650 - loss 0.13517231 - samples/sec: 540.62 -2019-08-20 02:21:28,737 epoch 96 - iter 530/2650 - loss 0.13330661 - samples/sec: 545.09 -2019-08-20 02:21:44,372 epoch 96 - iter 795/2650 - loss 0.13503575 - samples/sec: 546.60 -2019-08-20 02:22:00,066 epoch 96 - iter 1060/2650 - loss 0.13671624 - samples/sec: 544.40 -2019-08-20 02:22:15,466 epoch 96 - iter 1325/2650 - loss 0.13653488 - samples/sec: 554.94 -2019-08-20 02:22:31,054 epoch 96 - iter 1590/2650 - loss 0.13696049 - samples/sec: 548.42 -2019-08-20 02:22:46,569 epoch 96 - iter 1855/2650 - loss 0.13725642 - samples/sec: 550.89 -2019-08-20 02:23:02,155 epoch 96 - iter 2120/2650 - loss 0.13714598 - samples/sec: 548.31 -2019-08-20 02:23:17,594 epoch 96 - iter 2385/2650 - loss 0.13707197 - samples/sec: 553.63 -2019-08-20 02:23:33,322 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:23:33,322 EPOCH 96 done: loss 0.1376 - lr 0.1000 -2019-08-20 02:23:33,323 BAD EPOCHS (no improvement): 0 -2019-08-20 02:23:33,323 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:23:33,380 epoch 97 - iter 0/2650 - loss 0.11723986 - samples/sec: 163269.92 -2019-08-20 02:23:48,885 epoch 97 - iter 265/2650 - loss 0.13226177 - samples/sec: 551.46 -2019-08-20 02:24:04,395 epoch 97 - iter 530/2650 - loss 0.13435090 - samples/sec: 551.08 -2019-08-20 02:24:20,056 epoch 97 - iter 795/2650 - loss 0.13554297 - samples/sec: 545.69 -2019-08-20 02:24:35,645 epoch 97 - iter 1060/2650 - loss 0.13540423 - samples/sec: 548.18 -2019-08-20 02:24:51,322 epoch 97 - iter 1325/2650 - loss 0.13561918 - samples/sec: 545.14 -2019-08-20 02:25:06,907 epoch 97 - iter 1590/2650 - loss 0.13533488 - samples/sec: 548.56 -2019-08-20 02:25:22,525 epoch 97 - iter 1855/2650 - loss 0.13645758 - samples/sec: 547.06 -2019-08-20 02:25:38,194 epoch 97 - iter 2120/2650 - loss 0.13649320 - samples/sec: 545.45 -2019-08-20 02:25:53,801 epoch 97 - iter 2385/2650 - loss 0.13636269 - samples/sec: 547.51 -2019-08-20 02:26:09,550 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:26:09,550 EPOCH 97 done: loss 0.1361 - lr 0.1000 -2019-08-20 02:26:09,550 BAD EPOCHS (no improvement): 0 -2019-08-20 02:26:09,551 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:26:09,622 epoch 98 - iter 0/2650 - loss 0.10859960 - samples/sec: 131820.58 -2019-08-20 02:26:25,247 epoch 98 - iter 265/2650 - loss 0.13666957 - samples/sec: 547.15 -2019-08-20 02:26:40,928 epoch 98 - iter 530/2650 - loss 0.13799908 - samples/sec: 545.02 -2019-08-20 02:26:56,622 epoch 98 - iter 795/2650 - loss 0.13797678 - samples/sec: 544.56 -2019-08-20 02:27:12,358 epoch 98 - iter 1060/2650 - loss 0.13727599 - samples/sec: 543.00 -2019-08-20 02:27:28,058 epoch 98 - iter 1325/2650 - loss 0.13671219 - samples/sec: 544.25 -2019-08-20 02:27:43,738 epoch 98 - iter 1590/2650 - loss 0.13666028 - samples/sec: 545.24 -2019-08-20 02:27:59,232 epoch 98 - iter 1855/2650 - loss 0.13620095 - samples/sec: 551.67 -2019-08-20 02:28:14,697 epoch 98 - iter 2120/2650 - loss 0.13580360 - samples/sec: 552.70 -2019-08-20 02:28:30,507 epoch 98 - iter 2385/2650 - loss 0.13652376 - samples/sec: 540.51 -2019-08-20 02:28:45,985 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:28:45,986 EPOCH 98 done: loss 0.1364 - lr 0.1000 -2019-08-20 02:28:45,986 BAD EPOCHS (no improvement): 1 -2019-08-20 02:28:45,986 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:28:46,054 epoch 99 - iter 0/2650 - loss 0.16456270 - samples/sec: 131361.48 -2019-08-20 02:29:01,696 epoch 99 - iter 265/2650 - loss 0.13544814 - samples/sec: 546.51 -2019-08-20 02:29:17,370 epoch 99 - iter 530/2650 - loss 0.13562726 - samples/sec: 545.22 -2019-08-20 02:29:33,057 epoch 99 - iter 795/2650 - loss 0.13464006 - samples/sec: 544.93 -2019-08-20 02:29:48,998 epoch 99 - iter 1060/2650 - loss 0.13415335 - samples/sec: 536.07 -2019-08-20 02:30:04,587 epoch 99 - iter 1325/2650 - loss 0.13497450 - samples/sec: 548.25 -2019-08-20 02:30:20,206 epoch 99 - iter 1590/2650 - loss 0.13524781 - samples/sec: 547.23 -2019-08-20 02:30:35,946 epoch 99 - iter 1855/2650 - loss 0.13608755 - samples/sec: 543.04 -2019-08-20 02:30:51,568 epoch 99 - iter 2120/2650 - loss 0.13576747 - samples/sec: 547.14 -2019-08-20 02:31:07,206 epoch 99 - iter 2385/2650 - loss 0.13554329 - samples/sec: 546.47 -2019-08-20 02:31:22,511 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:31:22,511 EPOCH 99 done: loss 0.1355 - lr 0.1000 -2019-08-20 02:31:22,511 BAD EPOCHS (no improvement): 0 -2019-08-20 02:31:22,512 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:31:22,569 epoch 100 - iter 0/2650 - loss 0.10800902 - samples/sec: 164332.04 -2019-08-20 02:31:37,445 epoch 100 - iter 265/2650 - loss 0.13033123 - samples/sec: 574.63 -2019-08-20 02:31:53,066 epoch 100 - iter 530/2650 - loss 0.13284283 - samples/sec: 547.60 -2019-08-20 02:32:08,610 epoch 100 - iter 795/2650 - loss 0.13493330 - samples/sec: 549.81 -2019-08-20 02:32:24,389 epoch 100 - iter 1060/2650 - loss 0.13409611 - samples/sec: 541.49 -2019-08-20 02:32:40,050 epoch 100 - iter 1325/2650 - loss 0.13470017 - samples/sec: 546.21 -2019-08-20 02:32:55,836 epoch 100 - iter 1590/2650 - loss 0.13506392 - samples/sec: 541.46 -2019-08-20 02:33:11,203 epoch 100 - iter 1855/2650 - loss 0.13567481 - samples/sec: 556.26 -2019-08-20 02:33:26,610 epoch 100 - iter 2120/2650 - loss 0.13606092 - samples/sec: 554.70 -2019-08-20 02:33:42,141 epoch 100 - iter 2385/2650 - loss 0.13589777 - samples/sec: 550.22 -2019-08-20 02:33:57,813 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:33:57,813 EPOCH 100 done: loss 0.1361 - lr 0.1000 -2019-08-20 02:33:57,813 BAD EPOCHS (no improvement): 1 -2019-08-20 02:33:57,814 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:33:57,881 epoch 101 - iter 0/2650 - loss 0.10342588 - samples/sec: 139065.61 -2019-08-20 02:34:13,524 epoch 101 - iter 265/2650 - loss 0.13687150 - samples/sec: 546.46 -2019-08-20 02:34:29,284 epoch 101 - iter 530/2650 - loss 0.13446636 - samples/sec: 542.26 -2019-08-20 02:34:45,183 epoch 101 - iter 795/2650 - loss 0.13481183 - samples/sec: 537.57 -2019-08-20 02:35:00,703 epoch 101 - iter 1060/2650 - loss 0.13505485 - samples/sec: 550.72 -2019-08-20 02:35:16,386 epoch 101 - iter 1325/2650 - loss 0.13513141 - samples/sec: 545.81 -2019-08-20 02:35:31,756 epoch 101 - iter 1590/2650 - loss 0.13437270 - samples/sec: 556.27 -2019-08-20 02:35:47,419 epoch 101 - iter 1855/2650 - loss 0.13410838 - samples/sec: 545.58 -2019-08-20 02:36:02,793 epoch 101 - iter 2120/2650 - loss 0.13377237 - samples/sec: 555.97 -2019-08-20 02:36:18,593 epoch 101 - iter 2385/2650 - loss 0.13387739 - samples/sec: 540.86 -2019-08-20 02:36:34,122 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:36:34,122 EPOCH 101 done: loss 0.1339 - lr 0.1000 -2019-08-20 02:36:34,122 BAD EPOCHS (no improvement): 0 -2019-08-20 02:36:34,124 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:36:34,179 epoch 102 - iter 0/2650 - loss 0.17579088 - samples/sec: 168413.24 -2019-08-20 02:36:49,887 epoch 102 - iter 265/2650 - loss 0.13276816 - samples/sec: 544.48 -2019-08-20 02:37:05,247 epoch 102 - iter 530/2650 - loss 0.13407356 - samples/sec: 556.57 -2019-08-20 02:37:20,870 epoch 102 - iter 795/2650 - loss 0.13465557 - samples/sec: 547.06 -2019-08-20 02:37:36,336 epoch 102 - iter 1060/2650 - loss 0.13508513 - samples/sec: 552.55 -2019-08-20 02:37:51,947 epoch 102 - iter 1325/2650 - loss 0.13586783 - samples/sec: 547.31 -2019-08-20 02:38:07,759 epoch 102 - iter 1590/2650 - loss 0.13550015 - samples/sec: 540.64 -2019-08-20 02:38:23,391 epoch 102 - iter 1855/2650 - loss 0.13524711 - samples/sec: 546.91 -2019-08-20 02:38:39,279 epoch 102 - iter 2120/2650 - loss 0.13517925 - samples/sec: 537.84 -2019-08-20 02:38:54,811 epoch 102 - iter 2385/2650 - loss 0.13493883 - samples/sec: 550.18 -2019-08-20 02:39:10,420 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:39:10,420 EPOCH 102 done: loss 0.1348 - lr 0.1000 -2019-08-20 02:39:10,420 BAD EPOCHS (no improvement): 1 -2019-08-20 02:39:10,422 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:39:10,479 epoch 103 - iter 0/2650 - loss 0.14091110 - samples/sec: 160853.92 -2019-08-20 02:39:26,221 epoch 103 - iter 265/2650 - loss 0.13228974 - samples/sec: 543.39 -2019-08-20 02:39:41,749 epoch 103 - iter 530/2650 - loss 0.13301700 - samples/sec: 550.50 -2019-08-20 02:39:57,158 epoch 103 - iter 795/2650 - loss 0.13278205 - samples/sec: 554.63 -2019-08-20 02:40:12,641 epoch 103 - iter 1060/2650 - loss 0.13240837 - samples/sec: 552.00 -2019-08-20 02:40:28,360 epoch 103 - iter 1325/2650 - loss 0.13230701 - samples/sec: 543.46 -2019-08-20 02:40:43,975 epoch 103 - iter 1590/2650 - loss 0.13210099 - samples/sec: 547.45 -2019-08-20 02:40:59,527 epoch 103 - iter 1855/2650 - loss 0.13219142 - samples/sec: 549.72 -2019-08-20 02:41:15,120 epoch 103 - iter 2120/2650 - loss 0.13206703 - samples/sec: 548.04 -2019-08-20 02:41:31,139 epoch 103 - iter 2385/2650 - loss 0.13210665 - samples/sec: 533.31 -2019-08-20 02:41:46,696 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:41:46,697 EPOCH 103 done: loss 0.1322 - lr 0.1000 -2019-08-20 02:41:46,697 BAD EPOCHS (no improvement): 0 -2019-08-20 02:41:46,698 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:41:46,753 epoch 104 - iter 0/2650 - loss 0.11070710 - samples/sec: 164940.17 -2019-08-20 02:42:02,116 epoch 104 - iter 265/2650 - loss 0.13160012 - samples/sec: 556.30 -2019-08-20 02:42:17,787 epoch 104 - iter 530/2650 - loss 0.13388762 - samples/sec: 545.47 -2019-08-20 02:42:33,538 epoch 104 - iter 795/2650 - loss 0.13399212 - samples/sec: 542.62 -2019-08-20 02:42:49,177 epoch 104 - iter 1060/2650 - loss 0.13365786 - samples/sec: 546.53 -2019-08-20 02:43:04,851 epoch 104 - iter 1325/2650 - loss 0.13398476 - samples/sec: 545.15 -2019-08-20 02:43:20,796 epoch 104 - iter 1590/2650 - loss 0.13338608 - samples/sec: 535.91 -2019-08-20 02:43:36,207 epoch 104 - iter 1855/2650 - loss 0.13407085 - samples/sec: 554.75 -2019-08-20 02:43:51,617 epoch 104 - iter 2120/2650 - loss 0.13379069 - samples/sec: 554.76 -2019-08-20 02:44:07,426 epoch 104 - iter 2385/2650 - loss 0.13388936 - samples/sec: 540.48 -2019-08-20 02:44:22,896 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:44:22,897 EPOCH 104 done: loss 0.1339 - lr 0.1000 -2019-08-20 02:44:22,897 BAD EPOCHS (no improvement): 1 -2019-08-20 02:44:22,898 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:44:22,982 epoch 105 - iter 0/2650 - loss 0.10665163 - samples/sec: 107899.59 -2019-08-20 02:44:38,743 epoch 105 - iter 265/2650 - loss 0.13102731 - samples/sec: 542.19 -2019-08-20 02:44:54,191 epoch 105 - iter 530/2650 - loss 0.13113252 - samples/sec: 553.37 -2019-08-20 02:45:10,029 epoch 105 - iter 795/2650 - loss 0.13097214 - samples/sec: 539.61 -2019-08-20 02:45:25,526 epoch 105 - iter 1060/2650 - loss 0.13111299 - samples/sec: 551.45 -2019-08-20 02:45:41,101 epoch 105 - iter 1325/2650 - loss 0.13193762 - samples/sec: 548.66 -2019-08-20 02:45:56,804 epoch 105 - iter 1590/2650 - loss 0.13220465 - samples/sec: 544.22 -2019-08-20 02:46:12,403 epoch 105 - iter 1855/2650 - loss 0.13151702 - samples/sec: 547.94 -2019-08-20 02:46:28,040 epoch 105 - iter 2120/2650 - loss 0.13127404 - samples/sec: 546.56 -2019-08-20 02:46:43,526 epoch 105 - iter 2385/2650 - loss 0.13167676 - samples/sec: 551.84 -2019-08-20 02:46:59,221 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:46:59,222 EPOCH 105 done: loss 0.1318 - lr 0.1000 -2019-08-20 02:46:59,222 BAD EPOCHS (no improvement): 0 -2019-08-20 02:46:59,223 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:46:59,276 epoch 106 - iter 0/2650 - loss 0.11763535 - samples/sec: 179628.49 -2019-08-20 02:47:14,938 epoch 106 - iter 265/2650 - loss 0.13830553 - samples/sec: 545.60 -2019-08-20 02:47:30,403 epoch 106 - iter 530/2650 - loss 0.13450129 - samples/sec: 552.82 -2019-08-20 02:47:45,891 epoch 106 - iter 795/2650 - loss 0.13091871 - samples/sec: 551.81 -2019-08-20 02:48:01,459 epoch 106 - iter 1060/2650 - loss 0.13081764 - samples/sec: 548.88 -2019-08-20 02:48:17,079 epoch 106 - iter 1325/2650 - loss 0.13088705 - samples/sec: 547.12 -2019-08-20 02:48:33,069 epoch 106 - iter 1590/2650 - loss 0.13241377 - samples/sec: 534.29 -2019-08-20 02:48:48,629 epoch 106 - iter 1855/2650 - loss 0.13179044 - samples/sec: 549.58 -2019-08-20 02:49:04,245 epoch 106 - iter 2120/2650 - loss 0.13203722 - samples/sec: 547.41 -2019-08-20 02:49:19,801 epoch 106 - iter 2385/2650 - loss 0.13206357 - samples/sec: 549.33 -2019-08-20 02:49:35,461 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:49:35,462 EPOCH 106 done: loss 0.1325 - lr 0.1000 -2019-08-20 02:49:35,462 BAD EPOCHS (no improvement): 1 -2019-08-20 02:49:35,463 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:49:35,527 epoch 107 - iter 0/2650 - loss 0.08373642 - samples/sec: 144531.85 -2019-08-20 02:49:51,247 epoch 107 - iter 265/2650 - loss 0.13003890 - samples/sec: 543.42 -2019-08-20 02:50:06,820 epoch 107 - iter 530/2650 - loss 0.13127979 - samples/sec: 548.89 -2019-08-20 02:50:22,231 epoch 107 - iter 795/2650 - loss 0.13049966 - samples/sec: 554.69 -2019-08-20 02:50:37,864 epoch 107 - iter 1060/2650 - loss 0.12966869 - samples/sec: 546.61 -2019-08-20 02:50:53,665 epoch 107 - iter 1325/2650 - loss 0.13135317 - samples/sec: 540.74 -2019-08-20 02:51:09,319 epoch 107 - iter 1590/2650 - loss 0.13200197 - samples/sec: 545.85 -2019-08-20 02:51:24,841 epoch 107 - iter 1855/2650 - loss 0.13160152 - samples/sec: 550.78 -2019-08-20 02:51:40,652 epoch 107 - iter 2120/2650 - loss 0.13195964 - samples/sec: 540.53 -2019-08-20 02:51:56,386 epoch 107 - iter 2385/2650 - loss 0.13220081 - samples/sec: 543.12 -2019-08-20 02:52:12,098 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:52:12,098 EPOCH 107 done: loss 0.1320 - lr 0.1000 -2019-08-20 02:52:12,098 BAD EPOCHS (no improvement): 2 -2019-08-20 02:52:12,100 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:52:12,165 epoch 108 - iter 0/2650 - loss 0.14192571 - samples/sec: 139813.98 -2019-08-20 02:52:27,721 epoch 108 - iter 265/2650 - loss 0.13352743 - samples/sec: 549.18 -2019-08-20 02:52:43,363 epoch 108 - iter 530/2650 - loss 0.13155457 - samples/sec: 546.53 -2019-08-20 02:52:58,872 epoch 108 - iter 795/2650 - loss 0.13104193 - samples/sec: 551.12 -2019-08-20 02:53:14,557 epoch 108 - iter 1060/2650 - loss 0.13154656 - samples/sec: 544.82 -2019-08-20 02:53:30,286 epoch 108 - iter 1325/2650 - loss 0.13119334 - samples/sec: 543.29 -2019-08-20 02:53:46,059 epoch 108 - iter 1590/2650 - loss 0.13182361 - samples/sec: 541.62 -2019-08-20 02:54:01,818 epoch 108 - iter 1855/2650 - loss 0.13172535 - samples/sec: 542.47 -2019-08-20 02:54:17,691 epoch 108 - iter 2120/2650 - loss 0.13163855 - samples/sec: 538.27 -2019-08-20 02:54:33,217 epoch 108 - iter 2385/2650 - loss 0.13134634 - samples/sec: 550.29 -2019-08-20 02:54:48,631 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:54:48,632 EPOCH 108 done: loss 0.1313 - lr 0.1000 -2019-08-20 02:54:48,632 BAD EPOCHS (no improvement): 0 -2019-08-20 02:54:48,633 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:54:48,689 epoch 109 - iter 0/2650 - loss 0.12818643 - samples/sec: 164399.64 -2019-08-20 02:55:04,381 epoch 109 - iter 265/2650 - loss 0.12898021 - samples/sec: 544.17 -2019-08-20 02:55:19,989 epoch 109 - iter 530/2650 - loss 0.13072891 - samples/sec: 547.70 -2019-08-20 02:55:35,477 epoch 109 - iter 795/2650 - loss 0.13141698 - samples/sec: 551.79 -2019-08-20 02:55:51,263 epoch 109 - iter 1060/2650 - loss 0.13147529 - samples/sec: 541.08 -2019-08-20 02:56:06,754 epoch 109 - iter 1325/2650 - loss 0.12974942 - samples/sec: 551.59 -2019-08-20 02:56:22,566 epoch 109 - iter 1590/2650 - loss 0.13028052 - samples/sec: 539.99 -2019-08-20 02:56:38,032 epoch 109 - iter 1855/2650 - loss 0.12938241 - samples/sec: 554.62 -2019-08-20 02:56:53,761 epoch 109 - iter 2120/2650 - loss 0.12966718 - samples/sec: 543.21 -2019-08-20 02:57:09,584 epoch 109 - iter 2385/2650 - loss 0.12909395 - samples/sec: 539.89 -2019-08-20 02:57:24,980 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:57:24,980 EPOCH 109 done: loss 0.1294 - lr 0.1000 -2019-08-20 02:57:24,980 BAD EPOCHS (no improvement): 0 -2019-08-20 02:57:24,981 ---------------------------------------------------------------------------------------------------- -2019-08-20 02:57:25,038 epoch 110 - iter 0/2650 - loss 0.10599811 - samples/sec: 162386.59 -2019-08-20 02:57:40,584 epoch 110 - iter 265/2650 - loss 0.12892470 - samples/sec: 549.52 -2019-08-20 02:57:56,191 epoch 110 - iter 530/2650 - loss 0.12784712 - samples/sec: 547.42 -2019-08-20 02:58:11,706 epoch 110 - iter 795/2650 - loss 0.12774554 - samples/sec: 550.83 -2019-08-20 02:58:27,238 epoch 110 - iter 1060/2650 - loss 0.12833139 - samples/sec: 549.97 -2019-08-20 02:58:42,525 epoch 110 - iter 1325/2650 - loss 0.12815675 - samples/sec: 558.81 -2019-08-20 02:58:58,297 epoch 110 - iter 1590/2650 - loss 0.12892940 - samples/sec: 541.58 -2019-08-20 02:59:13,878 epoch 110 - iter 1855/2650 - loss 0.12865501 - samples/sec: 548.29 -2019-08-20 02:59:29,491 epoch 110 - iter 2120/2650 - loss 0.12902701 - samples/sec: 547.23 -2019-08-20 02:59:45,172 epoch 110 - iter 2385/2650 - loss 0.12984599 - samples/sec: 544.70 -2019-08-20 03:00:00,833 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:00:00,833 EPOCH 110 done: loss 0.1295 - lr 0.1000 -2019-08-20 03:00:00,833 BAD EPOCHS (no improvement): 1 -2019-08-20 03:00:00,834 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:00:00,889 epoch 111 - iter 0/2650 - loss 0.15146784 - samples/sec: 167453.05 -2019-08-20 03:00:16,675 epoch 111 - iter 265/2650 - loss 0.13107189 - samples/sec: 541.00 -2019-08-20 03:00:32,091 epoch 111 - iter 530/2650 - loss 0.13321382 - samples/sec: 554.39 -2019-08-20 03:00:47,621 epoch 111 - iter 795/2650 - loss 0.13196923 - samples/sec: 550.12 -2019-08-20 03:01:03,420 epoch 111 - iter 1060/2650 - loss 0.13178694 - samples/sec: 540.70 -2019-08-20 03:01:18,863 epoch 111 - iter 1325/2650 - loss 0.13054361 - samples/sec: 553.23 -2019-08-20 03:01:34,592 epoch 111 - iter 1590/2650 - loss 0.12976668 - samples/sec: 543.14 -2019-08-20 03:01:50,145 epoch 111 - iter 1855/2650 - loss 0.12954192 - samples/sec: 549.38 -2019-08-20 03:02:05,512 epoch 111 - iter 2120/2650 - loss 0.13075373 - samples/sec: 556.09 -2019-08-20 03:02:21,293 epoch 111 - iter 2385/2650 - loss 0.13061608 - samples/sec: 541.32 -2019-08-20 03:02:36,851 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:02:36,851 EPOCH 111 done: loss 0.1308 - lr 0.1000 -2019-08-20 03:02:36,851 BAD EPOCHS (no improvement): 2 -2019-08-20 03:02:36,852 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:02:36,913 epoch 112 - iter 0/2650 - loss 0.12111050 - samples/sec: 147610.76 -2019-08-20 03:02:52,280 epoch 112 - iter 265/2650 - loss 0.12890150 - samples/sec: 555.96 -2019-08-20 03:03:07,871 epoch 112 - iter 530/2650 - loss 0.12919811 - samples/sec: 547.99 -2019-08-20 03:03:23,520 epoch 112 - iter 795/2650 - loss 0.13127333 - samples/sec: 545.79 -2019-08-20 03:03:39,121 epoch 112 - iter 1060/2650 - loss 0.13119748 - samples/sec: 548.28 -2019-08-20 03:03:55,025 epoch 112 - iter 1325/2650 - loss 0.13104327 - samples/sec: 536.89 -2019-08-20 03:04:10,720 epoch 112 - iter 1590/2650 - loss 0.13080866 - samples/sec: 544.11 -2019-08-20 03:04:26,742 epoch 112 - iter 1855/2650 - loss 0.13056439 - samples/sec: 533.22 -2019-08-20 03:04:42,337 epoch 112 - iter 2120/2650 - loss 0.13045779 - samples/sec: 548.00 -2019-08-20 03:04:57,833 epoch 112 - iter 2385/2650 - loss 0.13046238 - samples/sec: 551.37 -2019-08-20 03:05:13,180 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:05:13,181 EPOCH 112 done: loss 0.1305 - lr 0.1000 -2019-08-20 03:05:13,181 BAD EPOCHS (no improvement): 3 -2019-08-20 03:05:13,182 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:05:13,240 epoch 113 - iter 0/2650 - loss 0.16794784 - samples/sec: 160683.88 -2019-08-20 03:05:28,903 epoch 113 - iter 265/2650 - loss 0.12367422 - samples/sec: 545.28 -2019-08-20 03:05:44,721 epoch 113 - iter 530/2650 - loss 0.12523295 - samples/sec: 540.01 -2019-08-20 03:06:00,276 epoch 113 - iter 795/2650 - loss 0.12717818 - samples/sec: 549.30 -2019-08-20 03:06:15,810 epoch 113 - iter 1060/2650 - loss 0.12915965 - samples/sec: 550.10 -2019-08-20 03:06:31,519 epoch 113 - iter 1325/2650 - loss 0.12852499 - samples/sec: 543.87 -2019-08-20 03:06:47,075 epoch 113 - iter 1590/2650 - loss 0.12884807 - samples/sec: 549.19 -2019-08-20 03:07:02,715 epoch 113 - iter 1855/2650 - loss 0.12889423 - samples/sec: 546.23 -2019-08-20 03:07:18,580 epoch 113 - iter 2120/2650 - loss 0.12906931 - samples/sec: 538.69 -2019-08-20 03:07:34,167 epoch 113 - iter 2385/2650 - loss 0.12877780 - samples/sec: 548.04 -2019-08-20 03:07:49,597 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:07:49,597 EPOCH 113 done: loss 0.1289 - lr 0.1000 -2019-08-20 03:07:49,597 BAD EPOCHS (no improvement): 0 -2019-08-20 03:07:49,598 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:07:49,658 epoch 114 - iter 0/2650 - loss 0.19821434 - samples/sec: 155077.05 -2019-08-20 03:08:05,325 epoch 114 - iter 265/2650 - loss 0.13106660 - samples/sec: 545.38 -2019-08-20 03:08:20,941 epoch 114 - iter 530/2650 - loss 0.13087086 - samples/sec: 547.07 -2019-08-20 03:08:36,513 epoch 114 - iter 795/2650 - loss 0.12913822 - samples/sec: 548.68 -2019-08-20 03:08:52,008 epoch 114 - iter 1060/2650 - loss 0.12899526 - samples/sec: 551.52 -2019-08-20 03:09:07,675 epoch 114 - iter 1325/2650 - loss 0.12885761 - samples/sec: 545.21 -2019-08-20 03:09:23,254 epoch 114 - iter 1590/2650 - loss 0.12894886 - samples/sec: 548.35 -2019-08-20 03:09:39,149 epoch 114 - iter 1855/2650 - loss 0.12840219 - samples/sec: 537.45 -2019-08-20 03:09:54,701 epoch 114 - iter 2120/2650 - loss 0.12842375 - samples/sec: 549.50 -2019-08-20 03:10:10,253 epoch 114 - iter 2385/2650 - loss 0.12879177 - samples/sec: 549.36 -2019-08-20 03:10:25,727 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:10:25,727 EPOCH 114 done: loss 0.1289 - lr 0.1000 -2019-08-20 03:10:25,728 BAD EPOCHS (no improvement): 1 -2019-08-20 03:10:25,728 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:10:25,791 epoch 115 - iter 0/2650 - loss 0.13888049 - samples/sec: 141212.83 -2019-08-20 03:10:41,289 epoch 115 - iter 265/2650 - loss 0.13026980 - samples/sec: 551.15 -2019-08-20 03:10:57,022 epoch 115 - iter 530/2650 - loss 0.12750413 - samples/sec: 542.93 -2019-08-20 03:11:12,301 epoch 115 - iter 795/2650 - loss 0.12687019 - samples/sec: 559.43 -2019-08-20 03:11:27,907 epoch 115 - iter 1060/2650 - loss 0.12745273 - samples/sec: 547.30 -2019-08-20 03:11:43,581 epoch 115 - iter 1325/2650 - loss 0.12708393 - samples/sec: 545.02 -2019-08-20 03:11:59,289 epoch 115 - iter 1590/2650 - loss 0.12875610 - samples/sec: 543.67 -2019-08-20 03:12:15,023 epoch 115 - iter 1855/2650 - loss 0.12781499 - samples/sec: 542.84 -2019-08-20 03:12:30,653 epoch 115 - iter 2120/2650 - loss 0.12796410 - samples/sec: 546.88 -2019-08-20 03:12:46,379 epoch 115 - iter 2385/2650 - loss 0.12798059 - samples/sec: 543.43 -2019-08-20 03:13:01,938 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:13:01,938 EPOCH 115 done: loss 0.1286 - lr 0.1000 -2019-08-20 03:13:01,938 BAD EPOCHS (no improvement): 0 -2019-08-20 03:13:01,939 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:13:02,001 epoch 116 - iter 0/2650 - loss 0.10951979 - samples/sec: 152221.84 -2019-08-20 03:13:17,419 epoch 116 - iter 265/2650 - loss 0.12359239 - samples/sec: 554.16 -2019-08-20 03:13:33,175 epoch 116 - iter 530/2650 - loss 0.12759647 - samples/sec: 541.96 -2019-08-20 03:13:47,553 epoch 116 - iter 795/2650 - loss 0.12691132 - samples/sec: 594.28 -2019-08-20 03:14:03,141 epoch 116 - iter 1060/2650 - loss 0.12721900 - samples/sec: 548.25 -2019-08-20 03:14:18,659 epoch 116 - iter 1325/2650 - loss 0.12679910 - samples/sec: 550.37 -2019-08-20 03:14:34,386 epoch 116 - iter 1590/2650 - loss 0.12777280 - samples/sec: 543.19 -2019-08-20 03:14:50,132 epoch 116 - iter 1855/2650 - loss 0.12719400 - samples/sec: 542.77 -2019-08-20 03:15:05,700 epoch 116 - iter 2120/2650 - loss 0.12694447 - samples/sec: 548.99 -2019-08-20 03:15:21,220 epoch 116 - iter 2385/2650 - loss 0.12635476 - samples/sec: 550.52 -2019-08-20 03:15:36,885 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:15:36,885 EPOCH 116 done: loss 0.1263 - lr 0.1000 -2019-08-20 03:15:36,885 BAD EPOCHS (no improvement): 0 -2019-08-20 03:15:36,886 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:15:36,950 epoch 117 - iter 0/2650 - loss 0.10271937 - samples/sec: 144024.43 -2019-08-20 03:15:52,555 epoch 117 - iter 265/2650 - loss 0.12982995 - samples/sec: 547.33 -2019-08-20 03:16:08,387 epoch 117 - iter 530/2650 - loss 0.12889124 - samples/sec: 539.37 -2019-08-20 03:16:23,878 epoch 117 - iter 795/2650 - loss 0.12703218 - samples/sec: 551.63 -2019-08-20 03:16:39,345 epoch 117 - iter 1060/2650 - loss 0.12647640 - samples/sec: 552.65 -2019-08-20 03:16:55,061 epoch 117 - iter 1325/2650 - loss 0.12668977 - samples/sec: 543.89 -2019-08-20 03:17:10,697 epoch 117 - iter 1590/2650 - loss 0.12681155 - samples/sec: 546.45 -2019-08-20 03:17:26,488 epoch 117 - iter 1855/2650 - loss 0.12758244 - samples/sec: 541.02 -2019-08-20 03:17:42,014 epoch 117 - iter 2120/2650 - loss 0.12780929 - samples/sec: 550.71 -2019-08-20 03:17:57,570 epoch 117 - iter 2385/2650 - loss 0.12752631 - samples/sec: 549.40 -2019-08-20 03:18:12,961 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:18:12,962 EPOCH 117 done: loss 0.1278 - lr 0.1000 -2019-08-20 03:18:12,962 BAD EPOCHS (no improvement): 1 -2019-08-20 03:18:12,962 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:18:13,016 epoch 118 - iter 0/2650 - loss 0.13629960 - samples/sec: 172131.47 -2019-08-20 03:18:28,483 epoch 118 - iter 265/2650 - loss 0.12737996 - samples/sec: 552.61 -2019-08-20 03:18:43,941 epoch 118 - iter 530/2650 - loss 0.12797714 - samples/sec: 552.72 -2019-08-20 03:18:59,686 epoch 118 - iter 795/2650 - loss 0.12801388 - samples/sec: 542.65 -2019-08-20 03:19:15,461 epoch 118 - iter 1060/2650 - loss 0.12685165 - samples/sec: 542.10 -2019-08-20 03:19:31,266 epoch 118 - iter 1325/2650 - loss 0.12716889 - samples/sec: 540.62 -2019-08-20 03:19:46,902 epoch 118 - iter 1590/2650 - loss 0.12741654 - samples/sec: 546.54 -2019-08-20 03:20:02,514 epoch 118 - iter 1855/2650 - loss 0.12758673 - samples/sec: 547.31 -2019-08-20 03:20:18,204 epoch 118 - iter 2120/2650 - loss 0.12755532 - samples/sec: 544.63 -2019-08-20 03:20:33,647 epoch 118 - iter 2385/2650 - loss 0.12682974 - samples/sec: 553.49 -2019-08-20 03:20:49,136 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:20:49,137 EPOCH 118 done: loss 0.1267 - lr 0.1000 -2019-08-20 03:20:49,137 BAD EPOCHS (no improvement): 2 -2019-08-20 03:20:49,138 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:20:49,204 epoch 119 - iter 0/2650 - loss 0.09639050 - samples/sec: 135351.62 -2019-08-20 03:21:04,910 epoch 119 - iter 265/2650 - loss 0.12547427 - samples/sec: 543.77 -2019-08-20 03:21:19,384 epoch 119 - iter 530/2650 - loss 0.12833527 - samples/sec: 594.71 -2019-08-20 03:21:33,662 epoch 119 - iter 795/2650 - loss 0.12758209 - samples/sec: 598.10 -2019-08-20 03:21:48,017 epoch 119 - iter 1060/2650 - loss 0.12886284 - samples/sec: 595.11 -2019-08-20 03:22:02,262 epoch 119 - iter 1325/2650 - loss 0.12794227 - samples/sec: 600.38 -2019-08-20 03:22:17,202 epoch 119 - iter 1590/2650 - loss 0.12799410 - samples/sec: 571.69 -2019-08-20 03:22:33,047 epoch 119 - iter 1855/2650 - loss 0.12699591 - samples/sec: 539.10 -2019-08-20 03:22:48,785 epoch 119 - iter 2120/2650 - loss 0.12703530 - samples/sec: 543.19 -2019-08-20 03:23:04,295 epoch 119 - iter 2385/2650 - loss 0.12708147 - samples/sec: 550.96 -2019-08-20 03:23:19,860 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:23:19,860 EPOCH 119 done: loss 0.1268 - lr 0.1000 -2019-08-20 03:23:19,860 BAD EPOCHS (no improvement): 3 -2019-08-20 03:23:19,861 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:23:19,921 epoch 120 - iter 0/2650 - loss 0.13248938 - samples/sec: 151495.02 -2019-08-20 03:23:35,329 epoch 120 - iter 265/2650 - loss 0.12465791 - samples/sec: 554.45 -2019-08-20 03:23:50,990 epoch 120 - iter 530/2650 - loss 0.12473472 - samples/sec: 545.51 -2019-08-20 03:24:06,431 epoch 120 - iter 795/2650 - loss 0.12545813 - samples/sec: 553.69 -2019-08-20 03:24:22,057 epoch 120 - iter 1060/2650 - loss 0.12673525 - samples/sec: 546.77 -2019-08-20 03:24:37,742 epoch 120 - iter 1325/2650 - loss 0.12609250 - samples/sec: 544.77 -2019-08-20 03:24:53,432 epoch 120 - iter 1590/2650 - loss 0.12613524 - samples/sec: 544.61 -2019-08-20 03:25:09,265 epoch 120 - iter 1855/2650 - loss 0.12647689 - samples/sec: 539.52 -2019-08-20 03:25:24,972 epoch 120 - iter 2120/2650 - loss 0.12647663 - samples/sec: 544.03 -2019-08-20 03:25:40,414 epoch 120 - iter 2385/2650 - loss 0.12627069 - samples/sec: 553.50 -2019-08-20 03:25:55,880 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:25:55,880 EPOCH 120 done: loss 0.1262 - lr 0.1000 -2019-08-20 03:25:55,880 BAD EPOCHS (no improvement): 0 -2019-08-20 03:25:55,881 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:25:55,940 epoch 121 - iter 0/2650 - loss 0.10822323 - samples/sec: 158570.58 -2019-08-20 03:26:11,722 epoch 121 - iter 265/2650 - loss 0.12180001 - samples/sec: 541.22 -2019-08-20 03:26:27,389 epoch 121 - iter 530/2650 - loss 0.12334250 - samples/sec: 545.36 -2019-08-20 03:26:42,948 epoch 121 - iter 795/2650 - loss 0.12428787 - samples/sec: 549.27 -2019-08-20 03:26:58,587 epoch 121 - iter 1060/2650 - loss 0.12474779 - samples/sec: 546.52 -2019-08-20 03:27:14,113 epoch 121 - iter 1325/2650 - loss 0.12412501 - samples/sec: 550.33 -2019-08-20 03:27:29,573 epoch 121 - iter 1590/2650 - loss 0.12470560 - samples/sec: 552.67 -2019-08-20 03:27:45,498 epoch 121 - iter 1855/2650 - loss 0.12475572 - samples/sec: 536.27 -2019-08-20 03:28:01,431 epoch 121 - iter 2120/2650 - loss 0.12488784 - samples/sec: 536.20 -2019-08-20 03:28:16,967 epoch 121 - iter 2385/2650 - loss 0.12530004 - samples/sec: 549.98 -2019-08-20 03:28:32,348 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:28:32,349 EPOCH 121 done: loss 0.1252 - lr 0.1000 -2019-08-20 03:28:32,349 BAD EPOCHS (no improvement): 0 -2019-08-20 03:28:32,350 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:28:32,408 epoch 122 - iter 0/2650 - loss 0.07788239 - samples/sec: 158250.98 -2019-08-20 03:28:48,201 epoch 122 - iter 265/2650 - loss 0.12467285 - samples/sec: 540.77 -2019-08-20 03:29:03,723 epoch 122 - iter 530/2650 - loss 0.12307362 - samples/sec: 550.49 -2019-08-20 03:29:19,534 epoch 122 - iter 795/2650 - loss 0.12206292 - samples/sec: 540.45 -2019-08-20 03:29:34,783 epoch 122 - iter 1060/2650 - loss 0.12405969 - samples/sec: 560.29 -2019-08-20 03:29:50,177 epoch 122 - iter 1325/2650 - loss 0.12439114 - samples/sec: 555.20 -2019-08-20 03:30:05,895 epoch 122 - iter 1590/2650 - loss 0.12487352 - samples/sec: 543.53 -2019-08-20 03:30:21,700 epoch 122 - iter 1855/2650 - loss 0.12509734 - samples/sec: 540.54 -2019-08-20 03:30:37,567 epoch 122 - iter 2120/2650 - loss 0.12474672 - samples/sec: 538.42 -2019-08-20 03:30:53,037 epoch 122 - iter 2385/2650 - loss 0.12489713 - samples/sec: 552.70 -2019-08-20 03:31:08,579 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:31:08,579 EPOCH 122 done: loss 0.1250 - lr 0.1000 -2019-08-20 03:31:08,580 BAD EPOCHS (no improvement): 0 -2019-08-20 03:31:08,580 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:31:08,634 epoch 123 - iter 0/2650 - loss 0.14321569 - samples/sec: 170706.38 -2019-08-20 03:31:24,131 epoch 123 - iter 265/2650 - loss 0.12789027 - samples/sec: 551.52 -2019-08-20 03:31:39,555 epoch 123 - iter 530/2650 - loss 0.12580434 - samples/sec: 553.89 -2019-08-20 03:31:54,974 epoch 123 - iter 795/2650 - loss 0.12577662 - samples/sec: 554.10 -2019-08-20 03:32:10,764 epoch 123 - iter 1060/2650 - loss 0.12711449 - samples/sec: 541.29 -2019-08-20 03:32:26,473 epoch 123 - iter 1325/2650 - loss 0.12650332 - samples/sec: 544.10 -2019-08-20 03:32:42,113 epoch 123 - iter 1590/2650 - loss 0.12553395 - samples/sec: 546.39 -2019-08-20 03:32:57,706 epoch 123 - iter 1855/2650 - loss 0.12481679 - samples/sec: 547.92 -2019-08-20 03:33:13,163 epoch 123 - iter 2120/2650 - loss 0.12493668 - samples/sec: 552.98 -2019-08-20 03:33:28,871 epoch 123 - iter 2385/2650 - loss 0.12542172 - samples/sec: 544.17 -2019-08-20 03:33:44,520 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:33:44,521 EPOCH 123 done: loss 0.1253 - lr 0.1000 -2019-08-20 03:33:44,521 BAD EPOCHS (no improvement): 1 -2019-08-20 03:33:44,521 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:33:44,569 epoch 124 - iter 0/2650 - loss 0.21911481 - samples/sec: 195290.64 -2019-08-20 03:34:00,122 epoch 124 - iter 265/2650 - loss 0.12251302 - samples/sec: 549.26 -2019-08-20 03:34:15,733 epoch 124 - iter 530/2650 - loss 0.12478941 - samples/sec: 547.16 -2019-08-20 03:34:31,283 epoch 124 - iter 795/2650 - loss 0.12462978 - samples/sec: 549.52 -2019-08-20 03:34:46,897 epoch 124 - iter 1060/2650 - loss 0.12378693 - samples/sec: 547.10 -2019-08-20 03:35:02,337 epoch 124 - iter 1325/2650 - loss 0.12466024 - samples/sec: 553.44 -2019-08-20 03:35:17,985 epoch 124 - iter 1590/2650 - loss 0.12466473 - samples/sec: 545.66 -2019-08-20 03:35:33,946 epoch 124 - iter 1855/2650 - loss 0.12464298 - samples/sec: 535.07 -2019-08-20 03:35:49,751 epoch 124 - iter 2120/2650 - loss 0.12490157 - samples/sec: 540.47 -2019-08-20 03:36:05,377 epoch 124 - iter 2385/2650 - loss 0.12479774 - samples/sec: 546.97 -2019-08-20 03:36:20,760 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:36:20,760 EPOCH 124 done: loss 0.1249 - lr 0.1000 -2019-08-20 03:36:20,760 BAD EPOCHS (no improvement): 0 -2019-08-20 03:36:20,761 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:36:20,821 epoch 125 - iter 0/2650 - loss 0.19313809 - samples/sec: 152607.84 -2019-08-20 03:36:36,222 epoch 125 - iter 265/2650 - loss 0.12168821 - samples/sec: 554.85 -2019-08-20 03:36:51,684 epoch 125 - iter 530/2650 - loss 0.12396470 - samples/sec: 552.32 -2019-08-20 03:37:07,446 epoch 125 - iter 795/2650 - loss 0.12462432 - samples/sec: 542.09 -2019-08-20 03:37:22,904 epoch 125 - iter 1060/2650 - loss 0.12388767 - samples/sec: 552.93 -2019-08-20 03:37:38,411 epoch 125 - iter 1325/2650 - loss 0.12326950 - samples/sec: 551.24 -2019-08-20 03:37:54,125 epoch 125 - iter 1590/2650 - loss 0.12324276 - samples/sec: 543.65 -2019-08-20 03:38:09,919 epoch 125 - iter 1855/2650 - loss 0.12379270 - samples/sec: 540.88 -2019-08-20 03:38:25,863 epoch 125 - iter 2120/2650 - loss 0.12384237 - samples/sec: 535.64 -2019-08-20 03:38:41,556 epoch 125 - iter 2385/2650 - loss 0.12380544 - samples/sec: 544.61 -2019-08-20 03:38:57,001 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:38:57,001 EPOCH 125 done: loss 0.1235 - lr 0.1000 -2019-08-20 03:38:57,002 BAD EPOCHS (no improvement): 0 -2019-08-20 03:38:57,002 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:38:57,079 epoch 126 - iter 0/2650 - loss 0.07421859 - samples/sec: 119403.98 -2019-08-20 03:39:12,611 epoch 126 - iter 265/2650 - loss 0.12572821 - samples/sec: 550.04 -2019-08-20 03:39:28,129 epoch 126 - iter 530/2650 - loss 0.12511997 - samples/sec: 550.53 -2019-08-20 03:39:43,865 epoch 126 - iter 795/2650 - loss 0.12415954 - samples/sec: 543.07 -2019-08-20 03:39:59,679 epoch 126 - iter 1060/2650 - loss 0.12400891 - samples/sec: 540.39 -2019-08-20 03:40:15,193 epoch 126 - iter 1325/2650 - loss 0.12420304 - samples/sec: 550.80 -2019-08-20 03:40:30,887 epoch 126 - iter 1590/2650 - loss 0.12366792 - samples/sec: 544.55 -2019-08-20 03:40:46,434 epoch 126 - iter 1855/2650 - loss 0.12325067 - samples/sec: 549.40 -2019-08-20 03:41:02,152 epoch 126 - iter 2120/2650 - loss 0.12328707 - samples/sec: 543.65 -2019-08-20 03:41:17,837 epoch 126 - iter 2385/2650 - loss 0.12336307 - samples/sec: 544.89 -2019-08-20 03:41:33,480 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:41:33,481 EPOCH 126 done: loss 0.1236 - lr 0.1000 -2019-08-20 03:41:33,481 BAD EPOCHS (no improvement): 1 -2019-08-20 03:41:33,482 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:41:33,550 epoch 127 - iter 0/2650 - loss 0.24426378 - samples/sec: 133630.76 -2019-08-20 03:41:48,974 epoch 127 - iter 265/2650 - loss 0.12123199 - samples/sec: 553.89 -2019-08-20 03:42:04,972 epoch 127 - iter 530/2650 - loss 0.12330180 - samples/sec: 533.94 -2019-08-20 03:42:20,749 epoch 127 - iter 795/2650 - loss 0.12299986 - samples/sec: 541.49 -2019-08-20 03:42:36,282 epoch 127 - iter 1060/2650 - loss 0.12288221 - samples/sec: 550.08 -2019-08-20 03:42:51,765 epoch 127 - iter 1325/2650 - loss 0.12212834 - samples/sec: 551.91 -2019-08-20 03:43:07,756 epoch 127 - iter 1590/2650 - loss 0.12216049 - samples/sec: 534.28 -2019-08-20 03:43:23,431 epoch 127 - iter 1855/2650 - loss 0.12217513 - samples/sec: 545.18 -2019-08-20 03:43:39,111 epoch 127 - iter 2120/2650 - loss 0.12181787 - samples/sec: 544.73 -2019-08-20 03:43:54,601 epoch 127 - iter 2385/2650 - loss 0.12234345 - samples/sec: 552.01 -2019-08-20 03:44:10,000 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:44:10,000 EPOCH 127 done: loss 0.1227 - lr 0.1000 -2019-08-20 03:44:10,000 BAD EPOCHS (no improvement): 0 -2019-08-20 03:44:10,001 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:44:10,079 epoch 128 - iter 0/2650 - loss 0.08604839 - samples/sec: 116134.49 -2019-08-20 03:44:25,942 epoch 128 - iter 265/2650 - loss 0.11516124 - samples/sec: 538.42 -2019-08-20 03:44:41,316 epoch 128 - iter 530/2650 - loss 0.11675191 - samples/sec: 555.79 -2019-08-20 03:44:56,902 epoch 128 - iter 795/2650 - loss 0.11804422 - samples/sec: 548.08 -2019-08-20 03:45:12,450 epoch 128 - iter 1060/2650 - loss 0.11797726 - samples/sec: 549.68 -2019-08-20 03:45:27,903 epoch 128 - iter 1325/2650 - loss 0.11820649 - samples/sec: 553.00 -2019-08-20 03:45:43,781 epoch 128 - iter 1590/2650 - loss 0.11902156 - samples/sec: 538.11 -2019-08-20 03:45:59,407 epoch 128 - iter 1855/2650 - loss 0.12035984 - samples/sec: 546.62 -2019-08-20 03:46:15,051 epoch 128 - iter 2120/2650 - loss 0.12071551 - samples/sec: 545.95 -2019-08-20 03:46:30,805 epoch 128 - iter 2385/2650 - loss 0.12113463 - samples/sec: 542.68 -2019-08-20 03:46:46,352 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:46:46,353 EPOCH 128 done: loss 0.1213 - lr 0.1000 -2019-08-20 03:46:46,353 BAD EPOCHS (no improvement): 0 -2019-08-20 03:46:46,353 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:46:46,409 epoch 129 - iter 0/2650 - loss 0.10932545 - samples/sec: 170250.43 -2019-08-20 03:47:02,017 epoch 129 - iter 265/2650 - loss 0.12066642 - samples/sec: 547.45 -2019-08-20 03:47:17,447 epoch 129 - iter 530/2650 - loss 0.12165283 - samples/sec: 553.73 -2019-08-20 03:47:33,150 epoch 129 - iter 795/2650 - loss 0.12182152 - samples/sec: 543.94 -2019-08-20 03:47:48,792 epoch 129 - iter 1060/2650 - loss 0.12145869 - samples/sec: 546.60 -2019-08-20 03:48:04,282 epoch 129 - iter 1325/2650 - loss 0.12207401 - samples/sec: 551.61 -2019-08-20 03:48:19,980 epoch 129 - iter 1590/2650 - loss 0.12206032 - samples/sec: 544.60 -2019-08-20 03:48:35,559 epoch 129 - iter 1855/2650 - loss 0.12202280 - samples/sec: 548.27 -2019-08-20 03:48:51,146 epoch 129 - iter 2120/2650 - loss 0.12191717 - samples/sec: 548.20 -2019-08-20 03:49:06,792 epoch 129 - iter 2385/2650 - loss 0.12242747 - samples/sec: 546.41 -2019-08-20 03:49:22,416 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:49:22,416 EPOCH 129 done: loss 0.1226 - lr 0.1000 -2019-08-20 03:49:22,416 BAD EPOCHS (no improvement): 1 -2019-08-20 03:49:22,417 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:49:22,483 epoch 130 - iter 0/2650 - loss 0.09705922 - samples/sec: 138231.13 -2019-08-20 03:49:38,028 epoch 130 - iter 265/2650 - loss 0.12345081 - samples/sec: 549.57 -2019-08-20 03:49:53,756 epoch 130 - iter 530/2650 - loss 0.12393093 - samples/sec: 543.07 -2019-08-20 03:50:09,504 epoch 130 - iter 795/2650 - loss 0.12253706 - samples/sec: 542.35 -2019-08-20 03:50:25,241 epoch 130 - iter 1060/2650 - loss 0.12200383 - samples/sec: 543.03 -2019-08-20 03:50:40,896 epoch 130 - iter 1325/2650 - loss 0.12221698 - samples/sec: 545.83 -2019-08-20 03:50:56,483 epoch 130 - iter 1590/2650 - loss 0.12211082 - samples/sec: 548.19 -2019-08-20 03:51:12,185 epoch 130 - iter 1855/2650 - loss 0.12251404 - samples/sec: 544.09 -2019-08-20 03:51:27,992 epoch 130 - iter 2120/2650 - loss 0.12267780 - samples/sec: 540.43 -2019-08-20 03:51:43,441 epoch 130 - iter 2385/2650 - loss 0.12246543 - samples/sec: 553.20 -2019-08-20 03:51:58,916 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:51:58,917 EPOCH 130 done: loss 0.1223 - lr 0.1000 -2019-08-20 03:51:58,917 BAD EPOCHS (no improvement): 2 -2019-08-20 03:51:58,917 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:51:58,984 epoch 131 - iter 0/2650 - loss 0.18312353 - samples/sec: 137973.20 -2019-08-20 03:52:14,437 epoch 131 - iter 265/2650 - loss 0.11579962 - samples/sec: 552.85 -2019-08-20 03:52:30,270 epoch 131 - iter 530/2650 - loss 0.11912891 - samples/sec: 539.86 -2019-08-20 03:52:45,822 epoch 131 - iter 795/2650 - loss 0.11994932 - samples/sec: 549.19 -2019-08-20 03:53:01,375 epoch 131 - iter 1060/2650 - loss 0.12004326 - samples/sec: 549.42 -2019-08-20 03:53:16,999 epoch 131 - iter 1325/2650 - loss 0.12068822 - samples/sec: 546.92 -2019-08-20 03:53:32,640 epoch 131 - iter 1590/2650 - loss 0.12103340 - samples/sec: 546.26 -2019-08-20 03:53:48,176 epoch 131 - iter 1855/2650 - loss 0.12071169 - samples/sec: 549.59 -2019-08-20 03:54:03,792 epoch 131 - iter 2120/2650 - loss 0.12184893 - samples/sec: 546.92 -2019-08-20 03:54:19,583 epoch 131 - iter 2385/2650 - loss 0.12241493 - samples/sec: 541.16 -2019-08-20 03:54:35,135 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:54:35,136 EPOCH 131 done: loss 0.1222 - lr 0.1000 -2019-08-20 03:54:35,136 BAD EPOCHS (no improvement): 3 -2019-08-20 03:54:35,137 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:54:35,196 epoch 132 - iter 0/2650 - loss 0.08674983 - samples/sec: 165210.62 -2019-08-20 03:54:50,695 epoch 132 - iter 265/2650 - loss 0.12169380 - samples/sec: 551.25 -2019-08-20 03:55:06,126 epoch 132 - iter 530/2650 - loss 0.12217153 - samples/sec: 553.63 -2019-08-20 03:55:21,920 epoch 132 - iter 795/2650 - loss 0.12210620 - samples/sec: 540.93 -2019-08-20 03:55:37,677 epoch 132 - iter 1060/2650 - loss 0.12223772 - samples/sec: 542.26 -2019-08-20 03:55:53,490 epoch 132 - iter 1325/2650 - loss 0.12251100 - samples/sec: 540.39 -2019-08-20 03:56:09,055 epoch 132 - iter 1590/2650 - loss 0.12328062 - samples/sec: 549.44 -2019-08-20 03:56:24,745 epoch 132 - iter 1855/2650 - loss 0.12328376 - samples/sec: 544.39 -2019-08-20 03:56:40,397 epoch 132 - iter 2120/2650 - loss 0.12283525 - samples/sec: 545.75 -2019-08-20 03:56:56,051 epoch 132 - iter 2385/2650 - loss 0.12266831 - samples/sec: 545.92 -2019-08-20 03:57:11,459 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:57:11,459 EPOCH 132 done: loss 0.1231 - lr 0.1000 -2019-08-20 03:57:11,459 BAD EPOCHS (no improvement): 4 -2019-08-20 03:57:11,460 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:57:11,528 epoch 133 - iter 0/2650 - loss 0.12733620 - samples/sec: 131733.68 -2019-08-20 03:57:27,120 epoch 133 - iter 265/2650 - loss 0.12607576 - samples/sec: 547.87 -2019-08-20 03:57:42,706 epoch 133 - iter 530/2650 - loss 0.12271461 - samples/sec: 548.18 -2019-08-20 03:57:58,282 epoch 133 - iter 795/2650 - loss 0.12294461 - samples/sec: 548.34 -2019-08-20 03:58:13,933 epoch 133 - iter 1060/2650 - loss 0.12287419 - samples/sec: 545.90 -2019-08-20 03:58:29,780 epoch 133 - iter 1325/2650 - loss 0.12312273 - samples/sec: 539.24 -2019-08-20 03:58:44,359 epoch 133 - iter 1590/2650 - loss 0.12222696 - samples/sec: 585.97 -2019-08-20 03:58:58,479 epoch 133 - iter 1855/2650 - loss 0.12120788 - samples/sec: 604.91 -2019-08-20 03:59:12,860 epoch 133 - iter 2120/2650 - loss 0.12099143 - samples/sec: 593.91 -2019-08-20 03:59:27,414 epoch 133 - iter 2385/2650 - loss 0.12106141 - samples/sec: 586.81 -2019-08-20 03:59:42,639 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:59:42,640 EPOCH 133 done: loss 0.1211 - lr 0.0500 -2019-08-20 03:59:42,640 BAD EPOCHS (no improvement): 0 -2019-08-20 03:59:42,640 ---------------------------------------------------------------------------------------------------- -2019-08-20 03:59:42,693 epoch 134 - iter 0/2650 - loss 0.08149858 - samples/sec: 175451.47 -2019-08-20 03:59:58,194 epoch 134 - iter 265/2650 - loss 0.11989706 - samples/sec: 551.22 -2019-08-20 04:00:13,697 epoch 134 - iter 530/2650 - loss 0.12058682 - samples/sec: 551.18 -2019-08-20 04:00:29,146 epoch 134 - iter 795/2650 - loss 0.11971547 - samples/sec: 553.05 -2019-08-20 04:00:44,442 epoch 134 - iter 1060/2650 - loss 0.11820764 - samples/sec: 558.67 -2019-08-20 04:01:00,116 epoch 134 - iter 1325/2650 - loss 0.11866518 - samples/sec: 545.30 -2019-08-20 04:01:15,803 epoch 134 - iter 1590/2650 - loss 0.11891566 - samples/sec: 544.80 -2019-08-20 04:01:31,411 epoch 134 - iter 1855/2650 - loss 0.11882659 - samples/sec: 547.27 -2019-08-20 04:01:47,238 epoch 134 - iter 2120/2650 - loss 0.11905945 - samples/sec: 540.05 -2019-08-20 04:02:03,277 epoch 134 - iter 2385/2650 - loss 0.11919367 - samples/sec: 532.69 -2019-08-20 04:02:18,922 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:02:18,922 EPOCH 134 done: loss 0.1195 - lr 0.0500 -2019-08-20 04:02:18,922 BAD EPOCHS (no improvement): 0 -2019-08-20 04:02:18,923 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:02:18,995 epoch 135 - iter 0/2650 - loss 0.14522125 - samples/sec: 128347.18 -2019-08-20 04:02:34,485 epoch 135 - iter 265/2650 - loss 0.11383425 - samples/sec: 551.32 -2019-08-20 04:02:49,959 epoch 135 - iter 530/2650 - loss 0.11522776 - samples/sec: 552.27 -2019-08-20 04:03:05,722 epoch 135 - iter 795/2650 - loss 0.11853371 - samples/sec: 541.73 -2019-08-20 04:03:21,443 epoch 135 - iter 1060/2650 - loss 0.11960681 - samples/sec: 543.33 -2019-08-20 04:03:37,119 epoch 135 - iter 1325/2650 - loss 0.11948472 - samples/sec: 545.00 -2019-08-20 04:03:52,744 epoch 135 - iter 1590/2650 - loss 0.11939175 - samples/sec: 547.00 -2019-08-20 04:04:08,244 epoch 135 - iter 1855/2650 - loss 0.11952622 - samples/sec: 551.23 -2019-08-20 04:04:24,100 epoch 135 - iter 2120/2650 - loss 0.11945015 - samples/sec: 538.89 -2019-08-20 04:04:39,685 epoch 135 - iter 2385/2650 - loss 0.11951413 - samples/sec: 548.25 -2019-08-20 04:04:55,032 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:04:55,033 EPOCH 135 done: loss 0.1196 - lr 0.0500 -2019-08-20 04:04:55,033 BAD EPOCHS (no improvement): 1 -2019-08-20 04:04:55,034 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:04:55,088 epoch 136 - iter 0/2650 - loss 0.07060177 - samples/sec: 165536.63 -2019-08-20 04:05:10,669 epoch 136 - iter 265/2650 - loss 0.11724176 - samples/sec: 548.34 -2019-08-20 04:05:26,556 epoch 136 - iter 530/2650 - loss 0.11904280 - samples/sec: 537.82 -2019-08-20 04:05:42,353 epoch 136 - iter 795/2650 - loss 0.11761869 - samples/sec: 540.62 -2019-08-20 04:05:57,745 epoch 136 - iter 1060/2650 - loss 0.11669615 - samples/sec: 555.00 -2019-08-20 04:06:13,342 epoch 136 - iter 1325/2650 - loss 0.11687947 - samples/sec: 548.22 -2019-08-20 04:06:29,023 epoch 136 - iter 1590/2650 - loss 0.11687204 - samples/sec: 544.92 -2019-08-20 04:06:44,436 epoch 136 - iter 1855/2650 - loss 0.11723960 - samples/sec: 554.44 -2019-08-20 04:07:00,163 epoch 136 - iter 2120/2650 - loss 0.11799878 - samples/sec: 543.22 -2019-08-20 04:07:15,841 epoch 136 - iter 2385/2650 - loss 0.11781072 - samples/sec: 544.95 -2019-08-20 04:07:31,248 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:07:31,249 EPOCH 136 done: loss 0.1179 - lr 0.0500 -2019-08-20 04:07:31,249 BAD EPOCHS (no improvement): 0 -2019-08-20 04:07:31,250 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:07:31,305 epoch 137 - iter 0/2650 - loss 0.07891906 - samples/sec: 167851.34 -2019-08-20 04:07:46,733 epoch 137 - iter 265/2650 - loss 0.11914431 - samples/sec: 553.72 -2019-08-20 04:08:02,385 epoch 137 - iter 530/2650 - loss 0.12010540 - samples/sec: 545.86 -2019-08-20 04:08:17,969 epoch 137 - iter 795/2650 - loss 0.11957631 - samples/sec: 548.04 -2019-08-20 04:08:33,574 epoch 137 - iter 1060/2650 - loss 0.11806271 - samples/sec: 547.39 -2019-08-20 04:08:49,261 epoch 137 - iter 1325/2650 - loss 0.11868114 - samples/sec: 544.98 -2019-08-20 04:09:05,028 epoch 137 - iter 1590/2650 - loss 0.11828497 - samples/sec: 541.69 -2019-08-20 04:09:20,529 epoch 137 - iter 1855/2650 - loss 0.11830552 - samples/sec: 551.16 -2019-08-20 04:09:36,109 epoch 137 - iter 2120/2650 - loss 0.11856906 - samples/sec: 548.34 -2019-08-20 04:09:51,993 epoch 137 - iter 2385/2650 - loss 0.11820849 - samples/sec: 537.87 -2019-08-20 04:10:07,671 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:10:07,671 EPOCH 137 done: loss 0.1192 - lr 0.0500 -2019-08-20 04:10:07,671 BAD EPOCHS (no improvement): 1 -2019-08-20 04:10:07,672 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:10:07,736 epoch 138 - iter 0/2650 - loss 0.09969399 - samples/sec: 143628.37 -2019-08-20 04:10:23,257 epoch 138 - iter 265/2650 - loss 0.11847470 - samples/sec: 550.42 -2019-08-20 04:10:38,435 epoch 138 - iter 530/2650 - loss 0.11810687 - samples/sec: 562.90 -2019-08-20 04:10:54,325 epoch 138 - iter 795/2650 - loss 0.11973381 - samples/sec: 537.60 -2019-08-20 04:11:09,893 epoch 138 - iter 1060/2650 - loss 0.11968213 - samples/sec: 548.89 -2019-08-20 04:11:25,657 epoch 138 - iter 1325/2650 - loss 0.11945503 - samples/sec: 542.24 -2019-08-20 04:11:41,151 epoch 138 - iter 1590/2650 - loss 0.11942868 - samples/sec: 551.67 -2019-08-20 04:11:56,857 epoch 138 - iter 1855/2650 - loss 0.11967264 - samples/sec: 543.98 -2019-08-20 04:12:12,589 epoch 138 - iter 2120/2650 - loss 0.11897517 - samples/sec: 542.91 -2019-08-20 04:12:28,267 epoch 138 - iter 2385/2650 - loss 0.11915967 - samples/sec: 544.79 -2019-08-20 04:12:43,888 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:12:43,889 EPOCH 138 done: loss 0.1193 - lr 0.0500 -2019-08-20 04:12:43,889 BAD EPOCHS (no improvement): 2 -2019-08-20 04:12:43,890 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:12:43,947 epoch 139 - iter 0/2650 - loss 0.07974821 - samples/sec: 161900.96 -2019-08-20 04:12:59,372 epoch 139 - iter 265/2650 - loss 0.12207165 - samples/sec: 554.00 -2019-08-20 04:13:14,986 epoch 139 - iter 530/2650 - loss 0.12095788 - samples/sec: 547.58 -2019-08-20 04:13:30,879 epoch 139 - iter 795/2650 - loss 0.11907055 - samples/sec: 537.58 -2019-08-20 04:13:46,572 epoch 139 - iter 1060/2650 - loss 0.11833088 - samples/sec: 544.25 -2019-08-20 04:14:02,006 epoch 139 - iter 1325/2650 - loss 0.11804197 - samples/sec: 553.84 -2019-08-20 04:14:17,597 epoch 139 - iter 1590/2650 - loss 0.11803005 - samples/sec: 547.89 -2019-08-20 04:14:33,251 epoch 139 - iter 1855/2650 - loss 0.11813464 - samples/sec: 545.48 -2019-08-20 04:14:47,828 epoch 139 - iter 2120/2650 - loss 0.11808494 - samples/sec: 586.02 -2019-08-20 04:15:02,224 epoch 139 - iter 2385/2650 - loss 0.11779484 - samples/sec: 593.02 -2019-08-20 04:15:16,652 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:15:16,653 EPOCH 139 done: loss 0.1177 - lr 0.0500 -2019-08-20 04:15:16,653 BAD EPOCHS (no improvement): 0 -2019-08-20 04:15:16,653 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:15:16,714 epoch 140 - iter 0/2650 - loss 0.12820213 - samples/sec: 145312.47 -2019-08-20 04:15:31,182 epoch 140 - iter 265/2650 - loss 0.11909616 - samples/sec: 590.20 -2019-08-20 04:15:45,584 epoch 140 - iter 530/2650 - loss 0.12087278 - samples/sec: 592.94 -2019-08-20 04:15:59,977 epoch 140 - iter 795/2650 - loss 0.11953532 - samples/sec: 593.37 -2019-08-20 04:16:15,704 epoch 140 - iter 1060/2650 - loss 0.12026357 - samples/sec: 543.43 -2019-08-20 04:16:31,185 epoch 140 - iter 1325/2650 - loss 0.12042194 - samples/sec: 552.04 -2019-08-20 04:16:46,704 epoch 140 - iter 1590/2650 - loss 0.11952595 - samples/sec: 550.68 -2019-08-20 04:17:02,238 epoch 140 - iter 1855/2650 - loss 0.11850102 - samples/sec: 549.88 -2019-08-20 04:17:18,233 epoch 140 - iter 2120/2650 - loss 0.11760619 - samples/sec: 533.86 -2019-08-20 04:17:33,745 epoch 140 - iter 2385/2650 - loss 0.11755734 - samples/sec: 550.93 -2019-08-20 04:17:49,085 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:17:49,086 EPOCH 140 done: loss 0.1177 - lr 0.0500 -2019-08-20 04:17:49,086 BAD EPOCHS (no improvement): 0 -2019-08-20 04:17:49,086 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:17:49,141 epoch 141 - iter 0/2650 - loss 0.13112056 - samples/sec: 171734.20 -2019-08-20 04:18:04,704 epoch 141 - iter 265/2650 - loss 0.11593156 - samples/sec: 548.91 -2019-08-20 04:18:20,055 epoch 141 - iter 530/2650 - loss 0.11842291 - samples/sec: 556.66 -2019-08-20 04:18:35,566 epoch 141 - iter 795/2650 - loss 0.11928575 - samples/sec: 551.01 -2019-08-20 04:18:51,592 epoch 141 - iter 1060/2650 - loss 0.11815213 - samples/sec: 532.74 -2019-08-20 04:19:07,296 epoch 141 - iter 1325/2650 - loss 0.11829916 - samples/sec: 544.03 -2019-08-20 04:19:22,830 epoch 141 - iter 1590/2650 - loss 0.11741599 - samples/sec: 550.11 -2019-08-20 04:19:38,344 epoch 141 - iter 1855/2650 - loss 0.11766766 - samples/sec: 550.81 -2019-08-20 04:19:54,245 epoch 141 - iter 2120/2650 - loss 0.11789509 - samples/sec: 537.00 -2019-08-20 04:20:09,739 epoch 141 - iter 2385/2650 - loss 0.11753828 - samples/sec: 551.48 -2019-08-20 04:20:25,389 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:20:25,390 EPOCH 141 done: loss 0.1176 - lr 0.0500 -2019-08-20 04:20:25,390 BAD EPOCHS (no improvement): 0 -2019-08-20 04:20:25,391 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:20:25,462 epoch 142 - iter 0/2650 - loss 0.10420612 - samples/sec: 124436.98 -2019-08-20 04:20:40,996 epoch 142 - iter 265/2650 - loss 0.11374600 - samples/sec: 550.14 -2019-08-20 04:20:56,479 epoch 142 - iter 530/2650 - loss 0.11441269 - samples/sec: 552.36 -2019-08-20 04:21:12,450 epoch 142 - iter 795/2650 - loss 0.11547999 - samples/sec: 534.85 -2019-08-20 04:21:28,127 epoch 142 - iter 1060/2650 - loss 0.11581499 - samples/sec: 545.41 -2019-08-20 04:21:43,685 epoch 142 - iter 1325/2650 - loss 0.11696258 - samples/sec: 549.31 -2019-08-20 04:21:59,145 epoch 142 - iter 1590/2650 - loss 0.11767194 - samples/sec: 552.75 -2019-08-20 04:22:14,710 epoch 142 - iter 1855/2650 - loss 0.11724295 - samples/sec: 548.86 -2019-08-20 04:22:30,432 epoch 142 - iter 2120/2650 - loss 0.11751346 - samples/sec: 543.33 -2019-08-20 04:22:46,088 epoch 142 - iter 2385/2650 - loss 0.11757038 - samples/sec: 545.64 -2019-08-20 04:23:01,722 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:23:01,723 EPOCH 142 done: loss 0.1174 - lr 0.0500 -2019-08-20 04:23:01,723 BAD EPOCHS (no improvement): 0 -2019-08-20 04:23:01,724 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:23:01,783 epoch 143 - iter 0/2650 - loss 0.09394922 - samples/sec: 149271.00 -2019-08-20 04:23:17,106 epoch 143 - iter 265/2650 - loss 0.11594735 - samples/sec: 557.75 -2019-08-20 04:23:32,670 epoch 143 - iter 530/2650 - loss 0.11836398 - samples/sec: 548.91 -2019-08-20 04:23:48,285 epoch 143 - iter 795/2650 - loss 0.11712885 - samples/sec: 547.05 -2019-08-20 04:24:04,010 epoch 143 - iter 1060/2650 - loss 0.11722537 - samples/sec: 543.07 -2019-08-20 04:24:19,841 epoch 143 - iter 1325/2650 - loss 0.11623272 - samples/sec: 539.82 -2019-08-20 04:24:35,281 epoch 143 - iter 1590/2650 - loss 0.11614576 - samples/sec: 553.45 -2019-08-20 04:24:50,724 epoch 143 - iter 1855/2650 - loss 0.11593446 - samples/sec: 553.42 -2019-08-20 04:25:06,379 epoch 143 - iter 2120/2650 - loss 0.11638519 - samples/sec: 545.82 -2019-08-20 04:25:22,225 epoch 143 - iter 2385/2650 - loss 0.11658144 - samples/sec: 539.14 -2019-08-20 04:25:37,950 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:25:37,951 EPOCH 143 done: loss 0.1160 - lr 0.0500 -2019-08-20 04:25:37,951 BAD EPOCHS (no improvement): 0 -2019-08-20 04:25:37,952 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:25:38,011 epoch 144 - iter 0/2650 - loss 0.09100603 - samples/sec: 155628.72 -2019-08-20 04:25:53,789 epoch 144 - iter 265/2650 - loss 0.11690280 - samples/sec: 541.59 -2019-08-20 04:26:09,246 epoch 144 - iter 530/2650 - loss 0.11499566 - samples/sec: 552.81 -2019-08-20 04:26:24,654 epoch 144 - iter 795/2650 - loss 0.11752711 - samples/sec: 554.52 -2019-08-20 04:26:40,564 epoch 144 - iter 1060/2650 - loss 0.11748084 - samples/sec: 536.92 -2019-08-20 04:26:55,990 epoch 144 - iter 1325/2650 - loss 0.11639372 - samples/sec: 554.07 -2019-08-20 04:27:11,454 epoch 144 - iter 1590/2650 - loss 0.11602075 - samples/sec: 552.70 -2019-08-20 04:27:26,741 epoch 144 - iter 1855/2650 - loss 0.11532472 - samples/sec: 559.06 -2019-08-20 04:27:42,682 epoch 144 - iter 2120/2650 - loss 0.11516215 - samples/sec: 535.76 -2019-08-20 04:27:58,509 epoch 144 - iter 2385/2650 - loss 0.11492226 - samples/sec: 539.84 -2019-08-20 04:28:14,153 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:28:14,154 EPOCH 144 done: loss 0.1153 - lr 0.0500 -2019-08-20 04:28:14,154 BAD EPOCHS (no improvement): 0 -2019-08-20 04:28:14,155 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:28:14,203 epoch 145 - iter 0/2650 - loss 0.06110338 - samples/sec: 187091.08 -2019-08-20 04:28:29,970 epoch 145 - iter 265/2650 - loss 0.11470985 - samples/sec: 541.89 -2019-08-20 04:28:45,446 epoch 145 - iter 530/2650 - loss 0.11814433 - samples/sec: 552.15 -2019-08-20 04:29:01,208 epoch 145 - iter 795/2650 - loss 0.11577664 - samples/sec: 541.95 -2019-08-20 04:29:16,706 epoch 145 - iter 1060/2650 - loss 0.11643099 - samples/sec: 551.05 -2019-08-20 04:29:32,420 epoch 145 - iter 1325/2650 - loss 0.11647188 - samples/sec: 543.82 -2019-08-20 04:29:48,220 epoch 145 - iter 1590/2650 - loss 0.11717816 - samples/sec: 540.72 -2019-08-20 04:30:03,774 epoch 145 - iter 1855/2650 - loss 0.11713044 - samples/sec: 549.37 -2019-08-20 04:30:19,386 epoch 145 - iter 2120/2650 - loss 0.11708520 - samples/sec: 547.34 -2019-08-20 04:30:34,966 epoch 145 - iter 2385/2650 - loss 0.11662757 - samples/sec: 548.35 -2019-08-20 04:30:50,472 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:30:50,473 EPOCH 145 done: loss 0.1165 - lr 0.0500 -2019-08-20 04:30:50,473 BAD EPOCHS (no improvement): 1 -2019-08-20 04:30:50,474 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:30:50,524 epoch 146 - iter 0/2650 - loss 0.07088616 - samples/sec: 189388.34 -2019-08-20 04:31:06,159 epoch 146 - iter 265/2650 - loss 0.11635891 - samples/sec: 546.50 -2019-08-20 04:31:21,609 epoch 146 - iter 530/2650 - loss 0.11402409 - samples/sec: 553.04 -2019-08-20 04:31:37,104 epoch 146 - iter 795/2650 - loss 0.11531276 - samples/sec: 551.39 -2019-08-20 04:31:52,769 epoch 146 - iter 1060/2650 - loss 0.11614334 - samples/sec: 545.36 -2019-08-20 04:32:08,470 epoch 146 - iter 1325/2650 - loss 0.11569153 - samples/sec: 544.26 -2019-08-20 04:32:24,286 epoch 146 - iter 1590/2650 - loss 0.11580147 - samples/sec: 540.26 -2019-08-20 04:32:39,899 epoch 146 - iter 1855/2650 - loss 0.11596814 - samples/sec: 547.31 -2019-08-20 04:32:55,352 epoch 146 - iter 2120/2650 - loss 0.11572094 - samples/sec: 552.93 -2019-08-20 04:33:11,071 epoch 146 - iter 2385/2650 - loss 0.11561025 - samples/sec: 543.33 -2019-08-20 04:33:26,738 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:33:26,739 EPOCH 146 done: loss 0.1154 - lr 0.0500 -2019-08-20 04:33:26,739 BAD EPOCHS (no improvement): 2 -2019-08-20 04:33:26,740 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:33:26,797 epoch 147 - iter 0/2650 - loss 0.10207205 - samples/sec: 164091.71 -2019-08-20 04:33:42,207 epoch 147 - iter 265/2650 - loss 0.11431030 - samples/sec: 554.66 -2019-08-20 04:33:57,669 epoch 147 - iter 530/2650 - loss 0.11465246 - samples/sec: 552.66 -2019-08-20 04:34:13,188 epoch 147 - iter 795/2650 - loss 0.11408833 - samples/sec: 550.48 -2019-08-20 04:34:28,768 epoch 147 - iter 1060/2650 - loss 0.11423864 - samples/sec: 548.08 -2019-08-20 04:34:44,296 epoch 147 - iter 1325/2650 - loss 0.11459540 - samples/sec: 550.41 -2019-08-20 04:35:00,145 epoch 147 - iter 1590/2650 - loss 0.11556562 - samples/sec: 539.06 -2019-08-20 04:35:15,703 epoch 147 - iter 1855/2650 - loss 0.11518452 - samples/sec: 549.28 -2019-08-20 04:35:31,350 epoch 147 - iter 2120/2650 - loss 0.11502520 - samples/sec: 545.87 -2019-08-20 04:35:46,891 epoch 147 - iter 2385/2650 - loss 0.11526756 - samples/sec: 549.63 -2019-08-20 04:36:02,630 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:36:02,631 EPOCH 147 done: loss 0.1155 - lr 0.0500 -2019-08-20 04:36:02,631 BAD EPOCHS (no improvement): 3 -2019-08-20 04:36:02,632 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:36:02,685 epoch 148 - iter 0/2650 - loss 0.07507715 - samples/sec: 175193.94 -2019-08-20 04:36:18,220 epoch 148 - iter 265/2650 - loss 0.11888475 - samples/sec: 550.04 -2019-08-20 04:36:33,445 epoch 148 - iter 530/2650 - loss 0.11471511 - samples/sec: 561.38 -2019-08-20 04:36:49,129 epoch 148 - iter 795/2650 - loss 0.11646606 - samples/sec: 544.61 -2019-08-20 04:37:04,846 epoch 148 - iter 1060/2650 - loss 0.11512168 - samples/sec: 543.39 -2019-08-20 04:37:20,599 epoch 148 - iter 1325/2650 - loss 0.11577714 - samples/sec: 542.34 -2019-08-20 04:37:36,182 epoch 148 - iter 1590/2650 - loss 0.11508591 - samples/sec: 548.06 -2019-08-20 04:37:51,805 epoch 148 - iter 1855/2650 - loss 0.11516156 - samples/sec: 546.96 -2019-08-20 04:38:07,387 epoch 148 - iter 2120/2650 - loss 0.11549227 - samples/sec: 548.22 -2019-08-20 04:38:23,208 epoch 148 - iter 2385/2650 - loss 0.11558959 - samples/sec: 540.12 -2019-08-20 04:38:38,357 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:38:38,357 EPOCH 148 done: loss 0.1152 - lr 0.0500 -2019-08-20 04:38:38,358 BAD EPOCHS (no improvement): 0 -2019-08-20 04:38:38,358 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:38:38,408 epoch 149 - iter 0/2650 - loss 0.26436725 - samples/sec: 180982.15 -2019-08-20 04:38:53,273 epoch 149 - iter 265/2650 - loss 0.11497009 - samples/sec: 574.78 -2019-08-20 04:39:08,513 epoch 149 - iter 530/2650 - loss 0.11763896 - samples/sec: 560.78 -2019-08-20 04:39:24,137 epoch 149 - iter 795/2650 - loss 0.11722557 - samples/sec: 546.67 -2019-08-20 04:39:39,766 epoch 149 - iter 1060/2650 - loss 0.11688167 - samples/sec: 546.37 -2019-08-20 04:39:55,535 epoch 149 - iter 1325/2650 - loss 0.11565059 - samples/sec: 541.73 -2019-08-20 04:40:11,315 epoch 149 - iter 1590/2650 - loss 0.11586694 - samples/sec: 541.22 -2019-08-20 04:40:26,945 epoch 149 - iter 1855/2650 - loss 0.11590683 - samples/sec: 546.63 -2019-08-20 04:40:42,708 epoch 149 - iter 2120/2650 - loss 0.11614393 - samples/sec: 541.95 -2019-08-20 04:40:58,296 epoch 149 - iter 2385/2650 - loss 0.11621696 - samples/sec: 547.96 -2019-08-20 04:41:13,903 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:41:13,904 EPOCH 149 done: loss 0.1163 - lr 0.0500 -2019-08-20 04:41:13,904 BAD EPOCHS (no improvement): 1 -2019-08-20 04:41:13,905 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:41:13,963 epoch 150 - iter 0/2650 - loss 0.12969644 - samples/sec: 161709.58 -2019-08-20 04:41:29,472 epoch 150 - iter 265/2650 - loss 0.11572828 - samples/sec: 551.02 -2019-08-20 04:41:45,193 epoch 150 - iter 530/2650 - loss 0.11539270 - samples/sec: 543.44 -2019-08-20 04:42:00,542 epoch 150 - iter 795/2650 - loss 0.11501968 - samples/sec: 556.68 -2019-08-20 04:42:16,020 epoch 150 - iter 1060/2650 - loss 0.11489605 - samples/sec: 551.84 -2019-08-20 04:42:31,839 epoch 150 - iter 1325/2650 - loss 0.11423076 - samples/sec: 539.98 -2019-08-20 04:42:47,196 epoch 150 - iter 1590/2650 - loss 0.11422642 - samples/sec: 556.90 -2019-08-20 04:43:02,776 epoch 150 - iter 1855/2650 - loss 0.11477540 - samples/sec: 548.52 -2019-08-20 04:43:17,164 epoch 150 - iter 2120/2650 - loss 0.11494124 - samples/sec: 593.73 -2019-08-20 04:43:31,765 epoch 150 - iter 2385/2650 - loss 0.11476158 - samples/sec: 584.84 -2019-08-20 04:43:46,216 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:43:46,217 EPOCH 150 done: loss 0.1152 - lr 0.0500 -2019-08-20 04:43:46,217 BAD EPOCHS (no improvement): 0 -2019-08-20 04:43:50,412 ---------------------------------------------------------------------------------------------------- -2019-08-20 04:43:50,412 Testing using best model ... -2019-08-20 05:24:19,249 0.9754 0.9754 0.9754 -2019-08-20 05:24:19,250 -MICRO_AVG: acc 0.952 - f1-score 0.9754 -MACRO_AVG: acc 0.4707 - f1-score 0.5170271193415626 -_ tp: 141264 - fp: 769 - fn: 1547 - tn: 141264 - precision: 0.9946 - recall: 0.9892 - accuracy: 0.9839 - f1-score: 0.9919 -abandon.01 tp: 8 - fp: 0 - fn: 0 - tn: 8 - precision: 1.0000 - recall: 1.0000 - accuracy: 1.0000 - f1-score: 1.0000 -abate.01 tp: 0 - fp: 0 - fn: 1 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -abduct.01 tp: 0 - fp: 0 - fn: 2 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -abide.01 tp: 2 - fp: 1 - fn: 0 - tn: 2 - precision: 0.6667 - recall: 1.0000 - accuracy: 0.6667 - f1-score: 0.8000 -abort.01 tp: 5 - fp: 0 - fn: 0 - tn: 5 - precision: 1.0000 - recall: 1.0000 - accuracy: 1.0000 - f1-score: 1.0000 -abound.01 tp: 0 - fp: 0 - fn: 2 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -absent.01 tp: 3 - fp: 0 - fn: 0 - tn: 3 - precision: 1.0000 - recall: 1.0000 - accuracy: 1.0000 - f1-score: 1.0000 -absorb.01 tp: 1 - fp: 1 - fn: 0 - tn: 1 - precision: 0.5000 - recall: 1.0000 - accuracy: 0.5000 - f1-score: 0.6667 -abuse.01 tp: 6 - fp: 14 - fn: 0 - tn: 6 - precision: 0.3000 - recall: 1.0000 - accuracy: 0.3000 - f1-score: 0.4615 -abuse.02 tp: 0 - fp: 1 - fn: 1 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -abut.01 tp: 0 - fp: 0 - fn: 1 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -accelerate.01 tp: 8 - fp: 0 - fn: 0 - tn: 8 - precision: 1.0000 - recall: 1.0000 - accuracy: 1.0000 - f1-score: 1.0000 -accept.01 tp: 34 - fp: 3 - fn: 1 - tn: 34 - precision: 0.9189 - recall: 0.9714 - accuracy: 0.8947 - f1-score: 0.9444 -access.01 tp: 4 - fp: 0 - fn: 1 - tn: 4 - precision: 1.0000 - recall: 0.8000 - accuracy: 0.8000 - f1-score: 0.8889 -accession.01 tp: 0 - fp: 0 - fn: 1 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -accommodate.01 tp: 1 - fp: 1 - fn: 0 - tn: 1 - precision: 0.5000 - recall: 1.0000 - accuracy: 0.5000 - f1-score: 0.6667 -accompany.01 tp: 2 - fp: 0 - fn: 0 - tn: 2 - precision: 1.0000 - recall: 1.0000 - accuracy: 1.0000 - f1-score: 1.0000 -accomplish.01 tp: 6 - fp: 0 - fn: 0 - tn: 6 - precision: 1.0000 - recall: 1.0000 - accuracy: 1.0000 - f1-score: 1.0000 -accord.02 tp: 6 - fp: 0 - fn: 0 - tn: 6 - precision: 1.0000 - recall: 1.0000 - accuracy: 1.0000 - f1-score: 1.0000 -account.01 tp: 26 - fp: 1 - fn: 11 - tn: 26 - precision: 0.9630 - recall: 0.7027 - accuracy: 0.6842 - f1-score: 0.8125 -accumulate.01 tp: 8 - fp: 0 - fn: 1 - tn: 8 - precision: 1.0000 - recall: 0.8889 - accuracy: 0.8889 - f1-score: 0.9412 -accuse.01 tp: 7 - fp: 0 - fn: 0 - tn: 7 - precision: 1.0000 - recall: 1.0000 - accuracy: 1.0000 - f1-score: 1.0000 -achieve.01 tp: 18 - fp: 0 - fn: 2 - tn: 18 - precision: 1.0000 - recall: 0.9000 - accuracy: 0.9000 - f1-score: 0.9474 -acknowledge.01 tp: 11 - fp: 5 - fn: 0 - tn: 11 - precision: 0.6875 - recall: 1.0000 - accuracy: 0.6875 - f1-score: 0.8148 -acquiesce.01 tp: 0 - fp: 0 - fn: 1 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -acquire.01 tp: 14 - fp: 1 - fn: 0 - tn: 14 - precision: 0.9333 - recall: 1.0000 - accuracy: 0.9333 - f1-score: 0.9655 -act.01 tp: 3 - fp: 3 - fn: 1 - tn: 3 - precision: 0.5000 - recall: 0.7500 - accuracy: 0.4286 - f1-score: 0.6000 -act.02 tp: 18 - fp: 12 - fn: 2 - tn: 18 - precision: 0.6000 - recall: 0.9000 - accuracy: 0.5625 - f1-score: 0.7200 -activate.01 tp: 0 - fp: 0 - fn: 8 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -adapt.01 tp: 1 - fp: 0 - fn: 0 - tn: 1 - precision: 1.0000 - recall: 1.0000 - accuracy: 1.0000 - f1-score: 1.0000 -add.01 tp: 19 - fp: 0 - fn: 0 - tn: 19 - precision: 1.0000 - recall: 1.0000 - accuracy: 1.0000 - f1-score: 1.0000 -add.02 tp: 36 - fp: 12 - fn: 0 - tn: 36 - precision: 0.7500 - recall: 1.0000 - accuracy: 0.7500 - f1-score: 0.8571 -add.03 tp: 0 - fp: 1 - fn: 4 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -add_up.04 tp: 0 - fp: 0 - fn: 1 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -address.01 tp: 0 - fp: 0 - fn: 2 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -address.02 tp: 6 - fp: 2 - fn: 0 - tn: 6 - precision: 0.7500 - recall: 1.0000 - accuracy: 0.7500 - f1-score: 0.8571 -address.03 tp: 2 - fp: 0 - fn: 0 - tn: 2 - precision: 1.0000 - recall: 1.0000 - accuracy: 1.0000 - f1-score: 1.0000 -adhere.02 tp: 1 - fp: 1 - fn: 0 - tn: 1 - precision: 0.5000 - recall: 1.0000 - accuracy: 0.5000 - f1-score: 0.6667 -adjust.01 tp: 11 - fp: 2 - fn: 0 - tn: 11 - precision: 0.8462 - recall: 1.0000 - accuracy: 0.8462 - f1-score: 0.9167 -administer.01 tp: 1 - fp: 0 - fn: 0 - tn: 1 - precision: 1.0000 - recall: 1.0000 - accuracy: 1.0000 - f1-score: 1.0000 -admire.01 tp: 1 - fp: 4 - fn: 0 - tn: 1 - precision: 0.2000 - recall: 1.0000 - accuracy: 0.2000 - f1-score: 0.3333 -admit.01 tp: 4 - fp: 1 - fn: 0 - tn: 4 - precision: 0.8000 - recall: 1.0000 - accuracy: 0.8000 - f1-score: 0.8889 -admit.02 tp: 2 - fp: 0 - fn: 1 - tn: 2 - precision: 1.0000 - recall: 0.6667 - accuracy: 0.6667 - f1-score: 0.8000 -admonish.02 tp: 0 - fp: 0 - fn: 1 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - 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-wheel.01 tp: 0 - fp: 0 - fn: 1 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -whip.01 tp: 0 - fp: 0 - fn: 2 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -whip_out.02 tp: 0 - fp: 0 - fn: 1 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -widen.01 tp: 2 - fp: 2 - fn: 0 - tn: 2 - precision: 0.5000 - recall: 1.0000 - accuracy: 0.5000 - f1-score: 0.6667 -wield.01 tp: 2 - fp: 1 - fn: 0 - tn: 2 - precision: 0.6667 - recall: 1.0000 - accuracy: 0.6667 - f1-score: 0.8000 -will.02 tp: 0 - fp: 0 - fn: 1 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -win.01 tp: 23 - fp: 3 - fn: 0 - tn: 23 - precision: 0.8846 - recall: 1.0000 - accuracy: 0.8846 - f1-score: 0.9388 -win_over.02 tp: 0 - fp: 0 - fn: 1 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -wince.01 tp: 0 - fp: 0 - fn: 1 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -wind_down.04 tp: 0 - fp: 0 - fn: 2 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -wind_up.02 tp: 1 - fp: 0 - fn: 0 - tn: 1 - precision: 1.0000 - recall: 1.0000 - accuracy: 1.0000 - f1-score: 1.0000 -wipe.01 tp: 0 - fp: 1 - fn: 0 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -wipe_out.02 tp: 0 - fp: 1 - fn: 0 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -wire.01 tp: 0 - fp: 0 - fn: 1 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -wish.01 tp: 15 - fp: 3 - fn: 0 - tn: 15 - precision: 0.8333 - recall: 1.0000 - accuracy: 0.8333 - f1-score: 0.9091 -withdraw.01 tp: 8 - fp: 4 - fn: 0 - tn: 8 - precision: 0.6667 - recall: 1.0000 - accuracy: 0.6667 - f1-score: 0.8000 -withdrawal.02 tp: 0 - fp: 0 - fn: 1 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -withhold.01 tp: 4 - fp: 0 - fn: 1 - tn: 4 - precision: 1.0000 - recall: 0.8000 - accuracy: 0.8000 - f1-score: 0.8889 -withstand.01 tp: 1 - fp: 0 - fn: 0 - tn: 1 - precision: 1.0000 - recall: 1.0000 - accuracy: 1.0000 - f1-score: 1.0000 -witness.01 tp: 1 - fp: 0 - fn: 0 - tn: 1 - precision: 1.0000 - recall: 1.0000 - accuracy: 1.0000 - f1-score: 1.0000 -wonder.01 tp: 10 - fp: 0 - fn: 0 - tn: 10 - precision: 1.0000 - recall: 1.0000 - accuracy: 1.0000 - f1-score: 1.0000 -woo.01 tp: 0 - fp: 0 - fn: 1 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -work.01 tp: 107 - fp: 28 - fn: 6 - tn: 107 - precision: 0.7926 - recall: 0.9469 - accuracy: 0.7589 - f1-score: 0.8629 -work.06 tp: 0 - fp: 0 - fn: 1 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -work.07 tp: 0 - fp: 0 - fn: 1 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -work.09 tp: 7 - fp: 1 - fn: 8 - tn: 7 - precision: 0.8750 - recall: 0.4667 - accuracy: 0.4375 - f1-score: 0.6087 -work.13 tp: 0 - fp: 0 - fn: 1 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -work_out.02 tp: 3 - fp: 1 - fn: 0 - tn: 3 - precision: 0.7500 - recall: 1.0000 - accuracy: 0.7500 - f1-score: 0.8571 -work_out.03 tp: 0 - fp: 0 - fn: 1 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -worry.01 tp: 3 - fp: 1 - fn: 2 - tn: 3 - precision: 0.7500 - recall: 0.6000 - accuracy: 0.5000 - f1-score: 0.6667 -worry.02 tp: 6 - fp: 4 - fn: 0 - tn: 6 - precision: 0.6000 - recall: 1.0000 - accuracy: 0.6000 - f1-score: 0.7500 -worsen.01 tp: 2 - fp: 0 - fn: 0 - tn: 2 - precision: 1.0000 - recall: 1.0000 - accuracy: 1.0000 - f1-score: 1.0000 -worship.01 tp: 11 - fp: 2 - fn: 0 - tn: 11 - precision: 0.8462 - recall: 1.0000 - accuracy: 0.8462 - f1-score: 0.9167 -wound.01 tp: 6 - fp: 0 - fn: 0 - tn: 6 - precision: 1.0000 - recall: 1.0000 - accuracy: 1.0000 - f1-score: 1.0000 -wrap.01 tp: 2 - fp: 1 - fn: 1 - tn: 2 - precision: 0.6667 - recall: 0.6667 - accuracy: 0.5000 - f1-score: 0.6667 -wrap_up.02 tp: 2 - fp: 4 - fn: 0 - tn: 2 - precision: 0.3333 - recall: 1.0000 - accuracy: 0.3333 - f1-score: 0.5000 -wreak.01 tp: 0 - fp: 0 - fn: 1 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -wreck.01 tp: 1 - fp: 1 - fn: 0 - tn: 1 - precision: 0.5000 - recall: 1.0000 - accuracy: 0.5000 - f1-score: 0.6667 -wrestle.01 tp: 0 - fp: 0 - fn: 2 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -write.01 tp: 62 - fp: 6 - fn: 0 - tn: 62 - precision: 0.9118 - recall: 1.0000 - accuracy: 0.9118 - f1-score: 0.9539 -write_down.03 tp: 1 - fp: 1 - fn: 0 - tn: 1 - precision: 0.5000 - recall: 1.0000 - accuracy: 0.5000 - f1-score: 0.6667 -write_up.07 tp: 0 - fp: 0 - fn: 1 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -yearn.01 tp: 0 - fp: 0 - fn: 1 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -yield.01 tp: 3 - fp: 1 - fn: 0 - tn: 3 - precision: 0.7500 - recall: 1.0000 - accuracy: 0.7500 - f1-score: 0.8571 -yield.02 tp: 0 - fp: 0 - fn: 1 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -zap.01 tp: 0 - fp: 0 - fn: 1 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -zip.01 tp: 0 - fp: 0 - fn: 1 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -zoom.01 tp: 0 - fp: 0 - fn: 1 - tn: 0 - precision: 0.0000 - recall: 0.0000 - accuracy: 0.0000 - f1-score: 0.0000 -2019-08-20 05:24:19,259 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:11:15,542 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:11:15,542 Corpus: "Corpus: 75187 train + 9603 dev + 9479 test sentences" +2023-04-06 02:11:15,542 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:11:15,542 Parameters: +2023-04-06 02:11:15,542 - learning_rate: "0.100000" +2023-04-06 02:11:15,542 - mini_batch_size: "32" +2023-04-06 02:11:15,542 - patience: "3" +2023-04-06 02:11:15,542 - anneal_factor: "0.5" +2023-04-06 02:11:15,542 - max_epochs: "150" +2023-04-06 02:11:15,542 - shuffle: "True" +2023-04-06 02:11:15,542 - train_with_dev: "True" +2023-04-06 02:11:15,542 - batch_growth_annealing: "False" +2023-04-06 02:11:15,542 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:11:15,542 Model training base path: "resources/taggers/release-frame-0" +2023-04-06 02:11:15,542 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:11:15,542 Device: cuda:2 +2023-04-06 02:11:15,542 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:11:15,542 Embeddings storage mode: cpu +2023-04-06 02:11:15,542 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:11:30,360 epoch 1 - iter 265/2650 - loss 1.08449696 - time (sec): 14.82 - samples/sec: 4353.55 - lr: 0.100000 +2023-04-06 02:11:59,078 epoch 1 - iter 530/2650 - loss 0.94979727 - time (sec): 43.54 - samples/sec: 5091.27 - lr: 0.100000 +2023-04-06 02:12:33,250 epoch 1 - iter 795/2650 - loss 0.86105698 - time (sec): 77.71 - samples/sec: 5118.32 - lr: 0.100000 +2023-04-06 02:13:21,340 epoch 1 - iter 1060/2650 - loss 0.81522136 - time (sec): 125.80 - samples/sec: 4417.67 - lr: 0.100000 +2023-04-06 02:13:41,096 epoch 1 - iter 1325/2650 - loss 0.73285602 - time (sec): 145.55 - samples/sec: 4641.89 - lr: 0.100000 +2023-04-06 02:14:05,668 epoch 1 - iter 1590/2650 - loss 0.67108142 - time (sec): 170.13 - samples/sec: 4794.30 - lr: 0.100000 +2023-04-06 02:14:47,186 epoch 1 - iter 1855/2650 - loss 0.64773141 - time (sec): 211.64 - samples/sec: 4868.75 - lr: 0.100000 +2023-04-06 02:15:17,836 epoch 1 - iter 2120/2650 - loss 0.62494351 - time (sec): 242.29 - samples/sec: 4967.78 - lr: 0.100000 +2023-04-06 02:15:41,956 epoch 1 - iter 2385/2650 - loss 0.60237175 - time (sec): 266.41 - samples/sec: 4943.33 - lr: 0.100000 +2023-04-06 02:16:15,340 epoch 1 - iter 2650/2650 - loss 0.58266052 - time (sec): 299.80 - samples/sec: 4916.05 - lr: 0.100000 +2023-04-06 02:16:15,340 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:16:15,340 EPOCH 1 done: loss 0.5827 - lr 0.100000 +2023-04-06 02:16:15,340 BAD EPOCHS (no improvement): 0 +2023-04-06 02:16:15,344 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:16:25,614 epoch 2 - iter 265/2650 - loss 0.37907178 - time (sec): 10.27 - samples/sec: 14453.31 - lr: 0.100000 +2023-04-06 02:16:35,693 epoch 2 - iter 530/2650 - loss 0.36840083 - time (sec): 20.35 - samples/sec: 14458.99 - lr: 0.100000 +2023-04-06 02:16:46,078 epoch 2 - iter 795/2650 - loss 0.36195097 - time (sec): 30.73 - samples/sec: 14460.57 - lr: 0.100000 +2023-04-06 02:16:56,165 epoch 2 - iter 1060/2650 - loss 0.35637116 - time (sec): 40.82 - samples/sec: 14460.56 - lr: 0.100000 +2023-04-06 02:17:06,378 epoch 2 - iter 1325/2650 - loss 0.35058875 - time (sec): 51.03 - samples/sec: 14453.43 - lr: 0.100000 +2023-04-06 02:17:16,411 epoch 2 - iter 1590/2650 - loss 0.34458668 - time (sec): 61.07 - samples/sec: 14458.00 - lr: 0.100000 +2023-04-06 02:17:26,697 epoch 2 - iter 1855/2650 - loss 0.33962920 - time (sec): 71.35 - samples/sec: 14447.60 - lr: 0.100000 +2023-04-06 02:17:36,925 epoch 2 - iter 2120/2650 - loss 0.33498268 - time (sec): 81.58 - samples/sec: 14443.26 - lr: 0.100000 +2023-04-06 02:17:47,150 epoch 2 - iter 2385/2650 - loss 0.33018179 - time (sec): 91.81 - samples/sec: 14454.86 - lr: 0.100000 +2023-04-06 02:17:57,353 epoch 2 - iter 2650/2650 - loss 0.32626485 - time (sec): 102.01 - samples/sec: 14447.93 - lr: 0.100000 +2023-04-06 02:17:57,353 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:17:57,354 EPOCH 2 done: loss 0.3263 - lr 0.100000 +2023-04-06 02:17:57,354 BAD EPOCHS (no improvement): 0 +2023-04-06 02:17:57,357 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:18:07,594 epoch 3 - iter 265/2650 - loss 0.26769113 - time (sec): 10.24 - samples/sec: 14514.57 - lr: 0.100000 +2023-04-06 02:18:17,784 epoch 3 - iter 530/2650 - loss 0.27169170 - time (sec): 20.43 - samples/sec: 14473.54 - lr: 0.100000 +2023-04-06 02:18:27,998 epoch 3 - iter 795/2650 - loss 0.27010141 - time (sec): 30.64 - samples/sec: 14500.05 - lr: 0.100000 +2023-04-06 02:18:38,312 epoch 3 - iter 1060/2650 - loss 0.26806000 - time (sec): 40.95 - samples/sec: 14435.60 - lr: 0.100000 +2023-04-06 02:18:48,541 epoch 3 - iter 1325/2650 - loss 0.26683627 - time (sec): 51.18 - samples/sec: 14430.35 - lr: 0.100000 +2023-04-06 02:18:58,683 epoch 3 - iter 1590/2650 - loss 0.26525738 - time (sec): 61.32 - samples/sec: 14417.79 - lr: 0.100000 +2023-04-06 02:19:08,958 epoch 3 - iter 1855/2650 - loss 0.26334737 - time (sec): 71.60 - samples/sec: 14433.10 - lr: 0.100000 +2023-04-06 02:19:19,033 epoch 3 - iter 2120/2650 - loss 0.26209323 - time (sec): 81.68 - samples/sec: 14436.50 - lr: 0.100000 +2023-04-06 02:19:29,191 epoch 3 - iter 2385/2650 - loss 0.26086725 - time (sec): 91.83 - samples/sec: 14453.44 - lr: 0.100000 +2023-04-06 02:19:39,402 epoch 3 - iter 2650/2650 - loss 0.25914486 - time (sec): 102.04 - samples/sec: 14443.00 - lr: 0.100000 +2023-04-06 02:19:39,402 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:19:39,402 EPOCH 3 done: loss 0.2591 - lr 0.100000 +2023-04-06 02:19:39,402 BAD EPOCHS (no improvement): 0 +2023-04-06 02:19:39,405 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:19:49,510 epoch 4 - iter 265/2650 - loss 0.24284925 - time (sec): 10.10 - samples/sec: 14597.98 - lr: 0.100000 +2023-04-06 02:19:59,741 epoch 4 - iter 530/2650 - loss 0.23644749 - time (sec): 20.34 - samples/sec: 14546.11 - lr: 0.100000 +2023-04-06 02:20:09,829 epoch 4 - iter 795/2650 - loss 0.23624373 - time (sec): 30.42 - samples/sec: 14548.33 - lr: 0.100000 +2023-04-06 02:20:20,068 epoch 4 - iter 1060/2650 - loss 0.23507210 - time (sec): 40.66 - samples/sec: 14535.56 - lr: 0.100000 +2023-04-06 02:20:30,221 epoch 4 - iter 1325/2650 - loss 0.23355953 - time (sec): 50.82 - samples/sec: 14507.00 - lr: 0.100000 +2023-04-06 02:20:40,342 epoch 4 - iter 1590/2650 - loss 0.23216924 - time (sec): 60.94 - samples/sec: 14487.60 - lr: 0.100000 +2023-04-06 02:20:50,708 epoch 4 - iter 1855/2650 - loss 0.23136157 - time (sec): 71.30 - samples/sec: 14478.11 - lr: 0.100000 +2023-04-06 02:21:00,917 epoch 4 - iter 2120/2650 - loss 0.23024709 - time (sec): 81.51 - samples/sec: 14477.89 - lr: 0.100000 +2023-04-06 02:21:11,164 epoch 4 - iter 2385/2650 - loss 0.22875688 - time (sec): 91.76 - samples/sec: 14458.06 - lr: 0.100000 +2023-04-06 02:21:21,402 epoch 4 - iter 2650/2650 - loss 0.22762539 - time (sec): 102.00 - samples/sec: 14449.73 - lr: 0.100000 +2023-04-06 02:21:21,402 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:21:21,402 EPOCH 4 done: loss 0.2276 - lr 0.100000 +2023-04-06 02:21:21,402 BAD EPOCHS (no improvement): 0 +2023-04-06 02:21:21,405 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:21:31,710 epoch 5 - iter 265/2650 - loss 0.20513274 - time (sec): 10.31 - samples/sec: 14287.21 - lr: 0.100000 +2023-04-06 02:21:41,847 epoch 5 - iter 530/2650 - loss 0.20850903 - time (sec): 20.44 - samples/sec: 14311.02 - lr: 0.100000 +2023-04-06 02:21:51,984 epoch 5 - iter 795/2650 - loss 0.20845230 - time (sec): 30.58 - samples/sec: 14342.92 - lr: 0.100000 +2023-04-06 02:22:02,169 epoch 5 - iter 1060/2650 - loss 0.20922840 - time (sec): 40.76 - samples/sec: 14374.38 - lr: 0.100000 +2023-04-06 02:22:12,388 epoch 5 - iter 1325/2650 - loss 0.21026307 - time (sec): 50.98 - samples/sec: 14366.00 - lr: 0.100000 +2023-04-06 02:22:22,531 epoch 5 - iter 1590/2650 - loss 0.20928679 - time (sec): 61.13 - samples/sec: 14379.20 - lr: 0.100000 +2023-04-06 02:22:32,815 epoch 5 - iter 1855/2650 - loss 0.20895905 - time (sec): 71.41 - samples/sec: 14370.60 - lr: 0.100000 +2023-04-06 02:22:43,254 epoch 5 - iter 2120/2650 - loss 0.20868555 - time (sec): 81.85 - samples/sec: 14379.98 - lr: 0.100000 +2023-04-06 02:22:53,655 epoch 5 - iter 2385/2650 - loss 0.20856411 - time (sec): 92.25 - samples/sec: 14366.42 - lr: 0.100000 +2023-04-06 02:23:03,886 epoch 5 - iter 2650/2650 - loss 0.20793197 - time (sec): 102.48 - samples/sec: 14381.45 - lr: 0.100000 +2023-04-06 02:23:03,886 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:23:03,886 EPOCH 5 done: loss 0.2079 - lr 0.100000 +2023-04-06 02:23:03,886 BAD EPOCHS (no improvement): 0 +2023-04-06 02:23:03,890 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:23:14,087 epoch 6 - iter 265/2650 - loss 0.19461827 - time (sec): 10.20 - samples/sec: 14412.12 - lr: 0.100000 +2023-04-06 02:23:24,310 epoch 6 - iter 530/2650 - loss 0.19418156 - time (sec): 20.42 - samples/sec: 14425.25 - lr: 0.100000 +2023-04-06 02:23:34,653 epoch 6 - iter 795/2650 - loss 0.19470356 - time (sec): 30.76 - samples/sec: 14379.28 - lr: 0.100000 +2023-04-06 02:23:44,798 epoch 6 - iter 1060/2650 - loss 0.19579152 - time (sec): 40.91 - samples/sec: 14412.92 - lr: 0.100000 +2023-04-06 02:23:55,141 epoch 6 - iter 1325/2650 - loss 0.19588665 - time (sec): 51.25 - samples/sec: 14390.50 - lr: 0.100000 +2023-04-06 02:24:05,357 epoch 6 - iter 1590/2650 - loss 0.19452170 - time (sec): 61.47 - samples/sec: 14391.60 - lr: 0.100000 +2023-04-06 02:24:15,496 epoch 6 - iter 1855/2650 - loss 0.19425622 - time (sec): 71.61 - samples/sec: 14408.13 - lr: 0.100000 +2023-04-06 02:24:25,693 epoch 6 - iter 2120/2650 - loss 0.19426291 - time (sec): 81.80 - samples/sec: 14423.79 - lr: 0.100000 +2023-04-06 02:24:35,856 epoch 6 - iter 2385/2650 - loss 0.19396701 - time (sec): 91.97 - samples/sec: 14430.47 - lr: 0.100000 +2023-04-06 02:24:45,960 epoch 6 - iter 2650/2650 - loss 0.19352088 - time (sec): 102.07 - samples/sec: 14439.31 - lr: 0.100000 +2023-04-06 02:24:45,960 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:24:45,960 EPOCH 6 done: loss 0.1935 - lr 0.100000 +2023-04-06 02:24:45,960 BAD EPOCHS (no improvement): 0 +2023-04-06 02:24:45,964 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:24:56,103 epoch 7 - iter 265/2650 - loss 0.18469698 - time (sec): 10.14 - samples/sec: 14523.46 - lr: 0.100000 +2023-04-06 02:25:06,234 epoch 7 - iter 530/2650 - loss 0.18457000 - time (sec): 20.27 - samples/sec: 14509.78 - lr: 0.100000 +2023-04-06 02:25:16,255 epoch 7 - iter 795/2650 - loss 0.18241107 - time (sec): 30.29 - samples/sec: 14540.37 - lr: 0.100000 +2023-04-06 02:25:26,488 epoch 7 - iter 1060/2650 - loss 0.18256146 - time (sec): 40.52 - samples/sec: 14512.23 - lr: 0.100000 +2023-04-06 02:25:36,589 epoch 7 - iter 1325/2650 - loss 0.18305730 - time (sec): 50.62 - samples/sec: 14534.37 - lr: 0.100000 +2023-04-06 02:25:46,764 epoch 7 - iter 1590/2650 - loss 0.18348080 - time (sec): 60.80 - samples/sec: 14524.08 - lr: 0.100000 +2023-04-06 02:25:56,937 epoch 7 - iter 1855/2650 - loss 0.18368002 - time (sec): 70.97 - samples/sec: 14517.57 - lr: 0.100000 +2023-04-06 02:26:07,200 epoch 7 - iter 2120/2650 - loss 0.18289438 - time (sec): 81.23 - samples/sec: 14509.55 - lr: 0.100000 +2023-04-06 02:26:17,344 epoch 7 - iter 2385/2650 - loss 0.18256651 - time (sec): 91.38 - samples/sec: 14514.06 - lr: 0.100000 +2023-04-06 02:26:27,559 epoch 7 - iter 2650/2650 - loss 0.18247052 - time (sec): 101.59 - samples/sec: 14506.99 - lr: 0.100000 +2023-04-06 02:26:27,559 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:26:27,559 EPOCH 7 done: loss 0.1825 - lr 0.100000 +2023-04-06 02:26:27,559 BAD EPOCHS (no improvement): 0 +2023-04-06 02:26:27,562 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:26:37,857 epoch 8 - iter 265/2650 - loss 0.17228877 - time (sec): 10.29 - samples/sec: 14544.89 - lr: 0.100000 +2023-04-06 02:26:52,220 epoch 8 - iter 530/2650 - loss 0.17326605 - time (sec): 24.66 - samples/sec: 12012.65 - lr: 0.100000 +2023-04-06 02:27:02,155 epoch 8 - iter 795/2650 - loss 0.17372002 - time (sec): 34.59 - samples/sec: 12775.40 - lr: 0.100000 +2023-04-06 02:27:12,287 epoch 8 - iter 1060/2650 - loss 0.17421309 - time (sec): 44.72 - samples/sec: 13164.04 - lr: 0.100000 +2023-04-06 02:27:22,558 epoch 8 - iter 1325/2650 - loss 0.17379893 - time (sec): 55.00 - samples/sec: 13421.01 - lr: 0.100000 +2023-04-06 02:27:32,610 epoch 8 - iter 1590/2650 - loss 0.17407961 - time (sec): 65.05 - samples/sec: 13588.41 - lr: 0.100000 +2023-04-06 02:27:42,826 epoch 8 - iter 1855/2650 - loss 0.17423869 - time (sec): 75.26 - samples/sec: 13711.79 - lr: 0.100000 +2023-04-06 02:27:53,004 epoch 8 - iter 2120/2650 - loss 0.17406275 - time (sec): 85.44 - samples/sec: 13812.40 - lr: 0.100000 +2023-04-06 02:28:03,123 epoch 8 - iter 2385/2650 - loss 0.17406324 - time (sec): 95.56 - samples/sec: 13885.30 - lr: 0.100000 +2023-04-06 02:28:13,198 epoch 8 - iter 2650/2650 - loss 0.17389449 - time (sec): 105.64 - samples/sec: 13951.99 - lr: 0.100000 +2023-04-06 02:28:13,198 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:28:13,198 EPOCH 8 done: loss 0.1739 - lr 0.100000 +2023-04-06 02:28:13,198 BAD EPOCHS (no improvement): 0 +2023-04-06 02:28:13,202 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:28:23,483 epoch 9 - iter 265/2650 - loss 0.16337308 - time (sec): 10.28 - samples/sec: 14468.12 - lr: 0.100000 +2023-04-06 02:28:33,681 epoch 9 - iter 530/2650 - loss 0.16477571 - time (sec): 20.48 - samples/sec: 14499.27 - lr: 0.100000 +2023-04-06 02:28:43,976 epoch 9 - iter 795/2650 - loss 0.16723699 - time (sec): 30.77 - samples/sec: 14512.55 - lr: 0.100000 +2023-04-06 02:28:54,079 epoch 9 - iter 1060/2650 - loss 0.16753690 - time (sec): 40.88 - samples/sec: 14522.85 - lr: 0.100000 +2023-04-06 02:29:04,205 epoch 9 - iter 1325/2650 - loss 0.16751283 - time (sec): 51.00 - samples/sec: 14529.00 - lr: 0.100000 +2023-04-06 02:29:14,179 epoch 9 - iter 1590/2650 - loss 0.16768511 - time (sec): 60.98 - samples/sec: 14525.19 - lr: 0.100000 +2023-04-06 02:29:24,349 epoch 9 - iter 1855/2650 - loss 0.16772178 - time (sec): 71.15 - samples/sec: 14521.27 - lr: 0.100000 +2023-04-06 02:29:34,496 epoch 9 - iter 2120/2650 - loss 0.16735455 - time (sec): 81.29 - samples/sec: 14527.66 - lr: 0.100000 +2023-04-06 02:29:44,531 epoch 9 - iter 2385/2650 - loss 0.16762510 - time (sec): 91.33 - samples/sec: 14533.99 - lr: 0.100000 +2023-04-06 02:29:54,572 epoch 9 - iter 2650/2650 - loss 0.16752268 - time (sec): 101.37 - samples/sec: 14538.99 - lr: 0.100000 +2023-04-06 02:29:54,572 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:29:54,572 EPOCH 9 done: loss 0.1675 - lr 0.100000 +2023-04-06 02:29:54,572 BAD EPOCHS (no improvement): 0 +2023-04-06 02:29:54,577 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:30:04,765 epoch 10 - iter 265/2650 - loss 0.16107407 - time (sec): 10.19 - samples/sec: 14523.58 - lr: 0.100000 +2023-04-06 02:30:14,869 epoch 10 - iter 530/2650 - loss 0.16078611 - time (sec): 20.29 - samples/sec: 14572.63 - lr: 0.100000 +2023-04-06 02:30:25,118 epoch 10 - iter 795/2650 - loss 0.16229343 - time (sec): 30.54 - samples/sec: 14521.01 - lr: 0.100000 +2023-04-06 02:30:35,264 epoch 10 - iter 1060/2650 - loss 0.16306431 - time (sec): 40.69 - samples/sec: 14529.64 - lr: 0.100000 +2023-04-06 02:30:45,495 epoch 10 - iter 1325/2650 - loss 0.16245788 - time (sec): 50.92 - samples/sec: 14522.75 - lr: 0.100000 +2023-04-06 02:30:55,523 epoch 10 - iter 1590/2650 - loss 0.16184579 - time (sec): 60.95 - samples/sec: 14533.67 - lr: 0.100000 +2023-04-06 02:31:05,541 epoch 10 - iter 1855/2650 - loss 0.16196778 - time (sec): 70.96 - samples/sec: 14532.72 - lr: 0.100000 +2023-04-06 02:31:15,818 epoch 10 - iter 2120/2650 - loss 0.16146446 - time (sec): 81.24 - samples/sec: 14530.07 - lr: 0.100000 +2023-04-06 02:31:25,956 epoch 10 - iter 2385/2650 - loss 0.16131970 - time (sec): 91.38 - samples/sec: 14519.74 - lr: 0.100000 +2023-04-06 02:31:36,027 epoch 10 - iter 2650/2650 - loss 0.16156552 - time (sec): 101.45 - samples/sec: 14527.56 - lr: 0.100000 +2023-04-06 02:31:36,027 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:31:36,027 EPOCH 10 done: loss 0.1616 - lr 0.100000 +2023-04-06 02:31:36,027 BAD EPOCHS (no improvement): 0 +2023-04-06 02:31:36,031 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:31:46,088 epoch 11 - iter 265/2650 - loss 0.15538296 - time (sec): 10.06 - samples/sec: 14590.97 - lr: 0.100000 +2023-04-06 02:31:56,151 epoch 11 - iter 530/2650 - loss 0.15707735 - time (sec): 20.12 - samples/sec: 14562.97 - lr: 0.100000 +2023-04-06 02:32:06,178 epoch 11 - iter 795/2650 - loss 0.15684719 - time (sec): 30.15 - samples/sec: 14548.70 - lr: 0.100000 +2023-04-06 02:32:16,323 epoch 11 - iter 1060/2650 - loss 0.15646655 - time (sec): 40.29 - samples/sec: 14546.90 - lr: 0.100000 +2023-04-06 02:32:26,466 epoch 11 - iter 1325/2650 - loss 0.15646630 - time (sec): 50.44 - samples/sec: 14547.13 - lr: 0.100000 +2023-04-06 02:32:36,758 epoch 11 - iter 1590/2650 - loss 0.15663690 - time (sec): 60.73 - samples/sec: 14542.23 - lr: 0.100000 +2023-04-06 02:32:46,918 epoch 11 - iter 1855/2650 - loss 0.15647583 - time (sec): 70.89 - samples/sec: 14552.70 - lr: 0.100000 +2023-04-06 02:32:57,205 epoch 11 - iter 2120/2650 - loss 0.15645287 - time (sec): 81.17 - samples/sec: 14542.76 - lr: 0.100000 +2023-04-06 02:33:07,350 epoch 11 - iter 2385/2650 - loss 0.15630136 - time (sec): 91.32 - samples/sec: 14531.07 - lr: 0.100000 +2023-04-06 02:33:17,514 epoch 11 - iter 2650/2650 - loss 0.15653181 - time (sec): 101.48 - samples/sec: 14522.90 - lr: 0.100000 +2023-04-06 02:33:17,514 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:33:17,514 EPOCH 11 done: loss 0.1565 - lr 0.100000 +2023-04-06 02:33:17,514 BAD EPOCHS (no improvement): 0 +2023-04-06 02:33:17,519 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:33:27,648 epoch 12 - iter 265/2650 - loss 0.15510266 - time (sec): 10.13 - samples/sec: 14489.18 - lr: 0.100000 +2023-04-06 02:33:37,939 epoch 12 - iter 530/2650 - loss 0.15317082 - time (sec): 20.42 - samples/sec: 14477.99 - lr: 0.100000 +2023-04-06 02:33:48,188 epoch 12 - iter 795/2650 - loss 0.15341940 - time (sec): 30.67 - samples/sec: 14462.76 - lr: 0.100000 +2023-04-06 02:33:58,482 epoch 12 - iter 1060/2650 - loss 0.15184994 - time (sec): 40.96 - samples/sec: 14447.41 - lr: 0.100000 +2023-04-06 02:34:08,743 epoch 12 - iter 1325/2650 - loss 0.15171051 - time (sec): 51.22 - samples/sec: 14457.33 - lr: 0.100000 +2023-04-06 02:34:18,793 epoch 12 - iter 1590/2650 - loss 0.15076472 - time (sec): 61.27 - samples/sec: 14456.07 - lr: 0.100000 +2023-04-06 02:34:28,822 epoch 12 - iter 1855/2650 - loss 0.15095448 - time (sec): 71.30 - samples/sec: 14474.23 - lr: 0.100000 +2023-04-06 02:34:38,936 epoch 12 - iter 2120/2650 - loss 0.15155303 - time (sec): 81.42 - samples/sec: 14475.53 - lr: 0.100000 +2023-04-06 02:34:49,080 epoch 12 - iter 2385/2650 - loss 0.15182494 - time (sec): 91.56 - samples/sec: 14473.86 - lr: 0.100000 +2023-04-06 02:34:59,248 epoch 12 - iter 2650/2650 - loss 0.15171036 - time (sec): 101.73 - samples/sec: 14487.73 - lr: 0.100000 +2023-04-06 02:34:59,248 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:34:59,248 EPOCH 12 done: loss 0.1517 - lr 0.100000 +2023-04-06 02:34:59,248 BAD EPOCHS (no improvement): 0 +2023-04-06 02:34:59,251 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:35:09,421 epoch 13 - iter 265/2650 - loss 0.14721313 - time (sec): 10.17 - samples/sec: 14463.61 - lr: 0.100000 +2023-04-06 02:35:19,574 epoch 13 - iter 530/2650 - loss 0.14736593 - time (sec): 20.32 - samples/sec: 14493.43 - lr: 0.100000 +2023-04-06 02:35:29,800 epoch 13 - iter 795/2650 - loss 0.14806926 - time (sec): 30.55 - samples/sec: 14455.25 - lr: 0.100000 +2023-04-06 02:35:40,052 epoch 13 - iter 1060/2650 - loss 0.14831645 - time (sec): 40.80 - samples/sec: 14457.40 - lr: 0.100000 +2023-04-06 02:35:50,300 epoch 13 - iter 1325/2650 - loss 0.14818671 - time (sec): 51.05 - samples/sec: 14461.94 - lr: 0.100000 +2023-04-06 02:36:00,590 epoch 13 - iter 1590/2650 - loss 0.14861968 - time (sec): 61.34 - samples/sec: 14458.54 - lr: 0.100000 +2023-04-06 02:36:10,659 epoch 13 - iter 1855/2650 - loss 0.14875829 - time (sec): 71.41 - samples/sec: 14448.03 - lr: 0.100000 +2023-04-06 02:36:20,799 epoch 13 - iter 2120/2650 - loss 0.14856673 - time (sec): 81.55 - samples/sec: 14454.87 - lr: 0.100000 +2023-04-06 02:36:30,910 epoch 13 - iter 2385/2650 - loss 0.14863777 - time (sec): 91.66 - samples/sec: 14463.53 - lr: 0.100000 +2023-04-06 02:36:41,079 epoch 13 - iter 2650/2650 - loss 0.14863411 - time (sec): 101.83 - samples/sec: 14473.70 - lr: 0.100000 +2023-04-06 02:36:41,079 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:36:41,079 EPOCH 13 done: loss 0.1486 - lr 0.100000 +2023-04-06 02:36:41,079 BAD EPOCHS (no improvement): 0 +2023-04-06 02:36:41,083 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:36:51,389 epoch 14 - iter 265/2650 - loss 0.14551595 - time (sec): 10.31 - samples/sec: 14383.05 - lr: 0.100000 +2023-04-06 02:37:01,572 epoch 14 - iter 530/2650 - loss 0.14454565 - time (sec): 20.49 - samples/sec: 14438.64 - lr: 0.100000 +2023-04-06 02:37:11,769 epoch 14 - iter 795/2650 - loss 0.14443090 - time (sec): 30.69 - samples/sec: 14463.49 - lr: 0.100000 +2023-04-06 02:37:26,218 epoch 14 - iter 1060/2650 - loss 0.14519431 - time (sec): 45.14 - samples/sec: 13138.92 - lr: 0.100000 +2023-04-06 02:37:36,301 epoch 14 - iter 1325/2650 - loss 0.14398398 - time (sec): 55.22 - samples/sec: 13386.59 - lr: 0.100000 +2023-04-06 02:37:46,467 epoch 14 - iter 1590/2650 - loss 0.14472356 - time (sec): 65.38 - samples/sec: 13555.74 - lr: 0.100000 +2023-04-06 02:37:56,584 epoch 14 - iter 1855/2650 - loss 0.14433323 - time (sec): 75.50 - samples/sec: 13677.36 - lr: 0.100000 +2023-04-06 02:38:06,802 epoch 14 - iter 2120/2650 - loss 0.14413282 - time (sec): 85.72 - samples/sec: 13768.25 - lr: 0.100000 +2023-04-06 02:38:17,028 epoch 14 - iter 2385/2650 - loss 0.14437411 - time (sec): 95.94 - samples/sec: 13820.13 - lr: 0.100000 +2023-04-06 02:38:27,233 epoch 14 - iter 2650/2650 - loss 0.14420075 - time (sec): 106.15 - samples/sec: 13884.24 - lr: 0.100000 +2023-04-06 02:38:27,234 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:38:27,234 EPOCH 14 done: loss 0.1442 - lr 0.100000 +2023-04-06 02:38:27,234 BAD EPOCHS (no improvement): 0 +2023-04-06 02:38:27,237 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:38:37,507 epoch 15 - iter 265/2650 - loss 0.13913664 - time (sec): 10.27 - samples/sec: 14424.93 - lr: 0.100000 +2023-04-06 02:38:47,819 epoch 15 - iter 530/2650 - loss 0.13986220 - time (sec): 20.58 - samples/sec: 14370.23 - lr: 0.100000 +2023-04-06 02:38:58,075 epoch 15 - iter 795/2650 - loss 0.13959127 - time (sec): 30.84 - samples/sec: 14357.83 - lr: 0.100000 +2023-04-06 02:39:08,268 epoch 15 - iter 1060/2650 - loss 0.13928157 - time (sec): 41.03 - samples/sec: 14383.70 - lr: 0.100000 +2023-04-06 02:39:18,641 epoch 15 - iter 1325/2650 - loss 0.14029752 - time (sec): 51.40 - samples/sec: 14355.37 - lr: 0.100000 +2023-04-06 02:39:28,827 epoch 15 - iter 1590/2650 - loss 0.14065452 - time (sec): 61.59 - samples/sec: 14364.83 - lr: 0.100000 +2023-04-06 02:39:38,923 epoch 15 - iter 1855/2650 - loss 0.14094785 - time (sec): 71.69 - samples/sec: 14375.88 - lr: 0.100000 +2023-04-06 02:39:49,037 epoch 15 - iter 2120/2650 - loss 0.14118270 - time (sec): 81.80 - samples/sec: 14381.80 - lr: 0.100000 +2023-04-06 02:39:59,349 epoch 15 - iter 2385/2650 - loss 0.14098035 - time (sec): 92.11 - samples/sec: 14391.74 - lr: 0.100000 +2023-04-06 02:40:09,609 epoch 15 - iter 2650/2650 - loss 0.14118690 - time (sec): 102.37 - samples/sec: 14396.79 - lr: 0.100000 +2023-04-06 02:40:09,609 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:40:09,609 EPOCH 15 done: loss 0.1412 - lr 0.100000 +2023-04-06 02:40:09,609 BAD EPOCHS (no improvement): 0 +2023-04-06 02:40:09,612 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:40:19,767 epoch 16 - iter 265/2650 - loss 0.13238412 - time (sec): 10.15 - samples/sec: 14408.10 - lr: 0.100000 +2023-04-06 02:40:30,132 epoch 16 - iter 530/2650 - loss 0.13418358 - time (sec): 20.52 - samples/sec: 14380.87 - lr: 0.100000 +2023-04-06 02:40:40,446 epoch 16 - iter 795/2650 - loss 0.13472064 - time (sec): 30.83 - samples/sec: 14383.24 - lr: 0.100000 +2023-04-06 02:40:50,743 epoch 16 - iter 1060/2650 - loss 0.13620931 - time (sec): 41.13 - samples/sec: 14390.58 - lr: 0.100000 +2023-04-06 02:41:00,811 epoch 16 - iter 1325/2650 - loss 0.13754961 - time (sec): 51.20 - samples/sec: 14420.74 - lr: 0.100000 +2023-04-06 02:41:10,945 epoch 16 - iter 1590/2650 - loss 0.13736925 - time (sec): 61.33 - samples/sec: 14434.23 - lr: 0.100000 +2023-04-06 02:41:21,023 epoch 16 - iter 1855/2650 - loss 0.13794920 - time (sec): 71.41 - samples/sec: 14451.57 - lr: 0.100000 +2023-04-06 02:41:31,211 epoch 16 - iter 2120/2650 - loss 0.13837734 - time (sec): 81.60 - samples/sec: 14459.88 - lr: 0.100000 +2023-04-06 02:41:41,195 epoch 16 - iter 2385/2650 - loss 0.13812855 - time (sec): 91.58 - samples/sec: 14479.93 - lr: 0.100000 +2023-04-06 02:41:51,469 epoch 16 - iter 2650/2650 - loss 0.13832713 - time (sec): 101.86 - samples/sec: 14469.63 - lr: 0.100000 +2023-04-06 02:41:51,469 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:41:51,469 EPOCH 16 done: loss 0.1383 - lr 0.100000 +2023-04-06 02:41:51,469 BAD EPOCHS (no improvement): 0 +2023-04-06 02:41:51,472 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:42:01,721 epoch 17 - iter 265/2650 - loss 0.13609328 - time (sec): 10.25 - samples/sec: 14460.51 - lr: 0.100000 +2023-04-06 02:42:12,123 epoch 17 - iter 530/2650 - loss 0.13514252 - time (sec): 20.65 - samples/sec: 14413.44 - lr: 0.100000 +2023-04-06 02:42:22,416 epoch 17 - iter 795/2650 - loss 0.13663071 - time (sec): 30.94 - samples/sec: 14426.13 - lr: 0.100000 +2023-04-06 02:42:32,583 epoch 17 - iter 1060/2650 - loss 0.13728130 - time (sec): 41.11 - samples/sec: 14403.04 - lr: 0.100000 +2023-04-06 02:42:42,821 epoch 17 - iter 1325/2650 - loss 0.13698261 - time (sec): 51.35 - samples/sec: 14415.53 - lr: 0.100000 +2023-04-06 02:42:53,155 epoch 17 - iter 1590/2650 - loss 0.13712257 - time (sec): 61.68 - samples/sec: 14397.42 - lr: 0.100000 +2023-04-06 02:43:03,288 epoch 17 - iter 1855/2650 - loss 0.13688137 - time (sec): 71.82 - samples/sec: 14401.92 - lr: 0.100000 +2023-04-06 02:43:13,416 epoch 17 - iter 2120/2650 - loss 0.13658140 - time (sec): 81.94 - samples/sec: 14409.55 - lr: 0.100000 +2023-04-06 02:43:23,566 epoch 17 - iter 2385/2650 - loss 0.13639942 - time (sec): 92.09 - samples/sec: 14409.02 - lr: 0.100000 +2023-04-06 02:43:33,704 epoch 17 - iter 2650/2650 - loss 0.13609748 - time (sec): 102.23 - samples/sec: 14416.42 - lr: 0.100000 +2023-04-06 02:43:33,704 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:43:33,705 EPOCH 17 done: loss 0.1361 - lr 0.100000 +2023-04-06 02:43:33,705 BAD EPOCHS (no improvement): 0 +2023-04-06 02:43:33,708 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:43:43,815 epoch 18 - iter 265/2650 - loss 0.13046248 - time (sec): 10.11 - samples/sec: 14371.78 - lr: 0.100000 +2023-04-06 02:43:53,946 epoch 18 - iter 530/2650 - loss 0.13248339 - time (sec): 20.24 - samples/sec: 14461.97 - lr: 0.100000 +2023-04-06 02:44:04,197 epoch 18 - iter 795/2650 - loss 0.13249772 - time (sec): 30.49 - samples/sec: 14431.29 - lr: 0.100000 +2023-04-06 02:44:14,423 epoch 18 - iter 1060/2650 - loss 0.13273165 - time (sec): 40.71 - samples/sec: 14431.84 - lr: 0.100000 +2023-04-06 02:44:24,758 epoch 18 - iter 1325/2650 - loss 0.13280738 - time (sec): 51.05 - samples/sec: 14426.03 - lr: 0.100000 +2023-04-06 02:44:34,806 epoch 18 - iter 1590/2650 - loss 0.13311784 - time (sec): 61.10 - samples/sec: 14449.30 - lr: 0.100000 +2023-04-06 02:44:45,121 epoch 18 - iter 1855/2650 - loss 0.13309927 - time (sec): 71.41 - samples/sec: 14447.47 - lr: 0.100000 +2023-04-06 02:44:55,279 epoch 18 - iter 2120/2650 - loss 0.13298202 - time (sec): 81.57 - samples/sec: 14456.49 - lr: 0.100000 +2023-04-06 02:45:05,348 epoch 18 - iter 2385/2650 - loss 0.13301418 - time (sec): 91.64 - samples/sec: 14457.06 - lr: 0.100000 +2023-04-06 02:45:15,618 epoch 18 - iter 2650/2650 - loss 0.13316536 - time (sec): 101.91 - samples/sec: 14462.05 - lr: 0.100000 +2023-04-06 02:45:15,618 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:45:15,618 EPOCH 18 done: loss 0.1332 - lr 0.100000 +2023-04-06 02:45:15,618 BAD EPOCHS (no improvement): 0 +2023-04-06 02:45:15,621 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:45:25,711 epoch 19 - iter 265/2650 - loss 0.13101039 - time (sec): 10.09 - samples/sec: 14503.23 - lr: 0.100000 +2023-04-06 02:45:35,752 epoch 19 - iter 530/2650 - loss 0.13240749 - time (sec): 20.13 - samples/sec: 14533.91 - lr: 0.100000 +2023-04-06 02:45:45,994 epoch 19 - iter 795/2650 - loss 0.13207783 - time (sec): 30.37 - samples/sec: 14502.91 - lr: 0.100000 +2023-04-06 02:45:56,124 epoch 19 - iter 1060/2650 - loss 0.13178938 - time (sec): 40.50 - samples/sec: 14495.08 - lr: 0.100000 +2023-04-06 02:46:06,378 epoch 19 - iter 1325/2650 - loss 0.13134672 - time (sec): 50.76 - samples/sec: 14501.20 - lr: 0.100000 +2023-04-06 02:46:16,477 epoch 19 - iter 1590/2650 - loss 0.13139676 - time (sec): 60.85 - samples/sec: 14511.90 - lr: 0.100000 +2023-04-06 02:46:26,676 epoch 19 - iter 1855/2650 - loss 0.13116518 - time (sec): 71.05 - samples/sec: 14504.36 - lr: 0.100000 +2023-04-06 02:46:36,907 epoch 19 - iter 2120/2650 - loss 0.13121583 - time (sec): 81.29 - samples/sec: 14501.01 - lr: 0.100000 +2023-04-06 02:46:46,979 epoch 19 - iter 2385/2650 - loss 0.13147841 - time (sec): 91.36 - samples/sec: 14498.21 - lr: 0.100000 +2023-04-06 02:46:57,312 epoch 19 - iter 2650/2650 - loss 0.13156927 - time (sec): 101.69 - samples/sec: 14493.26 - lr: 0.100000 +2023-04-06 02:46:57,312 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:46:57,312 EPOCH 19 done: loss 0.1316 - lr 0.100000 +2023-04-06 02:46:57,312 BAD EPOCHS (no improvement): 0 +2023-04-06 02:46:57,315 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:47:07,313 epoch 20 - iter 265/2650 - loss 0.12710469 - time (sec): 10.00 - samples/sec: 14560.61 - lr: 0.100000 +2023-04-06 02:47:17,527 epoch 20 - iter 530/2650 - loss 0.12697753 - time (sec): 20.21 - samples/sec: 14531.78 - lr: 0.100000 +2023-04-06 02:47:27,699 epoch 20 - iter 795/2650 - loss 0.12753680 - time (sec): 30.38 - samples/sec: 14514.55 - lr: 0.100000 +2023-04-06 02:47:37,939 epoch 20 - iter 1060/2650 - loss 0.12884679 - time (sec): 40.62 - samples/sec: 14508.22 - lr: 0.100000 +2023-04-06 02:47:52,256 epoch 20 - iter 1325/2650 - loss 0.12911247 - time (sec): 54.94 - samples/sec: 13405.79 - lr: 0.100000 +2023-04-06 02:48:02,311 epoch 20 - iter 1590/2650 - loss 0.12906778 - time (sec): 65.00 - samples/sec: 13590.75 - lr: 0.100000 +2023-04-06 02:48:12,405 epoch 20 - iter 1855/2650 - loss 0.12886972 - time (sec): 75.09 - samples/sec: 13718.05 - lr: 0.100000 +2023-04-06 02:48:22,554 epoch 20 - iter 2120/2650 - loss 0.12913793 - time (sec): 85.24 - samples/sec: 13818.13 - lr: 0.100000 +2023-04-06 02:48:32,725 epoch 20 - iter 2385/2650 - loss 0.12926786 - time (sec): 95.41 - samples/sec: 13892.58 - lr: 0.100000 +2023-04-06 02:48:43,109 epoch 20 - iter 2650/2650 - loss 0.12933287 - time (sec): 105.79 - samples/sec: 13931.19 - lr: 0.100000 +2023-04-06 02:48:43,109 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:48:43,109 EPOCH 20 done: loss 0.1293 - lr 0.100000 +2023-04-06 02:48:43,109 BAD EPOCHS (no improvement): 0 +2023-04-06 02:48:43,139 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:48:53,339 epoch 21 - iter 265/2650 - loss 0.12953339 - time (sec): 10.20 - samples/sec: 14506.35 - lr: 0.100000 +2023-04-06 02:49:03,513 epoch 21 - iter 530/2650 - loss 0.12813783 - time (sec): 20.37 - samples/sec: 14455.74 - lr: 0.100000 +2023-04-06 02:49:13,828 epoch 21 - iter 795/2650 - loss 0.12699977 - time (sec): 30.69 - samples/sec: 14422.59 - lr: 0.100000 +2023-04-06 02:49:24,061 epoch 21 - iter 1060/2650 - loss 0.12672504 - time (sec): 40.92 - samples/sec: 14416.27 - lr: 0.100000 +2023-04-06 02:49:34,382 epoch 21 - iter 1325/2650 - loss 0.12636576 - time (sec): 51.24 - samples/sec: 14409.70 - lr: 0.100000 +2023-04-06 02:49:44,726 epoch 21 - iter 1590/2650 - loss 0.12624573 - time (sec): 61.59 - samples/sec: 14407.44 - lr: 0.100000 +2023-04-06 02:49:54,781 epoch 21 - iter 1855/2650 - loss 0.12631772 - time (sec): 71.64 - samples/sec: 14416.95 - lr: 0.100000 +2023-04-06 02:50:04,980 epoch 21 - iter 2120/2650 - loss 0.12658817 - time (sec): 81.84 - samples/sec: 14413.59 - lr: 0.100000 +2023-04-06 02:50:15,050 epoch 21 - iter 2385/2650 - loss 0.12671606 - time (sec): 91.91 - samples/sec: 14424.68 - lr: 0.100000 +2023-04-06 02:50:25,350 epoch 21 - iter 2650/2650 - loss 0.12698228 - time (sec): 102.21 - samples/sec: 14419.53 - lr: 0.100000 +2023-04-06 02:50:25,350 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:50:25,350 EPOCH 21 done: loss 0.1270 - lr 0.100000 +2023-04-06 02:50:25,350 BAD EPOCHS (no improvement): 0 +2023-04-06 02:50:25,354 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:50:35,409 epoch 22 - iter 265/2650 - loss 0.12354271 - time (sec): 10.06 - samples/sec: 14615.34 - lr: 0.100000 +2023-04-06 02:50:45,533 epoch 22 - iter 530/2650 - loss 0.12395439 - time (sec): 20.18 - samples/sec: 14603.61 - lr: 0.100000 +2023-04-06 02:50:55,571 epoch 22 - iter 795/2650 - loss 0.12495642 - time (sec): 30.22 - samples/sec: 14586.44 - lr: 0.100000 +2023-04-06 02:51:05,640 epoch 22 - iter 1060/2650 - loss 0.12431742 - time (sec): 40.29 - samples/sec: 14574.07 - lr: 0.100000 +2023-04-06 02:51:15,881 epoch 22 - iter 1325/2650 - loss 0.12459478 - time (sec): 50.53 - samples/sec: 14568.92 - lr: 0.100000 +2023-04-06 02:51:25,954 epoch 22 - iter 1590/2650 - loss 0.12447852 - time (sec): 60.60 - samples/sec: 14572.84 - lr: 0.100000 +2023-04-06 02:51:36,230 epoch 22 - iter 1855/2650 - loss 0.12495196 - time (sec): 70.88 - samples/sec: 14550.34 - lr: 0.100000 +2023-04-06 02:51:46,432 epoch 22 - iter 2120/2650 - loss 0.12507927 - time (sec): 81.08 - samples/sec: 14530.31 - lr: 0.100000 +2023-04-06 02:51:56,798 epoch 22 - iter 2385/2650 - loss 0.12503849 - time (sec): 91.44 - samples/sec: 14507.62 - lr: 0.100000 +2023-04-06 02:52:06,989 epoch 22 - iter 2650/2650 - loss 0.12514561 - time (sec): 101.64 - samples/sec: 14501.03 - lr: 0.100000 +2023-04-06 02:52:06,990 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:52:06,990 EPOCH 22 done: loss 0.1251 - lr 0.100000 +2023-04-06 02:52:06,990 BAD EPOCHS (no improvement): 0 +2023-04-06 02:52:06,993 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:52:17,428 epoch 23 - iter 265/2650 - loss 0.12141115 - time (sec): 10.43 - samples/sec: 14298.23 - lr: 0.100000 +2023-04-06 02:52:27,632 epoch 23 - iter 530/2650 - loss 0.12296161 - time (sec): 20.64 - samples/sec: 14313.54 - lr: 0.100000 +2023-04-06 02:52:37,942 epoch 23 - iter 795/2650 - loss 0.12300908 - time (sec): 30.95 - samples/sec: 14320.46 - lr: 0.100000 +2023-04-06 02:52:48,122 epoch 23 - iter 1060/2650 - loss 0.12297994 - time (sec): 41.13 - samples/sec: 14331.50 - lr: 0.100000 +2023-04-06 02:52:58,356 epoch 23 - iter 1325/2650 - loss 0.12307097 - time (sec): 51.36 - samples/sec: 14339.86 - lr: 0.100000 +2023-04-06 02:53:08,736 epoch 23 - iter 1590/2650 - loss 0.12380573 - time (sec): 61.74 - samples/sec: 14331.73 - lr: 0.100000 +2023-04-06 02:53:18,929 epoch 23 - iter 1855/2650 - loss 0.12397285 - time (sec): 71.94 - samples/sec: 14346.32 - lr: 0.100000 +2023-04-06 02:53:29,071 epoch 23 - iter 2120/2650 - loss 0.12419077 - time (sec): 82.08 - samples/sec: 14356.83 - lr: 0.100000 +2023-04-06 02:53:39,411 epoch 23 - iter 2385/2650 - loss 0.12393081 - time (sec): 92.42 - samples/sec: 14350.53 - lr: 0.100000 +2023-04-06 02:53:49,671 epoch 23 - iter 2650/2650 - loss 0.12401765 - time (sec): 102.68 - samples/sec: 14353.80 - lr: 0.100000 +2023-04-06 02:53:49,672 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:53:49,672 EPOCH 23 done: loss 0.1240 - lr 0.100000 +2023-04-06 02:53:49,672 BAD EPOCHS (no improvement): 0 +2023-04-06 02:53:49,675 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:53:59,997 epoch 24 - iter 265/2650 - loss 0.12122589 - time (sec): 10.32 - samples/sec: 14211.48 - lr: 0.100000 +2023-04-06 02:54:10,288 epoch 24 - iter 530/2650 - loss 0.12196191 - time (sec): 20.61 - samples/sec: 14296.17 - lr: 0.100000 +2023-04-06 02:54:20,614 epoch 24 - iter 795/2650 - loss 0.12051320 - time (sec): 30.94 - samples/sec: 14299.63 - lr: 0.100000 +2023-04-06 02:54:30,843 epoch 24 - iter 1060/2650 - loss 0.12105663 - time (sec): 41.17 - samples/sec: 14319.86 - lr: 0.100000 +2023-04-06 02:54:41,249 epoch 24 - iter 1325/2650 - loss 0.12128221 - time (sec): 51.57 - samples/sec: 14297.37 - lr: 0.100000 +2023-04-06 02:54:51,673 epoch 24 - iter 1590/2650 - loss 0.12202385 - time (sec): 62.00 - samples/sec: 14314.84 - lr: 0.100000 +2023-04-06 02:55:01,721 epoch 24 - iter 1855/2650 - loss 0.12224218 - time (sec): 72.05 - samples/sec: 14332.43 - lr: 0.100000 +2023-04-06 02:55:11,983 epoch 24 - iter 2120/2650 - loss 0.12207776 - time (sec): 82.31 - samples/sec: 14334.35 - lr: 0.100000 +2023-04-06 02:55:22,202 epoch 24 - iter 2385/2650 - loss 0.12211445 - time (sec): 92.53 - samples/sec: 14342.42 - lr: 0.100000 +2023-04-06 02:55:32,446 epoch 24 - iter 2650/2650 - loss 0.12216263 - time (sec): 102.77 - samples/sec: 14340.95 - lr: 0.100000 +2023-04-06 02:55:32,446 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:55:32,446 EPOCH 24 done: loss 0.1222 - lr 0.100000 +2023-04-06 02:55:32,446 BAD EPOCHS (no improvement): 0 +2023-04-06 02:55:32,450 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:55:42,645 epoch 25 - iter 265/2650 - loss 0.12006350 - time (sec): 10.19 - samples/sec: 14385.13 - lr: 0.100000 +2023-04-06 02:55:52,997 epoch 25 - iter 530/2650 - loss 0.11982806 - time (sec): 20.55 - samples/sec: 14355.90 - lr: 0.100000 +2023-04-06 02:56:03,164 epoch 25 - iter 795/2650 - loss 0.11949375 - time (sec): 30.71 - samples/sec: 14349.19 - lr: 0.100000 +2023-04-06 02:56:13,463 epoch 25 - iter 1060/2650 - loss 0.11977136 - time (sec): 41.01 - samples/sec: 14329.28 - lr: 0.100000 +2023-04-06 02:56:23,776 epoch 25 - iter 1325/2650 - loss 0.11963397 - time (sec): 51.33 - samples/sec: 14340.75 - lr: 0.100000 +2023-04-06 02:56:34,156 epoch 25 - iter 1590/2650 - loss 0.11988480 - time (sec): 61.71 - samples/sec: 14328.78 - lr: 0.100000 +2023-04-06 02:56:44,449 epoch 25 - iter 1855/2650 - loss 0.12002669 - time (sec): 72.00 - samples/sec: 14318.33 - lr: 0.100000 +2023-04-06 02:56:54,698 epoch 25 - iter 2120/2650 - loss 0.11979513 - time (sec): 82.25 - samples/sec: 14316.28 - lr: 0.100000 +2023-04-06 02:57:04,874 epoch 25 - iter 2385/2650 - loss 0.11964939 - time (sec): 92.42 - samples/sec: 14340.61 - lr: 0.100000 +2023-04-06 02:57:15,126 epoch 25 - iter 2650/2650 - loss 0.11987647 - time (sec): 102.68 - samples/sec: 14354.10 - lr: 0.100000 +2023-04-06 02:57:15,127 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:57:15,127 EPOCH 25 done: loss 0.1199 - lr 0.100000 +2023-04-06 02:57:15,127 BAD EPOCHS (no improvement): 0 +2023-04-06 02:57:15,134 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:57:25,228 epoch 26 - iter 265/2650 - loss 0.11527945 - time (sec): 10.09 - samples/sec: 14579.36 - lr: 0.100000 +2023-04-06 02:57:35,436 epoch 26 - iter 530/2650 - loss 0.11835439 - time (sec): 20.30 - samples/sec: 14442.72 - lr: 0.100000 +2023-04-06 02:57:45,667 epoch 26 - iter 795/2650 - loss 0.11855658 - time (sec): 30.53 - samples/sec: 14510.38 - lr: 0.100000 +2023-04-06 02:57:55,784 epoch 26 - iter 1060/2650 - loss 0.11800707 - time (sec): 40.65 - samples/sec: 14526.28 - lr: 0.100000 +2023-04-06 02:58:05,940 epoch 26 - iter 1325/2650 - loss 0.11857779 - time (sec): 50.81 - samples/sec: 14529.75 - lr: 0.100000 +2023-04-06 02:58:16,042 epoch 26 - iter 1590/2650 - loss 0.11874183 - time (sec): 60.91 - samples/sec: 14529.19 - lr: 0.100000 +2023-04-06 02:58:26,387 epoch 26 - iter 1855/2650 - loss 0.11930774 - time (sec): 71.25 - samples/sec: 14501.47 - lr: 0.100000 +2023-04-06 02:58:40,598 epoch 26 - iter 2120/2650 - loss 0.11914346 - time (sec): 85.46 - samples/sec: 13773.60 - lr: 0.100000 +2023-04-06 02:58:50,876 epoch 26 - iter 2385/2650 - loss 0.11914649 - time (sec): 95.74 - samples/sec: 13858.07 - lr: 0.100000 +2023-04-06 02:59:01,155 epoch 26 - iter 2650/2650 - loss 0.11906060 - time (sec): 106.02 - samples/sec: 13901.28 - lr: 0.100000 +2023-04-06 02:59:01,155 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:59:01,155 EPOCH 26 done: loss 0.1191 - lr 0.100000 +2023-04-06 02:59:01,155 BAD EPOCHS (no improvement): 0 +2023-04-06 02:59:01,159 ---------------------------------------------------------------------------------------------------- +2023-04-06 02:59:11,423 epoch 27 - iter 265/2650 - loss 0.11571738 - time (sec): 10.26 - samples/sec: 14430.11 - lr: 0.100000 +2023-04-06 02:59:21,519 epoch 27 - iter 530/2650 - loss 0.11542162 - time (sec): 20.36 - samples/sec: 14444.84 - lr: 0.100000 +2023-04-06 02:59:31,745 epoch 27 - iter 795/2650 - loss 0.11625655 - time (sec): 30.59 - samples/sec: 14464.23 - lr: 0.100000 +2023-04-06 02:59:41,954 epoch 27 - iter 1060/2650 - loss 0.11598799 - time (sec): 40.79 - samples/sec: 14426.44 - lr: 0.100000 +2023-04-06 02:59:52,207 epoch 27 - iter 1325/2650 - loss 0.11641977 - time (sec): 51.05 - samples/sec: 14417.97 - lr: 0.100000 +2023-04-06 03:00:02,378 epoch 27 - iter 1590/2650 - loss 0.11677255 - time (sec): 61.22 - samples/sec: 14430.81 - lr: 0.100000 +2023-04-06 03:00:12,619 epoch 27 - iter 1855/2650 - loss 0.11709781 - time (sec): 71.46 - samples/sec: 14440.49 - lr: 0.100000 +2023-04-06 03:00:22,887 epoch 27 - iter 2120/2650 - loss 0.11732213 - time (sec): 81.73 - samples/sec: 14453.62 - lr: 0.100000 +2023-04-06 03:00:32,946 epoch 27 - iter 2385/2650 - loss 0.11746030 - time (sec): 91.79 - samples/sec: 14449.93 - lr: 0.100000 +2023-04-06 03:00:43,228 epoch 27 - iter 2650/2650 - loss 0.11761431 - time (sec): 102.07 - samples/sec: 14439.42 - lr: 0.100000 +2023-04-06 03:00:43,228 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:00:43,228 EPOCH 27 done: loss 0.1176 - lr 0.100000 +2023-04-06 03:00:43,229 BAD EPOCHS (no improvement): 0 +2023-04-06 03:00:43,232 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:00:53,384 epoch 28 - iter 265/2650 - loss 0.11728533 - time (sec): 10.15 - samples/sec: 14460.30 - lr: 0.100000 +2023-04-06 03:01:03,564 epoch 28 - iter 530/2650 - loss 0.11636204 - time (sec): 20.33 - samples/sec: 14507.23 - lr: 0.100000 +2023-04-06 03:01:13,867 epoch 28 - iter 795/2650 - loss 0.11644613 - time (sec): 30.63 - samples/sec: 14451.61 - lr: 0.100000 +2023-04-06 03:01:24,055 epoch 28 - iter 1060/2650 - loss 0.11556522 - time (sec): 40.82 - samples/sec: 14493.62 - lr: 0.100000 +2023-04-06 03:01:34,136 epoch 28 - iter 1325/2650 - loss 0.11511233 - time (sec): 50.90 - samples/sec: 14495.69 - lr: 0.100000 +2023-04-06 03:01:44,274 epoch 28 - iter 1590/2650 - loss 0.11496479 - time (sec): 61.04 - samples/sec: 14499.46 - lr: 0.100000 +2023-04-06 03:01:54,423 epoch 28 - iter 1855/2650 - loss 0.11482776 - time (sec): 71.19 - samples/sec: 14490.97 - lr: 0.100000 +2023-04-06 03:02:04,531 epoch 28 - iter 2120/2650 - loss 0.11470406 - time (sec): 81.30 - samples/sec: 14501.99 - lr: 0.100000 +2023-04-06 03:02:14,735 epoch 28 - iter 2385/2650 - loss 0.11486332 - time (sec): 91.50 - samples/sec: 14503.97 - lr: 0.100000 +2023-04-06 03:02:24,830 epoch 28 - iter 2650/2650 - loss 0.11540754 - time (sec): 101.60 - samples/sec: 14506.40 - lr: 0.100000 +2023-04-06 03:02:24,831 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:02:24,831 EPOCH 28 done: loss 0.1154 - lr 0.100000 +2023-04-06 03:02:24,831 BAD EPOCHS (no improvement): 0 +2023-04-06 03:02:24,835 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:02:34,974 epoch 29 - iter 265/2650 - loss 0.11094091 - time (sec): 10.14 - samples/sec: 14480.08 - lr: 0.100000 +2023-04-06 03:02:45,058 epoch 29 - iter 530/2650 - loss 0.11198180 - time (sec): 20.22 - samples/sec: 14497.90 - lr: 0.100000 +2023-04-06 03:02:55,125 epoch 29 - iter 795/2650 - loss 0.11323540 - time (sec): 30.29 - samples/sec: 14503.88 - lr: 0.100000 +2023-04-06 03:03:05,414 epoch 29 - iter 1060/2650 - loss 0.11363722 - time (sec): 40.58 - samples/sec: 14497.84 - lr: 0.100000 +2023-04-06 03:03:15,523 epoch 29 - iter 1325/2650 - loss 0.11393199 - time (sec): 50.69 - samples/sec: 14502.63 - lr: 0.100000 +2023-04-06 03:03:25,640 epoch 29 - iter 1590/2650 - loss 0.11406230 - time (sec): 60.80 - samples/sec: 14500.47 - lr: 0.100000 +2023-04-06 03:03:35,898 epoch 29 - iter 1855/2650 - loss 0.11415852 - time (sec): 71.06 - samples/sec: 14498.74 - lr: 0.100000 +2023-04-06 03:03:46,168 epoch 29 - iter 2120/2650 - loss 0.11458403 - time (sec): 81.33 - samples/sec: 14487.61 - lr: 0.100000 +2023-04-06 03:03:56,381 epoch 29 - iter 2385/2650 - loss 0.11499700 - time (sec): 91.55 - samples/sec: 14491.85 - lr: 0.100000 +2023-04-06 03:04:06,557 epoch 29 - iter 2650/2650 - loss 0.11547526 - time (sec): 101.72 - samples/sec: 14488.76 - lr: 0.100000 +2023-04-06 03:04:06,557 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:04:06,557 EPOCH 29 done: loss 0.1155 - lr 0.100000 +2023-04-06 03:04:06,557 BAD EPOCHS (no improvement): 1 +2023-04-06 03:04:06,562 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:04:16,617 epoch 30 - iter 265/2650 - loss 0.11136787 - time (sec): 10.06 - samples/sec: 14527.09 - lr: 0.100000 +2023-04-06 03:04:26,847 epoch 30 - iter 530/2650 - loss 0.11257179 - time (sec): 20.29 - samples/sec: 14462.29 - lr: 0.100000 +2023-04-06 03:04:36,966 epoch 30 - iter 795/2650 - loss 0.11328101 - time (sec): 30.40 - samples/sec: 14491.48 - lr: 0.100000 +2023-04-06 03:04:46,998 epoch 30 - iter 1060/2650 - loss 0.11386128 - time (sec): 40.44 - samples/sec: 14480.12 - lr: 0.100000 +2023-04-06 03:04:57,279 epoch 30 - iter 1325/2650 - loss 0.11363796 - time (sec): 50.72 - samples/sec: 14499.04 - lr: 0.100000 +2023-04-06 03:05:07,470 epoch 30 - iter 1590/2650 - loss 0.11377181 - time (sec): 60.91 - samples/sec: 14489.64 - lr: 0.100000 +2023-04-06 03:05:17,580 epoch 30 - iter 1855/2650 - loss 0.11410581 - time (sec): 71.02 - samples/sec: 14490.20 - lr: 0.100000 +2023-04-06 03:05:27,855 epoch 30 - iter 2120/2650 - loss 0.11439768 - time (sec): 81.29 - samples/sec: 14487.39 - lr: 0.100000 +2023-04-06 03:05:38,083 epoch 30 - iter 2385/2650 - loss 0.11436200 - time (sec): 91.52 - samples/sec: 14487.34 - lr: 0.100000 +2023-04-06 03:05:48,359 epoch 30 - iter 2650/2650 - loss 0.11458164 - time (sec): 101.80 - samples/sec: 14478.00 - lr: 0.100000 +2023-04-06 03:05:48,360 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:05:48,360 EPOCH 30 done: loss 0.1146 - lr 0.100000 +2023-04-06 03:05:48,360 BAD EPOCHS (no improvement): 0 +2023-04-06 03:05:48,364 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:05:58,376 epoch 31 - iter 265/2650 - loss 0.11248197 - time (sec): 10.01 - samples/sec: 14649.37 - lr: 0.100000 +2023-04-06 03:06:08,543 epoch 31 - iter 530/2650 - loss 0.11220198 - time (sec): 20.18 - samples/sec: 14607.13 - lr: 0.100000 +2023-04-06 03:06:18,748 epoch 31 - iter 795/2650 - loss 0.11282419 - time (sec): 30.38 - samples/sec: 14579.98 - lr: 0.100000 +2023-04-06 03:06:29,125 epoch 31 - iter 1060/2650 - loss 0.11274826 - time (sec): 40.76 - samples/sec: 14541.94 - lr: 0.100000 +2023-04-06 03:06:39,378 epoch 31 - iter 1325/2650 - loss 0.11249278 - time (sec): 51.01 - samples/sec: 14545.94 - lr: 0.100000 +2023-04-06 03:06:49,432 epoch 31 - iter 1590/2650 - loss 0.11280664 - time (sec): 61.07 - samples/sec: 14545.54 - lr: 0.100000 +2023-04-06 03:06:59,455 epoch 31 - iter 1855/2650 - loss 0.11275980 - time (sec): 71.09 - samples/sec: 14530.24 - lr: 0.100000 +2023-04-06 03:07:09,703 epoch 31 - iter 2120/2650 - loss 0.11299282 - time (sec): 81.34 - samples/sec: 14516.02 - lr: 0.100000 +2023-04-06 03:07:19,800 epoch 31 - iter 2385/2650 - loss 0.11324056 - time (sec): 91.44 - samples/sec: 14506.11 - lr: 0.100000 +2023-04-06 03:07:29,972 epoch 31 - iter 2650/2650 - loss 0.11344515 - time (sec): 101.61 - samples/sec: 14505.11 - lr: 0.100000 +2023-04-06 03:07:29,972 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:07:29,972 EPOCH 31 done: loss 0.1134 - lr 0.100000 +2023-04-06 03:07:29,972 BAD EPOCHS (no improvement): 0 +2023-04-06 03:07:29,979 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:07:40,188 epoch 32 - iter 265/2650 - loss 0.11168567 - time (sec): 10.21 - samples/sec: 14386.89 - lr: 0.100000 +2023-04-06 03:07:50,285 epoch 32 - iter 530/2650 - loss 0.11092435 - time (sec): 20.31 - samples/sec: 14495.02 - lr: 0.100000 +2023-04-06 03:08:00,457 epoch 32 - iter 795/2650 - loss 0.11149130 - time (sec): 30.48 - samples/sec: 14497.76 - lr: 0.100000 +2023-04-06 03:08:10,524 epoch 32 - iter 1060/2650 - loss 0.11090007 - time (sec): 40.55 - samples/sec: 14514.13 - lr: 0.100000 +2023-04-06 03:08:20,754 epoch 32 - iter 1325/2650 - loss 0.11069172 - time (sec): 50.78 - samples/sec: 14501.48 - lr: 0.100000 +2023-04-06 03:08:30,970 epoch 32 - iter 1590/2650 - loss 0.11097007 - time (sec): 60.99 - samples/sec: 14479.04 - lr: 0.100000 +2023-04-06 03:08:41,106 epoch 32 - iter 1855/2650 - loss 0.11121026 - time (sec): 71.13 - samples/sec: 14468.30 - lr: 0.100000 +2023-04-06 03:08:51,200 epoch 32 - iter 2120/2650 - loss 0.11135049 - time (sec): 81.22 - samples/sec: 14479.23 - lr: 0.100000 +2023-04-06 03:09:05,842 epoch 32 - iter 2385/2650 - loss 0.11112958 - time (sec): 95.86 - samples/sec: 13822.47 - lr: 0.100000 +2023-04-06 03:09:15,932 epoch 32 - iter 2650/2650 - loss 0.11164622 - time (sec): 105.95 - samples/sec: 13910.15 - lr: 0.100000 +2023-04-06 03:09:15,932 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:09:15,932 EPOCH 32 done: loss 0.1116 - lr 0.100000 +2023-04-06 03:09:15,932 BAD EPOCHS (no improvement): 0 +2023-04-06 03:09:15,936 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:09:26,017 epoch 33 - iter 265/2650 - loss 0.10994651 - time (sec): 10.08 - samples/sec: 14528.73 - lr: 0.100000 +2023-04-06 03:09:36,248 epoch 33 - iter 530/2650 - loss 0.10955454 - time (sec): 20.31 - samples/sec: 14499.08 - lr: 0.100000 +2023-04-06 03:09:46,529 epoch 33 - iter 795/2650 - loss 0.11039709 - time (sec): 30.59 - samples/sec: 14482.52 - lr: 0.100000 +2023-04-06 03:09:56,901 epoch 33 - iter 1060/2650 - loss 0.11036861 - time (sec): 40.97 - samples/sec: 14467.27 - lr: 0.100000 +2023-04-06 03:10:07,219 epoch 33 - iter 1325/2650 - loss 0.11046170 - time (sec): 51.28 - samples/sec: 14443.29 - lr: 0.100000 +2023-04-06 03:10:17,441 epoch 33 - iter 1590/2650 - loss 0.11053548 - time (sec): 61.50 - samples/sec: 14436.83 - lr: 0.100000 +2023-04-06 03:10:27,671 epoch 33 - iter 1855/2650 - loss 0.11080650 - time (sec): 71.73 - samples/sec: 14431.22 - lr: 0.100000 +2023-04-06 03:10:37,687 epoch 33 - iter 2120/2650 - loss 0.11111538 - time (sec): 81.75 - samples/sec: 14435.66 - lr: 0.100000 +2023-04-06 03:10:47,949 epoch 33 - iter 2385/2650 - loss 0.11122260 - time (sec): 92.01 - samples/sec: 14433.32 - lr: 0.100000 +2023-04-06 03:10:58,084 epoch 33 - iter 2650/2650 - loss 0.11108717 - time (sec): 102.15 - samples/sec: 14428.25 - lr: 0.100000 +2023-04-06 03:10:58,085 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:10:58,085 EPOCH 33 done: loss 0.1111 - lr 0.100000 +2023-04-06 03:10:58,085 BAD EPOCHS (no improvement): 0 +2023-04-06 03:10:58,088 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:11:08,240 epoch 34 - iter 265/2650 - loss 0.10804496 - time (sec): 10.15 - samples/sec: 14416.33 - lr: 0.100000 +2023-04-06 03:11:18,408 epoch 34 - iter 530/2650 - loss 0.11029659 - time (sec): 20.32 - samples/sec: 14366.49 - lr: 0.100000 +2023-04-06 03:11:28,642 epoch 34 - iter 795/2650 - loss 0.11101355 - time (sec): 30.55 - samples/sec: 14390.57 - lr: 0.100000 +2023-04-06 03:11:38,922 epoch 34 - iter 1060/2650 - loss 0.11101306 - time (sec): 40.83 - samples/sec: 14404.16 - lr: 0.100000 +2023-04-06 03:11:49,083 epoch 34 - iter 1325/2650 - loss 0.11102473 - time (sec): 50.99 - samples/sec: 14443.68 - lr: 0.100000 +2023-04-06 03:11:59,330 epoch 34 - iter 1590/2650 - loss 0.11100294 - time (sec): 61.24 - samples/sec: 14454.09 - lr: 0.100000 +2023-04-06 03:12:09,575 epoch 34 - iter 1855/2650 - loss 0.11033303 - time (sec): 71.49 - samples/sec: 14448.29 - lr: 0.100000 +2023-04-06 03:12:19,633 epoch 34 - iter 2120/2650 - loss 0.11018846 - time (sec): 81.54 - samples/sec: 14460.02 - lr: 0.100000 +2023-04-06 03:12:29,800 epoch 34 - iter 2385/2650 - loss 0.11043041 - time (sec): 91.71 - samples/sec: 14467.84 - lr: 0.100000 +2023-04-06 03:12:40,008 epoch 34 - iter 2650/2650 - loss 0.11051184 - time (sec): 101.92 - samples/sec: 14460.57 - lr: 0.100000 +2023-04-06 03:12:40,009 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:12:40,009 EPOCH 34 done: loss 0.1105 - lr 0.100000 +2023-04-06 03:12:40,009 BAD EPOCHS (no improvement): 0 +2023-04-06 03:12:40,013 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:12:50,278 epoch 35 - iter 265/2650 - loss 0.10831856 - time (sec): 10.27 - samples/sec: 14471.00 - lr: 0.100000 +2023-04-06 03:13:00,394 epoch 35 - iter 530/2650 - loss 0.10793836 - time (sec): 20.38 - samples/sec: 14480.07 - lr: 0.100000 +2023-04-06 03:13:10,485 epoch 35 - iter 795/2650 - loss 0.10765931 - time (sec): 30.47 - samples/sec: 14520.41 - lr: 0.100000 +2023-04-06 03:13:20,546 epoch 35 - iter 1060/2650 - loss 0.10800576 - time (sec): 40.53 - samples/sec: 14503.46 - lr: 0.100000 +2023-04-06 03:13:30,629 epoch 35 - iter 1325/2650 - loss 0.10807675 - time (sec): 50.62 - samples/sec: 14508.02 - lr: 0.100000 +2023-04-06 03:13:40,782 epoch 35 - iter 1590/2650 - loss 0.10794832 - time (sec): 60.77 - samples/sec: 14496.87 - lr: 0.100000 +2023-04-06 03:13:51,022 epoch 35 - iter 1855/2650 - loss 0.10840180 - time (sec): 71.01 - samples/sec: 14515.54 - lr: 0.100000 +2023-04-06 03:14:01,262 epoch 35 - iter 2120/2650 - loss 0.10860036 - time (sec): 81.25 - samples/sec: 14507.39 - lr: 0.100000 +2023-04-06 03:14:11,314 epoch 35 - iter 2385/2650 - loss 0.10874207 - time (sec): 91.30 - samples/sec: 14516.79 - lr: 0.100000 +2023-04-06 03:14:21,577 epoch 35 - iter 2650/2650 - loss 0.10898570 - time (sec): 101.56 - samples/sec: 14511.20 - lr: 0.100000 +2023-04-06 03:14:21,578 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:14:21,578 EPOCH 35 done: loss 0.1090 - lr 0.100000 +2023-04-06 03:14:21,578 BAD EPOCHS (no improvement): 0 +2023-04-06 03:14:21,581 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:14:31,826 epoch 36 - iter 265/2650 - loss 0.10788251 - time (sec): 10.24 - samples/sec: 14505.09 - lr: 0.100000 +2023-04-06 03:14:41,918 epoch 36 - iter 530/2650 - loss 0.10740207 - time (sec): 20.34 - samples/sec: 14552.45 - lr: 0.100000 +2023-04-06 03:14:51,980 epoch 36 - iter 795/2650 - loss 0.10764120 - time (sec): 30.40 - samples/sec: 14574.25 - lr: 0.100000 +2023-04-06 03:15:02,111 epoch 36 - iter 1060/2650 - loss 0.10754894 - time (sec): 40.53 - samples/sec: 14550.73 - lr: 0.100000 +2023-04-06 03:15:12,234 epoch 36 - iter 1325/2650 - loss 0.10780693 - time (sec): 50.65 - samples/sec: 14523.40 - lr: 0.100000 +2023-04-06 03:15:22,571 epoch 36 - iter 1590/2650 - loss 0.10736396 - time (sec): 60.99 - samples/sec: 14498.31 - lr: 0.100000 +2023-04-06 03:15:32,853 epoch 36 - iter 1855/2650 - loss 0.10741221 - time (sec): 71.27 - samples/sec: 14482.21 - lr: 0.100000 +2023-04-06 03:15:42,958 epoch 36 - iter 2120/2650 - loss 0.10827643 - time (sec): 81.38 - samples/sec: 14481.21 - lr: 0.100000 +2023-04-06 03:15:53,274 epoch 36 - iter 2385/2650 - loss 0.10829258 - time (sec): 91.69 - samples/sec: 14472.16 - lr: 0.100000 +2023-04-06 03:16:03,461 epoch 36 - iter 2650/2650 - loss 0.10859554 - time (sec): 101.88 - samples/sec: 14466.26 - lr: 0.100000 +2023-04-06 03:16:03,461 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:16:03,461 EPOCH 36 done: loss 0.1086 - lr 0.100000 +2023-04-06 03:16:03,462 BAD EPOCHS (no improvement): 0 +2023-04-06 03:16:03,466 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:16:13,642 epoch 37 - iter 265/2650 - loss 0.10384978 - time (sec): 10.18 - samples/sec: 14405.68 - lr: 0.100000 +2023-04-06 03:16:23,776 epoch 37 - iter 530/2650 - loss 0.10634621 - time (sec): 20.31 - samples/sec: 14421.16 - lr: 0.100000 +2023-04-06 03:16:33,962 epoch 37 - iter 795/2650 - loss 0.10727941 - time (sec): 30.50 - samples/sec: 14427.85 - lr: 0.100000 +2023-04-06 03:16:44,020 epoch 37 - iter 1060/2650 - loss 0.10737745 - time (sec): 40.55 - samples/sec: 14438.21 - lr: 0.100000 +2023-04-06 03:16:54,224 epoch 37 - iter 1325/2650 - loss 0.10735344 - time (sec): 50.76 - samples/sec: 14447.04 - lr: 0.100000 +2023-04-06 03:17:04,568 epoch 37 - iter 1590/2650 - loss 0.10712530 - time (sec): 61.10 - samples/sec: 14440.36 - lr: 0.100000 +2023-04-06 03:17:14,781 epoch 37 - iter 1855/2650 - loss 0.10756790 - time (sec): 71.32 - samples/sec: 14439.95 - lr: 0.100000 +2023-04-06 03:17:24,943 epoch 37 - iter 2120/2650 - loss 0.10759782 - time (sec): 81.48 - samples/sec: 14463.48 - lr: 0.100000 +2023-04-06 03:17:35,107 epoch 37 - iter 2385/2650 - loss 0.10780179 - time (sec): 91.64 - samples/sec: 14457.68 - lr: 0.100000 +2023-04-06 03:17:45,385 epoch 37 - iter 2650/2650 - loss 0.10778955 - time (sec): 101.92 - samples/sec: 14460.76 - lr: 0.100000 +2023-04-06 03:17:45,385 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:17:45,385 EPOCH 37 done: loss 0.1078 - lr 0.100000 +2023-04-06 03:17:45,385 BAD EPOCHS (no improvement): 0 +2023-04-06 03:17:45,393 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:17:55,529 epoch 38 - iter 265/2650 - loss 0.10570748 - time (sec): 10.14 - samples/sec: 14457.97 - lr: 0.100000 +2023-04-06 03:18:05,736 epoch 38 - iter 530/2650 - loss 0.10557299 - time (sec): 20.34 - samples/sec: 14488.76 - lr: 0.100000 +2023-04-06 03:18:15,827 epoch 38 - iter 795/2650 - loss 0.10594499 - time (sec): 30.43 - samples/sec: 14482.00 - lr: 0.100000 +2023-04-06 03:18:25,968 epoch 38 - iter 1060/2650 - loss 0.10626719 - time (sec): 40.57 - samples/sec: 14480.05 - lr: 0.100000 +2023-04-06 03:18:36,045 epoch 38 - iter 1325/2650 - loss 0.10562089 - time (sec): 50.65 - samples/sec: 14480.12 - lr: 0.100000 +2023-04-06 03:18:46,374 epoch 38 - iter 1590/2650 - loss 0.10598904 - time (sec): 60.98 - samples/sec: 14468.54 - lr: 0.100000 +2023-04-06 03:18:56,590 epoch 38 - iter 1855/2650 - loss 0.10633313 - time (sec): 71.20 - samples/sec: 14478.44 - lr: 0.100000 +2023-04-06 03:19:06,863 epoch 38 - iter 2120/2650 - loss 0.10638861 - time (sec): 81.47 - samples/sec: 14465.81 - lr: 0.100000 +2023-04-06 03:19:17,122 epoch 38 - iter 2385/2650 - loss 0.10656406 - time (sec): 91.73 - samples/sec: 14465.54 - lr: 0.100000 +2023-04-06 03:19:27,326 epoch 38 - iter 2650/2650 - loss 0.10680210 - time (sec): 101.93 - samples/sec: 14458.81 - lr: 0.100000 +2023-04-06 03:19:27,326 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:19:27,326 EPOCH 38 done: loss 0.1068 - lr 0.100000 +2023-04-06 03:19:27,326 BAD EPOCHS (no improvement): 0 +2023-04-06 03:19:27,330 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:19:41,638 epoch 39 - iter 265/2650 - loss 0.10432243 - time (sec): 14.31 - samples/sec: 10261.65 - lr: 0.100000 +2023-04-06 03:19:51,880 epoch 39 - iter 530/2650 - loss 0.10331434 - time (sec): 24.55 - samples/sec: 12000.17 - lr: 0.100000 +2023-04-06 03:20:01,932 epoch 39 - iter 795/2650 - loss 0.10336967 - time (sec): 34.60 - samples/sec: 12719.87 - lr: 0.100000 +2023-04-06 03:20:12,098 epoch 39 - iter 1060/2650 - loss 0.10417723 - time (sec): 44.77 - samples/sec: 13097.45 - lr: 0.100000 +2023-04-06 03:20:22,127 epoch 39 - iter 1325/2650 - loss 0.10425367 - time (sec): 54.80 - samples/sec: 13367.57 - lr: 0.100000 +2023-04-06 03:20:32,221 epoch 39 - iter 1590/2650 - loss 0.10467140 - time (sec): 64.89 - samples/sec: 13533.80 - lr: 0.100000 +2023-04-06 03:20:42,564 epoch 39 - iter 1855/2650 - loss 0.10490396 - time (sec): 75.23 - samples/sec: 13651.56 - lr: 0.100000 +2023-04-06 03:20:52,886 epoch 39 - iter 2120/2650 - loss 0.10490401 - time (sec): 85.56 - samples/sec: 13738.02 - lr: 0.100000 +2023-04-06 03:21:03,164 epoch 39 - iter 2385/2650 - loss 0.10513213 - time (sec): 95.83 - samples/sec: 13826.25 - lr: 0.100000 +2023-04-06 03:21:13,523 epoch 39 - iter 2650/2650 - loss 0.10510118 - time (sec): 106.19 - samples/sec: 13878.71 - lr: 0.100000 +2023-04-06 03:21:13,524 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:21:13,524 EPOCH 39 done: loss 0.1051 - lr 0.100000 +2023-04-06 03:21:13,524 BAD EPOCHS (no improvement): 0 +2023-04-06 03:21:13,527 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:21:23,668 epoch 40 - iter 265/2650 - loss 0.10265434 - time (sec): 10.14 - samples/sec: 14535.90 - lr: 0.100000 +2023-04-06 03:21:33,876 epoch 40 - iter 530/2650 - loss 0.10365321 - time (sec): 20.35 - samples/sec: 14493.49 - lr: 0.100000 +2023-04-06 03:21:44,011 epoch 40 - iter 795/2650 - loss 0.10497334 - time (sec): 30.48 - samples/sec: 14492.45 - lr: 0.100000 +2023-04-06 03:21:54,202 epoch 40 - iter 1060/2650 - loss 0.10496029 - time (sec): 40.67 - samples/sec: 14480.55 - lr: 0.100000 +2023-04-06 03:22:04,395 epoch 40 - iter 1325/2650 - loss 0.10546813 - time (sec): 50.87 - samples/sec: 14472.27 - lr: 0.100000 +2023-04-06 03:22:14,613 epoch 40 - iter 1590/2650 - loss 0.10615589 - time (sec): 61.09 - samples/sec: 14463.90 - lr: 0.100000 +2023-04-06 03:22:24,791 epoch 40 - iter 1855/2650 - loss 0.10592352 - time (sec): 71.26 - samples/sec: 14468.09 - lr: 0.100000 +2023-04-06 03:22:34,982 epoch 40 - iter 2120/2650 - loss 0.10606295 - time (sec): 81.45 - samples/sec: 14478.93 - lr: 0.100000 +2023-04-06 03:22:45,218 epoch 40 - iter 2385/2650 - loss 0.10592030 - time (sec): 91.69 - samples/sec: 14467.32 - lr: 0.100000 +2023-04-06 03:22:55,319 epoch 40 - iter 2650/2650 - loss 0.10593371 - time (sec): 101.79 - samples/sec: 14478.83 - lr: 0.100000 +2023-04-06 03:22:55,319 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:22:55,319 EPOCH 40 done: loss 0.1059 - lr 0.100000 +2023-04-06 03:22:55,319 BAD EPOCHS (no improvement): 1 +2023-04-06 03:22:55,323 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:23:05,500 epoch 41 - iter 265/2650 - loss 0.10130094 - time (sec): 10.18 - samples/sec: 14454.15 - lr: 0.100000 +2023-04-06 03:23:15,582 epoch 41 - iter 530/2650 - loss 0.10367368 - time (sec): 20.26 - samples/sec: 14442.85 - lr: 0.100000 +2023-04-06 03:23:26,021 epoch 41 - iter 795/2650 - loss 0.10431402 - time (sec): 30.70 - samples/sec: 14394.50 - lr: 0.100000 +2023-04-06 03:23:36,296 epoch 41 - iter 1060/2650 - loss 0.10481347 - time (sec): 40.97 - samples/sec: 14390.52 - lr: 0.100000 +2023-04-06 03:23:46,591 epoch 41 - iter 1325/2650 - loss 0.10491229 - time (sec): 51.27 - samples/sec: 14372.36 - lr: 0.100000 +2023-04-06 03:23:56,822 epoch 41 - iter 1590/2650 - loss 0.10525395 - time (sec): 61.50 - samples/sec: 14387.20 - lr: 0.100000 +2023-04-06 03:24:07,105 epoch 41 - iter 1855/2650 - loss 0.10489447 - time (sec): 71.78 - samples/sec: 14402.07 - lr: 0.100000 +2023-04-06 03:24:17,133 epoch 41 - iter 2120/2650 - loss 0.10496334 - time (sec): 81.81 - samples/sec: 14425.92 - lr: 0.100000 +2023-04-06 03:24:27,374 epoch 41 - iter 2385/2650 - loss 0.10504976 - time (sec): 92.05 - samples/sec: 14427.86 - lr: 0.100000 +2023-04-06 03:24:37,353 epoch 41 - iter 2650/2650 - loss 0.10524753 - time (sec): 102.03 - samples/sec: 14445.06 - lr: 0.100000 +2023-04-06 03:24:37,353 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:24:37,353 EPOCH 41 done: loss 0.1052 - lr 0.100000 +2023-04-06 03:24:37,354 BAD EPOCHS (no improvement): 2 +2023-04-06 03:24:37,357 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:24:47,535 epoch 42 - iter 265/2650 - loss 0.10323283 - time (sec): 10.18 - samples/sec: 14453.13 - lr: 0.100000 +2023-04-06 03:24:57,753 epoch 42 - iter 530/2650 - loss 0.10419123 - time (sec): 20.40 - samples/sec: 14485.24 - lr: 0.100000 +2023-04-06 03:25:07,998 epoch 42 - iter 795/2650 - loss 0.10324302 - time (sec): 30.64 - samples/sec: 14464.06 - lr: 0.100000 +2023-04-06 03:25:18,289 epoch 42 - iter 1060/2650 - loss 0.10360180 - time (sec): 40.93 - samples/sec: 14479.09 - lr: 0.100000 +2023-04-06 03:25:28,537 epoch 42 - iter 1325/2650 - loss 0.10371275 - time (sec): 51.18 - samples/sec: 14490.27 - lr: 0.100000 +2023-04-06 03:25:38,705 epoch 42 - iter 1590/2650 - loss 0.10357423 - time (sec): 61.35 - samples/sec: 14484.42 - lr: 0.100000 +2023-04-06 03:25:48,884 epoch 42 - iter 1855/2650 - loss 0.10414813 - time (sec): 71.53 - samples/sec: 14493.83 - lr: 0.100000 +2023-04-06 03:25:58,827 epoch 42 - iter 2120/2650 - loss 0.10444400 - time (sec): 81.47 - samples/sec: 14508.15 - lr: 0.100000 +2023-04-06 03:26:08,843 epoch 42 - iter 2385/2650 - loss 0.10432094 - time (sec): 91.49 - samples/sec: 14505.49 - lr: 0.100000 +2023-04-06 03:26:18,975 epoch 42 - iter 2650/2650 - loss 0.10437226 - time (sec): 101.62 - samples/sec: 14503.62 - lr: 0.100000 +2023-04-06 03:26:18,975 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:26:18,975 EPOCH 42 done: loss 0.1044 - lr 0.100000 +2023-04-06 03:26:18,976 BAD EPOCHS (no improvement): 0 +2023-04-06 03:26:18,979 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:26:29,130 epoch 43 - iter 265/2650 - loss 0.10083172 - time (sec): 10.15 - samples/sec: 14539.44 - lr: 0.100000 +2023-04-06 03:26:39,346 epoch 43 - iter 530/2650 - loss 0.10151996 - time (sec): 20.37 - samples/sec: 14509.36 - lr: 0.100000 +2023-04-06 03:26:49,521 epoch 43 - iter 795/2650 - loss 0.10268388 - time (sec): 30.54 - samples/sec: 14510.70 - lr: 0.100000 +2023-04-06 03:26:59,500 epoch 43 - iter 1060/2650 - loss 0.10258307 - time (sec): 40.52 - samples/sec: 14514.71 - lr: 0.100000 +2023-04-06 03:27:09,744 epoch 43 - iter 1325/2650 - loss 0.10315747 - time (sec): 50.77 - samples/sec: 14523.34 - lr: 0.100000 +2023-04-06 03:27:19,896 epoch 43 - iter 1590/2650 - loss 0.10286153 - time (sec): 60.92 - samples/sec: 14512.09 - lr: 0.100000 +2023-04-06 03:27:29,904 epoch 43 - iter 1855/2650 - loss 0.10311719 - time (sec): 70.93 - samples/sec: 14515.37 - lr: 0.100000 +2023-04-06 03:27:40,193 epoch 43 - iter 2120/2650 - loss 0.10336652 - time (sec): 81.21 - samples/sec: 14507.61 - lr: 0.100000 +2023-04-06 03:27:50,410 epoch 43 - iter 2385/2650 - loss 0.10339573 - time (sec): 91.43 - samples/sec: 14499.55 - lr: 0.100000 +2023-04-06 03:28:00,645 epoch 43 - iter 2650/2650 - loss 0.10351059 - time (sec): 101.67 - samples/sec: 14496.63 - lr: 0.100000 +2023-04-06 03:28:00,646 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:28:00,646 EPOCH 43 done: loss 0.1035 - lr 0.100000 +2023-04-06 03:28:00,646 BAD EPOCHS (no improvement): 0 +2023-04-06 03:28:00,652 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:28:10,749 epoch 44 - iter 265/2650 - loss 0.10195232 - time (sec): 10.10 - samples/sec: 14578.62 - lr: 0.100000 +2023-04-06 03:28:20,843 epoch 44 - iter 530/2650 - loss 0.10254630 - time (sec): 20.19 - samples/sec: 14566.69 - lr: 0.100000 +2023-04-06 03:28:30,990 epoch 44 - iter 795/2650 - loss 0.10152202 - time (sec): 30.34 - samples/sec: 14531.10 - lr: 0.100000 +2023-04-06 03:28:41,152 epoch 44 - iter 1060/2650 - loss 0.10178913 - time (sec): 40.50 - samples/sec: 14502.41 - lr: 0.100000 +2023-04-06 03:28:51,282 epoch 44 - iter 1325/2650 - loss 0.10260791 - time (sec): 50.63 - samples/sec: 14497.21 - lr: 0.100000 +2023-04-06 03:29:01,648 epoch 44 - iter 1590/2650 - loss 0.10284586 - time (sec): 61.00 - samples/sec: 14489.94 - lr: 0.100000 +2023-04-06 03:29:11,920 epoch 44 - iter 1855/2650 - loss 0.10261140 - time (sec): 71.27 - samples/sec: 14496.67 - lr: 0.100000 +2023-04-06 03:29:22,138 epoch 44 - iter 2120/2650 - loss 0.10245075 - time (sec): 81.49 - samples/sec: 14489.85 - lr: 0.100000 +2023-04-06 03:29:32,272 epoch 44 - iter 2385/2650 - loss 0.10289228 - time (sec): 91.62 - samples/sec: 14488.84 - lr: 0.100000 +2023-04-06 03:29:42,424 epoch 44 - iter 2650/2650 - loss 0.10293020 - time (sec): 101.77 - samples/sec: 14481.57 - lr: 0.100000 +2023-04-06 03:29:42,425 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:29:42,425 EPOCH 44 done: loss 0.1029 - lr 0.100000 +2023-04-06 03:29:42,425 BAD EPOCHS (no improvement): 0 +2023-04-06 03:29:42,428 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:29:52,607 epoch 45 - iter 265/2650 - loss 0.10215330 - time (sec): 10.18 - samples/sec: 14540.70 - lr: 0.100000 +2023-04-06 03:30:06,894 epoch 45 - iter 530/2650 - loss 0.10267703 - time (sec): 24.47 - samples/sec: 12073.32 - lr: 0.100000 +2023-04-06 03:30:17,180 epoch 45 - iter 795/2650 - loss 0.10292609 - time (sec): 34.75 - samples/sec: 12777.38 - lr: 0.100000 +2023-04-06 03:30:27,309 epoch 45 - iter 1060/2650 - loss 0.10202975 - time (sec): 44.88 - samples/sec: 13141.77 - lr: 0.100000 +2023-04-06 03:30:37,466 epoch 45 - iter 1325/2650 - loss 0.10126806 - time (sec): 55.04 - samples/sec: 13384.93 - lr: 0.100000 +2023-04-06 03:30:47,660 epoch 45 - iter 1590/2650 - loss 0.10134050 - time (sec): 65.23 - samples/sec: 13559.00 - lr: 0.100000 +2023-04-06 03:30:57,772 epoch 45 - iter 1855/2650 - loss 0.10192792 - time (sec): 75.34 - samples/sec: 13681.75 - lr: 0.100000 +2023-04-06 03:31:07,913 epoch 45 - iter 2120/2650 - loss 0.10199745 - time (sec): 85.48 - samples/sec: 13779.01 - lr: 0.100000 +2023-04-06 03:31:18,077 epoch 45 - iter 2385/2650 - loss 0.10209801 - time (sec): 95.65 - samples/sec: 13849.87 - lr: 0.100000 +2023-04-06 03:31:28,338 epoch 45 - iter 2650/2650 - loss 0.10242691 - time (sec): 105.91 - samples/sec: 13915.83 - lr: 0.100000 +2023-04-06 03:31:28,338 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:31:28,338 EPOCH 45 done: loss 0.1024 - lr 0.100000 +2023-04-06 03:31:28,338 BAD EPOCHS (no improvement): 0 +2023-04-06 03:31:28,342 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:31:38,591 epoch 46 - iter 265/2650 - loss 0.10072522 - time (sec): 10.25 - samples/sec: 14457.90 - lr: 0.100000 +2023-04-06 03:31:48,786 epoch 46 - iter 530/2650 - loss 0.10089247 - time (sec): 20.44 - samples/sec: 14502.85 - lr: 0.100000 +2023-04-06 03:31:59,102 epoch 46 - iter 795/2650 - loss 0.10210404 - time (sec): 30.76 - samples/sec: 14456.44 - lr: 0.100000 +2023-04-06 03:32:09,233 epoch 46 - iter 1060/2650 - loss 0.10163999 - time (sec): 40.89 - samples/sec: 14468.33 - lr: 0.100000 +2023-04-06 03:32:19,515 epoch 46 - iter 1325/2650 - loss 0.10222589 - time (sec): 51.17 - samples/sec: 14446.20 - lr: 0.100000 +2023-04-06 03:32:29,569 epoch 46 - iter 1590/2650 - loss 0.10164317 - time (sec): 61.23 - samples/sec: 14469.15 - lr: 0.100000 +2023-04-06 03:32:39,699 epoch 46 - iter 1855/2650 - loss 0.10188083 - time (sec): 71.36 - samples/sec: 14454.88 - lr: 0.100000 +2023-04-06 03:32:50,052 epoch 46 - iter 2120/2650 - loss 0.10196393 - time (sec): 81.71 - samples/sec: 14452.98 - lr: 0.100000 +2023-04-06 03:33:00,145 epoch 46 - iter 2385/2650 - loss 0.10209089 - time (sec): 91.80 - samples/sec: 14452.41 - lr: 0.100000 +2023-04-06 03:33:10,232 epoch 46 - iter 2650/2650 - loss 0.10223696 - time (sec): 101.89 - samples/sec: 14464.89 - lr: 0.100000 +2023-04-06 03:33:10,232 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:33:10,232 EPOCH 46 done: loss 0.1022 - lr 0.100000 +2023-04-06 03:33:10,232 BAD EPOCHS (no improvement): 0 +2023-04-06 03:33:10,236 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:33:20,469 epoch 47 - iter 265/2650 - loss 0.09908528 - time (sec): 10.23 - samples/sec: 14487.79 - lr: 0.100000 +2023-04-06 03:33:30,505 epoch 47 - iter 530/2650 - loss 0.10003158 - time (sec): 20.27 - samples/sec: 14538.23 - lr: 0.100000 +2023-04-06 03:33:40,618 epoch 47 - iter 795/2650 - loss 0.09998706 - time (sec): 30.38 - samples/sec: 14507.68 - lr: 0.100000 +2023-04-06 03:33:51,019 epoch 47 - iter 1060/2650 - loss 0.10065634 - time (sec): 40.78 - samples/sec: 14452.64 - lr: 0.100000 +2023-04-06 03:34:01,260 epoch 47 - iter 1325/2650 - loss 0.10035103 - time (sec): 51.02 - samples/sec: 14447.90 - lr: 0.100000 +2023-04-06 03:34:11,535 epoch 47 - iter 1590/2650 - loss 0.10056560 - time (sec): 61.30 - samples/sec: 14425.22 - lr: 0.100000 +2023-04-06 03:34:21,746 epoch 47 - iter 1855/2650 - loss 0.10045307 - time (sec): 71.51 - samples/sec: 14421.63 - lr: 0.100000 +2023-04-06 03:34:31,912 epoch 47 - iter 2120/2650 - loss 0.10081496 - time (sec): 81.68 - samples/sec: 14413.91 - lr: 0.100000 +2023-04-06 03:34:42,180 epoch 47 - iter 2385/2650 - loss 0.10112057 - time (sec): 91.94 - samples/sec: 14409.16 - lr: 0.100000 +2023-04-06 03:34:52,478 epoch 47 - iter 2650/2650 - loss 0.10077343 - time (sec): 102.24 - samples/sec: 14415.03 - lr: 0.100000 +2023-04-06 03:34:52,478 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:34:52,478 EPOCH 47 done: loss 0.1008 - lr 0.100000 +2023-04-06 03:34:52,478 BAD EPOCHS (no improvement): 0 +2023-04-06 03:34:52,483 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:35:02,715 epoch 48 - iter 265/2650 - loss 0.10196290 - time (sec): 10.23 - samples/sec: 14417.65 - lr: 0.100000 +2023-04-06 03:35:12,976 epoch 48 - iter 530/2650 - loss 0.10001255 - time (sec): 20.49 - samples/sec: 14370.35 - lr: 0.100000 +2023-04-06 03:35:23,322 epoch 48 - iter 795/2650 - loss 0.10015832 - time (sec): 30.84 - samples/sec: 14415.91 - lr: 0.100000 +2023-04-06 03:35:33,549 epoch 48 - iter 1060/2650 - loss 0.09994154 - time (sec): 41.07 - samples/sec: 14391.42 - lr: 0.100000 +2023-04-06 03:35:43,717 epoch 48 - iter 1325/2650 - loss 0.10039253 - time (sec): 51.23 - samples/sec: 14396.58 - lr: 0.100000 +2023-04-06 03:35:53,983 epoch 48 - iter 1590/2650 - loss 0.10059579 - time (sec): 61.50 - samples/sec: 14393.23 - lr: 0.100000 +2023-04-06 03:36:04,183 epoch 48 - iter 1855/2650 - loss 0.10033061 - time (sec): 71.70 - samples/sec: 14383.57 - lr: 0.100000 +2023-04-06 03:36:14,527 epoch 48 - iter 2120/2650 - loss 0.10034709 - time (sec): 82.04 - samples/sec: 14371.09 - lr: 0.100000 +2023-04-06 03:36:24,765 epoch 48 - iter 2385/2650 - loss 0.10030490 - time (sec): 92.28 - samples/sec: 14374.48 - lr: 0.100000 +2023-04-06 03:36:35,129 epoch 48 - iter 2650/2650 - loss 0.10045375 - time (sec): 102.65 - samples/sec: 14358.36 - lr: 0.100000 +2023-04-06 03:36:35,129 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:36:35,129 EPOCH 48 done: loss 0.1005 - lr 0.100000 +2023-04-06 03:36:35,129 BAD EPOCHS (no improvement): 0 +2023-04-06 03:36:35,132 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:36:45,562 epoch 49 - iter 265/2650 - loss 0.09913217 - time (sec): 10.43 - samples/sec: 14335.50 - lr: 0.100000 +2023-04-06 03:36:55,856 epoch 49 - iter 530/2650 - loss 0.09804710 - time (sec): 20.72 - samples/sec: 14338.33 - lr: 0.100000 +2023-04-06 03:37:06,187 epoch 49 - iter 795/2650 - loss 0.09802550 - time (sec): 31.05 - samples/sec: 14332.48 - lr: 0.100000 +2023-04-06 03:37:16,590 epoch 49 - iter 1060/2650 - loss 0.09797576 - time (sec): 41.46 - samples/sec: 14321.54 - lr: 0.100000 +2023-04-06 03:37:26,869 epoch 49 - iter 1325/2650 - loss 0.09827847 - time (sec): 51.74 - samples/sec: 14321.11 - lr: 0.100000 +2023-04-06 03:37:37,167 epoch 49 - iter 1590/2650 - loss 0.09819689 - time (sec): 62.03 - samples/sec: 14314.04 - lr: 0.100000 +2023-04-06 03:37:47,324 epoch 49 - iter 1855/2650 - loss 0.09830007 - time (sec): 72.19 - samples/sec: 14321.56 - lr: 0.100000 +2023-04-06 03:37:57,588 epoch 49 - iter 2120/2650 - loss 0.09860028 - time (sec): 82.46 - samples/sec: 14317.97 - lr: 0.100000 +2023-04-06 03:38:07,764 epoch 49 - iter 2385/2650 - loss 0.09895610 - time (sec): 92.63 - samples/sec: 14322.16 - lr: 0.100000 +2023-04-06 03:38:18,006 epoch 49 - iter 2650/2650 - loss 0.09922051 - time (sec): 102.87 - samples/sec: 14326.50 - lr: 0.100000 +2023-04-06 03:38:18,007 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:38:18,007 EPOCH 49 done: loss 0.0992 - lr 0.100000 +2023-04-06 03:38:18,007 BAD EPOCHS (no improvement): 0 +2023-04-06 03:38:18,014 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:38:28,256 epoch 50 - iter 265/2650 - loss 0.09678968 - time (sec): 10.24 - samples/sec: 14422.31 - lr: 0.100000 +2023-04-06 03:38:38,285 epoch 50 - iter 530/2650 - loss 0.09826595 - time (sec): 20.27 - samples/sec: 14463.83 - lr: 0.100000 +2023-04-06 03:38:48,296 epoch 50 - iter 795/2650 - loss 0.09811316 - time (sec): 30.28 - samples/sec: 14438.93 - lr: 0.100000 +2023-04-06 03:38:58,545 epoch 50 - iter 1060/2650 - loss 0.09851081 - time (sec): 40.53 - samples/sec: 14458.79 - lr: 0.100000 +2023-04-06 03:39:08,893 epoch 50 - iter 1325/2650 - loss 0.09838403 - time (sec): 50.88 - samples/sec: 14441.62 - lr: 0.100000 +2023-04-06 03:39:19,092 epoch 50 - iter 1590/2650 - loss 0.09887097 - time (sec): 61.08 - samples/sec: 14451.58 - lr: 0.100000 +2023-04-06 03:39:29,392 epoch 50 - iter 1855/2650 - loss 0.09870294 - time (sec): 71.38 - samples/sec: 14453.27 - lr: 0.100000 +2023-04-06 03:39:39,526 epoch 50 - iter 2120/2650 - loss 0.09882830 - time (sec): 81.51 - samples/sec: 14457.95 - lr: 0.100000 +2023-04-06 03:39:49,741 epoch 50 - iter 2385/2650 - loss 0.09893257 - time (sec): 91.73 - samples/sec: 14452.65 - lr: 0.100000 +2023-04-06 03:39:59,872 epoch 50 - iter 2650/2650 - loss 0.09916511 - time (sec): 101.86 - samples/sec: 14469.32 - lr: 0.100000 +2023-04-06 03:39:59,873 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:39:59,873 EPOCH 50 done: loss 0.0992 - lr 0.100000 +2023-04-06 03:39:59,873 BAD EPOCHS (no improvement): 0 +2023-04-06 03:39:59,876 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:40:09,997 epoch 51 - iter 265/2650 - loss 0.09663392 - time (sec): 10.12 - samples/sec: 14463.26 - lr: 0.100000 +2023-04-06 03:40:20,220 epoch 51 - iter 530/2650 - loss 0.09828781 - time (sec): 20.34 - samples/sec: 14495.55 - lr: 0.100000 +2023-04-06 03:40:30,613 epoch 51 - iter 795/2650 - loss 0.09817882 - time (sec): 30.74 - samples/sec: 14461.59 - lr: 0.100000 +2023-04-06 03:40:44,926 epoch 51 - iter 1060/2650 - loss 0.09843327 - time (sec): 45.05 - samples/sec: 13126.13 - lr: 0.100000 +2023-04-06 03:40:55,055 epoch 51 - iter 1325/2650 - loss 0.09898064 - time (sec): 55.18 - samples/sec: 13366.79 - lr: 0.100000 +2023-04-06 03:41:05,262 epoch 51 - iter 1590/2650 - loss 0.09868194 - time (sec): 65.39 - samples/sec: 13533.35 - lr: 0.100000 +2023-04-06 03:41:15,510 epoch 51 - iter 1855/2650 - loss 0.09855457 - time (sec): 75.63 - samples/sec: 13656.09 - lr: 0.100000 +2023-04-06 03:41:25,418 epoch 51 - iter 2120/2650 - loss 0.09870620 - time (sec): 85.54 - samples/sec: 13769.91 - lr: 0.100000 +2023-04-06 03:41:35,608 epoch 51 - iter 2385/2650 - loss 0.09878550 - time (sec): 95.73 - samples/sec: 13844.15 - lr: 0.100000 +2023-04-06 03:41:45,834 epoch 51 - iter 2650/2650 - loss 0.09884561 - time (sec): 105.96 - samples/sec: 13909.54 - lr: 0.100000 +2023-04-06 03:41:45,834 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:41:45,834 EPOCH 51 done: loss 0.0988 - lr 0.100000 +2023-04-06 03:41:45,834 BAD EPOCHS (no improvement): 0 +2023-04-06 03:41:45,838 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:41:56,247 epoch 52 - iter 265/2650 - loss 0.09746777 - time (sec): 10.41 - samples/sec: 14245.71 - lr: 0.100000 +2023-04-06 03:42:06,514 epoch 52 - iter 530/2650 - loss 0.09746823 - time (sec): 20.68 - samples/sec: 14302.39 - lr: 0.100000 +2023-04-06 03:42:16,718 epoch 52 - iter 795/2650 - loss 0.09856488 - time (sec): 30.88 - samples/sec: 14313.59 - lr: 0.100000 +2023-04-06 03:42:27,004 epoch 52 - iter 1060/2650 - loss 0.09860699 - time (sec): 41.16 - samples/sec: 14333.65 - lr: 0.100000 +2023-04-06 03:42:37,283 epoch 52 - iter 1325/2650 - loss 0.09892245 - time (sec): 51.44 - samples/sec: 14349.74 - lr: 0.100000 +2023-04-06 03:42:47,507 epoch 52 - iter 1590/2650 - loss 0.09867769 - time (sec): 61.67 - samples/sec: 14348.32 - lr: 0.100000 +2023-04-06 03:42:57,745 epoch 52 - iter 1855/2650 - loss 0.09890228 - time (sec): 71.91 - samples/sec: 14355.63 - lr: 0.100000 +2023-04-06 03:43:07,976 epoch 52 - iter 2120/2650 - loss 0.09894612 - time (sec): 82.14 - samples/sec: 14364.63 - lr: 0.100000 +2023-04-06 03:43:18,124 epoch 52 - iter 2385/2650 - loss 0.09900486 - time (sec): 92.29 - samples/sec: 14379.46 - lr: 0.100000 +2023-04-06 03:43:28,457 epoch 52 - iter 2650/2650 - loss 0.09890524 - time (sec): 102.62 - samples/sec: 14362.14 - lr: 0.100000 +2023-04-06 03:43:28,458 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:43:28,458 EPOCH 52 done: loss 0.0989 - lr 0.100000 +2023-04-06 03:43:28,458 BAD EPOCHS (no improvement): 1 +2023-04-06 03:43:28,461 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:43:38,655 epoch 53 - iter 265/2650 - loss 0.09198183 - time (sec): 10.19 - samples/sec: 14443.97 - lr: 0.100000 +2023-04-06 03:43:48,966 epoch 53 - iter 530/2650 - loss 0.09355247 - time (sec): 20.50 - samples/sec: 14428.91 - lr: 0.100000 +2023-04-06 03:43:59,188 epoch 53 - iter 795/2650 - loss 0.09456550 - time (sec): 30.73 - samples/sec: 14417.80 - lr: 0.100000 +2023-04-06 03:44:09,376 epoch 53 - iter 1060/2650 - loss 0.09515107 - time (sec): 40.91 - samples/sec: 14412.25 - lr: 0.100000 +2023-04-06 03:44:19,534 epoch 53 - iter 1325/2650 - loss 0.09656648 - time (sec): 51.07 - samples/sec: 14413.76 - lr: 0.100000 +2023-04-06 03:44:29,885 epoch 53 - iter 1590/2650 - loss 0.09725390 - time (sec): 61.42 - samples/sec: 14390.44 - lr: 0.100000 +2023-04-06 03:44:40,119 epoch 53 - iter 1855/2650 - loss 0.09792194 - time (sec): 71.66 - samples/sec: 14392.66 - lr: 0.100000 +2023-04-06 03:44:50,603 epoch 53 - iter 2120/2650 - loss 0.09801606 - time (sec): 82.14 - samples/sec: 14361.50 - lr: 0.100000 +2023-04-06 03:45:00,866 epoch 53 - iter 2385/2650 - loss 0.09794419 - time (sec): 92.41 - samples/sec: 14362.68 - lr: 0.100000 +2023-04-06 03:45:11,225 epoch 53 - iter 2650/2650 - loss 0.09795727 - time (sec): 102.76 - samples/sec: 14341.83 - lr: 0.100000 +2023-04-06 03:45:11,225 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:45:11,226 EPOCH 53 done: loss 0.0980 - lr 0.100000 +2023-04-06 03:45:11,226 BAD EPOCHS (no improvement): 0 +2023-04-06 03:45:11,229 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:45:21,540 epoch 54 - iter 265/2650 - loss 0.09340976 - time (sec): 10.31 - samples/sec: 14392.97 - lr: 0.100000 +2023-04-06 03:45:31,779 epoch 54 - iter 530/2650 - loss 0.09493586 - time (sec): 20.55 - samples/sec: 14411.19 - lr: 0.100000 +2023-04-06 03:45:41,915 epoch 54 - iter 795/2650 - loss 0.09527937 - time (sec): 30.69 - samples/sec: 14436.09 - lr: 0.100000 +2023-04-06 03:45:52,146 epoch 54 - iter 1060/2650 - loss 0.09606137 - time (sec): 40.92 - samples/sec: 14436.78 - lr: 0.100000 +2023-04-06 03:46:02,248 epoch 54 - iter 1325/2650 - loss 0.09649566 - time (sec): 51.02 - samples/sec: 14456.71 - lr: 0.100000 +2023-04-06 03:46:12,372 epoch 54 - iter 1590/2650 - loss 0.09643928 - time (sec): 61.14 - samples/sec: 14482.26 - lr: 0.100000 +2023-04-06 03:46:22,417 epoch 54 - iter 1855/2650 - loss 0.09695006 - time (sec): 71.19 - samples/sec: 14495.89 - lr: 0.100000 +2023-04-06 03:46:32,586 epoch 54 - iter 2120/2650 - loss 0.09721030 - time (sec): 81.36 - samples/sec: 14495.72 - lr: 0.100000 +2023-04-06 03:46:42,766 epoch 54 - iter 2385/2650 - loss 0.09773348 - time (sec): 91.54 - samples/sec: 14496.53 - lr: 0.100000 +2023-04-06 03:46:52,911 epoch 54 - iter 2650/2650 - loss 0.09764392 - time (sec): 101.68 - samples/sec: 14494.47 - lr: 0.100000 +2023-04-06 03:46:52,911 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:46:52,911 EPOCH 54 done: loss 0.0976 - lr 0.100000 +2023-04-06 03:46:52,911 BAD EPOCHS (no improvement): 0 +2023-04-06 03:46:52,915 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:47:03,119 epoch 55 - iter 265/2650 - loss 0.09414063 - time (sec): 10.20 - samples/sec: 14499.31 - lr: 0.100000 +2023-04-06 03:47:13,250 epoch 55 - iter 530/2650 - loss 0.09489586 - time (sec): 20.34 - samples/sec: 14478.54 - lr: 0.100000 +2023-04-06 03:47:23,406 epoch 55 - iter 795/2650 - loss 0.09582349 - time (sec): 30.49 - samples/sec: 14483.02 - lr: 0.100000 +2023-04-06 03:47:33,513 epoch 55 - iter 1060/2650 - loss 0.09630017 - time (sec): 40.60 - samples/sec: 14510.83 - lr: 0.100000 +2023-04-06 03:47:43,777 epoch 55 - iter 1325/2650 - loss 0.09674008 - time (sec): 50.86 - samples/sec: 14482.38 - lr: 0.100000 +2023-04-06 03:47:54,021 epoch 55 - iter 1590/2650 - loss 0.09680285 - time (sec): 61.11 - samples/sec: 14487.65 - lr: 0.100000 +2023-04-06 03:48:04,285 epoch 55 - iter 1855/2650 - loss 0.09654062 - time (sec): 71.37 - samples/sec: 14481.13 - lr: 0.100000 +2023-04-06 03:48:14,378 epoch 55 - iter 2120/2650 - loss 0.09679361 - time (sec): 81.46 - samples/sec: 14486.28 - lr: 0.100000 +2023-04-06 03:48:24,554 epoch 55 - iter 2385/2650 - loss 0.09686188 - time (sec): 91.64 - samples/sec: 14468.96 - lr: 0.100000 +2023-04-06 03:48:34,724 epoch 55 - iter 2650/2650 - loss 0.09726281 - time (sec): 101.81 - samples/sec: 14476.33 - lr: 0.100000 +2023-04-06 03:48:34,724 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:48:34,724 EPOCH 55 done: loss 0.0973 - lr 0.100000 +2023-04-06 03:48:34,725 BAD EPOCHS (no improvement): 0 +2023-04-06 03:48:34,731 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:48:44,948 epoch 56 - iter 265/2650 - loss 0.09426393 - time (sec): 10.22 - samples/sec: 14498.28 - lr: 0.100000 +2023-04-06 03:48:55,026 epoch 56 - iter 530/2650 - loss 0.09451371 - time (sec): 20.29 - samples/sec: 14503.51 - lr: 0.100000 +2023-04-06 03:49:05,245 epoch 56 - iter 795/2650 - loss 0.09549682 - time (sec): 30.51 - samples/sec: 14527.82 - lr: 0.100000 +2023-04-06 03:49:15,237 epoch 56 - iter 1060/2650 - loss 0.09512061 - time (sec): 40.51 - samples/sec: 14509.28 - lr: 0.100000 +2023-04-06 03:49:25,310 epoch 56 - iter 1325/2650 - loss 0.09538705 - time (sec): 50.58 - samples/sec: 14519.98 - lr: 0.100000 +2023-04-06 03:49:35,422 epoch 56 - iter 1590/2650 - loss 0.09560296 - time (sec): 60.69 - samples/sec: 14525.87 - lr: 0.100000 +2023-04-06 03:49:45,697 epoch 56 - iter 1855/2650 - loss 0.09605948 - time (sec): 70.97 - samples/sec: 14518.81 - lr: 0.100000 +2023-04-06 03:49:55,878 epoch 56 - iter 2120/2650 - loss 0.09610848 - time (sec): 81.15 - samples/sec: 14505.78 - lr: 0.100000 +2023-04-06 03:50:06,094 epoch 56 - iter 2385/2650 - loss 0.09608286 - time (sec): 91.36 - samples/sec: 14504.39 - lr: 0.100000 +2023-04-06 03:50:16,349 epoch 56 - iter 2650/2650 - loss 0.09616572 - time (sec): 101.62 - samples/sec: 14503.62 - lr: 0.100000 +2023-04-06 03:50:16,349 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:50:16,350 EPOCH 56 done: loss 0.0962 - lr 0.100000 +2023-04-06 03:50:16,350 BAD EPOCHS (no improvement): 0 +2023-04-06 03:50:16,353 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:50:26,434 epoch 57 - iter 265/2650 - loss 0.09428998 - time (sec): 10.08 - samples/sec: 14596.62 - lr: 0.100000 +2023-04-06 03:50:36,618 epoch 57 - iter 530/2650 - loss 0.09501402 - time (sec): 20.26 - samples/sec: 14512.51 - lr: 0.100000 +2023-04-06 03:50:46,746 epoch 57 - iter 795/2650 - loss 0.09545328 - time (sec): 30.39 - samples/sec: 14508.79 - lr: 0.100000 +2023-04-06 03:50:56,912 epoch 57 - iter 1060/2650 - loss 0.09522100 - time (sec): 40.56 - samples/sec: 14483.98 - lr: 0.100000 +2023-04-06 03:51:06,917 epoch 57 - iter 1325/2650 - loss 0.09588923 - time (sec): 50.56 - samples/sec: 14503.04 - lr: 0.100000 +2023-04-06 03:51:21,463 epoch 57 - iter 1590/2650 - loss 0.09576852 - time (sec): 65.11 - samples/sec: 13551.61 - lr: 0.100000 +2023-04-06 03:51:31,514 epoch 57 - iter 1855/2650 - loss 0.09549006 - time (sec): 75.16 - samples/sec: 13714.54 - lr: 0.100000 +2023-04-06 03:51:41,622 epoch 57 - iter 2120/2650 - loss 0.09569865 - time (sec): 85.27 - samples/sec: 13808.32 - lr: 0.100000 +2023-04-06 03:51:51,918 epoch 57 - iter 2385/2650 - loss 0.09590356 - time (sec): 95.57 - samples/sec: 13882.49 - lr: 0.100000 +2023-04-06 03:52:02,172 epoch 57 - iter 2650/2650 - loss 0.09605253 - time (sec): 105.82 - samples/sec: 13927.78 - lr: 0.100000 +2023-04-06 03:52:02,172 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:52:02,172 EPOCH 57 done: loss 0.0961 - lr 0.100000 +2023-04-06 03:52:02,172 BAD EPOCHS (no improvement): 0 +2023-04-06 03:52:02,176 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:52:12,284 epoch 58 - iter 265/2650 - loss 0.09516290 - time (sec): 10.11 - samples/sec: 14479.26 - lr: 0.100000 +2023-04-06 03:52:22,486 epoch 58 - iter 530/2650 - loss 0.09404455 - time (sec): 20.31 - samples/sec: 14379.70 - lr: 0.100000 +2023-04-06 03:52:32,606 epoch 58 - iter 795/2650 - loss 0.09446420 - time (sec): 30.43 - samples/sec: 14441.70 - lr: 0.100000 +2023-04-06 03:52:42,946 epoch 58 - iter 1060/2650 - loss 0.09493658 - time (sec): 40.77 - samples/sec: 14431.77 - lr: 0.100000 +2023-04-06 03:52:53,023 epoch 58 - iter 1325/2650 - loss 0.09499376 - time (sec): 50.85 - samples/sec: 14454.48 - lr: 0.100000 +2023-04-06 03:53:03,356 epoch 58 - iter 1590/2650 - loss 0.09539367 - time (sec): 61.18 - samples/sec: 14446.16 - lr: 0.100000 +2023-04-06 03:53:13,586 epoch 58 - iter 1855/2650 - loss 0.09588581 - time (sec): 71.41 - samples/sec: 14446.84 - lr: 0.100000 +2023-04-06 03:53:23,663 epoch 58 - iter 2120/2650 - loss 0.09576639 - time (sec): 81.49 - samples/sec: 14447.06 - lr: 0.100000 +2023-04-06 03:53:33,817 epoch 58 - iter 2385/2650 - loss 0.09592059 - time (sec): 91.64 - samples/sec: 14468.63 - lr: 0.100000 +2023-04-06 03:53:44,040 epoch 58 - iter 2650/2650 - loss 0.09588228 - time (sec): 101.86 - samples/sec: 14468.48 - lr: 0.100000 +2023-04-06 03:53:44,040 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:53:44,040 EPOCH 58 done: loss 0.0959 - lr 0.100000 +2023-04-06 03:53:44,040 BAD EPOCHS (no improvement): 0 +2023-04-06 03:53:44,044 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:53:54,242 epoch 59 - iter 265/2650 - loss 0.09289589 - time (sec): 10.20 - samples/sec: 14520.96 - lr: 0.100000 +2023-04-06 03:54:04,364 epoch 59 - iter 530/2650 - loss 0.09477596 - time (sec): 20.32 - samples/sec: 14504.66 - lr: 0.100000 +2023-04-06 03:54:14,466 epoch 59 - iter 795/2650 - loss 0.09480071 - time (sec): 30.42 - samples/sec: 14507.68 - lr: 0.100000 +2023-04-06 03:54:24,491 epoch 59 - iter 1060/2650 - loss 0.09530745 - time (sec): 40.45 - samples/sec: 14515.17 - lr: 0.100000 +2023-04-06 03:54:34,726 epoch 59 - iter 1325/2650 - loss 0.09533160 - time (sec): 50.68 - samples/sec: 14503.43 - lr: 0.100000 +2023-04-06 03:54:44,960 epoch 59 - iter 1590/2650 - loss 0.09568302 - time (sec): 60.92 - samples/sec: 14499.13 - lr: 0.100000 +2023-04-06 03:54:55,045 epoch 59 - iter 1855/2650 - loss 0.09543437 - time (sec): 71.00 - samples/sec: 14492.45 - lr: 0.100000 +2023-04-06 03:55:05,242 epoch 59 - iter 2120/2650 - loss 0.09537910 - time (sec): 81.20 - samples/sec: 14502.36 - lr: 0.100000 +2023-04-06 03:55:15,531 epoch 59 - iter 2385/2650 - loss 0.09589800 - time (sec): 91.49 - samples/sec: 14493.27 - lr: 0.100000 +2023-04-06 03:55:25,701 epoch 59 - iter 2650/2650 - loss 0.09579895 - time (sec): 101.66 - samples/sec: 14498.04 - lr: 0.100000 +2023-04-06 03:55:25,701 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:55:25,701 EPOCH 59 done: loss 0.0958 - lr 0.100000 +2023-04-06 03:55:25,701 BAD EPOCHS (no improvement): 0 +2023-04-06 03:55:25,705 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:55:35,899 epoch 60 - iter 265/2650 - loss 0.09420405 - time (sec): 10.19 - samples/sec: 14496.54 - lr: 0.100000 +2023-04-06 03:55:46,019 epoch 60 - iter 530/2650 - loss 0.09377646 - time (sec): 20.31 - samples/sec: 14491.91 - lr: 0.100000 +2023-04-06 03:55:56,203 epoch 60 - iter 795/2650 - loss 0.09421307 - time (sec): 30.50 - samples/sec: 14482.77 - lr: 0.100000 +2023-04-06 03:56:06,325 epoch 60 - iter 1060/2650 - loss 0.09484692 - time (sec): 40.62 - samples/sec: 14503.49 - lr: 0.100000 +2023-04-06 03:56:16,560 epoch 60 - iter 1325/2650 - loss 0.09459399 - time (sec): 50.85 - samples/sec: 14494.81 - lr: 0.100000 +2023-04-06 03:56:26,686 epoch 60 - iter 1590/2650 - loss 0.09483917 - time (sec): 60.98 - samples/sec: 14502.00 - lr: 0.100000 +2023-04-06 03:56:36,879 epoch 60 - iter 1855/2650 - loss 0.09489104 - time (sec): 71.17 - samples/sec: 14482.24 - lr: 0.100000 +2023-04-06 03:56:47,042 epoch 60 - iter 2120/2650 - loss 0.09509711 - time (sec): 81.34 - samples/sec: 14492.75 - lr: 0.100000 +2023-04-06 03:56:57,288 epoch 60 - iter 2385/2650 - loss 0.09523308 - time (sec): 91.58 - samples/sec: 14496.24 - lr: 0.100000 +2023-04-06 03:57:07,484 epoch 60 - iter 2650/2650 - loss 0.09528797 - time (sec): 101.78 - samples/sec: 14480.64 - lr: 0.100000 +2023-04-06 03:57:07,485 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:57:07,485 EPOCH 60 done: loss 0.0953 - lr 0.100000 +2023-04-06 03:57:07,485 BAD EPOCHS (no improvement): 0 +2023-04-06 03:57:07,489 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:57:17,629 epoch 61 - iter 265/2650 - loss 0.09254083 - time (sec): 10.14 - samples/sec: 14442.70 - lr: 0.100000 +2023-04-06 03:57:27,910 epoch 61 - iter 530/2650 - loss 0.09217445 - time (sec): 20.42 - samples/sec: 14393.72 - lr: 0.100000 +2023-04-06 03:57:38,022 epoch 61 - iter 795/2650 - loss 0.09304948 - time (sec): 30.53 - samples/sec: 14414.47 - lr: 0.100000 +2023-04-06 03:57:48,183 epoch 61 - iter 1060/2650 - loss 0.09340662 - time (sec): 40.69 - samples/sec: 14440.92 - lr: 0.100000 +2023-04-06 03:57:58,277 epoch 61 - iter 1325/2650 - loss 0.09395428 - time (sec): 50.79 - samples/sec: 14450.60 - lr: 0.100000 +2023-04-06 03:58:08,588 epoch 61 - iter 1590/2650 - loss 0.09439016 - time (sec): 61.10 - samples/sec: 14420.43 - lr: 0.100000 +2023-04-06 03:58:18,770 epoch 61 - iter 1855/2650 - loss 0.09426182 - time (sec): 71.28 - samples/sec: 14429.59 - lr: 0.100000 +2023-04-06 03:58:29,071 epoch 61 - iter 2120/2650 - loss 0.09436156 - time (sec): 81.58 - samples/sec: 14427.26 - lr: 0.100000 +2023-04-06 03:58:39,246 epoch 61 - iter 2385/2650 - loss 0.09428534 - time (sec): 91.76 - samples/sec: 14434.74 - lr: 0.100000 +2023-04-06 03:58:49,713 epoch 61 - iter 2650/2650 - loss 0.09453470 - time (sec): 102.22 - samples/sec: 14417.53 - lr: 0.100000 +2023-04-06 03:58:49,713 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:58:49,713 EPOCH 61 done: loss 0.0945 - lr 0.100000 +2023-04-06 03:58:49,713 BAD EPOCHS (no improvement): 0 +2023-04-06 03:58:49,720 ---------------------------------------------------------------------------------------------------- +2023-04-06 03:58:59,924 epoch 62 - iter 265/2650 - loss 0.09327108 - time (sec): 10.20 - samples/sec: 14538.69 - lr: 0.100000 +2023-04-06 03:59:10,134 epoch 62 - iter 530/2650 - loss 0.09439884 - time (sec): 20.41 - samples/sec: 14506.52 - lr: 0.100000 +2023-04-06 03:59:20,428 epoch 62 - iter 795/2650 - loss 0.09429763 - time (sec): 30.71 - samples/sec: 14467.49 - lr: 0.100000 +2023-04-06 03:59:30,730 epoch 62 - iter 1060/2650 - loss 0.09432183 - time (sec): 41.01 - samples/sec: 14456.91 - lr: 0.100000 +2023-04-06 03:59:40,977 epoch 62 - iter 1325/2650 - loss 0.09443980 - time (sec): 51.26 - samples/sec: 14444.16 - lr: 0.100000 +2023-04-06 03:59:51,133 epoch 62 - iter 1590/2650 - loss 0.09457644 - time (sec): 61.41 - samples/sec: 14457.53 - lr: 0.100000 +2023-04-06 04:00:01,223 epoch 62 - iter 1855/2650 - loss 0.09452141 - time (sec): 71.50 - samples/sec: 14460.13 - lr: 0.100000 +2023-04-06 04:00:11,700 epoch 62 - iter 2120/2650 - loss 0.09492779 - time (sec): 81.98 - samples/sec: 14435.21 - lr: 0.100000 +2023-04-06 04:00:21,621 epoch 62 - iter 2385/2650 - loss 0.09496170 - time (sec): 91.90 - samples/sec: 14437.64 - lr: 0.100000 +2023-04-06 04:00:31,785 epoch 62 - iter 2650/2650 - loss 0.09493288 - time (sec): 102.06 - samples/sec: 14440.07 - lr: 0.100000 +2023-04-06 04:00:31,785 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:00:31,785 EPOCH 62 done: loss 0.0949 - lr 0.100000 +2023-04-06 04:00:31,785 BAD EPOCHS (no improvement): 1 +2023-04-06 04:00:31,789 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:00:42,026 epoch 63 - iter 265/2650 - loss 0.09369145 - time (sec): 10.24 - samples/sec: 14523.52 - lr: 0.100000 +2023-04-06 04:00:52,327 epoch 63 - iter 530/2650 - loss 0.09360541 - time (sec): 20.54 - samples/sec: 14470.32 - lr: 0.100000 +2023-04-06 04:01:02,550 epoch 63 - iter 795/2650 - loss 0.09351074 - time (sec): 30.76 - samples/sec: 14452.71 - lr: 0.100000 +2023-04-06 04:01:12,671 epoch 63 - iter 1060/2650 - loss 0.09333853 - time (sec): 40.88 - samples/sec: 14444.61 - lr: 0.100000 +2023-04-06 04:01:22,964 epoch 63 - iter 1325/2650 - loss 0.09370224 - time (sec): 51.17 - samples/sec: 14424.47 - lr: 0.100000 +2023-04-06 04:01:33,228 epoch 63 - iter 1590/2650 - loss 0.09364369 - time (sec): 61.44 - samples/sec: 14432.02 - lr: 0.100000 +2023-04-06 04:01:43,408 epoch 63 - iter 1855/2650 - loss 0.09399018 - time (sec): 71.62 - samples/sec: 14445.76 - lr: 0.100000 +2023-04-06 04:01:57,550 epoch 63 - iter 2120/2650 - loss 0.09397280 - time (sec): 85.76 - samples/sec: 13753.64 - lr: 0.100000 +2023-04-06 04:02:07,712 epoch 63 - iter 2385/2650 - loss 0.09389295 - time (sec): 95.92 - samples/sec: 13840.57 - lr: 0.100000 +2023-04-06 04:02:17,740 epoch 63 - iter 2650/2650 - loss 0.09435296 - time (sec): 105.95 - samples/sec: 13910.42 - lr: 0.100000 +2023-04-06 04:02:17,740 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:02:17,740 EPOCH 63 done: loss 0.0944 - lr 0.100000 +2023-04-06 04:02:17,740 BAD EPOCHS (no improvement): 0 +2023-04-06 04:02:17,744 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:02:27,950 epoch 64 - iter 265/2650 - loss 0.09433259 - time (sec): 10.20 - samples/sec: 14400.46 - lr: 0.100000 +2023-04-06 04:02:38,090 epoch 64 - iter 530/2650 - loss 0.09325865 - time (sec): 20.35 - samples/sec: 14523.63 - lr: 0.100000 +2023-04-06 04:02:48,114 epoch 64 - iter 795/2650 - loss 0.09278355 - time (sec): 30.37 - samples/sec: 14521.11 - lr: 0.100000 +2023-04-06 04:02:58,380 epoch 64 - iter 1060/2650 - loss 0.09388605 - time (sec): 40.64 - samples/sec: 14491.07 - lr: 0.100000 +2023-04-06 04:03:08,559 epoch 64 - iter 1325/2650 - loss 0.09392504 - time (sec): 50.81 - samples/sec: 14486.07 - lr: 0.100000 +2023-04-06 04:03:18,600 epoch 64 - iter 1590/2650 - loss 0.09376735 - time (sec): 60.86 - samples/sec: 14511.09 - lr: 0.100000 +2023-04-06 04:03:28,771 epoch 64 - iter 1855/2650 - loss 0.09403017 - time (sec): 71.03 - samples/sec: 14515.03 - lr: 0.100000 +2023-04-06 04:03:38,910 epoch 64 - iter 2120/2650 - loss 0.09421549 - time (sec): 81.16 - samples/sec: 14525.18 - lr: 0.100000 +2023-04-06 04:03:49,039 epoch 64 - iter 2385/2650 - loss 0.09436820 - time (sec): 91.29 - samples/sec: 14520.82 - lr: 0.100000 +2023-04-06 04:03:59,234 epoch 64 - iter 2650/2650 - loss 0.09454694 - time (sec): 101.49 - samples/sec: 14521.99 - lr: 0.100000 +2023-04-06 04:03:59,234 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:03:59,234 EPOCH 64 done: loss 0.0945 - lr 0.100000 +2023-04-06 04:03:59,234 BAD EPOCHS (no improvement): 1 +2023-04-06 04:03:59,238 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:04:09,445 epoch 65 - iter 265/2650 - loss 0.09131859 - time (sec): 10.21 - samples/sec: 14478.81 - lr: 0.100000 +2023-04-06 04:04:19,467 epoch 65 - iter 530/2650 - loss 0.09194799 - time (sec): 20.23 - samples/sec: 14526.18 - lr: 0.100000 +2023-04-06 04:04:29,632 epoch 65 - iter 795/2650 - loss 0.09335725 - time (sec): 30.39 - samples/sec: 14519.62 - lr: 0.100000 +2023-04-06 04:04:39,790 epoch 65 - iter 1060/2650 - loss 0.09345533 - time (sec): 40.55 - samples/sec: 14520.56 - lr: 0.100000 +2023-04-06 04:04:50,029 epoch 65 - iter 1325/2650 - loss 0.09359930 - time (sec): 50.79 - samples/sec: 14513.98 - lr: 0.100000 +2023-04-06 04:05:00,170 epoch 65 - iter 1590/2650 - loss 0.09397764 - time (sec): 60.93 - samples/sec: 14526.35 - lr: 0.100000 +2023-04-06 04:05:10,353 epoch 65 - iter 1855/2650 - loss 0.09402017 - time (sec): 71.11 - samples/sec: 14534.71 - lr: 0.100000 +2023-04-06 04:05:20,428 epoch 65 - iter 2120/2650 - loss 0.09376844 - time (sec): 81.19 - samples/sec: 14533.45 - lr: 0.100000 +2023-04-06 04:05:30,572 epoch 65 - iter 2385/2650 - loss 0.09374590 - time (sec): 91.33 - samples/sec: 14524.92 - lr: 0.100000 +2023-04-06 04:05:40,745 epoch 65 - iter 2650/2650 - loss 0.09375804 - time (sec): 101.51 - samples/sec: 14519.47 - lr: 0.100000 +2023-04-06 04:05:40,745 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:05:40,745 EPOCH 65 done: loss 0.0938 - lr 0.100000 +2023-04-06 04:05:40,745 BAD EPOCHS (no improvement): 0 +2023-04-06 04:05:40,749 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:05:50,701 epoch 66 - iter 265/2650 - loss 0.08954511 - time (sec): 9.95 - samples/sec: 14604.30 - lr: 0.100000 +2023-04-06 04:06:00,926 epoch 66 - iter 530/2650 - loss 0.09092455 - time (sec): 20.18 - samples/sec: 14552.56 - lr: 0.100000 +2023-04-06 04:06:11,142 epoch 66 - iter 795/2650 - loss 0.09227201 - time (sec): 30.39 - samples/sec: 14506.08 - lr: 0.100000 +2023-04-06 04:06:21,588 epoch 66 - iter 1060/2650 - loss 0.09238344 - time (sec): 40.84 - samples/sec: 14409.23 - lr: 0.100000 +2023-04-06 04:06:31,832 epoch 66 - iter 1325/2650 - loss 0.09296019 - time (sec): 51.08 - samples/sec: 14408.91 - lr: 0.100000 +2023-04-06 04:06:42,251 epoch 66 - iter 1590/2650 - loss 0.09324652 - time (sec): 61.50 - samples/sec: 14378.59 - lr: 0.100000 +2023-04-06 04:06:52,524 epoch 66 - iter 1855/2650 - loss 0.09342655 - time (sec): 71.78 - samples/sec: 14373.09 - lr: 0.100000 +2023-04-06 04:07:02,804 epoch 66 - iter 2120/2650 - loss 0.09309511 - time (sec): 82.06 - samples/sec: 14367.21 - lr: 0.100000 +2023-04-06 04:07:13,045 epoch 66 - iter 2385/2650 - loss 0.09319554 - time (sec): 92.30 - samples/sec: 14361.16 - lr: 0.100000 +2023-04-06 04:07:23,392 epoch 66 - iter 2650/2650 - loss 0.09329337 - time (sec): 102.64 - samples/sec: 14358.72 - lr: 0.100000 +2023-04-06 04:07:23,392 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:07:23,392 EPOCH 66 done: loss 0.0933 - lr 0.100000 +2023-04-06 04:07:23,392 BAD EPOCHS (no improvement): 0 +2023-04-06 04:07:23,396 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:07:33,671 epoch 67 - iter 265/2650 - loss 0.09281769 - time (sec): 10.27 - samples/sec: 14419.12 - lr: 0.100000 +2023-04-06 04:07:44,066 epoch 67 - iter 530/2650 - loss 0.09250065 - time (sec): 20.67 - samples/sec: 14382.66 - lr: 0.100000 +2023-04-06 04:07:54,321 epoch 67 - iter 795/2650 - loss 0.09168825 - time (sec): 30.93 - samples/sec: 14350.46 - lr: 0.100000 +2023-04-06 04:08:04,637 epoch 67 - iter 1060/2650 - loss 0.09277832 - time (sec): 41.24 - samples/sec: 14339.24 - lr: 0.100000 +2023-04-06 04:08:14,936 epoch 67 - iter 1325/2650 - loss 0.09304300 - time (sec): 51.54 - samples/sec: 14333.88 - lr: 0.100000 +2023-04-06 04:08:25,116 epoch 67 - iter 1590/2650 - loss 0.09307971 - time (sec): 61.72 - samples/sec: 14336.50 - lr: 0.100000 +2023-04-06 04:08:35,211 epoch 67 - iter 1855/2650 - loss 0.09306137 - time (sec): 71.82 - samples/sec: 14329.76 - lr: 0.100000 +2023-04-06 04:08:45,674 epoch 67 - iter 2120/2650 - loss 0.09307567 - time (sec): 82.28 - samples/sec: 14330.93 - lr: 0.100000 +2023-04-06 04:08:55,979 epoch 67 - iter 2385/2650 - loss 0.09318599 - time (sec): 92.58 - samples/sec: 14325.49 - lr: 0.100000 +2023-04-06 04:09:06,254 epoch 67 - iter 2650/2650 - loss 0.09350696 - time (sec): 102.86 - samples/sec: 14328.69 - lr: 0.100000 +2023-04-06 04:09:06,254 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:09:06,254 EPOCH 67 done: loss 0.0935 - lr 0.100000 +2023-04-06 04:09:06,254 BAD EPOCHS (no improvement): 1 +2023-04-06 04:09:06,260 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:09:16,619 epoch 68 - iter 265/2650 - loss 0.09411261 - time (sec): 10.36 - samples/sec: 14322.21 - lr: 0.100000 +2023-04-06 04:09:26,749 epoch 68 - iter 530/2650 - loss 0.09502678 - time (sec): 20.49 - samples/sec: 14374.54 - lr: 0.100000 +2023-04-06 04:09:36,957 epoch 68 - iter 795/2650 - loss 0.09341420 - time (sec): 30.70 - samples/sec: 14394.39 - lr: 0.100000 +2023-04-06 04:09:47,086 epoch 68 - iter 1060/2650 - loss 0.09347245 - time (sec): 40.83 - samples/sec: 14399.58 - lr: 0.100000 +2023-04-06 04:09:57,349 epoch 68 - iter 1325/2650 - loss 0.09308225 - time (sec): 51.09 - samples/sec: 14374.46 - lr: 0.100000 +2023-04-06 04:10:07,722 epoch 68 - iter 1590/2650 - loss 0.09323788 - time (sec): 61.46 - samples/sec: 14387.95 - lr: 0.100000 +2023-04-06 04:10:17,993 epoch 68 - iter 1855/2650 - loss 0.09318535 - time (sec): 71.73 - samples/sec: 14381.33 - lr: 0.100000 +2023-04-06 04:10:28,165 epoch 68 - iter 2120/2650 - loss 0.09299953 - time (sec): 81.90 - samples/sec: 14400.46 - lr: 0.100000 +2023-04-06 04:10:38,414 epoch 68 - iter 2385/2650 - loss 0.09314580 - time (sec): 92.15 - samples/sec: 14407.78 - lr: 0.100000 +2023-04-06 04:10:48,509 epoch 68 - iter 2650/2650 - loss 0.09317509 - time (sec): 102.25 - samples/sec: 14414.03 - lr: 0.100000 +2023-04-06 04:10:48,509 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:10:48,509 EPOCH 68 done: loss 0.0932 - lr 0.100000 +2023-04-06 04:10:48,509 BAD EPOCHS (no improvement): 0 +2023-04-06 04:10:48,513 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:10:58,667 epoch 69 - iter 265/2650 - loss 0.09048874 - time (sec): 10.15 - samples/sec: 14445.50 - lr: 0.100000 +2023-04-06 04:11:08,870 epoch 69 - iter 530/2650 - loss 0.09125774 - time (sec): 20.36 - samples/sec: 14480.49 - lr: 0.100000 +2023-04-06 04:11:18,966 epoch 69 - iter 795/2650 - loss 0.09229100 - time (sec): 30.45 - samples/sec: 14505.02 - lr: 0.100000 +2023-04-06 04:11:29,165 epoch 69 - iter 1060/2650 - loss 0.09286190 - time (sec): 40.65 - samples/sec: 14501.95 - lr: 0.100000 +2023-04-06 04:11:39,290 epoch 69 - iter 1325/2650 - loss 0.09291963 - time (sec): 50.78 - samples/sec: 14500.06 - lr: 0.100000 +2023-04-06 04:11:49,499 epoch 69 - iter 1590/2650 - loss 0.09312472 - time (sec): 60.99 - samples/sec: 14487.61 - lr: 0.100000 +2023-04-06 04:11:59,750 epoch 69 - iter 1855/2650 - loss 0.09297419 - time (sec): 71.24 - samples/sec: 14468.68 - lr: 0.100000 +2023-04-06 04:12:09,972 epoch 69 - iter 2120/2650 - loss 0.09290360 - time (sec): 81.46 - samples/sec: 14468.19 - lr: 0.100000 +2023-04-06 04:12:24,217 epoch 69 - iter 2385/2650 - loss 0.09304509 - time (sec): 95.70 - samples/sec: 13835.09 - lr: 0.100000 +2023-04-06 04:12:34,466 epoch 69 - iter 2650/2650 - loss 0.09269205 - time (sec): 105.95 - samples/sec: 13910.23 - lr: 0.100000 +2023-04-06 04:12:34,466 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:12:34,466 EPOCH 69 done: loss 0.0927 - lr 0.100000 +2023-04-06 04:12:34,466 BAD EPOCHS (no improvement): 0 +2023-04-06 04:12:34,469 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:12:44,407 epoch 70 - iter 265/2650 - loss 0.08918612 - time (sec): 9.94 - samples/sec: 14605.82 - lr: 0.100000 +2023-04-06 04:12:54,535 epoch 70 - iter 530/2650 - loss 0.08981270 - time (sec): 20.07 - samples/sec: 14558.20 - lr: 0.100000 +2023-04-06 04:13:04,676 epoch 70 - iter 795/2650 - loss 0.09000592 - time (sec): 30.21 - samples/sec: 14536.35 - lr: 0.100000 +2023-04-06 04:13:14,943 epoch 70 - iter 1060/2650 - loss 0.09025327 - time (sec): 40.47 - samples/sec: 14510.91 - lr: 0.100000 +2023-04-06 04:13:25,164 epoch 70 - iter 1325/2650 - loss 0.09051947 - time (sec): 50.69 - samples/sec: 14514.06 - lr: 0.100000 +2023-04-06 04:13:35,297 epoch 70 - iter 1590/2650 - loss 0.09050660 - time (sec): 60.83 - samples/sec: 14500.54 - lr: 0.100000 +2023-04-06 04:13:45,393 epoch 70 - iter 1855/2650 - loss 0.09124731 - time (sec): 70.92 - samples/sec: 14512.12 - lr: 0.100000 +2023-04-06 04:13:55,593 epoch 70 - iter 2120/2650 - loss 0.09148541 - time (sec): 81.12 - samples/sec: 14497.86 - lr: 0.100000 +2023-04-06 04:14:05,808 epoch 70 - iter 2385/2650 - loss 0.09177303 - time (sec): 91.34 - samples/sec: 14504.63 - lr: 0.100000 +2023-04-06 04:14:16,156 epoch 70 - iter 2650/2650 - loss 0.09199457 - time (sec): 101.69 - samples/sec: 14493.74 - lr: 0.100000 +2023-04-06 04:14:16,157 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:14:16,157 EPOCH 70 done: loss 0.0920 - lr 0.100000 +2023-04-06 04:14:16,157 BAD EPOCHS (no improvement): 0 +2023-04-06 04:14:16,161 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:14:26,369 epoch 71 - iter 265/2650 - loss 0.08987095 - time (sec): 10.21 - samples/sec: 14601.26 - lr: 0.100000 +2023-04-06 04:14:36,620 epoch 71 - iter 530/2650 - loss 0.09038876 - time (sec): 20.46 - samples/sec: 14540.35 - lr: 0.100000 +2023-04-06 04:14:46,790 epoch 71 - iter 795/2650 - loss 0.09106839 - time (sec): 30.63 - samples/sec: 14507.54 - lr: 0.100000 +2023-04-06 04:14:57,062 epoch 71 - iter 1060/2650 - loss 0.09094524 - time (sec): 40.90 - samples/sec: 14492.42 - lr: 0.100000 +2023-04-06 04:15:07,240 epoch 71 - iter 1325/2650 - loss 0.09096297 - time (sec): 51.08 - samples/sec: 14505.94 - lr: 0.100000 +2023-04-06 04:15:17,365 epoch 71 - iter 1590/2650 - loss 0.09155723 - time (sec): 61.20 - samples/sec: 14505.86 - lr: 0.100000 +2023-04-06 04:15:27,473 epoch 71 - iter 1855/2650 - loss 0.09179258 - time (sec): 71.31 - samples/sec: 14509.29 - lr: 0.100000 +2023-04-06 04:15:37,722 epoch 71 - iter 2120/2650 - loss 0.09219347 - time (sec): 81.56 - samples/sec: 14494.63 - lr: 0.100000 +2023-04-06 04:15:47,738 epoch 71 - iter 2385/2650 - loss 0.09222124 - time (sec): 91.58 - samples/sec: 14501.97 - lr: 0.100000 +2023-04-06 04:15:57,834 epoch 71 - iter 2650/2650 - loss 0.09224161 - time (sec): 101.67 - samples/sec: 14495.72 - lr: 0.100000 +2023-04-06 04:15:57,834 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:15:57,834 EPOCH 71 done: loss 0.0922 - lr 0.100000 +2023-04-06 04:15:57,834 BAD EPOCHS (no improvement): 1 +2023-04-06 04:15:57,837 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:16:08,131 epoch 72 - iter 265/2650 - loss 0.09040554 - time (sec): 10.29 - samples/sec: 14436.75 - lr: 0.100000 +2023-04-06 04:16:18,216 epoch 72 - iter 530/2650 - loss 0.08965582 - time (sec): 20.38 - samples/sec: 14522.22 - lr: 0.100000 +2023-04-06 04:16:28,468 epoch 72 - iter 795/2650 - loss 0.08956752 - time (sec): 30.63 - samples/sec: 14500.00 - lr: 0.100000 +2023-04-06 04:16:38,449 epoch 72 - iter 1060/2650 - loss 0.09014766 - time (sec): 40.61 - samples/sec: 14526.64 - lr: 0.100000 +2023-04-06 04:16:48,647 epoch 72 - iter 1325/2650 - loss 0.09078679 - time (sec): 50.81 - samples/sec: 14512.86 - lr: 0.100000 +2023-04-06 04:16:58,736 epoch 72 - iter 1590/2650 - loss 0.09148872 - time (sec): 60.90 - samples/sec: 14513.04 - lr: 0.100000 +2023-04-06 04:17:08,960 epoch 72 - iter 1855/2650 - loss 0.09144408 - time (sec): 71.12 - samples/sec: 14485.47 - lr: 0.100000 +2023-04-06 04:17:19,352 epoch 72 - iter 2120/2650 - loss 0.09150036 - time (sec): 81.51 - samples/sec: 14465.08 - lr: 0.100000 +2023-04-06 04:17:29,616 epoch 72 - iter 2385/2650 - loss 0.09157609 - time (sec): 91.78 - samples/sec: 14457.45 - lr: 0.100000 +2023-04-06 04:17:39,810 epoch 72 - iter 2650/2650 - loss 0.09151922 - time (sec): 101.97 - samples/sec: 14453.03 - lr: 0.100000 +2023-04-06 04:17:39,811 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:17:39,811 EPOCH 72 done: loss 0.0915 - lr 0.100000 +2023-04-06 04:17:39,811 BAD EPOCHS (no improvement): 0 +2023-04-06 04:17:39,815 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:17:49,924 epoch 73 - iter 265/2650 - loss 0.09029847 - time (sec): 10.11 - samples/sec: 14431.05 - lr: 0.100000 +2023-04-06 04:18:00,149 epoch 73 - iter 530/2650 - loss 0.09063659 - time (sec): 20.33 - samples/sec: 14461.25 - lr: 0.100000 +2023-04-06 04:18:10,484 epoch 73 - iter 795/2650 - loss 0.09054764 - time (sec): 30.67 - samples/sec: 14399.93 - lr: 0.100000 +2023-04-06 04:18:20,610 epoch 73 - iter 1060/2650 - loss 0.09016852 - time (sec): 40.79 - samples/sec: 14434.34 - lr: 0.100000 +2023-04-06 04:18:30,882 epoch 73 - iter 1325/2650 - loss 0.09118376 - time (sec): 51.07 - samples/sec: 14429.41 - lr: 0.100000 +2023-04-06 04:18:41,153 epoch 73 - iter 1590/2650 - loss 0.09175331 - time (sec): 61.34 - samples/sec: 14421.35 - lr: 0.100000 +2023-04-06 04:18:51,357 epoch 73 - iter 1855/2650 - loss 0.09157526 - time (sec): 71.54 - samples/sec: 14428.74 - lr: 0.100000 +2023-04-06 04:19:01,480 epoch 73 - iter 2120/2650 - loss 0.09123422 - time (sec): 81.66 - samples/sec: 14443.46 - lr: 0.100000 +2023-04-06 04:19:11,741 epoch 73 - iter 2385/2650 - loss 0.09146531 - time (sec): 91.93 - samples/sec: 14442.76 - lr: 0.100000 +2023-04-06 04:19:21,809 epoch 73 - iter 2650/2650 - loss 0.09152525 - time (sec): 101.99 - samples/sec: 14450.05 - lr: 0.100000 +2023-04-06 04:19:21,810 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:19:21,810 EPOCH 73 done: loss 0.0915 - lr 0.100000 +2023-04-06 04:19:21,810 BAD EPOCHS (no improvement): 1 +2023-04-06 04:19:21,817 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:19:32,032 epoch 74 - iter 265/2650 - loss 0.09171549 - time (sec): 10.21 - samples/sec: 14484.39 - lr: 0.100000 +2023-04-06 04:19:42,329 epoch 74 - iter 530/2650 - loss 0.09084298 - time (sec): 20.51 - samples/sec: 14464.07 - lr: 0.100000 +2023-04-06 04:19:52,420 epoch 74 - iter 795/2650 - loss 0.09144970 - time (sec): 30.60 - samples/sec: 14463.71 - lr: 0.100000 +2023-04-06 04:20:02,683 epoch 74 - iter 1060/2650 - loss 0.09165401 - time (sec): 40.86 - samples/sec: 14453.45 - lr: 0.100000 +2023-04-06 04:20:12,931 epoch 74 - iter 1325/2650 - loss 0.09150483 - time (sec): 51.11 - samples/sec: 14458.63 - lr: 0.100000 +2023-04-06 04:20:23,167 epoch 74 - iter 1590/2650 - loss 0.09142535 - time (sec): 61.35 - samples/sec: 14465.98 - lr: 0.100000 +2023-04-06 04:20:33,249 epoch 74 - iter 1855/2650 - loss 0.09142134 - time (sec): 71.43 - samples/sec: 14460.82 - lr: 0.100000 +2023-04-06 04:20:43,439 epoch 74 - iter 2120/2650 - loss 0.09160474 - time (sec): 81.62 - samples/sec: 14445.65 - lr: 0.100000 +2023-04-06 04:20:53,630 epoch 74 - iter 2385/2650 - loss 0.09140863 - time (sec): 91.81 - samples/sec: 14451.30 - lr: 0.100000 +2023-04-06 04:21:03,913 epoch 74 - iter 2650/2650 - loss 0.09134285 - time (sec): 102.10 - samples/sec: 14435.69 - lr: 0.100000 +2023-04-06 04:21:03,914 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:21:03,914 EPOCH 74 done: loss 0.0913 - lr 0.100000 +2023-04-06 04:21:03,914 BAD EPOCHS (no improvement): 0 +2023-04-06 04:21:03,918 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:21:14,133 epoch 75 - iter 265/2650 - loss 0.08788198 - time (sec): 10.22 - samples/sec: 14460.41 - lr: 0.100000 +2023-04-06 04:21:24,328 epoch 75 - iter 530/2650 - loss 0.08925181 - time (sec): 20.41 - samples/sec: 14408.35 - lr: 0.100000 +2023-04-06 04:21:34,593 epoch 75 - iter 795/2650 - loss 0.08953673 - time (sec): 30.68 - samples/sec: 14400.38 - lr: 0.100000 +2023-04-06 04:21:44,801 epoch 75 - iter 1060/2650 - loss 0.09066961 - time (sec): 40.88 - samples/sec: 14415.65 - lr: 0.100000 +2023-04-06 04:21:54,921 epoch 75 - iter 1325/2650 - loss 0.09074201 - time (sec): 51.00 - samples/sec: 14448.73 - lr: 0.100000 +2023-04-06 04:22:05,191 epoch 75 - iter 1590/2650 - loss 0.09077918 - time (sec): 61.27 - samples/sec: 14422.43 - lr: 0.100000 +2023-04-06 04:22:15,469 epoch 75 - iter 1855/2650 - loss 0.09097050 - time (sec): 71.55 - samples/sec: 14425.30 - lr: 0.100000 +2023-04-06 04:22:25,731 epoch 75 - iter 2120/2650 - loss 0.09110485 - time (sec): 81.81 - samples/sec: 14423.87 - lr: 0.100000 +2023-04-06 04:22:35,863 epoch 75 - iter 2385/2650 - loss 0.09127782 - time (sec): 91.95 - samples/sec: 14434.70 - lr: 0.100000 +2023-04-06 04:22:45,962 epoch 75 - iter 2650/2650 - loss 0.09136324 - time (sec): 102.04 - samples/sec: 14442.93 - lr: 0.100000 +2023-04-06 04:22:45,963 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:22:45,963 EPOCH 75 done: loss 0.0914 - lr 0.100000 +2023-04-06 04:22:45,963 BAD EPOCHS (no improvement): 1 +2023-04-06 04:22:45,967 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:23:00,412 epoch 76 - iter 265/2650 - loss 0.08812318 - time (sec): 14.44 - samples/sec: 10334.99 - lr: 0.100000 +2023-04-06 04:23:10,642 epoch 76 - iter 530/2650 - loss 0.08912671 - time (sec): 24.67 - samples/sec: 12079.26 - lr: 0.100000 +2023-04-06 04:23:20,790 epoch 76 - iter 795/2650 - loss 0.08903704 - time (sec): 34.82 - samples/sec: 12786.49 - lr: 0.100000 +2023-04-06 04:23:30,844 epoch 76 - iter 1060/2650 - loss 0.08993708 - time (sec): 44.88 - samples/sec: 13167.43 - lr: 0.100000 +2023-04-06 04:23:40,888 epoch 76 - iter 1325/2650 - loss 0.09035288 - time (sec): 54.92 - samples/sec: 13417.98 - lr: 0.100000 +2023-04-06 04:23:51,058 epoch 76 - iter 1590/2650 - loss 0.09066339 - time (sec): 65.09 - samples/sec: 13588.42 - lr: 0.100000 +2023-04-06 04:24:01,260 epoch 76 - iter 1855/2650 - loss 0.09070726 - time (sec): 75.29 - samples/sec: 13700.13 - lr: 0.100000 +2023-04-06 04:24:11,508 epoch 76 - iter 2120/2650 - loss 0.09065398 - time (sec): 85.54 - samples/sec: 13779.03 - lr: 0.100000 +2023-04-06 04:24:21,801 epoch 76 - iter 2385/2650 - loss 0.09092510 - time (sec): 95.83 - samples/sec: 13837.72 - lr: 0.100000 +2023-04-06 04:24:32,037 epoch 76 - iter 2650/2650 - loss 0.09105979 - time (sec): 106.07 - samples/sec: 13894.82 - lr: 0.100000 +2023-04-06 04:24:32,037 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:24:32,037 EPOCH 76 done: loss 0.0911 - lr 0.100000 +2023-04-06 04:24:32,037 BAD EPOCHS (no improvement): 0 +2023-04-06 04:24:32,041 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:24:42,325 epoch 77 - iter 265/2650 - loss 0.09044634 - time (sec): 10.28 - samples/sec: 14404.29 - lr: 0.100000 +2023-04-06 04:24:52,525 epoch 77 - iter 530/2650 - loss 0.08912198 - time (sec): 20.48 - samples/sec: 14414.06 - lr: 0.100000 +2023-04-06 04:25:02,788 epoch 77 - iter 795/2650 - loss 0.08898236 - time (sec): 30.75 - samples/sec: 14391.73 - lr: 0.100000 +2023-04-06 04:25:12,908 epoch 77 - iter 1060/2650 - loss 0.08922383 - time (sec): 40.87 - samples/sec: 14424.18 - lr: 0.100000 +2023-04-06 04:25:23,050 epoch 77 - iter 1325/2650 - loss 0.08992857 - time (sec): 51.01 - samples/sec: 14422.78 - lr: 0.100000 +2023-04-06 04:25:33,210 epoch 77 - iter 1590/2650 - loss 0.09025853 - time (sec): 61.17 - samples/sec: 14440.61 - lr: 0.100000 +2023-04-06 04:25:43,506 epoch 77 - iter 1855/2650 - loss 0.09030122 - time (sec): 71.46 - samples/sec: 14452.65 - lr: 0.100000 +2023-04-06 04:25:53,634 epoch 77 - iter 2120/2650 - loss 0.09048242 - time (sec): 81.59 - samples/sec: 14473.41 - lr: 0.100000 +2023-04-06 04:26:03,725 epoch 77 - iter 2385/2650 - loss 0.09054973 - time (sec): 91.68 - samples/sec: 14479.05 - lr: 0.100000 +2023-04-06 04:26:13,754 epoch 77 - iter 2650/2650 - loss 0.09074831 - time (sec): 101.71 - samples/sec: 14490.07 - lr: 0.100000 +2023-04-06 04:26:13,754 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:26:13,754 EPOCH 77 done: loss 0.0907 - lr 0.100000 +2023-04-06 04:26:13,754 BAD EPOCHS (no improvement): 0 +2023-04-06 04:26:13,758 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:26:23,802 epoch 78 - iter 265/2650 - loss 0.08763843 - time (sec): 10.04 - samples/sec: 14527.71 - lr: 0.100000 +2023-04-06 04:26:34,089 epoch 78 - iter 530/2650 - loss 0.08940872 - time (sec): 20.33 - samples/sec: 14472.45 - lr: 0.100000 +2023-04-06 04:26:44,543 epoch 78 - iter 795/2650 - loss 0.08946774 - time (sec): 30.78 - samples/sec: 14438.36 - lr: 0.100000 +2023-04-06 04:26:54,825 epoch 78 - iter 1060/2650 - loss 0.08998604 - time (sec): 41.07 - samples/sec: 14416.96 - lr: 0.100000 +2023-04-06 04:27:04,945 epoch 78 - iter 1325/2650 - loss 0.08990088 - time (sec): 51.19 - samples/sec: 14418.47 - lr: 0.100000 +2023-04-06 04:27:15,130 epoch 78 - iter 1590/2650 - loss 0.08971696 - time (sec): 61.37 - samples/sec: 14437.57 - lr: 0.100000 +2023-04-06 04:27:25,383 epoch 78 - iter 1855/2650 - loss 0.08984242 - time (sec): 71.62 - samples/sec: 14431.40 - lr: 0.100000 +2023-04-06 04:27:35,530 epoch 78 - iter 2120/2650 - loss 0.09009775 - time (sec): 81.77 - samples/sec: 14429.47 - lr: 0.100000 +2023-04-06 04:27:45,620 epoch 78 - iter 2385/2650 - loss 0.09013786 - time (sec): 91.86 - samples/sec: 14434.01 - lr: 0.100000 +2023-04-06 04:27:55,889 epoch 78 - iter 2650/2650 - loss 0.09026931 - time (sec): 102.13 - samples/sec: 14430.67 - lr: 0.100000 +2023-04-06 04:27:55,890 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:27:55,890 EPOCH 78 done: loss 0.0903 - lr 0.100000 +2023-04-06 04:27:55,890 BAD EPOCHS (no improvement): 0 +2023-04-06 04:27:55,894 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:28:06,113 epoch 79 - iter 265/2650 - loss 0.09286065 - time (sec): 10.22 - samples/sec: 14527.52 - lr: 0.100000 +2023-04-06 04:28:16,218 epoch 79 - iter 530/2650 - loss 0.09068622 - time (sec): 20.32 - samples/sec: 14447.48 - lr: 0.100000 +2023-04-06 04:28:26,347 epoch 79 - iter 795/2650 - loss 0.09067542 - time (sec): 30.45 - samples/sec: 14464.19 - lr: 0.100000 +2023-04-06 04:28:36,639 epoch 79 - iter 1060/2650 - loss 0.09043994 - time (sec): 40.74 - samples/sec: 14479.20 - lr: 0.100000 +2023-04-06 04:28:46,640 epoch 79 - iter 1325/2650 - loss 0.09047346 - time (sec): 50.75 - samples/sec: 14488.83 - lr: 0.100000 +2023-04-06 04:28:56,834 epoch 79 - iter 1590/2650 - loss 0.09022128 - time (sec): 60.94 - samples/sec: 14496.72 - lr: 0.100000 +2023-04-06 04:29:06,918 epoch 79 - iter 1855/2650 - loss 0.09009059 - time (sec): 71.02 - samples/sec: 14517.94 - lr: 0.100000 +2023-04-06 04:29:17,090 epoch 79 - iter 2120/2650 - loss 0.09001318 - time (sec): 81.20 - samples/sec: 14521.70 - lr: 0.100000 +2023-04-06 04:29:27,141 epoch 79 - iter 2385/2650 - loss 0.08980393 - time (sec): 91.25 - samples/sec: 14527.46 - lr: 0.100000 +2023-04-06 04:29:37,388 epoch 79 - iter 2650/2650 - loss 0.09010633 - time (sec): 101.49 - samples/sec: 14521.30 - lr: 0.100000 +2023-04-06 04:29:37,389 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:29:37,389 EPOCH 79 done: loss 0.0901 - lr 0.100000 +2023-04-06 04:29:37,389 BAD EPOCHS (no improvement): 0 +2023-04-06 04:29:37,396 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:29:47,461 epoch 80 - iter 265/2650 - loss 0.08754027 - time (sec): 10.07 - samples/sec: 14570.09 - lr: 0.100000 +2023-04-06 04:29:57,600 epoch 80 - iter 530/2650 - loss 0.08888185 - time (sec): 20.20 - samples/sec: 14558.11 - lr: 0.100000 +2023-04-06 04:30:07,780 epoch 80 - iter 795/2650 - loss 0.08843406 - time (sec): 30.38 - samples/sec: 14551.05 - lr: 0.100000 +2023-04-06 04:30:18,066 epoch 80 - iter 1060/2650 - loss 0.08865428 - time (sec): 40.67 - samples/sec: 14516.79 - lr: 0.100000 +2023-04-06 04:30:28,216 epoch 80 - iter 1325/2650 - loss 0.08878725 - time (sec): 50.82 - samples/sec: 14517.29 - lr: 0.100000 +2023-04-06 04:30:38,330 epoch 80 - iter 1590/2650 - loss 0.08903230 - time (sec): 60.93 - samples/sec: 14524.82 - lr: 0.100000 +2023-04-06 04:30:48,447 epoch 80 - iter 1855/2650 - loss 0.08889945 - time (sec): 71.05 - samples/sec: 14536.79 - lr: 0.100000 +2023-04-06 04:30:58,574 epoch 80 - iter 2120/2650 - loss 0.08887894 - time (sec): 81.18 - samples/sec: 14540.55 - lr: 0.100000 +2023-04-06 04:31:08,717 epoch 80 - iter 2385/2650 - loss 0.08921566 - time (sec): 91.32 - samples/sec: 14535.91 - lr: 0.100000 +2023-04-06 04:31:18,865 epoch 80 - iter 2650/2650 - loss 0.08938123 - time (sec): 101.47 - samples/sec: 14524.96 - lr: 0.100000 +2023-04-06 04:31:18,865 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:31:18,865 EPOCH 80 done: loss 0.0894 - lr 0.100000 +2023-04-06 04:31:18,865 BAD EPOCHS (no improvement): 0 +2023-04-06 04:31:18,868 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:31:28,855 epoch 81 - iter 265/2650 - loss 0.08805005 - time (sec): 9.99 - samples/sec: 14637.49 - lr: 0.100000 +2023-04-06 04:31:39,155 epoch 81 - iter 530/2650 - loss 0.08867173 - time (sec): 20.29 - samples/sec: 14566.52 - lr: 0.100000 +2023-04-06 04:31:49,367 epoch 81 - iter 795/2650 - loss 0.08795342 - time (sec): 30.50 - samples/sec: 14505.48 - lr: 0.100000 +2023-04-06 04:31:59,708 epoch 81 - iter 1060/2650 - loss 0.08867225 - time (sec): 40.84 - samples/sec: 14521.62 - lr: 0.100000 +2023-04-06 04:32:09,929 epoch 81 - iter 1325/2650 - loss 0.08913092 - time (sec): 51.06 - samples/sec: 14495.27 - lr: 0.100000 +2023-04-06 04:32:19,925 epoch 81 - iter 1590/2650 - loss 0.08914534 - time (sec): 61.06 - samples/sec: 14492.29 - lr: 0.100000 +2023-04-06 04:32:30,069 epoch 81 - iter 1855/2650 - loss 0.08955207 - time (sec): 71.20 - samples/sec: 14485.88 - lr: 0.100000 +2023-04-06 04:32:40,428 epoch 81 - iter 2120/2650 - loss 0.08959358 - time (sec): 81.56 - samples/sec: 14474.05 - lr: 0.100000 +2023-04-06 04:32:50,646 epoch 81 - iter 2385/2650 - loss 0.08964951 - time (sec): 91.78 - samples/sec: 14463.32 - lr: 0.100000 +2023-04-06 04:33:00,690 epoch 81 - iter 2650/2650 - loss 0.08985024 - time (sec): 101.82 - samples/sec: 14474.58 - lr: 0.100000 +2023-04-06 04:33:00,690 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:33:00,690 EPOCH 81 done: loss 0.0899 - lr 0.100000 +2023-04-06 04:33:00,690 BAD EPOCHS (no improvement): 1 +2023-04-06 04:33:00,695 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:33:10,981 epoch 82 - iter 265/2650 - loss 0.09134360 - time (sec): 10.29 - samples/sec: 14476.28 - lr: 0.100000 +2023-04-06 04:33:21,196 epoch 82 - iter 530/2650 - loss 0.09056674 - time (sec): 20.50 - samples/sec: 14457.05 - lr: 0.100000 +2023-04-06 04:33:35,829 epoch 82 - iter 795/2650 - loss 0.08973422 - time (sec): 35.13 - samples/sec: 12656.30 - lr: 0.100000 +2023-04-06 04:33:46,052 epoch 82 - iter 1060/2650 - loss 0.08972652 - time (sec): 45.36 - samples/sec: 13057.74 - lr: 0.100000 +2023-04-06 04:33:56,182 epoch 82 - iter 1325/2650 - loss 0.08970175 - time (sec): 55.49 - samples/sec: 13317.11 - lr: 0.100000 +2023-04-06 04:34:06,321 epoch 82 - iter 1590/2650 - loss 0.08980760 - time (sec): 65.63 - samples/sec: 13487.92 - lr: 0.100000 +2023-04-06 04:34:16,412 epoch 82 - iter 1855/2650 - loss 0.08984274 - time (sec): 75.72 - samples/sec: 13613.27 - lr: 0.100000 +2023-04-06 04:34:26,562 epoch 82 - iter 2120/2650 - loss 0.08986488 - time (sec): 85.87 - samples/sec: 13716.42 - lr: 0.100000 +2023-04-06 04:34:36,832 epoch 82 - iter 2385/2650 - loss 0.08988644 - time (sec): 96.14 - samples/sec: 13783.85 - lr: 0.100000 +2023-04-06 04:34:47,205 epoch 82 - iter 2650/2650 - loss 0.09018965 - time (sec): 106.51 - samples/sec: 13837.36 - lr: 0.100000 +2023-04-06 04:34:47,206 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:34:47,206 EPOCH 82 done: loss 0.0902 - lr 0.100000 +2023-04-06 04:34:47,206 BAD EPOCHS (no improvement): 2 +2023-04-06 04:34:47,210 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:34:57,279 epoch 83 - iter 265/2650 - loss 0.08920100 - time (sec): 10.07 - samples/sec: 14505.17 - lr: 0.100000 +2023-04-06 04:35:07,547 epoch 83 - iter 530/2650 - loss 0.08763085 - time (sec): 20.34 - samples/sec: 14472.29 - lr: 0.100000 +2023-04-06 04:35:17,615 epoch 83 - iter 795/2650 - loss 0.08707666 - time (sec): 30.41 - samples/sec: 14455.27 - lr: 0.100000 +2023-04-06 04:35:27,904 epoch 83 - iter 1060/2650 - loss 0.08786022 - time (sec): 40.69 - samples/sec: 14438.36 - lr: 0.100000 +2023-04-06 04:35:38,232 epoch 83 - iter 1325/2650 - loss 0.08809630 - time (sec): 51.02 - samples/sec: 14425.53 - lr: 0.100000 +2023-04-06 04:35:48,523 epoch 83 - iter 1590/2650 - loss 0.08847112 - time (sec): 61.31 - samples/sec: 14432.29 - lr: 0.100000 +2023-04-06 04:35:58,627 epoch 83 - iter 1855/2650 - loss 0.08839780 - time (sec): 71.42 - samples/sec: 14446.44 - lr: 0.100000 +2023-04-06 04:36:08,941 epoch 83 - iter 2120/2650 - loss 0.08836218 - time (sec): 81.73 - samples/sec: 14443.64 - lr: 0.100000 +2023-04-06 04:36:19,076 epoch 83 - iter 2385/2650 - loss 0.08854310 - time (sec): 91.87 - samples/sec: 14439.06 - lr: 0.100000 +2023-04-06 04:36:29,252 epoch 83 - iter 2650/2650 - loss 0.08896868 - time (sec): 102.04 - samples/sec: 14443.29 - lr: 0.100000 +2023-04-06 04:36:29,252 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:36:29,252 EPOCH 83 done: loss 0.0890 - lr 0.100000 +2023-04-06 04:36:29,252 BAD EPOCHS (no improvement): 0 +2023-04-06 04:36:29,256 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:36:39,313 epoch 84 - iter 265/2650 - loss 0.08877390 - time (sec): 10.06 - samples/sec: 14493.64 - lr: 0.100000 +2023-04-06 04:36:49,635 epoch 84 - iter 530/2650 - loss 0.08947744 - time (sec): 20.38 - samples/sec: 14405.32 - lr: 0.100000 +2023-04-06 04:36:59,861 epoch 84 - iter 795/2650 - loss 0.08875911 - time (sec): 30.60 - samples/sec: 14391.34 - lr: 0.100000 +2023-04-06 04:37:10,139 epoch 84 - iter 1060/2650 - loss 0.08833885 - time (sec): 40.88 - samples/sec: 14387.15 - lr: 0.100000 +2023-04-06 04:37:20,358 epoch 84 - iter 1325/2650 - loss 0.08884855 - time (sec): 51.10 - samples/sec: 14398.89 - lr: 0.100000 +2023-04-06 04:37:30,630 epoch 84 - iter 1590/2650 - loss 0.08873414 - time (sec): 61.37 - samples/sec: 14401.21 - lr: 0.100000 +2023-04-06 04:37:40,813 epoch 84 - iter 1855/2650 - loss 0.08915535 - time (sec): 71.56 - samples/sec: 14413.21 - lr: 0.100000 +2023-04-06 04:37:51,134 epoch 84 - iter 2120/2650 - loss 0.08927585 - time (sec): 81.88 - samples/sec: 14396.52 - lr: 0.100000 +2023-04-06 04:38:01,365 epoch 84 - iter 2385/2650 - loss 0.08947641 - time (sec): 92.11 - samples/sec: 14399.58 - lr: 0.100000 +2023-04-06 04:38:11,631 epoch 84 - iter 2650/2650 - loss 0.08964787 - time (sec): 102.37 - samples/sec: 14396.39 - lr: 0.100000 +2023-04-06 04:38:11,631 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:38:11,631 EPOCH 84 done: loss 0.0896 - lr 0.100000 +2023-04-06 04:38:11,631 BAD EPOCHS (no improvement): 1 +2023-04-06 04:38:11,635 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:38:21,992 epoch 85 - iter 265/2650 - loss 0.08758184 - time (sec): 10.36 - samples/sec: 14422.17 - lr: 0.100000 +2023-04-06 04:38:32,289 epoch 85 - iter 530/2650 - loss 0.08727258 - time (sec): 20.65 - samples/sec: 14390.37 - lr: 0.100000 +2023-04-06 04:38:42,622 epoch 85 - iter 795/2650 - loss 0.08861359 - time (sec): 30.99 - samples/sec: 14378.59 - lr: 0.100000 +2023-04-06 04:38:52,884 epoch 85 - iter 1060/2650 - loss 0.08848816 - time (sec): 41.25 - samples/sec: 14366.12 - lr: 0.100000 +2023-04-06 04:39:03,106 epoch 85 - iter 1325/2650 - loss 0.08834582 - time (sec): 51.47 - samples/sec: 14387.72 - lr: 0.100000 +2023-04-06 04:39:13,173 epoch 85 - iter 1590/2650 - loss 0.08832801 - time (sec): 61.54 - samples/sec: 14395.01 - lr: 0.100000 +2023-04-06 04:39:23,500 epoch 85 - iter 1855/2650 - loss 0.08857438 - time (sec): 71.87 - samples/sec: 14387.35 - lr: 0.100000 +2023-04-06 04:39:33,614 epoch 85 - iter 2120/2650 - loss 0.08871166 - time (sec): 81.98 - samples/sec: 14391.65 - lr: 0.100000 +2023-04-06 04:39:43,785 epoch 85 - iter 2385/2650 - loss 0.08884937 - time (sec): 92.15 - samples/sec: 14389.41 - lr: 0.100000 +2023-04-06 04:39:54,051 epoch 85 - iter 2650/2650 - loss 0.08886541 - time (sec): 102.42 - samples/sec: 14390.53 - lr: 0.100000 +2023-04-06 04:39:54,051 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:39:54,051 EPOCH 85 done: loss 0.0889 - lr 0.100000 +2023-04-06 04:39:54,051 BAD EPOCHS (no improvement): 0 +2023-04-06 04:39:54,056 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:40:04,357 epoch 86 - iter 265/2650 - loss 0.08664919 - time (sec): 10.30 - samples/sec: 14295.61 - lr: 0.100000 +2023-04-06 04:40:14,395 epoch 86 - iter 530/2650 - loss 0.08674092 - time (sec): 20.34 - samples/sec: 14443.42 - lr: 0.100000 +2023-04-06 04:40:24,696 epoch 86 - iter 795/2650 - loss 0.08767412 - time (sec): 30.64 - samples/sec: 14452.80 - lr: 0.100000 +2023-04-06 04:40:34,831 epoch 86 - iter 1060/2650 - loss 0.08797722 - time (sec): 40.78 - samples/sec: 14500.35 - lr: 0.100000 +2023-04-06 04:40:45,161 epoch 86 - iter 1325/2650 - loss 0.08848584 - time (sec): 51.11 - samples/sec: 14518.93 - lr: 0.100000 +2023-04-06 04:40:55,174 epoch 86 - iter 1590/2650 - loss 0.08871684 - time (sec): 61.12 - samples/sec: 14528.91 - lr: 0.100000 +2023-04-06 04:41:05,383 epoch 86 - iter 1855/2650 - loss 0.08901880 - time (sec): 71.33 - samples/sec: 14509.90 - lr: 0.100000 +2023-04-06 04:41:15,567 epoch 86 - iter 2120/2650 - loss 0.08876488 - time (sec): 81.51 - samples/sec: 14503.07 - lr: 0.100000 +2023-04-06 04:41:25,675 epoch 86 - iter 2385/2650 - loss 0.08876026 - time (sec): 91.62 - samples/sec: 14492.21 - lr: 0.100000 +2023-04-06 04:41:35,742 epoch 86 - iter 2650/2650 - loss 0.08871752 - time (sec): 101.69 - samples/sec: 14493.77 - lr: 0.100000 +2023-04-06 04:41:35,743 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:41:35,743 EPOCH 86 done: loss 0.0887 - lr 0.100000 +2023-04-06 04:41:35,743 BAD EPOCHS (no improvement): 0 +2023-04-06 04:41:35,746 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:41:45,767 epoch 87 - iter 265/2650 - loss 0.08686058 - time (sec): 10.02 - samples/sec: 14515.80 - lr: 0.100000 +2023-04-06 04:41:56,093 epoch 87 - iter 530/2650 - loss 0.08894694 - time (sec): 20.35 - samples/sec: 14477.64 - lr: 0.100000 +2023-04-06 04:42:06,222 epoch 87 - iter 795/2650 - loss 0.08844934 - time (sec): 30.48 - samples/sec: 14465.86 - lr: 0.100000 +2023-04-06 04:42:16,285 epoch 87 - iter 1060/2650 - loss 0.08807092 - time (sec): 40.54 - samples/sec: 14477.99 - lr: 0.100000 +2023-04-06 04:42:26,459 epoch 87 - iter 1325/2650 - loss 0.08824834 - time (sec): 50.71 - samples/sec: 14494.53 - lr: 0.100000 +2023-04-06 04:42:36,664 epoch 87 - iter 1590/2650 - loss 0.08826801 - time (sec): 60.92 - samples/sec: 14511.34 - lr: 0.100000 +2023-04-06 04:42:46,814 epoch 87 - iter 1855/2650 - loss 0.08857822 - time (sec): 71.07 - samples/sec: 14504.80 - lr: 0.100000 +2023-04-06 04:42:57,243 epoch 87 - iter 2120/2650 - loss 0.08853850 - time (sec): 81.50 - samples/sec: 14486.34 - lr: 0.100000 +2023-04-06 04:43:07,464 epoch 87 - iter 2385/2650 - loss 0.08853335 - time (sec): 91.72 - samples/sec: 14486.06 - lr: 0.100000 +2023-04-06 04:43:17,583 epoch 87 - iter 2650/2650 - loss 0.08864860 - time (sec): 101.84 - samples/sec: 14472.44 - lr: 0.100000 +2023-04-06 04:43:17,583 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:43:17,583 EPOCH 87 done: loss 0.0886 - lr 0.100000 +2023-04-06 04:43:17,583 BAD EPOCHS (no improvement): 0 +2023-04-06 04:43:17,587 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:43:27,893 epoch 88 - iter 265/2650 - loss 0.08377799 - time (sec): 10.31 - samples/sec: 14443.17 - lr: 0.100000 +2023-04-06 04:43:38,030 epoch 88 - iter 530/2650 - loss 0.08548613 - time (sec): 20.44 - samples/sec: 14407.17 - lr: 0.100000 +2023-04-06 04:43:48,242 epoch 88 - iter 795/2650 - loss 0.08563705 - time (sec): 30.66 - samples/sec: 14465.73 - lr: 0.100000 +2023-04-06 04:44:03,000 epoch 88 - iter 1060/2650 - loss 0.08690237 - time (sec): 45.41 - samples/sec: 13044.82 - lr: 0.100000 +2023-04-06 04:44:13,048 epoch 88 - iter 1325/2650 - loss 0.08705716 - time (sec): 55.46 - samples/sec: 13343.83 - lr: 0.100000 +2023-04-06 04:44:23,249 epoch 88 - iter 1590/2650 - loss 0.08765271 - time (sec): 65.66 - samples/sec: 13507.26 - lr: 0.100000 +2023-04-06 04:44:33,444 epoch 88 - iter 1855/2650 - loss 0.08766001 - time (sec): 75.86 - samples/sec: 13637.60 - lr: 0.100000 +2023-04-06 04:44:43,603 epoch 88 - iter 2120/2650 - loss 0.08797221 - time (sec): 86.02 - samples/sec: 13719.21 - lr: 0.100000 +2023-04-06 04:44:53,826 epoch 88 - iter 2385/2650 - loss 0.08859132 - time (sec): 96.24 - samples/sec: 13793.03 - lr: 0.100000 +2023-04-06 04:45:03,993 epoch 88 - iter 2650/2650 - loss 0.08873761 - time (sec): 106.41 - samples/sec: 13850.95 - lr: 0.100000 +2023-04-06 04:45:03,993 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:45:03,994 EPOCH 88 done: loss 0.0887 - lr 0.100000 +2023-04-06 04:45:03,994 BAD EPOCHS (no improvement): 1 +2023-04-06 04:45:03,997 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:45:14,160 epoch 89 - iter 265/2650 - loss 0.08459005 - time (sec): 10.16 - samples/sec: 14569.62 - lr: 0.100000 +2023-04-06 04:45:24,324 epoch 89 - iter 530/2650 - loss 0.08626964 - time (sec): 20.33 - samples/sec: 14476.21 - lr: 0.100000 +2023-04-06 04:45:34,515 epoch 89 - iter 795/2650 - loss 0.08729857 - time (sec): 30.52 - samples/sec: 14491.44 - lr: 0.100000 +2023-04-06 04:45:44,577 epoch 89 - iter 1060/2650 - loss 0.08682184 - time (sec): 40.58 - samples/sec: 14497.21 - lr: 0.100000 +2023-04-06 04:45:54,823 epoch 89 - iter 1325/2650 - loss 0.08700652 - time (sec): 50.83 - samples/sec: 14491.31 - lr: 0.100000 +2023-04-06 04:46:05,008 epoch 89 - iter 1590/2650 - loss 0.08754767 - time (sec): 61.01 - samples/sec: 14490.56 - lr: 0.100000 +2023-04-06 04:46:15,193 epoch 89 - iter 1855/2650 - loss 0.08748794 - time (sec): 71.20 - samples/sec: 14509.99 - lr: 0.100000 +2023-04-06 04:46:25,244 epoch 89 - iter 2120/2650 - loss 0.08750495 - time (sec): 81.25 - samples/sec: 14514.67 - lr: 0.100000 +2023-04-06 04:46:35,265 epoch 89 - iter 2385/2650 - loss 0.08739637 - time (sec): 91.27 - samples/sec: 14529.71 - lr: 0.100000 +2023-04-06 04:46:45,347 epoch 89 - iter 2650/2650 - loss 0.08736372 - time (sec): 101.35 - samples/sec: 14541.89 - lr: 0.100000 +2023-04-06 04:46:45,347 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:46:45,348 EPOCH 89 done: loss 0.0874 - lr 0.100000 +2023-04-06 04:46:45,348 BAD EPOCHS (no improvement): 0 +2023-04-06 04:46:45,351 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:46:55,420 epoch 90 - iter 265/2650 - loss 0.08667362 - time (sec): 10.07 - samples/sec: 14657.41 - lr: 0.100000 +2023-04-06 04:47:05,509 epoch 90 - iter 530/2650 - loss 0.08689853 - time (sec): 20.16 - samples/sec: 14620.81 - lr: 0.100000 +2023-04-06 04:47:15,786 epoch 90 - iter 795/2650 - loss 0.08737105 - time (sec): 30.43 - samples/sec: 14532.95 - lr: 0.100000 +2023-04-06 04:47:25,977 epoch 90 - iter 1060/2650 - loss 0.08740567 - time (sec): 40.63 - samples/sec: 14537.40 - lr: 0.100000 +2023-04-06 04:47:35,927 epoch 90 - iter 1325/2650 - loss 0.08753970 - time (sec): 50.58 - samples/sec: 14536.20 - lr: 0.100000 +2023-04-06 04:47:46,104 epoch 90 - iter 1590/2650 - loss 0.08751891 - time (sec): 60.75 - samples/sec: 14535.65 - lr: 0.100000 +2023-04-06 04:47:56,357 epoch 90 - iter 1855/2650 - loss 0.08750081 - time (sec): 71.01 - samples/sec: 14515.10 - lr: 0.100000 +2023-04-06 04:48:06,612 epoch 90 - iter 2120/2650 - loss 0.08774575 - time (sec): 81.26 - samples/sec: 14513.42 - lr: 0.100000 +2023-04-06 04:48:16,827 epoch 90 - iter 2385/2650 - loss 0.08747603 - time (sec): 91.48 - samples/sec: 14501.21 - lr: 0.100000 +2023-04-06 04:48:27,019 epoch 90 - iter 2650/2650 - loss 0.08759660 - time (sec): 101.67 - samples/sec: 14496.42 - lr: 0.100000 +2023-04-06 04:48:27,020 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:48:27,020 EPOCH 90 done: loss 0.0876 - lr 0.100000 +2023-04-06 04:48:27,020 BAD EPOCHS (no improvement): 1 +2023-04-06 04:48:27,022 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:48:37,137 epoch 91 - iter 265/2650 - loss 0.08471630 - time (sec): 10.11 - samples/sec: 14543.86 - lr: 0.100000 +2023-04-06 04:48:47,206 epoch 91 - iter 530/2650 - loss 0.08642630 - time (sec): 20.18 - samples/sec: 14545.78 - lr: 0.100000 +2023-04-06 04:48:57,413 epoch 91 - iter 795/2650 - loss 0.08675540 - time (sec): 30.39 - samples/sec: 14481.06 - lr: 0.100000 +2023-04-06 04:49:07,532 epoch 91 - iter 1060/2650 - loss 0.08717829 - time (sec): 40.51 - samples/sec: 14470.97 - lr: 0.100000 +2023-04-06 04:49:17,810 epoch 91 - iter 1325/2650 - loss 0.08731443 - time (sec): 50.79 - samples/sec: 14467.21 - lr: 0.100000 +2023-04-06 04:49:28,029 epoch 91 - iter 1590/2650 - loss 0.08772776 - time (sec): 61.01 - samples/sec: 14487.06 - lr: 0.100000 +2023-04-06 04:49:38,290 epoch 91 - iter 1855/2650 - loss 0.08771578 - time (sec): 71.27 - samples/sec: 14482.60 - lr: 0.100000 +2023-04-06 04:49:48,504 epoch 91 - iter 2120/2650 - loss 0.08759599 - time (sec): 81.48 - samples/sec: 14484.85 - lr: 0.100000 +2023-04-06 04:49:58,763 epoch 91 - iter 2385/2650 - loss 0.08757036 - time (sec): 91.74 - samples/sec: 14475.78 - lr: 0.100000 +2023-04-06 04:50:08,807 epoch 91 - iter 2650/2650 - loss 0.08753395 - time (sec): 101.78 - samples/sec: 14479.88 - lr: 0.100000 +2023-04-06 04:50:08,807 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:50:08,807 EPOCH 91 done: loss 0.0875 - lr 0.100000 +2023-04-06 04:50:08,807 BAD EPOCHS (no improvement): 2 +2023-04-06 04:50:08,814 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:50:19,051 epoch 92 - iter 265/2650 - loss 0.08550004 - time (sec): 10.24 - samples/sec: 14478.72 - lr: 0.100000 +2023-04-06 04:50:29,352 epoch 92 - iter 530/2650 - loss 0.08595918 - time (sec): 20.54 - samples/sec: 14431.52 - lr: 0.100000 +2023-04-06 04:50:39,538 epoch 92 - iter 795/2650 - loss 0.08713660 - time (sec): 30.72 - samples/sec: 14471.40 - lr: 0.100000 +2023-04-06 04:50:49,801 epoch 92 - iter 1060/2650 - loss 0.08736664 - time (sec): 40.99 - samples/sec: 14480.55 - lr: 0.100000 +2023-04-06 04:51:00,018 epoch 92 - iter 1325/2650 - loss 0.08741382 - time (sec): 51.20 - samples/sec: 14479.20 - lr: 0.100000 +2023-04-06 04:51:10,163 epoch 92 - iter 1590/2650 - loss 0.08789634 - time (sec): 61.35 - samples/sec: 14468.64 - lr: 0.100000 +2023-04-06 04:51:20,167 epoch 92 - iter 1855/2650 - loss 0.08791477 - time (sec): 71.35 - samples/sec: 14482.07 - lr: 0.100000 +2023-04-06 04:51:30,374 epoch 92 - iter 2120/2650 - loss 0.08762360 - time (sec): 81.56 - samples/sec: 14468.51 - lr: 0.100000 +2023-04-06 04:51:40,539 epoch 92 - iter 2385/2650 - loss 0.08790243 - time (sec): 91.72 - samples/sec: 14475.51 - lr: 0.100000 +2023-04-06 04:51:50,722 epoch 92 - iter 2650/2650 - loss 0.08789626 - time (sec): 101.91 - samples/sec: 14462.21 - lr: 0.100000 +2023-04-06 04:51:50,723 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:51:50,723 EPOCH 92 done: loss 0.0879 - lr 0.100000 +2023-04-06 04:51:50,723 BAD EPOCHS (no improvement): 3 +2023-04-06 04:51:50,727 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:52:00,897 epoch 93 - iter 265/2650 - loss 0.08494345 - time (sec): 10.17 - samples/sec: 14552.82 - lr: 0.100000 +2023-04-06 04:52:11,017 epoch 93 - iter 530/2650 - loss 0.08469305 - time (sec): 20.29 - samples/sec: 14515.98 - lr: 0.100000 +2023-04-06 04:52:21,256 epoch 93 - iter 795/2650 - loss 0.08580297 - time (sec): 30.53 - samples/sec: 14522.40 - lr: 0.100000 +2023-04-06 04:52:31,353 epoch 93 - iter 1060/2650 - loss 0.08553379 - time (sec): 40.63 - samples/sec: 14505.19 - lr: 0.100000 +2023-04-06 04:52:41,614 epoch 93 - iter 1325/2650 - loss 0.08590591 - time (sec): 50.89 - samples/sec: 14498.19 - lr: 0.100000 +2023-04-06 04:52:51,717 epoch 93 - iter 1590/2650 - loss 0.08635285 - time (sec): 60.99 - samples/sec: 14509.61 - lr: 0.100000 +2023-04-06 04:53:01,975 epoch 93 - iter 1855/2650 - loss 0.08665454 - time (sec): 71.25 - samples/sec: 14482.16 - lr: 0.100000 +2023-04-06 04:53:12,175 epoch 93 - iter 2120/2650 - loss 0.08680153 - time (sec): 81.45 - samples/sec: 14476.50 - lr: 0.100000 +2023-04-06 04:53:22,607 epoch 93 - iter 2385/2650 - loss 0.08702116 - time (sec): 91.88 - samples/sec: 14451.90 - lr: 0.100000 +2023-04-06 04:53:32,685 epoch 93 - iter 2650/2650 - loss 0.08728956 - time (sec): 101.96 - samples/sec: 14455.18 - lr: 0.100000 +2023-04-06 04:53:32,685 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:53:32,685 EPOCH 93 done: loss 0.0873 - lr 0.100000 +2023-04-06 04:53:32,685 BAD EPOCHS (no improvement): 0 +2023-04-06 04:53:32,689 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:53:42,820 epoch 94 - iter 265/2650 - loss 0.08585640 - time (sec): 10.13 - samples/sec: 14406.14 - lr: 0.100000 +2023-04-06 04:53:53,009 epoch 94 - iter 530/2650 - loss 0.08561460 - time (sec): 20.32 - samples/sec: 14437.89 - lr: 0.100000 +2023-04-06 04:54:03,390 epoch 94 - iter 795/2650 - loss 0.08668999 - time (sec): 30.70 - samples/sec: 14396.68 - lr: 0.100000 +2023-04-06 04:54:13,595 epoch 94 - iter 1060/2650 - loss 0.08606690 - time (sec): 40.91 - samples/sec: 14402.40 - lr: 0.100000 +2023-04-06 04:54:23,847 epoch 94 - iter 1325/2650 - loss 0.08609009 - time (sec): 51.16 - samples/sec: 14390.18 - lr: 0.100000 +2023-04-06 04:54:38,226 epoch 94 - iter 1590/2650 - loss 0.08639081 - time (sec): 65.54 - samples/sec: 13481.98 - lr: 0.100000 +2023-04-06 04:54:48,582 epoch 94 - iter 1855/2650 - loss 0.08658361 - time (sec): 75.89 - samples/sec: 13601.15 - lr: 0.100000 +2023-04-06 04:54:58,765 epoch 94 - iter 2120/2650 - loss 0.08692525 - time (sec): 86.08 - samples/sec: 13704.97 - lr: 0.100000 +2023-04-06 04:55:09,076 epoch 94 - iter 2385/2650 - loss 0.08731743 - time (sec): 96.39 - samples/sec: 13783.43 - lr: 0.100000 +2023-04-06 04:55:19,074 epoch 94 - iter 2650/2650 - loss 0.08763320 - time (sec): 106.38 - samples/sec: 13853.74 - lr: 0.100000 +2023-04-06 04:55:19,074 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:55:19,074 EPOCH 94 done: loss 0.0876 - lr 0.100000 +2023-04-06 04:55:19,074 BAD EPOCHS (no improvement): 1 +2023-04-06 04:55:19,077 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:55:29,275 epoch 95 - iter 265/2650 - loss 0.08351397 - time (sec): 10.20 - samples/sec: 14490.34 - lr: 0.100000 +2023-04-06 04:55:39,395 epoch 95 - iter 530/2650 - loss 0.08526013 - time (sec): 20.32 - samples/sec: 14480.83 - lr: 0.100000 +2023-04-06 04:55:49,562 epoch 95 - iter 795/2650 - loss 0.08555665 - time (sec): 30.48 - samples/sec: 14431.20 - lr: 0.100000 +2023-04-06 04:55:59,832 epoch 95 - iter 1060/2650 - loss 0.08710328 - time (sec): 40.76 - samples/sec: 14433.08 - lr: 0.100000 +2023-04-06 04:56:10,126 epoch 95 - iter 1325/2650 - loss 0.08679012 - time (sec): 51.05 - samples/sec: 14426.80 - lr: 0.100000 +2023-04-06 04:56:20,337 epoch 95 - iter 1590/2650 - loss 0.08655551 - time (sec): 61.26 - samples/sec: 14429.58 - lr: 0.100000 +2023-04-06 04:56:30,677 epoch 95 - iter 1855/2650 - loss 0.08662748 - time (sec): 71.60 - samples/sec: 14405.71 - lr: 0.100000 +2023-04-06 04:56:40,896 epoch 95 - iter 2120/2650 - loss 0.08678102 - time (sec): 81.82 - samples/sec: 14402.76 - lr: 0.100000 +2023-04-06 04:56:51,268 epoch 95 - iter 2385/2650 - loss 0.08705650 - time (sec): 92.19 - samples/sec: 14388.58 - lr: 0.100000 +2023-04-06 04:57:01,544 epoch 95 - iter 2650/2650 - loss 0.08718940 - time (sec): 102.47 - samples/sec: 14383.43 - lr: 0.100000 +2023-04-06 04:57:01,544 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:57:01,544 EPOCH 95 done: loss 0.0872 - lr 0.100000 +2023-04-06 04:57:01,544 BAD EPOCHS (no improvement): 0 +2023-04-06 04:57:01,548 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:57:11,737 epoch 96 - iter 265/2650 - loss 0.08527503 - time (sec): 10.19 - samples/sec: 14471.06 - lr: 0.100000 +2023-04-06 04:57:21,900 epoch 96 - iter 530/2650 - loss 0.08596150 - time (sec): 20.35 - samples/sec: 14504.18 - lr: 0.100000 +2023-04-06 04:57:32,009 epoch 96 - iter 795/2650 - loss 0.08621536 - time (sec): 30.46 - samples/sec: 14514.07 - lr: 0.100000 +2023-04-06 04:57:42,266 epoch 96 - iter 1060/2650 - loss 0.08595165 - time (sec): 40.72 - samples/sec: 14483.08 - lr: 0.100000 +2023-04-06 04:57:52,512 epoch 96 - iter 1325/2650 - loss 0.08596112 - time (sec): 50.96 - samples/sec: 14481.48 - lr: 0.100000 +2023-04-06 04:58:02,591 epoch 96 - iter 1590/2650 - loss 0.08611027 - time (sec): 61.04 - samples/sec: 14468.42 - lr: 0.100000 +2023-04-06 04:58:12,921 epoch 96 - iter 1855/2650 - loss 0.08635775 - time (sec): 71.37 - samples/sec: 14455.24 - lr: 0.100000 +2023-04-06 04:58:23,292 epoch 96 - iter 2120/2650 - loss 0.08641859 - time (sec): 81.74 - samples/sec: 14444.42 - lr: 0.100000 +2023-04-06 04:58:33,457 epoch 96 - iter 2385/2650 - loss 0.08670417 - time (sec): 91.91 - samples/sec: 14441.68 - lr: 0.100000 +2023-04-06 04:58:43,717 epoch 96 - iter 2650/2650 - loss 0.08670475 - time (sec): 102.17 - samples/sec: 14425.33 - lr: 0.100000 +2023-04-06 04:58:43,718 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:58:43,718 EPOCH 96 done: loss 0.0867 - lr 0.100000 +2023-04-06 04:58:43,718 BAD EPOCHS (no improvement): 0 +2023-04-06 04:58:43,722 ---------------------------------------------------------------------------------------------------- +2023-04-06 04:58:53,789 epoch 97 - iter 265/2650 - loss 0.08586302 - time (sec): 10.07 - samples/sec: 14501.34 - lr: 0.100000 +2023-04-06 04:59:04,043 epoch 97 - iter 530/2650 - loss 0.08564755 - time (sec): 20.32 - samples/sec: 14430.85 - lr: 0.100000 +2023-04-06 04:59:14,162 epoch 97 - iter 795/2650 - loss 0.08593732 - time (sec): 30.44 - samples/sec: 14445.69 - lr: 0.100000 +2023-04-06 04:59:24,299 epoch 97 - iter 1060/2650 - loss 0.08593686 - time (sec): 40.58 - samples/sec: 14402.79 - lr: 0.100000 +2023-04-06 04:59:34,754 epoch 97 - iter 1325/2650 - loss 0.08577947 - time (sec): 51.03 - samples/sec: 14402.50 - lr: 0.100000 +2023-04-06 04:59:44,980 epoch 97 - iter 1590/2650 - loss 0.08627186 - time (sec): 61.26 - samples/sec: 14401.69 - lr: 0.100000 +2023-04-06 04:59:55,165 epoch 97 - iter 1855/2650 - loss 0.08651457 - time (sec): 71.44 - samples/sec: 14405.66 - lr: 0.100000 +2023-04-06 05:00:05,448 epoch 97 - iter 2120/2650 - loss 0.08648006 - time (sec): 81.73 - samples/sec: 14421.42 - lr: 0.100000 +2023-04-06 05:00:15,644 epoch 97 - iter 2385/2650 - loss 0.08662402 - time (sec): 91.92 - samples/sec: 14424.13 - lr: 0.100000 +2023-04-06 05:00:25,865 epoch 97 - iter 2650/2650 - loss 0.08690571 - time (sec): 102.14 - samples/sec: 14428.95 - lr: 0.100000 +2023-04-06 05:00:25,866 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:00:25,866 EPOCH 97 done: loss 0.0869 - lr 0.100000 +2023-04-06 05:00:25,866 BAD EPOCHS (no improvement): 1 +2023-04-06 05:00:25,872 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:00:36,073 epoch 98 - iter 265/2650 - loss 0.08532899 - time (sec): 10.20 - samples/sec: 14561.12 - lr: 0.100000 +2023-04-06 05:00:46,244 epoch 98 - iter 530/2650 - loss 0.08545677 - time (sec): 20.37 - samples/sec: 14499.93 - lr: 0.100000 +2023-04-06 05:00:56,554 epoch 98 - iter 795/2650 - loss 0.08573821 - time (sec): 30.68 - samples/sec: 14517.16 - lr: 0.100000 +2023-04-06 05:01:06,612 epoch 98 - iter 1060/2650 - loss 0.08591352 - time (sec): 40.74 - samples/sec: 14526.86 - lr: 0.100000 +2023-04-06 05:01:16,644 epoch 98 - iter 1325/2650 - loss 0.08572499 - time (sec): 50.77 - samples/sec: 14533.93 - lr: 0.100000 +2023-04-06 05:01:26,659 epoch 98 - iter 1590/2650 - loss 0.08547032 - time (sec): 60.79 - samples/sec: 14529.55 - lr: 0.100000 +2023-04-06 05:01:36,774 epoch 98 - iter 1855/2650 - loss 0.08549183 - time (sec): 70.90 - samples/sec: 14523.96 - lr: 0.100000 +2023-04-06 05:01:46,892 epoch 98 - iter 2120/2650 - loss 0.08593946 - time (sec): 81.02 - samples/sec: 14534.87 - lr: 0.100000 +2023-04-06 05:01:57,086 epoch 98 - iter 2385/2650 - loss 0.08601095 - time (sec): 91.21 - samples/sec: 14521.95 - lr: 0.100000 +2023-04-06 05:02:07,470 epoch 98 - iter 2650/2650 - loss 0.08627255 - time (sec): 101.60 - samples/sec: 14506.56 - lr: 0.100000 +2023-04-06 05:02:07,470 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:02:07,470 EPOCH 98 done: loss 0.0863 - lr 0.100000 +2023-04-06 05:02:07,470 BAD EPOCHS (no improvement): 0 +2023-04-06 05:02:07,473 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:02:17,653 epoch 99 - iter 265/2650 - loss 0.08463173 - time (sec): 10.18 - samples/sec: 14350.43 - lr: 0.100000 +2023-04-06 05:02:27,601 epoch 99 - iter 530/2650 - loss 0.08513024 - time (sec): 20.13 - samples/sec: 14450.28 - lr: 0.100000 +2023-04-06 05:02:37,858 epoch 99 - iter 795/2650 - loss 0.08507060 - time (sec): 30.38 - samples/sec: 14427.93 - lr: 0.100000 +2023-04-06 05:02:47,976 epoch 99 - iter 1060/2650 - loss 0.08534421 - time (sec): 40.50 - samples/sec: 14462.89 - lr: 0.100000 +2023-04-06 05:02:58,372 epoch 99 - iter 1325/2650 - loss 0.08529374 - time (sec): 50.90 - samples/sec: 14465.92 - lr: 0.100000 +2023-04-06 05:03:08,523 epoch 99 - iter 1590/2650 - loss 0.08568305 - time (sec): 61.05 - samples/sec: 14460.51 - lr: 0.100000 +2023-04-06 05:03:18,660 epoch 99 - iter 1855/2650 - loss 0.08585713 - time (sec): 71.19 - samples/sec: 14466.22 - lr: 0.100000 +2023-04-06 05:03:28,862 epoch 99 - iter 2120/2650 - loss 0.08614377 - time (sec): 81.39 - samples/sec: 14480.22 - lr: 0.100000 +2023-04-06 05:03:38,978 epoch 99 - iter 2385/2650 - loss 0.08645114 - time (sec): 91.50 - samples/sec: 14481.63 - lr: 0.100000 +2023-04-06 05:03:49,176 epoch 99 - iter 2650/2650 - loss 0.08642223 - time (sec): 101.70 - samples/sec: 14491.54 - lr: 0.100000 +2023-04-06 05:03:49,176 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:03:49,176 EPOCH 99 done: loss 0.0864 - lr 0.100000 +2023-04-06 05:03:49,176 BAD EPOCHS (no improvement): 1 +2023-04-06 05:03:49,181 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:03:59,336 epoch 100 - iter 265/2650 - loss 0.08387010 - time (sec): 10.15 - samples/sec: 14533.69 - lr: 0.100000 +2023-04-06 05:04:09,419 epoch 100 - iter 530/2650 - loss 0.08567468 - time (sec): 20.24 - samples/sec: 14509.16 - lr: 0.100000 +2023-04-06 05:04:19,615 epoch 100 - iter 795/2650 - loss 0.08614737 - time (sec): 30.43 - samples/sec: 14487.21 - lr: 0.100000 +2023-04-06 05:04:29,880 epoch 100 - iter 1060/2650 - loss 0.08625215 - time (sec): 40.70 - samples/sec: 14475.78 - lr: 0.100000 +2023-04-06 05:04:40,110 epoch 100 - iter 1325/2650 - loss 0.08583688 - time (sec): 50.93 - samples/sec: 14455.38 - lr: 0.100000 +2023-04-06 05:04:50,298 epoch 100 - iter 1590/2650 - loss 0.08588355 - time (sec): 61.12 - samples/sec: 14441.12 - lr: 0.100000 +2023-04-06 05:05:05,012 epoch 100 - iter 1855/2650 - loss 0.08569820 - time (sec): 75.83 - samples/sec: 13564.77 - lr: 0.100000 +2023-04-06 05:05:15,214 epoch 100 - iter 2120/2650 - loss 0.08590922 - time (sec): 86.03 - samples/sec: 13687.84 - lr: 0.100000 +2023-04-06 05:05:25,396 epoch 100 - iter 2385/2650 - loss 0.08584945 - time (sec): 96.21 - samples/sec: 13769.81 - lr: 0.100000 +2023-04-06 05:05:35,750 epoch 100 - iter 2650/2650 - loss 0.08605911 - time (sec): 106.57 - samples/sec: 13829.87 - lr: 0.100000 +2023-04-06 05:05:35,750 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:05:35,750 EPOCH 100 done: loss 0.0861 - lr 0.100000 +2023-04-06 05:05:35,750 BAD EPOCHS (no improvement): 0 +2023-04-06 05:05:35,754 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:05:45,954 epoch 101 - iter 265/2650 - loss 0.08773316 - time (sec): 10.20 - samples/sec: 14464.07 - lr: 0.100000 +2023-04-06 05:05:56,106 epoch 101 - iter 530/2650 - loss 0.08771436 - time (sec): 20.35 - samples/sec: 14453.22 - lr: 0.100000 +2023-04-06 05:06:06,429 epoch 101 - iter 795/2650 - loss 0.08778659 - time (sec): 30.67 - samples/sec: 14469.71 - lr: 0.100000 +2023-04-06 05:06:16,657 epoch 101 - iter 1060/2650 - loss 0.08731032 - time (sec): 40.90 - samples/sec: 14435.45 - lr: 0.100000 +2023-04-06 05:06:26,922 epoch 101 - iter 1325/2650 - loss 0.08744010 - time (sec): 51.17 - samples/sec: 14450.18 - lr: 0.100000 +2023-04-06 05:06:37,114 epoch 101 - iter 1590/2650 - loss 0.08754944 - time (sec): 61.36 - samples/sec: 14441.40 - lr: 0.100000 +2023-04-06 05:06:47,279 epoch 101 - iter 1855/2650 - loss 0.08745490 - time (sec): 71.52 - samples/sec: 14447.48 - lr: 0.100000 +2023-04-06 05:06:57,446 epoch 101 - iter 2120/2650 - loss 0.08716793 - time (sec): 81.69 - samples/sec: 14442.43 - lr: 0.100000 +2023-04-06 05:07:07,654 epoch 101 - iter 2385/2650 - loss 0.08732013 - time (sec): 91.90 - samples/sec: 14442.50 - lr: 0.100000 +2023-04-06 05:07:17,856 epoch 101 - iter 2650/2650 - loss 0.08726792 - time (sec): 102.10 - samples/sec: 14434.90 - lr: 0.100000 +2023-04-06 05:07:17,856 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:07:17,856 EPOCH 101 done: loss 0.0873 - lr 0.100000 +2023-04-06 05:07:17,856 BAD EPOCHS (no improvement): 1 +2023-04-06 05:07:17,860 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:07:27,948 epoch 102 - iter 265/2650 - loss 0.08489752 - time (sec): 10.09 - samples/sec: 14547.39 - lr: 0.100000 +2023-04-06 05:07:38,325 epoch 102 - iter 530/2650 - loss 0.08517209 - time (sec): 20.47 - samples/sec: 14442.87 - lr: 0.100000 +2023-04-06 05:07:48,492 epoch 102 - iter 795/2650 - loss 0.08567012 - time (sec): 30.63 - samples/sec: 14502.19 - lr: 0.100000 +2023-04-06 05:07:58,581 epoch 102 - iter 1060/2650 - loss 0.08571080 - time (sec): 40.72 - samples/sec: 14503.32 - lr: 0.100000 +2023-04-06 05:08:08,585 epoch 102 - iter 1325/2650 - loss 0.08571021 - time (sec): 50.73 - samples/sec: 14522.33 - lr: 0.100000 +2023-04-06 05:08:18,731 epoch 102 - iter 1590/2650 - loss 0.08551912 - time (sec): 60.87 - samples/sec: 14507.92 - lr: 0.100000 +2023-04-06 05:08:28,832 epoch 102 - iter 1855/2650 - loss 0.08568349 - time (sec): 70.97 - samples/sec: 14504.81 - lr: 0.100000 +2023-04-06 05:08:39,119 epoch 102 - iter 2120/2650 - loss 0.08578362 - time (sec): 81.26 - samples/sec: 14507.36 - lr: 0.100000 +2023-04-06 05:08:49,269 epoch 102 - iter 2385/2650 - loss 0.08598264 - time (sec): 91.41 - samples/sec: 14512.42 - lr: 0.100000 +2023-04-06 05:08:59,414 epoch 102 - iter 2650/2650 - loss 0.08597937 - time (sec): 101.55 - samples/sec: 14512.67 - lr: 0.100000 +2023-04-06 05:08:59,414 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:08:59,414 EPOCH 102 done: loss 0.0860 - lr 0.100000 +2023-04-06 05:08:59,414 BAD EPOCHS (no improvement): 0 +2023-04-06 05:08:59,418 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:09:09,600 epoch 103 - iter 265/2650 - loss 0.08565470 - time (sec): 10.18 - samples/sec: 14481.75 - lr: 0.100000 +2023-04-06 05:09:19,526 epoch 103 - iter 530/2650 - loss 0.08506883 - time (sec): 20.11 - samples/sec: 14571.74 - lr: 0.100000 +2023-04-06 05:09:29,625 epoch 103 - iter 795/2650 - loss 0.08504370 - time (sec): 30.21 - samples/sec: 14551.51 - lr: 0.100000 +2023-04-06 05:09:39,758 epoch 103 - iter 1060/2650 - loss 0.08468965 - time (sec): 40.34 - samples/sec: 14558.41 - lr: 0.100000 +2023-04-06 05:09:49,808 epoch 103 - iter 1325/2650 - loss 0.08538160 - time (sec): 50.39 - samples/sec: 14560.22 - lr: 0.100000 +2023-04-06 05:09:59,960 epoch 103 - iter 1590/2650 - loss 0.08593599 - time (sec): 60.54 - samples/sec: 14558.68 - lr: 0.100000 +2023-04-06 05:10:10,287 epoch 103 - iter 1855/2650 - loss 0.08595349 - time (sec): 70.87 - samples/sec: 14521.80 - lr: 0.100000 +2023-04-06 05:10:20,589 epoch 103 - iter 2120/2650 - loss 0.08581603 - time (sec): 81.17 - samples/sec: 14519.57 - lr: 0.100000 +2023-04-06 05:10:30,757 epoch 103 - iter 2385/2650 - loss 0.08582159 - time (sec): 91.34 - samples/sec: 14516.34 - lr: 0.100000 +2023-04-06 05:10:40,946 epoch 103 - iter 2650/2650 - loss 0.08575550 - time (sec): 101.53 - samples/sec: 14516.35 - lr: 0.100000 +2023-04-06 05:10:40,947 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:10:40,947 EPOCH 103 done: loss 0.0858 - lr 0.100000 +2023-04-06 05:10:40,947 BAD EPOCHS (no improvement): 0 +2023-04-06 05:10:40,954 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:10:51,260 epoch 104 - iter 265/2650 - loss 0.08526550 - time (sec): 10.31 - samples/sec: 14527.22 - lr: 0.100000 +2023-04-06 05:11:01,381 epoch 104 - iter 530/2650 - loss 0.08626043 - time (sec): 20.43 - samples/sec: 14556.05 - lr: 0.100000 +2023-04-06 05:11:11,647 epoch 104 - iter 795/2650 - loss 0.08595941 - time (sec): 30.69 - samples/sec: 14534.87 - lr: 0.100000 +2023-04-06 05:11:21,709 epoch 104 - iter 1060/2650 - loss 0.08566513 - time (sec): 40.75 - samples/sec: 14536.19 - lr: 0.100000 +2023-04-06 05:11:31,820 epoch 104 - iter 1325/2650 - loss 0.08551685 - time (sec): 50.87 - samples/sec: 14525.57 - lr: 0.100000 +2023-04-06 05:11:41,896 epoch 104 - iter 1590/2650 - loss 0.08584667 - time (sec): 60.94 - samples/sec: 14512.76 - lr: 0.100000 +2023-04-06 05:11:52,001 epoch 104 - iter 1855/2650 - loss 0.08545316 - time (sec): 71.05 - samples/sec: 14522.01 - lr: 0.100000 +2023-04-06 05:12:02,071 epoch 104 - iter 2120/2650 - loss 0.08539573 - time (sec): 81.12 - samples/sec: 14526.01 - lr: 0.100000 +2023-04-06 05:12:12,326 epoch 104 - iter 2385/2650 - loss 0.08566920 - time (sec): 91.37 - samples/sec: 14525.78 - lr: 0.100000 +2023-04-06 05:12:22,406 epoch 104 - iter 2650/2650 - loss 0.08571071 - time (sec): 101.45 - samples/sec: 14527.27 - lr: 0.100000 +2023-04-06 05:12:22,407 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:12:22,407 EPOCH 104 done: loss 0.0857 - lr 0.100000 +2023-04-06 05:12:22,407 BAD EPOCHS (no improvement): 0 +2023-04-06 05:12:22,410 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:12:32,500 epoch 105 - iter 265/2650 - loss 0.08587935 - time (sec): 10.09 - samples/sec: 14553.34 - lr: 0.100000 +2023-04-06 05:12:42,775 epoch 105 - iter 530/2650 - loss 0.08578547 - time (sec): 20.37 - samples/sec: 14464.32 - lr: 0.100000 +2023-04-06 05:12:52,779 epoch 105 - iter 795/2650 - loss 0.08582809 - time (sec): 30.37 - samples/sec: 14529.60 - lr: 0.100000 +2023-04-06 05:13:02,875 epoch 105 - iter 1060/2650 - loss 0.08581036 - time (sec): 40.46 - samples/sec: 14523.80 - lr: 0.100000 +2023-04-06 05:13:12,893 epoch 105 - iter 1325/2650 - loss 0.08594505 - time (sec): 50.48 - samples/sec: 14543.68 - lr: 0.100000 +2023-04-06 05:13:23,233 epoch 105 - iter 1590/2650 - loss 0.08585018 - time (sec): 60.82 - samples/sec: 14511.02 - lr: 0.100000 +2023-04-06 05:13:33,560 epoch 105 - iter 1855/2650 - loss 0.08630854 - time (sec): 71.15 - samples/sec: 14507.42 - lr: 0.100000 +2023-04-06 05:13:43,725 epoch 105 - iter 2120/2650 - loss 0.08654076 - time (sec): 81.31 - samples/sec: 14500.13 - lr: 0.100000 +2023-04-06 05:13:53,969 epoch 105 - iter 2385/2650 - loss 0.08654395 - time (sec): 91.56 - samples/sec: 14501.09 - lr: 0.100000 +2023-04-06 05:14:04,115 epoch 105 - iter 2650/2650 - loss 0.08653547 - time (sec): 101.70 - samples/sec: 14491.16 - lr: 0.100000 +2023-04-06 05:14:04,115 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:14:04,115 EPOCH 105 done: loss 0.0865 - lr 0.100000 +2023-04-06 05:14:04,115 BAD EPOCHS (no improvement): 1 +2023-04-06 05:14:04,119 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:14:14,435 epoch 106 - iter 265/2650 - loss 0.08283838 - time (sec): 10.32 - samples/sec: 14536.10 - lr: 0.100000 +2023-04-06 05:14:24,731 epoch 106 - iter 530/2650 - loss 0.08468584 - time (sec): 20.61 - samples/sec: 14472.25 - lr: 0.100000 +2023-04-06 05:14:34,884 epoch 106 - iter 795/2650 - loss 0.08489869 - time (sec): 30.77 - samples/sec: 14472.67 - lr: 0.100000 +2023-04-06 05:14:45,036 epoch 106 - iter 1060/2650 - loss 0.08510894 - time (sec): 40.92 - samples/sec: 14445.60 - lr: 0.100000 +2023-04-06 05:14:55,195 epoch 106 - iter 1325/2650 - loss 0.08540901 - time (sec): 51.08 - samples/sec: 14450.56 - lr: 0.100000 +2023-04-06 05:15:05,436 epoch 106 - iter 1590/2650 - loss 0.08541305 - time (sec): 61.32 - samples/sec: 14454.65 - lr: 0.100000 +2023-04-06 05:15:15,566 epoch 106 - iter 1855/2650 - loss 0.08532228 - time (sec): 71.45 - samples/sec: 14464.46 - lr: 0.100000 +2023-04-06 05:15:25,659 epoch 106 - iter 2120/2650 - loss 0.08545255 - time (sec): 81.54 - samples/sec: 14469.72 - lr: 0.100000 +2023-04-06 05:15:40,125 epoch 106 - iter 2385/2650 - loss 0.08553071 - time (sec): 96.01 - samples/sec: 13827.02 - lr: 0.100000 +2023-04-06 05:15:50,207 epoch 106 - iter 2650/2650 - loss 0.08555615 - time (sec): 106.09 - samples/sec: 13892.45 - lr: 0.100000 +2023-04-06 05:15:50,207 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:15:50,207 EPOCH 106 done: loss 0.0856 - lr 0.100000 +2023-04-06 05:15:50,208 BAD EPOCHS (no improvement): 0 +2023-04-06 05:15:50,211 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:16:00,444 epoch 107 - iter 265/2650 - loss 0.08412007 - time (sec): 10.23 - samples/sec: 14429.72 - lr: 0.100000 +2023-04-06 05:16:10,594 epoch 107 - iter 530/2650 - loss 0.08389753 - time (sec): 20.38 - samples/sec: 14392.73 - lr: 0.100000 +2023-04-06 05:16:20,886 epoch 107 - iter 795/2650 - loss 0.08396818 - time (sec): 30.68 - samples/sec: 14363.88 - lr: 0.100000 +2023-04-06 05:16:31,035 epoch 107 - iter 1060/2650 - loss 0.08461630 - time (sec): 40.82 - samples/sec: 14415.46 - lr: 0.100000 +2023-04-06 05:16:41,039 epoch 107 - iter 1325/2650 - loss 0.08484995 - time (sec): 50.83 - samples/sec: 14447.29 - lr: 0.100000 +2023-04-06 05:16:51,190 epoch 107 - iter 1590/2650 - loss 0.08453263 - time (sec): 60.98 - samples/sec: 14472.40 - lr: 0.100000 +2023-04-06 05:17:01,407 epoch 107 - iter 1855/2650 - loss 0.08480982 - time (sec): 71.20 - samples/sec: 14480.11 - lr: 0.100000 +2023-04-06 05:17:11,665 epoch 107 - iter 2120/2650 - loss 0.08506504 - time (sec): 81.45 - samples/sec: 14494.46 - lr: 0.100000 +2023-04-06 05:17:21,871 epoch 107 - iter 2385/2650 - loss 0.08504020 - time (sec): 91.66 - samples/sec: 14494.47 - lr: 0.100000 +2023-04-06 05:17:31,828 epoch 107 - iter 2650/2650 - loss 0.08549439 - time (sec): 101.62 - samples/sec: 14503.64 - lr: 0.100000 +2023-04-06 05:17:31,829 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:17:31,829 EPOCH 107 done: loss 0.0855 - lr 0.100000 +2023-04-06 05:17:31,829 BAD EPOCHS (no improvement): 0 +2023-04-06 05:17:31,832 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:17:42,017 epoch 108 - iter 265/2650 - loss 0.08703712 - time (sec): 10.18 - samples/sec: 14360.03 - lr: 0.100000 +2023-04-06 05:17:52,049 epoch 108 - iter 530/2650 - loss 0.08687831 - time (sec): 20.22 - samples/sec: 14482.57 - lr: 0.100000 +2023-04-06 05:18:02,064 epoch 108 - iter 795/2650 - loss 0.08613118 - time (sec): 30.23 - samples/sec: 14503.00 - lr: 0.100000 +2023-04-06 05:18:12,239 epoch 108 - iter 1060/2650 - loss 0.08540679 - time (sec): 40.41 - samples/sec: 14523.92 - lr: 0.100000 +2023-04-06 05:18:22,562 epoch 108 - iter 1325/2650 - loss 0.08595425 - time (sec): 50.73 - samples/sec: 14510.19 - lr: 0.100000 +2023-04-06 05:18:32,672 epoch 108 - iter 1590/2650 - loss 0.08587179 - time (sec): 60.84 - samples/sec: 14527.44 - lr: 0.100000 +2023-04-06 05:18:42,899 epoch 108 - iter 1855/2650 - loss 0.08572018 - time (sec): 71.07 - samples/sec: 14514.29 - lr: 0.100000 +2023-04-06 05:18:53,074 epoch 108 - iter 2120/2650 - loss 0.08572005 - time (sec): 81.24 - samples/sec: 14521.75 - lr: 0.100000 +2023-04-06 05:19:03,271 epoch 108 - iter 2385/2650 - loss 0.08573716 - time (sec): 91.44 - samples/sec: 14511.48 - lr: 0.100000 +2023-04-06 05:19:13,443 epoch 108 - iter 2650/2650 - loss 0.08595950 - time (sec): 101.61 - samples/sec: 14504.56 - lr: 0.100000 +2023-04-06 05:19:13,444 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:19:13,444 EPOCH 108 done: loss 0.0860 - lr 0.100000 +2023-04-06 05:19:13,444 BAD EPOCHS (no improvement): 1 +2023-04-06 05:19:13,447 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:19:23,499 epoch 109 - iter 265/2650 - loss 0.08438106 - time (sec): 10.05 - samples/sec: 14501.29 - lr: 0.100000 +2023-04-06 05:19:33,791 epoch 109 - iter 530/2650 - loss 0.08431913 - time (sec): 20.34 - samples/sec: 14477.22 - lr: 0.100000 +2023-04-06 05:19:43,818 epoch 109 - iter 795/2650 - loss 0.08341939 - time (sec): 30.37 - samples/sec: 14513.81 - lr: 0.100000 +2023-04-06 05:19:53,761 epoch 109 - iter 1060/2650 - loss 0.08321691 - time (sec): 40.31 - samples/sec: 14518.09 - lr: 0.100000 +2023-04-06 05:20:04,099 epoch 109 - iter 1325/2650 - loss 0.08383658 - time (sec): 50.65 - samples/sec: 14521.42 - lr: 0.100000 +2023-04-06 05:20:14,258 epoch 109 - iter 1590/2650 - loss 0.08408037 - time (sec): 60.81 - samples/sec: 14520.10 - lr: 0.100000 +2023-04-06 05:20:24,409 epoch 109 - iter 1855/2650 - loss 0.08457398 - time (sec): 70.96 - samples/sec: 14523.39 - lr: 0.100000 +2023-04-06 05:20:34,583 epoch 109 - iter 2120/2650 - loss 0.08457895 - time (sec): 81.14 - samples/sec: 14517.74 - lr: 0.100000 +2023-04-06 05:20:44,777 epoch 109 - iter 2385/2650 - loss 0.08495050 - time (sec): 91.33 - samples/sec: 14522.14 - lr: 0.100000 +2023-04-06 05:20:54,949 epoch 109 - iter 2650/2650 - loss 0.08509157 - time (sec): 101.50 - samples/sec: 14520.23 - lr: 0.100000 +2023-04-06 05:20:54,949 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:20:54,949 EPOCH 109 done: loss 0.0851 - lr 0.100000 +2023-04-06 05:20:54,949 BAD EPOCHS (no improvement): 0 +2023-04-06 05:20:54,957 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:21:05,179 epoch 110 - iter 265/2650 - loss 0.08563755 - time (sec): 10.22 - samples/sec: 14531.38 - lr: 0.100000 +2023-04-06 05:21:15,407 epoch 110 - iter 530/2650 - loss 0.08505521 - time (sec): 20.45 - samples/sec: 14475.25 - lr: 0.100000 +2023-04-06 05:21:25,510 epoch 110 - iter 795/2650 - loss 0.08492055 - time (sec): 30.55 - samples/sec: 14535.99 - lr: 0.100000 +2023-04-06 05:21:35,881 epoch 110 - iter 1060/2650 - loss 0.08498776 - time (sec): 40.92 - samples/sec: 14504.57 - lr: 0.100000 +2023-04-06 05:21:46,070 epoch 110 - iter 1325/2650 - loss 0.08516091 - time (sec): 51.11 - samples/sec: 14493.37 - lr: 0.100000 +2023-04-06 05:21:56,212 epoch 110 - iter 1590/2650 - loss 0.08499445 - time (sec): 61.26 - samples/sec: 14485.78 - lr: 0.100000 +2023-04-06 05:22:06,430 epoch 110 - iter 1855/2650 - loss 0.08458101 - time (sec): 71.47 - samples/sec: 14488.75 - lr: 0.100000 +2023-04-06 05:22:16,533 epoch 110 - iter 2120/2650 - loss 0.08472756 - time (sec): 81.58 - samples/sec: 14480.61 - lr: 0.100000 +2023-04-06 05:22:26,833 epoch 110 - iter 2385/2650 - loss 0.08466181 - time (sec): 91.88 - samples/sec: 14471.04 - lr: 0.100000 +2023-04-06 05:22:36,818 epoch 110 - iter 2650/2650 - loss 0.08452699 - time (sec): 101.86 - samples/sec: 14469.01 - lr: 0.100000 +2023-04-06 05:22:36,818 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:22:36,818 EPOCH 110 done: loss 0.0845 - lr 0.100000 +2023-04-06 05:22:36,818 BAD EPOCHS (no improvement): 0 +2023-04-06 05:22:36,821 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:22:47,089 epoch 111 - iter 265/2650 - loss 0.08559215 - time (sec): 10.27 - samples/sec: 14390.01 - lr: 0.100000 +2023-04-06 05:22:57,282 epoch 111 - iter 530/2650 - loss 0.08539734 - time (sec): 20.46 - samples/sec: 14434.27 - lr: 0.100000 +2023-04-06 05:23:07,471 epoch 111 - iter 795/2650 - loss 0.08577811 - time (sec): 30.65 - samples/sec: 14407.43 - lr: 0.100000 +2023-04-06 05:23:17,476 epoch 111 - iter 1060/2650 - loss 0.08590775 - time (sec): 40.65 - samples/sec: 14420.40 - lr: 0.100000 +2023-04-06 05:23:27,577 epoch 111 - iter 1325/2650 - loss 0.08536560 - time (sec): 50.75 - samples/sec: 14447.80 - lr: 0.100000 +2023-04-06 05:23:37,850 epoch 111 - iter 1590/2650 - loss 0.08548720 - time (sec): 61.03 - samples/sec: 14452.82 - lr: 0.100000 +2023-04-06 05:23:48,132 epoch 111 - iter 1855/2650 - loss 0.08551492 - time (sec): 71.31 - samples/sec: 14444.66 - lr: 0.100000 +2023-04-06 05:23:58,254 epoch 111 - iter 2120/2650 - loss 0.08557210 - time (sec): 81.43 - samples/sec: 14462.64 - lr: 0.100000 +2023-04-06 05:24:08,481 epoch 111 - iter 2385/2650 - loss 0.08580337 - time (sec): 91.66 - samples/sec: 14472.17 - lr: 0.100000 +2023-04-06 05:24:18,636 epoch 111 - iter 2650/2650 - loss 0.08549921 - time (sec): 101.81 - samples/sec: 14475.62 - lr: 0.100000 +2023-04-06 05:24:18,636 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:24:18,636 EPOCH 111 done: loss 0.0855 - lr 0.100000 +2023-04-06 05:24:18,636 BAD EPOCHS (no improvement): 1 +2023-04-06 05:24:18,639 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:24:28,976 epoch 112 - iter 265/2650 - loss 0.08470386 - time (sec): 10.34 - samples/sec: 14409.16 - lr: 0.100000 +2023-04-06 05:24:39,211 epoch 112 - iter 530/2650 - loss 0.08395896 - time (sec): 20.57 - samples/sec: 14449.28 - lr: 0.100000 +2023-04-06 05:24:49,286 epoch 112 - iter 795/2650 - loss 0.08417611 - time (sec): 30.65 - samples/sec: 14472.03 - lr: 0.100000 +2023-04-06 05:24:59,350 epoch 112 - iter 1060/2650 - loss 0.08393088 - time (sec): 40.71 - samples/sec: 14480.42 - lr: 0.100000 +2023-04-06 05:25:09,557 epoch 112 - iter 1325/2650 - loss 0.08377496 - time (sec): 50.92 - samples/sec: 14463.46 - lr: 0.100000 +2023-04-06 05:25:19,713 epoch 112 - iter 1590/2650 - loss 0.08389840 - time (sec): 61.07 - samples/sec: 14469.53 - lr: 0.100000 +2023-04-06 05:25:29,868 epoch 112 - iter 1855/2650 - loss 0.08377845 - time (sec): 71.23 - samples/sec: 14477.23 - lr: 0.100000 +2023-04-06 05:25:40,062 epoch 112 - iter 2120/2650 - loss 0.08420190 - time (sec): 81.42 - samples/sec: 14476.01 - lr: 0.100000 +2023-04-06 05:25:50,182 epoch 112 - iter 2385/2650 - loss 0.08464231 - time (sec): 91.54 - samples/sec: 14480.80 - lr: 0.100000 +2023-04-06 05:26:00,386 epoch 112 - iter 2650/2650 - loss 0.08486143 - time (sec): 101.75 - samples/sec: 14485.20 - lr: 0.100000 +2023-04-06 05:26:00,386 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:26:00,386 EPOCH 112 done: loss 0.0849 - lr 0.100000 +2023-04-06 05:26:00,386 BAD EPOCHS (no improvement): 2 +2023-04-06 05:26:00,406 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:26:15,123 epoch 113 - iter 265/2650 - loss 0.08406757 - time (sec): 14.72 - samples/sec: 10260.48 - lr: 0.100000 +2023-04-06 05:26:25,252 epoch 113 - iter 530/2650 - loss 0.08337089 - time (sec): 24.85 - samples/sec: 12040.41 - lr: 0.100000 +2023-04-06 05:26:35,311 epoch 113 - iter 795/2650 - loss 0.08357468 - time (sec): 34.90 - samples/sec: 12768.77 - lr: 0.100000 +2023-04-06 05:26:45,456 epoch 113 - iter 1060/2650 - loss 0.08398339 - time (sec): 45.05 - samples/sec: 13149.26 - lr: 0.100000 +2023-04-06 05:26:55,610 epoch 113 - iter 1325/2650 - loss 0.08406345 - time (sec): 55.20 - samples/sec: 13382.68 - lr: 0.100000 +2023-04-06 05:27:05,829 epoch 113 - iter 1590/2650 - loss 0.08407792 - time (sec): 65.42 - samples/sec: 13551.42 - lr: 0.100000 +2023-04-06 05:27:15,952 epoch 113 - iter 1855/2650 - loss 0.08424942 - time (sec): 75.55 - samples/sec: 13684.53 - lr: 0.100000 +2023-04-06 05:27:26,000 epoch 113 - iter 2120/2650 - loss 0.08458475 - time (sec): 85.59 - samples/sec: 13785.18 - lr: 0.100000 +2023-04-06 05:27:36,125 epoch 113 - iter 2385/2650 - loss 0.08485825 - time (sec): 95.72 - samples/sec: 13865.32 - lr: 0.100000 +2023-04-06 05:27:46,289 epoch 113 - iter 2650/2650 - loss 0.08496625 - time (sec): 105.88 - samples/sec: 13919.30 - lr: 0.100000 +2023-04-06 05:27:46,290 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:27:46,290 EPOCH 113 done: loss 0.0850 - lr 0.100000 +2023-04-06 05:27:46,290 BAD EPOCHS (no improvement): 3 +2023-04-06 05:27:46,293 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:27:56,343 epoch 114 - iter 265/2650 - loss 0.08444100 - time (sec): 10.05 - samples/sec: 14530.11 - lr: 0.100000 +2023-04-06 05:28:06,618 epoch 114 - iter 530/2650 - loss 0.08436213 - time (sec): 20.32 - samples/sec: 14464.62 - lr: 0.100000 +2023-04-06 05:28:16,607 epoch 114 - iter 795/2650 - loss 0.08510608 - time (sec): 30.31 - samples/sec: 14471.42 - lr: 0.100000 +2023-04-06 05:28:26,799 epoch 114 - iter 1060/2650 - loss 0.08546183 - time (sec): 40.51 - samples/sec: 14461.38 - lr: 0.100000 +2023-04-06 05:28:37,088 epoch 114 - iter 1325/2650 - loss 0.08530369 - time (sec): 50.79 - samples/sec: 14448.59 - lr: 0.100000 +2023-04-06 05:28:47,312 epoch 114 - iter 1590/2650 - loss 0.08491927 - time (sec): 61.02 - samples/sec: 14426.14 - lr: 0.100000 +2023-04-06 05:28:57,624 epoch 114 - iter 1855/2650 - loss 0.08477310 - time (sec): 71.33 - samples/sec: 14431.41 - lr: 0.100000 +2023-04-06 05:29:07,958 epoch 114 - iter 2120/2650 - loss 0.08486755 - time (sec): 81.66 - samples/sec: 14416.26 - lr: 0.100000 +2023-04-06 05:29:18,195 epoch 114 - iter 2385/2650 - loss 0.08498770 - time (sec): 91.90 - samples/sec: 14422.69 - lr: 0.100000 +2023-04-06 05:29:28,566 epoch 114 - iter 2650/2650 - loss 0.08499562 - time (sec): 102.27 - samples/sec: 14410.65 - lr: 0.100000 +2023-04-06 05:29:28,567 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:29:28,567 EPOCH 114 done: loss 0.0850 - lr 0.100000 +2023-04-06 05:29:28,567 Epoch 114: reducing learning rate of group 0 to 5.0000e-02. +2023-04-06 05:29:28,567 BAD EPOCHS (no improvement): 4 +2023-04-06 05:29:28,571 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:29:38,803 epoch 115 - iter 265/2650 - loss 0.08072395 - time (sec): 10.23 - samples/sec: 14453.06 - lr: 0.050000 +2023-04-06 05:29:49,068 epoch 115 - iter 530/2650 - loss 0.08030789 - time (sec): 20.50 - samples/sec: 14445.59 - lr: 0.050000 +2023-04-06 05:29:59,384 epoch 115 - iter 795/2650 - loss 0.08017749 - time (sec): 30.81 - samples/sec: 14456.69 - lr: 0.050000 +2023-04-06 05:30:09,631 epoch 115 - iter 1060/2650 - loss 0.07958167 - time (sec): 41.06 - samples/sec: 14439.35 - lr: 0.050000 +2023-04-06 05:30:19,959 epoch 115 - iter 1325/2650 - loss 0.07973553 - time (sec): 51.39 - samples/sec: 14412.72 - lr: 0.050000 +2023-04-06 05:30:30,233 epoch 115 - iter 1590/2650 - loss 0.07998099 - time (sec): 61.66 - samples/sec: 14413.48 - lr: 0.050000 +2023-04-06 05:30:40,474 epoch 115 - iter 1855/2650 - loss 0.08016963 - time (sec): 71.90 - samples/sec: 14406.78 - lr: 0.050000 +2023-04-06 05:30:50,623 epoch 115 - iter 2120/2650 - loss 0.07976818 - time (sec): 82.05 - samples/sec: 14402.95 - lr: 0.050000 +2023-04-06 05:31:00,792 epoch 115 - iter 2385/2650 - loss 0.07988957 - time (sec): 92.22 - samples/sec: 14403.83 - lr: 0.050000 +2023-04-06 05:31:10,950 epoch 115 - iter 2650/2650 - loss 0.07982406 - time (sec): 102.38 - samples/sec: 14395.82 - lr: 0.050000 +2023-04-06 05:31:10,950 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:31:10,950 EPOCH 115 done: loss 0.0798 - lr 0.050000 +2023-04-06 05:31:10,950 BAD EPOCHS (no improvement): 0 +2023-04-06 05:31:10,955 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:31:21,092 epoch 116 - iter 265/2650 - loss 0.07479397 - time (sec): 10.14 - samples/sec: 14428.62 - lr: 0.050000 +2023-04-06 05:31:31,242 epoch 116 - iter 530/2650 - loss 0.07541725 - time (sec): 20.29 - samples/sec: 14433.11 - lr: 0.050000 +2023-04-06 05:31:41,332 epoch 116 - iter 795/2650 - loss 0.07624117 - time (sec): 30.38 - samples/sec: 14432.08 - lr: 0.050000 +2023-04-06 05:31:51,630 epoch 116 - iter 1060/2650 - loss 0.07668081 - time (sec): 40.67 - samples/sec: 14411.66 - lr: 0.050000 +2023-04-06 05:32:01,938 epoch 116 - iter 1325/2650 - loss 0.07732031 - time (sec): 50.98 - samples/sec: 14374.33 - lr: 0.050000 +2023-04-06 05:32:12,248 epoch 116 - iter 1590/2650 - loss 0.07711708 - time (sec): 61.29 - samples/sec: 14367.11 - lr: 0.050000 +2023-04-06 05:32:22,698 epoch 116 - iter 1855/2650 - loss 0.07729527 - time (sec): 71.74 - samples/sec: 14366.60 - lr: 0.050000 +2023-04-06 05:32:32,922 epoch 116 - iter 2120/2650 - loss 0.07712799 - time (sec): 81.97 - samples/sec: 14378.91 - lr: 0.050000 +2023-04-06 05:32:43,200 epoch 116 - iter 2385/2650 - loss 0.07693778 - time (sec): 92.24 - samples/sec: 14379.43 - lr: 0.050000 +2023-04-06 05:32:53,395 epoch 116 - iter 2650/2650 - loss 0.07675975 - time (sec): 102.44 - samples/sec: 14387.17 - lr: 0.050000 +2023-04-06 05:32:53,395 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:32:53,396 EPOCH 116 done: loss 0.0768 - lr 0.050000 +2023-04-06 05:32:53,396 BAD EPOCHS (no improvement): 0 +2023-04-06 05:32:53,399 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:33:03,648 epoch 117 - iter 265/2650 - loss 0.07630526 - time (sec): 10.25 - samples/sec: 14385.17 - lr: 0.050000 +2023-04-06 05:33:13,803 epoch 117 - iter 530/2650 - loss 0.07505957 - time (sec): 20.40 - samples/sec: 14408.23 - lr: 0.050000 +2023-04-06 05:33:24,004 epoch 117 - iter 795/2650 - loss 0.07515553 - time (sec): 30.60 - samples/sec: 14402.93 - lr: 0.050000 +2023-04-06 05:33:34,184 epoch 117 - iter 1060/2650 - loss 0.07507908 - time (sec): 40.78 - samples/sec: 14381.47 - lr: 0.050000 +2023-04-06 05:33:44,276 epoch 117 - iter 1325/2650 - loss 0.07534554 - time (sec): 50.88 - samples/sec: 14396.22 - lr: 0.050000 +2023-04-06 05:33:54,567 epoch 117 - iter 1590/2650 - loss 0.07574163 - time (sec): 61.17 - samples/sec: 14390.23 - lr: 0.050000 +2023-04-06 05:34:04,823 epoch 117 - iter 1855/2650 - loss 0.07633712 - time (sec): 71.42 - samples/sec: 14395.22 - lr: 0.050000 +2023-04-06 05:34:15,204 epoch 117 - iter 2120/2650 - loss 0.07639056 - time (sec): 81.80 - samples/sec: 14404.53 - lr: 0.050000 +2023-04-06 05:34:25,571 epoch 117 - iter 2385/2650 - loss 0.07650981 - time (sec): 92.17 - samples/sec: 14400.27 - lr: 0.050000 +2023-04-06 05:34:35,836 epoch 117 - iter 2650/2650 - loss 0.07653889 - time (sec): 102.44 - samples/sec: 14387.70 - lr: 0.050000 +2023-04-06 05:34:35,836 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:34:35,836 EPOCH 117 done: loss 0.0765 - lr 0.050000 +2023-04-06 05:34:35,836 BAD EPOCHS (no improvement): 0 +2023-04-06 05:34:35,840 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:34:46,025 epoch 118 - iter 265/2650 - loss 0.07565537 - time (sec): 10.18 - samples/sec: 14414.01 - lr: 0.050000 +2023-04-06 05:34:56,335 epoch 118 - iter 530/2650 - loss 0.07655257 - time (sec): 20.49 - samples/sec: 14394.23 - lr: 0.050000 +2023-04-06 05:35:06,636 epoch 118 - iter 795/2650 - loss 0.07663494 - time (sec): 30.80 - samples/sec: 14415.67 - lr: 0.050000 +2023-04-06 05:35:16,884 epoch 118 - iter 1060/2650 - loss 0.07700656 - time (sec): 41.04 - samples/sec: 14390.84 - lr: 0.050000 +2023-04-06 05:35:27,067 epoch 118 - iter 1325/2650 - loss 0.07672789 - time (sec): 51.23 - samples/sec: 14406.32 - lr: 0.050000 +2023-04-06 05:35:37,103 epoch 118 - iter 1590/2650 - loss 0.07636292 - time (sec): 61.26 - samples/sec: 14417.85 - lr: 0.050000 +2023-04-06 05:35:47,286 epoch 118 - iter 1855/2650 - loss 0.07648904 - time (sec): 71.45 - samples/sec: 14436.79 - lr: 0.050000 +2023-04-06 05:35:57,446 epoch 118 - iter 2120/2650 - loss 0.07661261 - time (sec): 81.61 - samples/sec: 14445.87 - lr: 0.050000 +2023-04-06 05:36:07,671 epoch 118 - iter 2385/2650 - loss 0.07663303 - time (sec): 91.83 - samples/sec: 14459.34 - lr: 0.050000 +2023-04-06 05:36:17,720 epoch 118 - iter 2650/2650 - loss 0.07660689 - time (sec): 101.88 - samples/sec: 14466.27 - lr: 0.050000 +2023-04-06 05:36:17,721 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:36:17,721 EPOCH 118 done: loss 0.0766 - lr 0.050000 +2023-04-06 05:36:17,721 BAD EPOCHS (no improvement): 1 +2023-04-06 05:36:17,724 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:36:27,628 epoch 119 - iter 265/2650 - loss 0.07719001 - time (sec): 9.90 - samples/sec: 14738.29 - lr: 0.050000 +2023-04-06 05:36:42,078 epoch 119 - iter 530/2650 - loss 0.07533117 - time (sec): 24.35 - samples/sec: 11998.08 - lr: 0.050000 +2023-04-06 05:36:51,972 epoch 119 - iter 795/2650 - loss 0.07508773 - time (sec): 34.25 - samples/sec: 12798.43 - lr: 0.050000 +2023-04-06 05:37:02,100 epoch 119 - iter 1060/2650 - loss 0.07542025 - time (sec): 44.38 - samples/sec: 13208.54 - lr: 0.050000 +2023-04-06 05:37:12,250 epoch 119 - iter 1325/2650 - loss 0.07580390 - time (sec): 54.53 - samples/sec: 13471.28 - lr: 0.050000 +2023-04-06 05:37:22,636 epoch 119 - iter 1590/2650 - loss 0.07569584 - time (sec): 64.91 - samples/sec: 13625.77 - lr: 0.050000 +2023-04-06 05:37:32,686 epoch 119 - iter 1855/2650 - loss 0.07571807 - time (sec): 74.96 - samples/sec: 13749.49 - lr: 0.050000 +2023-04-06 05:37:42,900 epoch 119 - iter 2120/2650 - loss 0.07568211 - time (sec): 85.18 - samples/sec: 13843.46 - lr: 0.050000 +2023-04-06 05:37:53,050 epoch 119 - iter 2385/2650 - loss 0.07584356 - time (sec): 95.33 - samples/sec: 13915.25 - lr: 0.050000 +2023-04-06 05:38:03,277 epoch 119 - iter 2650/2650 - loss 0.07582098 - time (sec): 105.55 - samples/sec: 13962.89 - lr: 0.050000 +2023-04-06 05:38:03,278 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:38:03,278 EPOCH 119 done: loss 0.0758 - lr 0.050000 +2023-04-06 05:38:03,278 BAD EPOCHS (no improvement): 0 +2023-04-06 05:38:03,282 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:38:13,564 epoch 120 - iter 265/2650 - loss 0.07618152 - time (sec): 10.28 - samples/sec: 14505.38 - lr: 0.050000 +2023-04-06 05:38:23,643 epoch 120 - iter 530/2650 - loss 0.07549061 - time (sec): 20.36 - samples/sec: 14567.05 - lr: 0.050000 +2023-04-06 05:38:33,757 epoch 120 - iter 795/2650 - loss 0.07491790 - time (sec): 30.47 - samples/sec: 14545.61 - lr: 0.050000 +2023-04-06 05:38:43,804 epoch 120 - iter 1060/2650 - loss 0.07527088 - time (sec): 40.52 - samples/sec: 14564.45 - lr: 0.050000 +2023-04-06 05:38:54,003 epoch 120 - iter 1325/2650 - loss 0.07492467 - time (sec): 50.72 - samples/sec: 14546.22 - lr: 0.050000 +2023-04-06 05:39:04,029 epoch 120 - iter 1590/2650 - loss 0.07523061 - time (sec): 60.75 - samples/sec: 14554.03 - lr: 0.050000 +2023-04-06 05:39:14,219 epoch 120 - iter 1855/2650 - loss 0.07544369 - time (sec): 70.94 - samples/sec: 14545.86 - lr: 0.050000 +2023-04-06 05:39:24,378 epoch 120 - iter 2120/2650 - loss 0.07538245 - time (sec): 81.10 - samples/sec: 14545.85 - lr: 0.050000 +2023-04-06 05:39:34,561 epoch 120 - iter 2385/2650 - loss 0.07551683 - time (sec): 91.28 - samples/sec: 14536.29 - lr: 0.050000 +2023-04-06 05:39:44,637 epoch 120 - iter 2650/2650 - loss 0.07555902 - time (sec): 101.36 - samples/sec: 14541.16 - lr: 0.050000 +2023-04-06 05:39:44,637 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:39:44,637 EPOCH 120 done: loss 0.0756 - lr 0.050000 +2023-04-06 05:39:44,637 BAD EPOCHS (no improvement): 0 +2023-04-06 05:39:44,641 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:39:54,796 epoch 121 - iter 265/2650 - loss 0.07277726 - time (sec): 10.16 - samples/sec: 14493.16 - lr: 0.050000 +2023-04-06 05:40:04,869 epoch 121 - iter 530/2650 - loss 0.07497268 - time (sec): 20.23 - samples/sec: 14567.39 - lr: 0.050000 +2023-04-06 05:40:14,930 epoch 121 - iter 795/2650 - loss 0.07476223 - time (sec): 30.29 - samples/sec: 14562.15 - lr: 0.050000 +2023-04-06 05:40:25,087 epoch 121 - iter 1060/2650 - loss 0.07496630 - time (sec): 40.45 - samples/sec: 14552.49 - lr: 0.050000 +2023-04-06 05:40:35,280 epoch 121 - iter 1325/2650 - loss 0.07452567 - time (sec): 50.64 - samples/sec: 14514.22 - lr: 0.050000 +2023-04-06 05:40:45,596 epoch 121 - iter 1590/2650 - loss 0.07461301 - time (sec): 60.95 - samples/sec: 14494.42 - lr: 0.050000 +2023-04-06 05:40:55,901 epoch 121 - iter 1855/2650 - loss 0.07474607 - time (sec): 71.26 - samples/sec: 14478.04 - lr: 0.050000 +2023-04-06 05:41:06,049 epoch 121 - iter 2120/2650 - loss 0.07490983 - time (sec): 81.41 - samples/sec: 14471.34 - lr: 0.050000 +2023-04-06 05:41:16,254 epoch 121 - iter 2385/2650 - loss 0.07486648 - time (sec): 91.61 - samples/sec: 14472.85 - lr: 0.050000 +2023-04-06 05:41:26,546 epoch 121 - iter 2650/2650 - loss 0.07479346 - time (sec): 101.91 - samples/sec: 14462.64 - lr: 0.050000 +2023-04-06 05:41:26,546 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:41:26,547 EPOCH 121 done: loss 0.0748 - lr 0.050000 +2023-04-06 05:41:26,547 BAD EPOCHS (no improvement): 0 +2023-04-06 05:41:26,554 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:41:36,609 epoch 122 - iter 265/2650 - loss 0.07302979 - time (sec): 10.06 - samples/sec: 14432.07 - lr: 0.050000 +2023-04-06 05:41:46,686 epoch 122 - iter 530/2650 - loss 0.07265434 - time (sec): 20.13 - samples/sec: 14423.72 - lr: 0.050000 +2023-04-06 05:41:56,886 epoch 122 - iter 795/2650 - loss 0.07250289 - time (sec): 30.33 - samples/sec: 14418.01 - lr: 0.050000 +2023-04-06 05:42:07,279 epoch 122 - iter 1060/2650 - loss 0.07290962 - time (sec): 40.72 - samples/sec: 14408.50 - lr: 0.050000 +2023-04-06 05:42:17,455 epoch 122 - iter 1325/2650 - loss 0.07330363 - time (sec): 50.90 - samples/sec: 14412.72 - lr: 0.050000 +2023-04-06 05:42:27,794 epoch 122 - iter 1590/2650 - loss 0.07361541 - time (sec): 61.24 - samples/sec: 14404.42 - lr: 0.050000 +2023-04-06 05:42:38,084 epoch 122 - iter 1855/2650 - loss 0.07395857 - time (sec): 71.53 - samples/sec: 14412.11 - lr: 0.050000 +2023-04-06 05:42:48,403 epoch 122 - iter 2120/2650 - loss 0.07420531 - time (sec): 81.85 - samples/sec: 14423.06 - lr: 0.050000 +2023-04-06 05:42:58,421 epoch 122 - iter 2385/2650 - loss 0.07411257 - time (sec): 91.87 - samples/sec: 14432.91 - lr: 0.050000 +2023-04-06 05:43:08,733 epoch 122 - iter 2650/2650 - loss 0.07418415 - time (sec): 102.18 - samples/sec: 14423.99 - lr: 0.050000 +2023-04-06 05:43:08,733 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:43:08,733 EPOCH 122 done: loss 0.0742 - lr 0.050000 +2023-04-06 05:43:08,733 BAD EPOCHS (no improvement): 0 +2023-04-06 05:43:08,737 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:43:18,861 epoch 123 - iter 265/2650 - loss 0.07541415 - time (sec): 10.12 - samples/sec: 14472.47 - lr: 0.050000 +2023-04-06 05:43:29,122 epoch 123 - iter 530/2650 - loss 0.07505464 - time (sec): 20.38 - samples/sec: 14426.32 - lr: 0.050000 +2023-04-06 05:43:39,271 epoch 123 - iter 795/2650 - loss 0.07412452 - time (sec): 30.53 - samples/sec: 14437.13 - lr: 0.050000 +2023-04-06 05:43:49,462 epoch 123 - iter 1060/2650 - loss 0.07422116 - time (sec): 40.72 - samples/sec: 14423.31 - lr: 0.050000 +2023-04-06 05:43:59,655 epoch 123 - iter 1325/2650 - loss 0.07449723 - time (sec): 50.92 - samples/sec: 14410.09 - lr: 0.050000 +2023-04-06 05:44:09,892 epoch 123 - iter 1590/2650 - loss 0.07436845 - time (sec): 61.15 - samples/sec: 14396.15 - lr: 0.050000 +2023-04-06 05:44:20,221 epoch 123 - iter 1855/2650 - loss 0.07418952 - time (sec): 71.48 - samples/sec: 14408.89 - lr: 0.050000 +2023-04-06 05:44:30,371 epoch 123 - iter 2120/2650 - loss 0.07417569 - time (sec): 81.63 - samples/sec: 14415.25 - lr: 0.050000 +2023-04-06 05:44:40,656 epoch 123 - iter 2385/2650 - loss 0.07397582 - time (sec): 91.92 - samples/sec: 14416.31 - lr: 0.050000 +2023-04-06 05:44:50,972 epoch 123 - iter 2650/2650 - loss 0.07387657 - time (sec): 102.23 - samples/sec: 14416.08 - lr: 0.050000 +2023-04-06 05:44:50,972 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:44:50,972 EPOCH 123 done: loss 0.0739 - lr 0.050000 +2023-04-06 05:44:50,972 BAD EPOCHS (no improvement): 0 +2023-04-06 05:44:50,976 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:45:01,140 epoch 124 - iter 265/2650 - loss 0.07351572 - time (sec): 10.16 - samples/sec: 14471.13 - lr: 0.050000 +2023-04-06 05:45:11,249 epoch 124 - iter 530/2650 - loss 0.07403125 - time (sec): 20.27 - samples/sec: 14485.09 - lr: 0.050000 +2023-04-06 05:45:21,469 epoch 124 - iter 795/2650 - loss 0.07358958 - time (sec): 30.49 - samples/sec: 14456.56 - lr: 0.050000 +2023-04-06 05:45:31,674 epoch 124 - iter 1060/2650 - loss 0.07353978 - time (sec): 40.70 - samples/sec: 14443.66 - lr: 0.050000 +2023-04-06 05:45:42,143 epoch 124 - iter 1325/2650 - loss 0.07391003 - time (sec): 51.17 - samples/sec: 14427.43 - lr: 0.050000 +2023-04-06 05:45:52,244 epoch 124 - iter 1590/2650 - loss 0.07402756 - time (sec): 61.27 - samples/sec: 14440.37 - lr: 0.050000 +2023-04-06 05:46:02,470 epoch 124 - iter 1855/2650 - loss 0.07373514 - time (sec): 71.49 - samples/sec: 14433.14 - lr: 0.050000 +2023-04-06 05:46:12,760 epoch 124 - iter 2120/2650 - loss 0.07348650 - time (sec): 81.78 - samples/sec: 14423.31 - lr: 0.050000 +2023-04-06 05:46:22,956 epoch 124 - iter 2385/2650 - loss 0.07365493 - time (sec): 91.98 - samples/sec: 14421.34 - lr: 0.050000 +2023-04-06 05:46:33,211 epoch 124 - iter 2650/2650 - loss 0.07380678 - time (sec): 102.24 - samples/sec: 14415.96 - lr: 0.050000 +2023-04-06 05:46:33,211 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:46:33,212 EPOCH 124 done: loss 0.0738 - lr 0.050000 +2023-04-06 05:46:33,212 BAD EPOCHS (no improvement): 0 +2023-04-06 05:46:33,215 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:46:43,356 epoch 125 - iter 265/2650 - loss 0.07391849 - time (sec): 10.14 - samples/sec: 14431.01 - lr: 0.050000 +2023-04-06 05:46:53,542 epoch 125 - iter 530/2650 - loss 0.07294080 - time (sec): 20.33 - samples/sec: 14431.81 - lr: 0.050000 +2023-04-06 05:47:03,749 epoch 125 - iter 795/2650 - loss 0.07365149 - time (sec): 30.53 - samples/sec: 14410.48 - lr: 0.050000 +2023-04-06 05:47:18,094 epoch 125 - iter 1060/2650 - loss 0.07384150 - time (sec): 44.88 - samples/sec: 13072.98 - lr: 0.050000 +2023-04-06 05:47:28,384 epoch 125 - iter 1325/2650 - loss 0.07418249 - time (sec): 55.17 - samples/sec: 13321.02 - lr: 0.050000 +2023-04-06 05:47:38,607 epoch 125 - iter 1590/2650 - loss 0.07405702 - time (sec): 65.39 - samples/sec: 13496.45 - lr: 0.050000 +2023-04-06 05:47:48,963 epoch 125 - iter 1855/2650 - loss 0.07362430 - time (sec): 75.75 - samples/sec: 13616.27 - lr: 0.050000 +2023-04-06 05:47:59,206 epoch 125 - iter 2120/2650 - loss 0.07342182 - time (sec): 85.99 - samples/sec: 13712.09 - lr: 0.050000 +2023-04-06 05:48:09,459 epoch 125 - iter 2385/2650 - loss 0.07320703 - time (sec): 96.24 - samples/sec: 13788.99 - lr: 0.050000 +2023-04-06 05:48:19,575 epoch 125 - iter 2650/2650 - loss 0.07317767 - time (sec): 106.36 - samples/sec: 13856.89 - lr: 0.050000 +2023-04-06 05:48:19,575 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:48:19,576 EPOCH 125 done: loss 0.0732 - lr 0.050000 +2023-04-06 05:48:19,576 BAD EPOCHS (no improvement): 0 +2023-04-06 05:48:19,580 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:48:29,818 epoch 126 - iter 265/2650 - loss 0.07167821 - time (sec): 10.24 - samples/sec: 14443.74 - lr: 0.050000 +2023-04-06 05:48:39,821 epoch 126 - iter 530/2650 - loss 0.07282050 - time (sec): 20.24 - samples/sec: 14495.60 - lr: 0.050000 +2023-04-06 05:48:50,221 epoch 126 - iter 795/2650 - loss 0.07251490 - time (sec): 30.64 - samples/sec: 14471.44 - lr: 0.050000 +2023-04-06 05:49:00,278 epoch 126 - iter 1060/2650 - loss 0.07319843 - time (sec): 40.70 - samples/sec: 14473.27 - lr: 0.050000 +2023-04-06 05:49:10,496 epoch 126 - iter 1325/2650 - loss 0.07329997 - time (sec): 50.92 - samples/sec: 14499.31 - lr: 0.050000 +2023-04-06 05:49:20,656 epoch 126 - iter 1590/2650 - loss 0.07356355 - time (sec): 61.08 - samples/sec: 14509.92 - lr: 0.050000 +2023-04-06 05:49:30,688 epoch 126 - iter 1855/2650 - loss 0.07306954 - time (sec): 71.11 - samples/sec: 14518.67 - lr: 0.050000 +2023-04-06 05:49:40,696 epoch 126 - iter 2120/2650 - loss 0.07311298 - time (sec): 81.12 - samples/sec: 14520.81 - lr: 0.050000 +2023-04-06 05:49:50,868 epoch 126 - iter 2385/2650 - loss 0.07330760 - time (sec): 91.29 - samples/sec: 14519.27 - lr: 0.050000 +2023-04-06 05:50:01,207 epoch 126 - iter 2650/2650 - loss 0.07334427 - time (sec): 101.63 - samples/sec: 14502.27 - lr: 0.050000 +2023-04-06 05:50:01,207 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:50:01,207 EPOCH 126 done: loss 0.0733 - lr 0.050000 +2023-04-06 05:50:01,207 BAD EPOCHS (no improvement): 1 +2023-04-06 05:50:01,210 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:50:11,408 epoch 127 - iter 265/2650 - loss 0.07160410 - time (sec): 10.20 - samples/sec: 14374.47 - lr: 0.050000 +2023-04-06 05:50:21,602 epoch 127 - iter 530/2650 - loss 0.07257429 - time (sec): 20.39 - samples/sec: 14387.75 - lr: 0.050000 +2023-04-06 05:50:31,656 epoch 127 - iter 795/2650 - loss 0.07209163 - time (sec): 30.45 - samples/sec: 14417.69 - lr: 0.050000 +2023-04-06 05:50:41,679 epoch 127 - iter 1060/2650 - loss 0.07199916 - time (sec): 40.47 - samples/sec: 14421.23 - lr: 0.050000 +2023-04-06 05:50:51,934 epoch 127 - iter 1325/2650 - loss 0.07238051 - time (sec): 50.72 - samples/sec: 14421.84 - lr: 0.050000 +2023-04-06 05:51:02,259 epoch 127 - iter 1590/2650 - loss 0.07271980 - time (sec): 61.05 - samples/sec: 14400.58 - lr: 0.050000 +2023-04-06 05:51:12,528 epoch 127 - iter 1855/2650 - loss 0.07290998 - time (sec): 71.32 - samples/sec: 14420.05 - lr: 0.050000 +2023-04-06 05:51:22,807 epoch 127 - iter 2120/2650 - loss 0.07288362 - time (sec): 81.60 - samples/sec: 14411.68 - lr: 0.050000 +2023-04-06 05:51:33,156 epoch 127 - iter 2385/2650 - loss 0.07302029 - time (sec): 91.95 - samples/sec: 14411.96 - lr: 0.050000 +2023-04-06 05:51:43,501 epoch 127 - iter 2650/2650 - loss 0.07312318 - time (sec): 102.29 - samples/sec: 14408.13 - lr: 0.050000 +2023-04-06 05:51:43,501 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:51:43,502 EPOCH 127 done: loss 0.0731 - lr 0.050000 +2023-04-06 05:51:43,502 BAD EPOCHS (no improvement): 0 +2023-04-06 05:51:43,508 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:51:53,537 epoch 128 - iter 265/2650 - loss 0.06989096 - time (sec): 10.03 - samples/sec: 14470.25 - lr: 0.050000 +2023-04-06 05:52:03,938 epoch 128 - iter 530/2650 - loss 0.07180639 - time (sec): 20.43 - samples/sec: 14381.90 - lr: 0.050000 +2023-04-06 05:52:14,103 epoch 128 - iter 795/2650 - loss 0.07185783 - time (sec): 30.59 - samples/sec: 14458.67 - lr: 0.050000 +2023-04-06 05:52:24,213 epoch 128 - iter 1060/2650 - loss 0.07168462 - time (sec): 40.70 - samples/sec: 14480.03 - lr: 0.050000 +2023-04-06 05:52:34,349 epoch 128 - iter 1325/2650 - loss 0.07220237 - time (sec): 50.84 - samples/sec: 14489.83 - lr: 0.050000 +2023-04-06 05:52:44,507 epoch 128 - iter 1590/2650 - loss 0.07222181 - time (sec): 61.00 - samples/sec: 14497.27 - lr: 0.050000 +2023-04-06 05:52:54,658 epoch 128 - iter 1855/2650 - loss 0.07200144 - time (sec): 71.15 - samples/sec: 14493.66 - lr: 0.050000 +2023-04-06 05:53:04,936 epoch 128 - iter 2120/2650 - loss 0.07188980 - time (sec): 81.43 - samples/sec: 14485.94 - lr: 0.050000 +2023-04-06 05:53:15,132 epoch 128 - iter 2385/2650 - loss 0.07188923 - time (sec): 91.62 - samples/sec: 14491.54 - lr: 0.050000 +2023-04-06 05:53:25,177 epoch 128 - iter 2650/2650 - loss 0.07194620 - time (sec): 101.67 - samples/sec: 14496.31 - lr: 0.050000 +2023-04-06 05:53:25,177 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:53:25,177 EPOCH 128 done: loss 0.0719 - lr 0.050000 +2023-04-06 05:53:25,177 BAD EPOCHS (no improvement): 0 +2023-04-06 05:53:25,180 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:53:35,359 epoch 129 - iter 265/2650 - loss 0.07123884 - time (sec): 10.18 - samples/sec: 14543.25 - lr: 0.050000 +2023-04-06 05:53:45,517 epoch 129 - iter 530/2650 - loss 0.07085253 - time (sec): 20.34 - samples/sec: 14531.59 - lr: 0.050000 +2023-04-06 05:53:55,683 epoch 129 - iter 795/2650 - loss 0.07149990 - time (sec): 30.50 - samples/sec: 14536.78 - lr: 0.050000 +2023-04-06 05:54:05,874 epoch 129 - iter 1060/2650 - loss 0.07223179 - time (sec): 40.69 - samples/sec: 14552.63 - lr: 0.050000 +2023-04-06 05:54:16,102 epoch 129 - iter 1325/2650 - loss 0.07217718 - time (sec): 50.92 - samples/sec: 14540.66 - lr: 0.050000 +2023-04-06 05:54:26,075 epoch 129 - iter 1590/2650 - loss 0.07211040 - time (sec): 60.90 - samples/sec: 14540.68 - lr: 0.050000 +2023-04-06 05:54:36,332 epoch 129 - iter 1855/2650 - loss 0.07235703 - time (sec): 71.15 - samples/sec: 14521.94 - lr: 0.050000 +2023-04-06 05:54:46,460 epoch 129 - iter 2120/2650 - loss 0.07221692 - time (sec): 81.28 - samples/sec: 14507.39 - lr: 0.050000 +2023-04-06 05:54:56,740 epoch 129 - iter 2385/2650 - loss 0.07219341 - time (sec): 91.56 - samples/sec: 14492.69 - lr: 0.050000 +2023-04-06 05:55:06,874 epoch 129 - iter 2650/2650 - loss 0.07216985 - time (sec): 101.69 - samples/sec: 14492.73 - lr: 0.050000 +2023-04-06 05:55:06,874 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:55:06,874 EPOCH 129 done: loss 0.0722 - lr 0.050000 +2023-04-06 05:55:06,874 BAD EPOCHS (no improvement): 1 +2023-04-06 05:55:06,878 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:55:16,856 epoch 130 - iter 265/2650 - loss 0.07156777 - time (sec): 9.98 - samples/sec: 14478.19 - lr: 0.050000 +2023-04-06 05:55:26,846 epoch 130 - iter 530/2650 - loss 0.07192180 - time (sec): 19.97 - samples/sec: 14472.30 - lr: 0.050000 +2023-04-06 05:55:37,157 epoch 130 - iter 795/2650 - loss 0.07187552 - time (sec): 30.28 - samples/sec: 14438.58 - lr: 0.050000 +2023-04-06 05:55:47,423 epoch 130 - iter 1060/2650 - loss 0.07114642 - time (sec): 40.54 - samples/sec: 14452.01 - lr: 0.050000 +2023-04-06 05:55:57,650 epoch 130 - iter 1325/2650 - loss 0.07148242 - time (sec): 50.77 - samples/sec: 14455.08 - lr: 0.050000 +2023-04-06 05:56:07,746 epoch 130 - iter 1590/2650 - loss 0.07141457 - time (sec): 60.87 - samples/sec: 14451.09 - lr: 0.050000 +2023-04-06 05:56:18,151 epoch 130 - iter 1855/2650 - loss 0.07166190 - time (sec): 71.27 - samples/sec: 14452.68 - lr: 0.050000 +2023-04-06 05:56:28,360 epoch 130 - iter 2120/2650 - loss 0.07158339 - time (sec): 81.48 - samples/sec: 14453.90 - lr: 0.050000 +2023-04-06 05:56:38,583 epoch 130 - iter 2385/2650 - loss 0.07180347 - time (sec): 91.70 - samples/sec: 14457.54 - lr: 0.050000 +2023-04-06 05:56:48,748 epoch 130 - iter 2650/2650 - loss 0.07183069 - time (sec): 101.87 - samples/sec: 14467.78 - lr: 0.050000 +2023-04-06 05:56:48,748 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:56:48,748 EPOCH 130 done: loss 0.0718 - lr 0.050000 +2023-04-06 05:56:48,748 BAD EPOCHS (no improvement): 0 +2023-04-06 05:56:48,752 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:56:58,832 epoch 131 - iter 265/2650 - loss 0.06993547 - time (sec): 10.08 - samples/sec: 14612.44 - lr: 0.050000 +2023-04-06 05:57:08,954 epoch 131 - iter 530/2650 - loss 0.07190945 - time (sec): 20.20 - samples/sec: 14560.77 - lr: 0.050000 +2023-04-06 05:57:19,046 epoch 131 - iter 795/2650 - loss 0.07103220 - time (sec): 30.29 - samples/sec: 14555.33 - lr: 0.050000 +2023-04-06 05:57:29,205 epoch 131 - iter 1060/2650 - loss 0.07131628 - time (sec): 40.45 - samples/sec: 14532.07 - lr: 0.050000 +2023-04-06 05:57:39,283 epoch 131 - iter 1325/2650 - loss 0.07147848 - time (sec): 50.53 - samples/sec: 14535.06 - lr: 0.050000 +2023-04-06 05:57:53,671 epoch 131 - iter 1590/2650 - loss 0.07175252 - time (sec): 64.92 - samples/sec: 13547.09 - lr: 0.050000 +2023-04-06 05:58:03,800 epoch 131 - iter 1855/2650 - loss 0.07177452 - time (sec): 75.05 - samples/sec: 13701.79 - lr: 0.050000 +2023-04-06 05:58:14,101 epoch 131 - iter 2120/2650 - loss 0.07197258 - time (sec): 85.35 - samples/sec: 13794.93 - lr: 0.050000 +2023-04-06 05:58:24,353 epoch 131 - iter 2385/2650 - loss 0.07202037 - time (sec): 95.60 - samples/sec: 13872.21 - lr: 0.050000 +2023-04-06 05:58:34,584 epoch 131 - iter 2650/2650 - loss 0.07189353 - time (sec): 105.83 - samples/sec: 13926.05 - lr: 0.050000 +2023-04-06 05:58:34,584 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:58:34,584 EPOCH 131 done: loss 0.0719 - lr 0.050000 +2023-04-06 05:58:34,584 BAD EPOCHS (no improvement): 1 +2023-04-06 05:58:34,588 ---------------------------------------------------------------------------------------------------- +2023-04-06 05:58:44,803 epoch 132 - iter 265/2650 - loss 0.07069847 - time (sec): 10.22 - samples/sec: 14417.58 - lr: 0.050000 +2023-04-06 05:58:55,150 epoch 132 - iter 530/2650 - loss 0.07182581 - time (sec): 20.56 - samples/sec: 14405.96 - lr: 0.050000 +2023-04-06 05:59:05,340 epoch 132 - iter 795/2650 - loss 0.07104858 - time (sec): 30.75 - samples/sec: 14453.65 - lr: 0.050000 +2023-04-06 05:59:15,603 epoch 132 - iter 1060/2650 - loss 0.07144458 - time (sec): 41.01 - samples/sec: 14453.48 - lr: 0.050000 +2023-04-06 05:59:25,730 epoch 132 - iter 1325/2650 - loss 0.07136200 - time (sec): 51.14 - samples/sec: 14454.65 - lr: 0.050000 +2023-04-06 05:59:35,912 epoch 132 - iter 1590/2650 - loss 0.07137759 - time (sec): 61.32 - samples/sec: 14448.67 - lr: 0.050000 +2023-04-06 05:59:46,123 epoch 132 - iter 1855/2650 - loss 0.07181440 - time (sec): 71.54 - samples/sec: 14449.56 - lr: 0.050000 +2023-04-06 05:59:56,290 epoch 132 - iter 2120/2650 - loss 0.07169080 - time (sec): 81.70 - samples/sec: 14448.38 - lr: 0.050000 +2023-04-06 06:00:06,461 epoch 132 - iter 2385/2650 - loss 0.07159183 - time (sec): 91.87 - samples/sec: 14456.25 - lr: 0.050000 +2023-04-06 06:00:16,531 epoch 132 - iter 2650/2650 - loss 0.07164641 - time (sec): 101.94 - samples/sec: 14457.35 - lr: 0.050000 +2023-04-06 06:00:16,531 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:00:16,531 EPOCH 132 done: loss 0.0716 - lr 0.050000 +2023-04-06 06:00:16,531 BAD EPOCHS (no improvement): 0 +2023-04-06 06:00:16,534 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:00:26,709 epoch 133 - iter 265/2650 - loss 0.06991611 - time (sec): 10.17 - samples/sec: 14402.87 - lr: 0.050000 +2023-04-06 06:00:37,031 epoch 133 - iter 530/2650 - loss 0.06962504 - time (sec): 20.50 - samples/sec: 14403.43 - lr: 0.050000 +2023-04-06 06:00:47,208 epoch 133 - iter 795/2650 - loss 0.07018914 - time (sec): 30.67 - samples/sec: 14436.78 - lr: 0.050000 +2023-04-06 06:00:57,486 epoch 133 - iter 1060/2650 - loss 0.07020071 - time (sec): 40.95 - samples/sec: 14449.91 - lr: 0.050000 +2023-04-06 06:01:07,692 epoch 133 - iter 1325/2650 - loss 0.07057650 - time (sec): 51.16 - samples/sec: 14454.09 - lr: 0.050000 +2023-04-06 06:01:17,710 epoch 133 - iter 1590/2650 - loss 0.07023432 - time (sec): 61.18 - samples/sec: 14459.35 - lr: 0.050000 +2023-04-06 06:01:27,862 epoch 133 - iter 1855/2650 - loss 0.07044292 - time (sec): 71.33 - samples/sec: 14464.60 - lr: 0.050000 +2023-04-06 06:01:38,004 epoch 133 - iter 2120/2650 - loss 0.07083787 - time (sec): 81.47 - samples/sec: 14462.61 - lr: 0.050000 +2023-04-06 06:01:48,257 epoch 133 - iter 2385/2650 - loss 0.07100420 - time (sec): 91.72 - samples/sec: 14462.41 - lr: 0.050000 +2023-04-06 06:01:58,379 epoch 133 - iter 2650/2650 - loss 0.07097400 - time (sec): 101.84 - samples/sec: 14471.28 - lr: 0.050000 +2023-04-06 06:01:58,379 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:01:58,379 EPOCH 133 done: loss 0.0710 - lr 0.050000 +2023-04-06 06:01:58,379 BAD EPOCHS (no improvement): 0 +2023-04-06 06:01:58,386 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:02:08,616 epoch 134 - iter 265/2650 - loss 0.06938914 - time (sec): 10.23 - samples/sec: 14399.83 - lr: 0.050000 +2023-04-06 06:02:18,828 epoch 134 - iter 530/2650 - loss 0.07091000 - time (sec): 20.44 - samples/sec: 14470.68 - lr: 0.050000 +2023-04-06 06:02:29,179 epoch 134 - iter 795/2650 - loss 0.07105165 - time (sec): 30.79 - samples/sec: 14442.42 - lr: 0.050000 +2023-04-06 06:02:39,270 epoch 134 - iter 1060/2650 - loss 0.07097038 - time (sec): 40.88 - samples/sec: 14465.42 - lr: 0.050000 +2023-04-06 06:02:49,487 epoch 134 - iter 1325/2650 - loss 0.07110510 - time (sec): 51.10 - samples/sec: 14450.91 - lr: 0.050000 +2023-04-06 06:02:59,531 epoch 134 - iter 1590/2650 - loss 0.07119903 - time (sec): 61.15 - samples/sec: 14462.03 - lr: 0.050000 +2023-04-06 06:03:09,841 epoch 134 - iter 1855/2650 - loss 0.07150678 - time (sec): 71.46 - samples/sec: 14447.37 - lr: 0.050000 +2023-04-06 06:03:19,950 epoch 134 - iter 2120/2650 - loss 0.07148234 - time (sec): 81.56 - samples/sec: 14460.81 - lr: 0.050000 +2023-04-06 06:03:30,042 epoch 134 - iter 2385/2650 - loss 0.07155171 - time (sec): 91.66 - samples/sec: 14461.43 - lr: 0.050000 +2023-04-06 06:03:40,225 epoch 134 - iter 2650/2650 - loss 0.07145287 - time (sec): 101.84 - samples/sec: 14472.10 - lr: 0.050000 +2023-04-06 06:03:40,225 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:03:40,225 EPOCH 134 done: loss 0.0715 - lr 0.050000 +2023-04-06 06:03:40,225 BAD EPOCHS (no improvement): 1 +2023-04-06 06:03:40,231 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:03:50,425 epoch 135 - iter 265/2650 - loss 0.06982390 - time (sec): 10.19 - samples/sec: 14519.77 - lr: 0.050000 +2023-04-06 06:04:00,724 epoch 135 - iter 530/2650 - loss 0.07016826 - time (sec): 20.49 - samples/sec: 14527.25 - lr: 0.050000 +2023-04-06 06:04:10,855 epoch 135 - iter 795/2650 - loss 0.07108229 - time (sec): 30.62 - samples/sec: 14485.53 - lr: 0.050000 +2023-04-06 06:04:21,016 epoch 135 - iter 1060/2650 - loss 0.07095020 - time (sec): 40.78 - samples/sec: 14462.05 - lr: 0.050000 +2023-04-06 06:04:31,156 epoch 135 - iter 1325/2650 - loss 0.07063523 - time (sec): 50.92 - samples/sec: 14472.47 - lr: 0.050000 +2023-04-06 06:04:41,353 epoch 135 - iter 1590/2650 - loss 0.07080118 - time (sec): 61.12 - samples/sec: 14463.80 - lr: 0.050000 +2023-04-06 06:04:51,584 epoch 135 - iter 1855/2650 - loss 0.07052857 - time (sec): 71.35 - samples/sec: 14461.71 - lr: 0.050000 +2023-04-06 06:05:01,956 epoch 135 - iter 2120/2650 - loss 0.07081092 - time (sec): 81.73 - samples/sec: 14444.21 - lr: 0.050000 +2023-04-06 06:05:12,287 epoch 135 - iter 2385/2650 - loss 0.07094031 - time (sec): 92.06 - samples/sec: 14439.95 - lr: 0.050000 +2023-04-06 06:05:22,352 epoch 135 - iter 2650/2650 - loss 0.07083522 - time (sec): 102.12 - samples/sec: 14432.18 - lr: 0.050000 +2023-04-06 06:05:22,352 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:05:22,352 EPOCH 135 done: loss 0.0708 - lr 0.050000 +2023-04-06 06:05:22,352 BAD EPOCHS (no improvement): 0 +2023-04-06 06:05:22,356 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:05:32,631 epoch 136 - iter 265/2650 - loss 0.07030095 - time (sec): 10.28 - samples/sec: 14492.94 - lr: 0.050000 +2023-04-06 06:05:42,891 epoch 136 - iter 530/2650 - loss 0.07171919 - time (sec): 20.53 - samples/sec: 14433.77 - lr: 0.050000 +2023-04-06 06:05:53,260 epoch 136 - iter 795/2650 - loss 0.07081465 - time (sec): 30.90 - samples/sec: 14392.94 - lr: 0.050000 +2023-04-06 06:06:03,574 epoch 136 - iter 1060/2650 - loss 0.07048184 - time (sec): 41.22 - samples/sec: 14387.56 - lr: 0.050000 +2023-04-06 06:06:13,552 epoch 136 - iter 1325/2650 - loss 0.07057184 - time (sec): 51.20 - samples/sec: 14420.30 - lr: 0.050000 +2023-04-06 06:06:23,806 epoch 136 - iter 1590/2650 - loss 0.07066760 - time (sec): 61.45 - samples/sec: 14417.83 - lr: 0.050000 +2023-04-06 06:06:33,870 epoch 136 - iter 1855/2650 - loss 0.07087409 - time (sec): 71.51 - samples/sec: 14423.24 - lr: 0.050000 +2023-04-06 06:06:44,149 epoch 136 - iter 2120/2650 - loss 0.07074231 - time (sec): 81.79 - samples/sec: 14409.35 - lr: 0.050000 +2023-04-06 06:06:54,355 epoch 136 - iter 2385/2650 - loss 0.07080621 - time (sec): 92.00 - samples/sec: 14414.68 - lr: 0.050000 +2023-04-06 06:07:04,623 epoch 136 - iter 2650/2650 - loss 0.07089156 - time (sec): 102.27 - samples/sec: 14411.57 - lr: 0.050000 +2023-04-06 06:07:04,623 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:07:04,623 EPOCH 136 done: loss 0.0709 - lr 0.050000 +2023-04-06 06:07:04,623 BAD EPOCHS (no improvement): 1 +2023-04-06 06:07:04,627 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:07:14,874 epoch 137 - iter 265/2650 - loss 0.06892503 - time (sec): 10.25 - samples/sec: 14461.33 - lr: 0.050000 +2023-04-06 06:07:25,251 epoch 137 - iter 530/2650 - loss 0.07017638 - time (sec): 20.62 - samples/sec: 14410.79 - lr: 0.050000 +2023-04-06 06:07:35,403 epoch 137 - iter 795/2650 - loss 0.07021715 - time (sec): 30.78 - samples/sec: 14409.18 - lr: 0.050000 +2023-04-06 06:07:45,576 epoch 137 - iter 1060/2650 - loss 0.06961045 - time (sec): 40.95 - samples/sec: 14411.43 - lr: 0.050000 +2023-04-06 06:07:55,771 epoch 137 - iter 1325/2650 - loss 0.06971019 - time (sec): 51.14 - samples/sec: 14435.50 - lr: 0.050000 +2023-04-06 06:08:05,834 epoch 137 - iter 1590/2650 - loss 0.06954130 - time (sec): 61.21 - samples/sec: 14460.72 - lr: 0.050000 +2023-04-06 06:08:16,069 epoch 137 - iter 1855/2650 - loss 0.06996827 - time (sec): 71.44 - samples/sec: 14453.05 - lr: 0.050000 +2023-04-06 06:08:30,591 epoch 137 - iter 2120/2650 - loss 0.07013308 - time (sec): 85.96 - samples/sec: 13723.84 - lr: 0.050000 +2023-04-06 06:08:40,718 epoch 137 - iter 2385/2650 - loss 0.06997085 - time (sec): 96.09 - samples/sec: 13816.13 - lr: 0.050000 +2023-04-06 06:08:50,818 epoch 137 - iter 2650/2650 - loss 0.07017596 - time (sec): 106.19 - samples/sec: 13879.05 - lr: 0.050000 +2023-04-06 06:08:50,818 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:08:50,818 EPOCH 137 done: loss 0.0702 - lr 0.050000 +2023-04-06 06:08:50,818 BAD EPOCHS (no improvement): 0 +2023-04-06 06:08:50,821 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:09:00,882 epoch 138 - iter 265/2650 - loss 0.06989798 - time (sec): 10.06 - samples/sec: 14486.78 - lr: 0.050000 +2023-04-06 06:09:11,028 epoch 138 - iter 530/2650 - loss 0.07207804 - time (sec): 20.21 - samples/sec: 14557.45 - lr: 0.050000 +2023-04-06 06:09:21,296 epoch 138 - iter 795/2650 - loss 0.07209954 - time (sec): 30.47 - samples/sec: 14540.31 - lr: 0.050000 +2023-04-06 06:09:31,556 epoch 138 - iter 1060/2650 - loss 0.07185692 - time (sec): 40.73 - samples/sec: 14537.57 - lr: 0.050000 +2023-04-06 06:09:41,739 epoch 138 - iter 1325/2650 - loss 0.07156425 - time (sec): 50.92 - samples/sec: 14521.27 - lr: 0.050000 +2023-04-06 06:09:51,846 epoch 138 - iter 1590/2650 - loss 0.07136113 - time (sec): 61.02 - samples/sec: 14517.76 - lr: 0.050000 +2023-04-06 06:10:01,905 epoch 138 - iter 1855/2650 - loss 0.07132167 - time (sec): 71.08 - samples/sec: 14528.73 - lr: 0.050000 +2023-04-06 06:10:12,064 epoch 138 - iter 2120/2650 - loss 0.07091307 - time (sec): 81.24 - samples/sec: 14532.18 - lr: 0.050000 +2023-04-06 06:10:22,405 epoch 138 - iter 2385/2650 - loss 0.07084835 - time (sec): 91.58 - samples/sec: 14505.38 - lr: 0.050000 +2023-04-06 06:10:32,412 epoch 138 - iter 2650/2650 - loss 0.07060385 - time (sec): 101.59 - samples/sec: 14507.43 - lr: 0.050000 +2023-04-06 06:10:32,412 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:10:32,412 EPOCH 138 done: loss 0.0706 - lr 0.050000 +2023-04-06 06:10:32,413 BAD EPOCHS (no improvement): 1 +2023-04-06 06:10:32,417 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:10:42,705 epoch 139 - iter 265/2650 - loss 0.06964083 - time (sec): 10.29 - samples/sec: 14397.90 - lr: 0.050000 +2023-04-06 06:10:52,848 epoch 139 - iter 530/2650 - loss 0.06934608 - time (sec): 20.43 - samples/sec: 14425.31 - lr: 0.050000 +2023-04-06 06:11:03,110 epoch 139 - iter 795/2650 - loss 0.06940262 - time (sec): 30.69 - samples/sec: 14433.42 - lr: 0.050000 +2023-04-06 06:11:13,287 epoch 139 - iter 1060/2650 - loss 0.06906814 - time (sec): 40.87 - samples/sec: 14443.76 - lr: 0.050000 +2023-04-06 06:11:23,356 epoch 139 - iter 1325/2650 - loss 0.06936961 - time (sec): 50.94 - samples/sec: 14437.01 - lr: 0.050000 +2023-04-06 06:11:33,539 epoch 139 - iter 1590/2650 - loss 0.06895254 - time (sec): 61.12 - samples/sec: 14453.04 - lr: 0.050000 +2023-04-06 06:11:43,811 epoch 139 - iter 1855/2650 - loss 0.06939724 - time (sec): 71.39 - samples/sec: 14444.98 - lr: 0.050000 +2023-04-06 06:11:53,929 epoch 139 - iter 2120/2650 - loss 0.06946709 - time (sec): 81.51 - samples/sec: 14451.68 - lr: 0.050000 +2023-04-06 06:12:04,218 epoch 139 - iter 2385/2650 - loss 0.06951387 - time (sec): 91.80 - samples/sec: 14452.74 - lr: 0.050000 +2023-04-06 06:12:14,416 epoch 139 - iter 2650/2650 - loss 0.06952088 - time (sec): 102.00 - samples/sec: 14449.34 - lr: 0.050000 +2023-04-06 06:12:14,417 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:12:14,417 EPOCH 139 done: loss 0.0695 - lr 0.050000 +2023-04-06 06:12:14,417 BAD EPOCHS (no improvement): 0 +2023-04-06 06:12:14,424 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:12:24,567 epoch 140 - iter 265/2650 - loss 0.06958310 - time (sec): 10.14 - samples/sec: 14504.85 - lr: 0.050000 +2023-04-06 06:12:34,672 epoch 140 - iter 530/2650 - loss 0.06872336 - time (sec): 20.25 - samples/sec: 14479.22 - lr: 0.050000 +2023-04-06 06:12:44,890 epoch 140 - iter 795/2650 - loss 0.06955041 - time (sec): 30.47 - samples/sec: 14447.29 - lr: 0.050000 +2023-04-06 06:12:55,120 epoch 140 - iter 1060/2650 - loss 0.06986238 - time (sec): 40.70 - samples/sec: 14439.30 - lr: 0.050000 +2023-04-06 06:13:05,385 epoch 140 - iter 1325/2650 - loss 0.06968415 - time (sec): 50.96 - samples/sec: 14465.52 - lr: 0.050000 +2023-04-06 06:13:15,692 epoch 140 - iter 1590/2650 - loss 0.06969235 - time (sec): 61.27 - samples/sec: 14447.28 - lr: 0.050000 +2023-04-06 06:13:25,846 epoch 140 - iter 1855/2650 - loss 0.06949556 - time (sec): 71.42 - samples/sec: 14445.47 - lr: 0.050000 +2023-04-06 06:13:36,046 epoch 140 - iter 2120/2650 - loss 0.06976983 - time (sec): 81.62 - samples/sec: 14437.73 - lr: 0.050000 +2023-04-06 06:13:46,282 epoch 140 - iter 2385/2650 - loss 0.06985533 - time (sec): 91.86 - samples/sec: 14449.01 - lr: 0.050000 +2023-04-06 06:13:56,467 epoch 140 - iter 2650/2650 - loss 0.06991413 - time (sec): 102.04 - samples/sec: 14443.17 - lr: 0.050000 +2023-04-06 06:13:56,467 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:13:56,467 EPOCH 140 done: loss 0.0699 - lr 0.050000 +2023-04-06 06:13:56,467 BAD EPOCHS (no improvement): 1 +2023-04-06 06:13:56,471 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:14:06,661 epoch 141 - iter 265/2650 - loss 0.06797319 - time (sec): 10.19 - samples/sec: 14467.82 - lr: 0.050000 +2023-04-06 06:14:16,784 epoch 141 - iter 530/2650 - loss 0.06856668 - time (sec): 20.31 - samples/sec: 14442.56 - lr: 0.050000 +2023-04-06 06:14:26,809 epoch 141 - iter 795/2650 - loss 0.06895352 - time (sec): 30.34 - samples/sec: 14499.48 - lr: 0.050000 +2023-04-06 06:14:37,119 epoch 141 - iter 1060/2650 - loss 0.06855669 - time (sec): 40.65 - samples/sec: 14474.49 - lr: 0.050000 +2023-04-06 06:14:47,293 epoch 141 - iter 1325/2650 - loss 0.06889422 - time (sec): 50.82 - samples/sec: 14472.69 - lr: 0.050000 +2023-04-06 06:14:57,526 epoch 141 - iter 1590/2650 - loss 0.06879491 - time (sec): 61.05 - samples/sec: 14469.20 - lr: 0.050000 +2023-04-06 06:15:07,640 epoch 141 - iter 1855/2650 - loss 0.06893479 - time (sec): 71.17 - samples/sec: 14472.83 - lr: 0.050000 +2023-04-06 06:15:17,772 epoch 141 - iter 2120/2650 - loss 0.06930550 - time (sec): 81.30 - samples/sec: 14480.61 - lr: 0.050000 +2023-04-06 06:15:27,926 epoch 141 - iter 2385/2650 - loss 0.06936587 - time (sec): 91.45 - samples/sec: 14482.47 - lr: 0.050000 +2023-04-06 06:15:38,262 epoch 141 - iter 2650/2650 - loss 0.06959428 - time (sec): 101.79 - samples/sec: 14478.93 - lr: 0.050000 +2023-04-06 06:15:38,262 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:15:38,262 EPOCH 141 done: loss 0.0696 - lr 0.050000 +2023-04-06 06:15:38,262 BAD EPOCHS (no improvement): 2 +2023-04-06 06:15:38,266 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:15:48,553 epoch 142 - iter 265/2650 - loss 0.06992317 - time (sec): 10.29 - samples/sec: 14332.70 - lr: 0.050000 +2023-04-06 06:15:58,725 epoch 142 - iter 530/2650 - loss 0.06893254 - time (sec): 20.46 - samples/sec: 14405.28 - lr: 0.050000 +2023-04-06 06:16:08,823 epoch 142 - iter 795/2650 - loss 0.06900064 - time (sec): 30.56 - samples/sec: 14438.05 - lr: 0.050000 +2023-04-06 06:16:19,298 epoch 142 - iter 1060/2650 - loss 0.06885106 - time (sec): 41.03 - samples/sec: 14365.83 - lr: 0.050000 +2023-04-06 06:16:29,463 epoch 142 - iter 1325/2650 - loss 0.06882324 - time (sec): 51.20 - samples/sec: 14394.21 - lr: 0.050000 +2023-04-06 06:16:39,689 epoch 142 - iter 1590/2650 - loss 0.06927915 - time (sec): 61.42 - samples/sec: 14409.41 - lr: 0.050000 +2023-04-06 06:16:49,944 epoch 142 - iter 1855/2650 - loss 0.06929636 - time (sec): 71.68 - samples/sec: 14403.35 - lr: 0.050000 +2023-04-06 06:17:00,200 epoch 142 - iter 2120/2650 - loss 0.06968504 - time (sec): 81.93 - samples/sec: 14405.30 - lr: 0.050000 +2023-04-06 06:17:10,390 epoch 142 - iter 2385/2650 - loss 0.06988854 - time (sec): 92.12 - samples/sec: 14398.27 - lr: 0.050000 +2023-04-06 06:17:20,665 epoch 142 - iter 2650/2650 - loss 0.07001256 - time (sec): 102.40 - samples/sec: 14392.94 - lr: 0.050000 +2023-04-06 06:17:20,665 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:17:20,665 EPOCH 142 done: loss 0.0700 - lr 0.050000 +2023-04-06 06:17:20,665 BAD EPOCHS (no improvement): 3 +2023-04-06 06:17:20,669 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:17:30,984 epoch 143 - iter 265/2650 - loss 0.06959535 - time (sec): 10.31 - samples/sec: 14359.81 - lr: 0.050000 +2023-04-06 06:17:41,210 epoch 143 - iter 530/2650 - loss 0.06894295 - time (sec): 20.54 - samples/sec: 14398.46 - lr: 0.050000 +2023-04-06 06:17:51,411 epoch 143 - iter 795/2650 - loss 0.06835523 - time (sec): 30.74 - samples/sec: 14384.09 - lr: 0.050000 +2023-04-06 06:18:01,624 epoch 143 - iter 1060/2650 - loss 0.06877084 - time (sec): 40.95 - samples/sec: 14392.82 - lr: 0.050000 +2023-04-06 06:18:11,959 epoch 143 - iter 1325/2650 - loss 0.06882057 - time (sec): 51.29 - samples/sec: 14380.09 - lr: 0.050000 +2023-04-06 06:18:22,243 epoch 143 - iter 1590/2650 - loss 0.06928107 - time (sec): 61.57 - samples/sec: 14378.80 - lr: 0.050000 +2023-04-06 06:18:32,441 epoch 143 - iter 1855/2650 - loss 0.06943087 - time (sec): 71.77 - samples/sec: 14368.53 - lr: 0.050000 +2023-04-06 06:18:42,743 epoch 143 - iter 2120/2650 - loss 0.06967234 - time (sec): 82.07 - samples/sec: 14365.08 - lr: 0.050000 +2023-04-06 06:18:53,056 epoch 143 - iter 2385/2650 - loss 0.06979552 - time (sec): 92.39 - samples/sec: 14360.69 - lr: 0.050000 +2023-04-06 06:19:07,562 epoch 143 - iter 2650/2650 - loss 0.06994262 - time (sec): 106.89 - samples/sec: 13787.96 - lr: 0.050000 +2023-04-06 06:19:07,562 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:19:07,562 EPOCH 143 done: loss 0.0699 - lr 0.050000 +2023-04-06 06:19:07,562 Epoch 143: reducing learning rate of group 0 to 2.5000e-02. +2023-04-06 06:19:07,562 BAD EPOCHS (no improvement): 4 +2023-04-06 06:19:07,565 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:19:17,664 epoch 144 - iter 265/2650 - loss 0.06744818 - time (sec): 10.10 - samples/sec: 14450.81 - lr: 0.025000 +2023-04-06 06:19:27,910 epoch 144 - iter 530/2650 - loss 0.06733948 - time (sec): 20.34 - samples/sec: 14419.15 - lr: 0.025000 +2023-04-06 06:19:38,168 epoch 144 - iter 795/2650 - loss 0.06690861 - time (sec): 30.60 - samples/sec: 14385.18 - lr: 0.025000 +2023-04-06 06:19:48,364 epoch 144 - iter 1060/2650 - loss 0.06667746 - time (sec): 40.80 - samples/sec: 14392.90 - lr: 0.025000 +2023-04-06 06:19:58,847 epoch 144 - iter 1325/2650 - loss 0.06735374 - time (sec): 51.28 - samples/sec: 14364.12 - lr: 0.025000 +2023-04-06 06:20:08,950 epoch 144 - iter 1590/2650 - loss 0.06762446 - time (sec): 61.38 - samples/sec: 14373.66 - lr: 0.025000 +2023-04-06 06:20:19,301 epoch 144 - iter 1855/2650 - loss 0.06766167 - time (sec): 71.74 - samples/sec: 14369.49 - lr: 0.025000 +2023-04-06 06:20:29,384 epoch 144 - iter 2120/2650 - loss 0.06750314 - time (sec): 81.82 - samples/sec: 14391.68 - lr: 0.025000 +2023-04-06 06:20:39,661 epoch 144 - iter 2385/2650 - loss 0.06738077 - time (sec): 92.10 - samples/sec: 14401.46 - lr: 0.025000 +2023-04-06 06:20:49,799 epoch 144 - iter 2650/2650 - loss 0.06750812 - time (sec): 102.23 - samples/sec: 14416.27 - lr: 0.025000 +2023-04-06 06:20:49,799 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:20:49,799 EPOCH 144 done: loss 0.0675 - lr 0.025000 +2023-04-06 06:20:49,799 BAD EPOCHS (no improvement): 0 +2023-04-06 06:20:49,803 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:20:59,959 epoch 145 - iter 265/2650 - loss 0.06696410 - time (sec): 10.16 - samples/sec: 14487.22 - lr: 0.025000 +2023-04-06 06:21:10,050 epoch 145 - iter 530/2650 - loss 0.06666544 - time (sec): 20.25 - samples/sec: 14548.62 - lr: 0.025000 +2023-04-06 06:21:20,070 epoch 145 - iter 795/2650 - loss 0.06652937 - time (sec): 30.27 - samples/sec: 14527.80 - lr: 0.025000 +2023-04-06 06:21:30,248 epoch 145 - iter 1060/2650 - loss 0.06691299 - time (sec): 40.44 - samples/sec: 14532.89 - lr: 0.025000 +2023-04-06 06:21:40,407 epoch 145 - iter 1325/2650 - loss 0.06693342 - time (sec): 50.60 - samples/sec: 14528.77 - lr: 0.025000 +2023-04-06 06:21:50,448 epoch 145 - iter 1590/2650 - loss 0.06702710 - time (sec): 60.64 - samples/sec: 14521.67 - lr: 0.025000 +2023-04-06 06:22:00,588 epoch 145 - iter 1855/2650 - loss 0.06671242 - time (sec): 70.78 - samples/sec: 14525.53 - lr: 0.025000 +2023-04-06 06:22:10,891 epoch 145 - iter 2120/2650 - loss 0.06703938 - time (sec): 81.09 - samples/sec: 14503.97 - lr: 0.025000 +2023-04-06 06:22:21,086 epoch 145 - iter 2385/2650 - loss 0.06708862 - time (sec): 91.28 - samples/sec: 14512.92 - lr: 0.025000 +2023-04-06 06:22:31,385 epoch 145 - iter 2650/2650 - loss 0.06695835 - time (sec): 101.58 - samples/sec: 14508.72 - lr: 0.025000 +2023-04-06 06:22:31,385 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:22:31,385 EPOCH 145 done: loss 0.0670 - lr 0.025000 +2023-04-06 06:22:31,385 BAD EPOCHS (no improvement): 0 +2023-04-06 06:22:31,388 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:22:41,436 epoch 146 - iter 265/2650 - loss 0.06665060 - time (sec): 10.05 - samples/sec: 14530.46 - lr: 0.025000 +2023-04-06 06:22:51,664 epoch 146 - iter 530/2650 - loss 0.06739331 - time (sec): 20.28 - samples/sec: 14505.94 - lr: 0.025000 +2023-04-06 06:23:01,755 epoch 146 - iter 795/2650 - loss 0.06726033 - time (sec): 30.37 - samples/sec: 14551.76 - lr: 0.025000 +2023-04-06 06:23:11,960 epoch 146 - iter 1060/2650 - loss 0.06686025 - time (sec): 40.57 - samples/sec: 14553.14 - lr: 0.025000 +2023-04-06 06:23:22,022 epoch 146 - iter 1325/2650 - loss 0.06698105 - time (sec): 50.63 - samples/sec: 14554.16 - lr: 0.025000 +2023-04-06 06:23:32,227 epoch 146 - iter 1590/2650 - loss 0.06672128 - time (sec): 60.84 - samples/sec: 14539.87 - lr: 0.025000 +2023-04-06 06:23:42,478 epoch 146 - iter 1855/2650 - loss 0.06662504 - time (sec): 71.09 - samples/sec: 14530.90 - lr: 0.025000 +2023-04-06 06:23:52,531 epoch 146 - iter 2120/2650 - loss 0.06660243 - time (sec): 81.14 - samples/sec: 14529.39 - lr: 0.025000 +2023-04-06 06:24:02,622 epoch 146 - iter 2385/2650 - loss 0.06666841 - time (sec): 91.23 - samples/sec: 14529.75 - lr: 0.025000 +2023-04-06 06:24:12,807 epoch 146 - iter 2650/2650 - loss 0.06653441 - time (sec): 101.42 - samples/sec: 14532.07 - lr: 0.025000 +2023-04-06 06:24:12,807 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:24:12,807 EPOCH 146 done: loss 0.0665 - lr 0.025000 +2023-04-06 06:24:12,807 BAD EPOCHS (no improvement): 0 +2023-04-06 06:24:12,813 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:24:22,835 epoch 147 - iter 265/2650 - loss 0.06752645 - time (sec): 10.02 - samples/sec: 14544.30 - lr: 0.025000 +2023-04-06 06:24:32,933 epoch 147 - iter 530/2650 - loss 0.06616153 - time (sec): 20.12 - samples/sec: 14498.52 - lr: 0.025000 +2023-04-06 06:24:43,062 epoch 147 - iter 795/2650 - loss 0.06626572 - time (sec): 30.25 - samples/sec: 14501.96 - lr: 0.025000 +2023-04-06 06:24:53,310 epoch 147 - iter 1060/2650 - loss 0.06683154 - time (sec): 40.50 - samples/sec: 14524.75 - lr: 0.025000 +2023-04-06 06:25:03,508 epoch 147 - iter 1325/2650 - loss 0.06639169 - time (sec): 50.70 - samples/sec: 14515.32 - lr: 0.025000 +2023-04-06 06:25:13,616 epoch 147 - iter 1590/2650 - loss 0.06650885 - time (sec): 60.80 - samples/sec: 14511.99 - lr: 0.025000 +2023-04-06 06:25:23,934 epoch 147 - iter 1855/2650 - loss 0.06665525 - time (sec): 71.12 - samples/sec: 14481.80 - lr: 0.025000 +2023-04-06 06:25:34,132 epoch 147 - iter 2120/2650 - loss 0.06667740 - time (sec): 81.32 - samples/sec: 14501.99 - lr: 0.025000 +2023-04-06 06:25:44,319 epoch 147 - iter 2385/2650 - loss 0.06680321 - time (sec): 91.51 - samples/sec: 14503.65 - lr: 0.025000 +2023-04-06 06:25:54,380 epoch 147 - iter 2650/2650 - loss 0.06655792 - time (sec): 101.57 - samples/sec: 14510.77 - lr: 0.025000 +2023-04-06 06:25:54,381 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:25:54,381 EPOCH 147 done: loss 0.0666 - lr 0.025000 +2023-04-06 06:25:54,381 BAD EPOCHS (no improvement): 1 +2023-04-06 06:25:54,384 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:26:04,422 epoch 148 - iter 265/2650 - loss 0.06382851 - time (sec): 10.04 - samples/sec: 14546.22 - lr: 0.025000 +2023-04-06 06:26:14,706 epoch 148 - iter 530/2650 - loss 0.06432853 - time (sec): 20.32 - samples/sec: 14595.45 - lr: 0.025000 +2023-04-06 06:26:24,808 epoch 148 - iter 795/2650 - loss 0.06510025 - time (sec): 30.42 - samples/sec: 14565.34 - lr: 0.025000 +2023-04-06 06:26:34,960 epoch 148 - iter 1060/2650 - loss 0.06548926 - time (sec): 40.58 - samples/sec: 14560.09 - lr: 0.025000 +2023-04-06 06:26:45,143 epoch 148 - iter 1325/2650 - loss 0.06568544 - time (sec): 50.76 - samples/sec: 14534.70 - lr: 0.025000 +2023-04-06 06:26:55,381 epoch 148 - iter 1590/2650 - loss 0.06532667 - time (sec): 61.00 - samples/sec: 14520.30 - lr: 0.025000 +2023-04-06 06:27:05,609 epoch 148 - iter 1855/2650 - loss 0.06517306 - time (sec): 71.22 - samples/sec: 14512.70 - lr: 0.025000 +2023-04-06 06:27:15,667 epoch 148 - iter 2120/2650 - loss 0.06506706 - time (sec): 81.28 - samples/sec: 14515.13 - lr: 0.025000 +2023-04-06 06:27:25,763 epoch 148 - iter 2385/2650 - loss 0.06500050 - time (sec): 91.38 - samples/sec: 14521.33 - lr: 0.025000 +2023-04-06 06:27:35,912 epoch 148 - iter 2650/2650 - loss 0.06498654 - time (sec): 101.53 - samples/sec: 14516.53 - lr: 0.025000 +2023-04-06 06:27:35,912 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:27:35,912 EPOCH 148 done: loss 0.0650 - lr 0.025000 +2023-04-06 06:27:35,912 BAD EPOCHS (no improvement): 0 +2023-04-06 06:27:35,916 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:27:46,239 epoch 149 - iter 265/2650 - loss 0.06655529 - time (sec): 10.32 - samples/sec: 14504.23 - lr: 0.025000 +2023-04-06 06:27:56,620 epoch 149 - iter 530/2650 - loss 0.06536531 - time (sec): 20.70 - samples/sec: 14464.15 - lr: 0.025000 +2023-04-06 06:28:06,667 epoch 149 - iter 795/2650 - loss 0.06599197 - time (sec): 30.75 - samples/sec: 14470.30 - lr: 0.025000 +2023-04-06 06:28:16,920 epoch 149 - iter 1060/2650 - loss 0.06554313 - time (sec): 41.00 - samples/sec: 14446.68 - lr: 0.025000 +2023-04-06 06:28:26,911 epoch 149 - iter 1325/2650 - loss 0.06540311 - time (sec): 50.99 - samples/sec: 14469.29 - lr: 0.025000 +2023-04-06 06:28:37,117 epoch 149 - iter 1590/2650 - loss 0.06540663 - time (sec): 61.20 - samples/sec: 14465.57 - lr: 0.025000 +2023-04-06 06:28:47,241 epoch 149 - iter 1855/2650 - loss 0.06514876 - time (sec): 71.32 - samples/sec: 14480.31 - lr: 0.025000 +2023-04-06 06:28:57,352 epoch 149 - iter 2120/2650 - loss 0.06516196 - time (sec): 81.44 - samples/sec: 14483.45 - lr: 0.025000 +2023-04-06 06:29:07,467 epoch 149 - iter 2385/2650 - loss 0.06556300 - time (sec): 91.55 - samples/sec: 14487.86 - lr: 0.025000 +2023-04-06 06:29:17,704 epoch 149 - iter 2650/2650 - loss 0.06553227 - time (sec): 101.79 - samples/sec: 14479.42 - lr: 0.025000 +2023-04-06 06:29:17,704 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:29:17,704 EPOCH 149 done: loss 0.0655 - lr 0.025000 +2023-04-06 06:29:17,704 BAD EPOCHS (no improvement): 1 +2023-04-06 06:29:17,708 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:29:32,139 epoch 150 - iter 265/2650 - loss 0.06293066 - time (sec): 14.43 - samples/sec: 10309.41 - lr: 0.025000 +2023-04-06 06:29:42,062 epoch 150 - iter 530/2650 - loss 0.06396340 - time (sec): 24.35 - samples/sec: 12089.77 - lr: 0.025000 +2023-04-06 06:29:52,197 epoch 150 - iter 795/2650 - loss 0.06450383 - time (sec): 34.49 - samples/sec: 12791.45 - lr: 0.025000 +2023-04-06 06:30:02,494 epoch 150 - iter 1060/2650 - loss 0.06423106 - time (sec): 44.79 - samples/sec: 13145.47 - lr: 0.025000 +2023-04-06 06:30:12,808 epoch 150 - iter 1325/2650 - loss 0.06408416 - time (sec): 55.10 - samples/sec: 13382.78 - lr: 0.025000 +2023-04-06 06:30:23,146 epoch 150 - iter 1590/2650 - loss 0.06394808 - time (sec): 65.44 - samples/sec: 13542.28 - lr: 0.025000 +2023-04-06 06:30:33,271 epoch 150 - iter 1855/2650 - loss 0.06385460 - time (sec): 75.56 - samples/sec: 13664.53 - lr: 0.025000 +2023-04-06 06:30:43,778 epoch 150 - iter 2120/2650 - loss 0.06421264 - time (sec): 86.07 - samples/sec: 13729.23 - lr: 0.025000 +2023-04-06 06:30:53,752 epoch 150 - iter 2385/2650 - loss 0.06425239 - time (sec): 96.04 - samples/sec: 13816.92 - lr: 0.025000 +2023-04-06 06:31:03,974 epoch 150 - iter 2650/2650 - loss 0.06424798 - time (sec): 106.27 - samples/sec: 13869.30 - lr: 0.025000 +2023-04-06 06:31:03,974 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:31:03,974 EPOCH 150 done: loss 0.0642 - lr 0.025000 +2023-04-06 06:31:03,974 BAD EPOCHS (no improvement): 0 +2023-04-06 06:31:05,328 ---------------------------------------------------------------------------------------------------- +2023-04-06 06:31:05,329 Testing using last state of model ... +2023-04-06 06:31:29,169 Evaluating as a multi-label problem: False +2023-04-06 06:31:29,422 0.901 0.9384 0.9193 0.889 +2023-04-06 06:31:29,422 +Results: +- F-score (micro) 0.9193 +- F-score (macro) 0.6849 +- Accuracy 0.889 + +By class: + precision recall f1-score support + + be.01 0.9703 0.9803 0.9753 3562 + be.03 0.9504 0.9572 0.9538 1962 + have.01 0.9756 0.9812 0.9784 1225 + say.01 0.9971 0.9990 0.9981 1048 + do.01 0.9637 0.9845 0.9740 647 + have.03 0.9155 0.9620 0.9382 552 + think.01 1.0000 1.0000 1.0000 320 + be.02 0.9556 0.9710 0.9632 310 + do.02 0.8486 0.9573 0.8997 281 + see.01 0.9792 0.9930 0.9860 284 + come.01 0.9328 0.9712 0.9516 243 + know.01 0.9457 0.8531 0.8970 245 + go.02 0.9075 0.9115 0.9095 226 + want.01 1.0000 0.9952 0.9976 207 + tell.01 0.9832 1.0000 0.9915 176 + take.01 0.8742 0.8688 0.8715 160 + talk.01 0.9750 0.9811 0.9781 159 + use.01 0.9404 0.9930 0.9660 143 + give.01 0.9527 0.9860 0.9691 143 + make.02 0.9371 0.9178 0.9273 146 + have.02 0.9478 0.9769 0.9621 130 + price.01 0.9847 0.9699 0.9773 133 + get.01 0.8800 0.9322 0.9053 118 + work.01 0.8455 0.9204 0.8814 113 + know.06 0.7364 0.9794 0.8407 97 + believe.01 1.0000 1.0000 1.0000 113 + go.04 0.9636 0.9815 0.9725 108 + become.01 0.9815 1.0000 0.9907 106 + find.01 0.9320 0.9697 0.9505 99 + make.01 0.7000 0.8556 0.7700 90 + try.01 0.9900 0.9900 0.9900 100 + need.01 0.8750 1.0000 0.9333 91 + look.01 0.8900 0.9780 0.9319 91 + make.LV 0.7980 0.8587 0.8272 92 + mean.01 0.9895 1.0000 0.9947 94 + happen.01 1.0000 1.0000 1.0000 91 + trade.01 0.8602 0.9756 0.9143 82 + kill.01 0.9540 1.0000 0.9765 83 + show.01 0.9881 0.9881 0.9881 84 + invest.01 0.9080 0.9753 0.9405 81 + sell.01 0.9036 0.9868 0.9434 76 + begin.01 0.9390 1.0000 0.9686 77 + live.01 0.9136 0.9737 0.9427 76 + call.01 0.8987 0.9467 0.9221 75 + increase.01 0.9125 1.0000 0.9542 73 + pay.01 0.9605 0.9733 0.9669 75 + let.01 0.9868 1.0000 0.9934 75 + hear.01 1.0000 1.0000 1.0000 75 + offer.01 0.9605 1.0000 0.9799 73 + continue.01 0.9605 1.0000 0.9799 73 + bring.01 1.0000 1.0000 1.0000 74 + put.01 0.8816 0.9710 0.9241 69 + report.01 0.9296 0.9041 0.9167 73 + die.01 0.9857 1.0000 0.9928 69 + get.03 0.8529 0.8657 0.8593 67 + help.01 0.9286 1.0000 0.9630 65 + expect.01 1.0000 1.0000 1.0000 67 + write.01 0.8986 1.0000 0.9466 62 + ask.02 1.0000 0.8696 0.9302 69 + start.01 0.8551 1.0000 0.9219 59 + ask.01 0.8676 0.9833 0.9219 60 + speak.01 1.0000 0.9844 0.9921 64 + support.01 0.9242 1.0000 0.9606 61 + deal.01 0.9385 1.0000 0.9683 61 + decide.01 0.9219 1.0000 0.9593 59 + former.01 0.9833 1.0000 0.9916 59 + get.05 0.7458 0.7586 0.7521 58 + answer.01 0.9167 1.0000 0.9565 55 + seem.01 1.0000 1.0000 1.0000 56 + change.01 1.0000 1.0000 1.0000 55 + provide.01 0.9815 1.0000 0.9907 53 + produce.01 0.8393 0.9216 0.8785 51 + establish.01 0.9273 1.0000 0.9623 51 + develop.02 0.8889 0.9231 0.9057 52 + agree.01 0.9615 0.9434 0.9524 53 + reach.01 0.9444 1.0000 0.9714 51 + call.02 0.9184 0.8654 0.8911 52 + receive.01 0.9800 0.9800 0.9800 50 + feel.01 0.9400 0.9592 0.9495 49 + grow.01 0.8776 0.8958 0.8866 48 + lose.02 0.8600 0.9348 0.8958 46 + buy.01 0.9592 1.0000 0.9792 47 + operate.01 0.8627 0.9778 0.9167 45 + show.04 0.8431 0.9556 0.8958 45 + learn.01 1.0000 1.0000 1.0000 47 + end.01 0.6727 0.9737 0.7957 38 + test.01 0.8400 1.0000 0.9130 42 + own.01 1.0000 0.9783 0.9890 46 + go.01 0.6000 0.6000 0.6000 45 + negotiate.01 0.9556 1.0000 0.9773 43 + stay.01 0.9318 0.9762 0.9535 42 + remember.01 1.0000 0.9767 0.9882 43 + plan.01 0.9756 0.9302 0.9524 43 + move.01 0.9302 0.9756 0.9524 41 + include.01 0.9524 0.9756 0.9639 41 + stop.01 0.9070 1.0000 0.9512 39 + add.02 0.7556 0.9444 0.8395 36 + state.01 0.8837 1.0000 0.9383 38 + war.01 0.8409 1.0000 0.9136 37 + serve.01 0.6383 0.9091 0.7500 33 + rise.01 0.9500 1.0000 0.9744 38 + charge.05 0.9487 0.9737 0.9610 38 + reduce.01 0.9487 0.9737 0.9610 38 + leave.11 0.8500 0.9714 0.9067 35 + expand.01 0.9231 1.0000 0.9600 36 + hope.01 1.0000 1.0000 1.0000 37 + account.01 0.9189 0.9189 0.9189 37 + announce.01 0.7619 1.0000 0.8649 32 + enter.01 0.9211 1.0000 0.9589 35 + take.LV 0.6341 0.8387 0.7222 31 + implement.01 1.0000 1.0000 1.0000 36 + accept.01 0.9444 0.9714 0.9577 35 + look.02 0.9189 1.0000 0.9577 34 + fall.01 0.9189 1.0000 0.9577 34 + face.01 0.7250 0.9667 0.8286 30 + hold.01 0.7632 0.9355 0.8406 31 + watch.01 0.9167 1.0000 0.9565 33 + keep.02 0.8182 0.7714 0.7941 35 + require.01 1.0000 1.0000 1.0000 34 + relation.03 0.7368 0.9655 0.8358 29 + meet.03 0.7429 0.8387 0.7879 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