2022-11-01 12:49:03,490 ---------------------------------------------------------------------------------------------------- 2022-11-01 12:49:03,490 Model: "SequenceTagger( (embeddings): StackedEmbeddings( (list_embedding_0): FlairEmbeddings( (lm): LanguageModel( (drop): Dropout(p=0.1, inplace=False) (encoder): Embedding(962, 100) (rnn): LSTM(100, 1024) (decoder): Linear(in_features=1024, out_features=962, bias=True) ) ) (list_embedding_1): FlairEmbeddings( (lm): LanguageModel( (drop): Dropout(p=0.1, inplace=False) (encoder): Embedding(962, 100) (rnn): LSTM(100, 1024) (decoder): Linear(in_features=1024, out_features=962, bias=True) ) ) ) (dropout): Dropout(p=0.3380078963015963, inplace=False) (word_dropout): WordDropout(p=0.05) (locked_dropout): LockedDropout(p=0.5) (embedding2nn): Linear(in_features=2048, out_features=2048, bias=True) (rnn): LSTM(2048, 128, num_layers=2, batch_first=True, dropout=0.5, bidirectional=True) (linear): Linear(in_features=256, out_features=19, bias=True) (loss_function): ViterbiLoss() (crf): CRF() )" 2022-11-01 12:49:03,490 ---------------------------------------------------------------------------------------------------- 2022-11-01 12:49:03,490 Corpus: "Corpus: 7886 train + 876 dev + 4045 test sentences" 2022-11-01 12:49:03,490 ---------------------------------------------------------------------------------------------------- 2022-11-01 12:49:03,490 Parameters: 2022-11-01 12:49:03,490 - learning_rate: "0.100000" 2022-11-01 12:49:03,490 - mini_batch_size: "32" 2022-11-01 12:49:03,490 - patience: "3" 2022-11-01 12:49:03,490 - anneal_factor: "0.5" 2022-11-01 12:49:03,490 - max_epochs: "150" 2022-11-01 12:49:03,490 - shuffle: "True" 2022-11-01 12:49:03,490 - train_with_dev: "True" 2022-11-01 12:49:03,490 - batch_growth_annealing: "False" 2022-11-01 12:49:03,490 ---------------------------------------------------------------------------------------------------- 2022-11-01 12:49:03,490 Model training base path: "ner-tests/uk.flairembeddings.champ" 2022-11-01 12:49:03,491 ---------------------------------------------------------------------------------------------------- 2022-11-01 12:49:03,491 Device: cpu 2022-11-01 12:49:03,491 ---------------------------------------------------------------------------------------------------- 2022-11-01 12:49:03,491 Embeddings storage mode: gpu 2022-11-01 12:49:03,491 ---------------------------------------------------------------------------------------------------- 2022-11-01 12:50:09,565 epoch 1 - iter 27/274 - loss 0.61951446 - samples/sec: 13.08 - lr: 0.100000 2022-11-01 12:51:14,717 epoch 1 - iter 54/274 - loss 0.51046988 - samples/sec: 13.26 - lr: 0.100000 2022-11-01 12:52:22,958 epoch 1 - iter 81/274 - loss 0.40838070 - samples/sec: 12.66 - lr: 0.100000 2022-11-01 12:53:46,868 epoch 1 - iter 108/274 - loss 0.36574824 - samples/sec: 10.30 - lr: 0.100000 2022-11-01 12:54:38,313 epoch 1 - iter 135/274 - loss 0.32373590 - samples/sec: 16.80 - lr: 0.100000 2022-11-01 12:55:23,882 epoch 1 - iter 162/274 - loss 0.28818606 - samples/sec: 18.96 - lr: 0.100000 2022-11-01 12:56:20,788 epoch 1 - iter 189/274 - loss 0.25828452 - samples/sec: 15.18 - lr: 0.100000 2022-11-01 12:56:58,874 epoch 1 - iter 216/274 - loss 0.23950005 - samples/sec: 22.69 - lr: 0.100000 2022-11-01 12:57:50,282 epoch 1 - iter 243/274 - loss 0.22160623 - samples/sec: 16.81 - lr: 0.100000 2022-11-01 12:58:46,515 epoch 1 - iter 270/274 - loss 0.21126815 - samples/sec: 15.37 - lr: 0.100000 2022-11-01 12:58:55,152 ---------------------------------------------------------------------------------------------------- 2022-11-01 12:58:55,153 EPOCH 1 done: loss 0.2089 - lr 0.100000 2022-11-01 13:03:03,629 Evaluating as a multi-label problem: False 2022-11-01 13:03:03,647 TEST : loss 0.13904191553592682 - f1-score (micro avg) 0.5512 2022-11-01 13:03:03,698 BAD EPOCHS (no improvement): 0 2022-11-01 13:03:03,756 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:03:15,574 epoch 2 - iter 27/274 - loss 0.10819005 - samples/sec: 73.14 - lr: 0.100000 2022-11-01 13:03:27,236 epoch 2 - iter 54/274 - loss 0.10311525 - samples/sec: 74.11 - lr: 0.100000 2022-11-01 13:03:39,859 epoch 2 - iter 81/274 - loss 0.10132389 - samples/sec: 68.46 - lr: 0.100000 2022-11-01 13:03:50,897 epoch 2 - iter 108/274 - loss 0.10064433 - samples/sec: 78.30 - lr: 0.100000 2022-11-01 13:04:02,826 epoch 2 - iter 135/274 - loss 0.10064467 - samples/sec: 72.45 - lr: 0.100000 2022-11-01 13:04:16,449 epoch 2 - iter 162/274 - loss 0.10836500 - samples/sec: 63.44 - lr: 0.100000 2022-11-01 13:04:28,828 epoch 2 - iter 189/274 - loss 0.10522271 - samples/sec: 69.81 - lr: 0.100000 2022-11-01 13:04:42,197 epoch 2 - iter 216/274 - loss 0.10281006 - samples/sec: 64.64 - lr: 0.100000 2022-11-01 13:04:54,240 epoch 2 - iter 243/274 - loss 0.10025360 - samples/sec: 71.77 - lr: 0.100000 2022-11-01 13:05:07,501 epoch 2 - iter 270/274 - loss 0.09897187 - samples/sec: 65.17 - lr: 0.100000 2022-11-01 13:05:10,043 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:05:10,043 EPOCH 2 done: loss 0.0992 - lr 0.100000 2022-11-01 13:05:35,346 Evaluating as a multi-label problem: False 2022-11-01 13:05:35,362 TEST : loss 0.08393135666847229 - f1-score (micro avg) 0.739 2022-11-01 13:05:35,413 BAD EPOCHS (no improvement): 0 2022-11-01 13:05:35,503 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:05:48,724 epoch 3 - iter 27/274 - loss 0.08097851 - samples/sec: 65.37 - lr: 0.100000 2022-11-01 13:06:01,967 epoch 3 - iter 54/274 - loss 0.07444780 - samples/sec: 65.26 - lr: 0.100000 2022-11-01 13:06:14,499 epoch 3 - iter 81/274 - loss 0.07164834 - samples/sec: 68.96 - lr: 0.100000 2022-11-01 13:06:26,228 epoch 3 - iter 108/274 - loss 0.07237300 - samples/sec: 73.68 - lr: 0.100000 2022-11-01 13:06:37,579 epoch 3 - iter 135/274 - loss 0.07152923 - samples/sec: 76.14 - lr: 0.100000 2022-11-01 13:06:50,615 epoch 3 - iter 162/274 - loss 0.07222106 - samples/sec: 66.30 - lr: 0.100000 2022-11-01 13:07:03,210 epoch 3 - iter 189/274 - loss 0.07203354 - samples/sec: 68.62 - lr: 0.100000 2022-11-01 13:07:16,259 epoch 3 - iter 216/274 - loss 0.07359814 - samples/sec: 66.23 - lr: 0.100000 2022-11-01 13:07:27,473 epoch 3 - iter 243/274 - loss 0.07244371 - samples/sec: 77.07 - lr: 0.100000 2022-11-01 13:07:39,487 epoch 3 - iter 270/274 - loss 0.07220347 - samples/sec: 71.94 - lr: 0.100000 2022-11-01 13:07:41,274 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:07:41,274 EPOCH 3 done: loss 0.0718 - lr 0.100000 2022-11-01 13:08:06,634 Evaluating as a multi-label problem: False 2022-11-01 13:08:06,649 TEST : loss 0.06586140394210815 - f1-score (micro avg) 0.7879 2022-11-01 13:08:06,702 BAD EPOCHS (no improvement): 0 2022-11-01 13:08:06,788 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:08:17,828 epoch 4 - iter 27/274 - loss 0.06119555 - samples/sec: 78.29 - lr: 0.100000 2022-11-01 13:08:30,426 epoch 4 - iter 54/274 - loss 0.06264965 - samples/sec: 68.60 - lr: 0.100000 2022-11-01 13:08:42,231 epoch 4 - iter 81/274 - loss 0.06322773 - samples/sec: 73.21 - lr: 0.100000 2022-11-01 13:08:53,700 epoch 4 - iter 108/274 - loss 0.06038977 - samples/sec: 75.35 - lr: 0.100000 2022-11-01 13:09:06,851 epoch 4 - iter 135/274 - loss 0.06248566 - samples/sec: 65.71 - lr: 0.100000 2022-11-01 13:09:19,477 epoch 4 - iter 162/274 - loss 0.06279878 - samples/sec: 68.45 - lr: 0.100000 2022-11-01 13:09:33,000 epoch 4 - iter 189/274 - loss 0.06245445 - samples/sec: 63.91 - lr: 0.100000 2022-11-01 13:09:45,946 epoch 4 - iter 216/274 - loss 0.06230904 - samples/sec: 66.76 - lr: 0.100000 2022-11-01 13:09:59,830 epoch 4 - iter 243/274 - loss 0.06128421 - samples/sec: 62.24 - lr: 0.100000 2022-11-01 13:10:11,584 epoch 4 - iter 270/274 - loss 0.06083109 - samples/sec: 73.53 - lr: 0.100000 2022-11-01 13:10:13,492 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:10:13,492 EPOCH 4 done: loss 0.0608 - lr 0.100000 2022-11-01 13:10:38,798 Evaluating as a multi-label problem: False 2022-11-01 13:10:38,813 TEST : loss 0.061087507754564285 - f1-score (micro avg) 0.7982 2022-11-01 13:10:38,866 BAD EPOCHS (no improvement): 0 2022-11-01 13:10:38,953 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:10:50,869 epoch 5 - iter 27/274 - loss 0.05534610 - samples/sec: 72.53 - lr: 0.100000 2022-11-01 13:11:02,268 epoch 5 - iter 54/274 - loss 0.05243949 - samples/sec: 75.82 - lr: 0.100000 2022-11-01 13:11:16,824 epoch 5 - iter 81/274 - loss 0.05033856 - samples/sec: 59.37 - lr: 0.100000 2022-11-01 13:11:29,824 epoch 5 - iter 108/274 - loss 0.05199909 - samples/sec: 66.48 - lr: 0.100000 2022-11-01 13:11:42,909 epoch 5 - iter 135/274 - loss 0.05390198 - samples/sec: 66.05 - lr: 0.100000 2022-11-01 13:11:54,210 epoch 5 - iter 162/274 - loss 0.05559011 - samples/sec: 76.47 - lr: 0.100000 2022-11-01 13:12:07,160 epoch 5 - iter 189/274 - loss 0.05545001 - samples/sec: 66.74 - lr: 0.100000 2022-11-01 13:12:18,635 epoch 5 - iter 216/274 - loss 0.05452558 - samples/sec: 75.32 - lr: 0.100000 2022-11-01 13:12:30,242 epoch 5 - iter 243/274 - loss 0.05387747 - samples/sec: 74.46 - lr: 0.100000 2022-11-01 13:12:43,258 epoch 5 - iter 270/274 - loss 0.05358782 - samples/sec: 66.40 - lr: 0.100000 2022-11-01 13:12:44,917 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:12:44,917 EPOCH 5 done: loss 0.0535 - lr 0.100000 2022-11-01 13:13:10,313 Evaluating as a multi-label problem: False 2022-11-01 13:13:10,329 TEST : loss 0.045144665986299515 - f1-score (micro avg) 0.8098 2022-11-01 13:13:10,381 BAD EPOCHS (no improvement): 0 2022-11-01 13:13:10,468 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:13:23,647 epoch 6 - iter 27/274 - loss 0.05037224 - samples/sec: 65.57 - lr: 0.100000 2022-11-01 13:13:36,723 epoch 6 - iter 54/274 - loss 0.04536131 - samples/sec: 66.09 - lr: 0.100000 2022-11-01 13:13:49,037 epoch 6 - iter 81/274 - loss 0.04718256 - samples/sec: 70.18 - lr: 0.100000 2022-11-01 13:14:01,344 epoch 6 - iter 108/274 - loss 0.04840201 - samples/sec: 70.22 - lr: 0.100000 2022-11-01 13:14:14,416 epoch 6 - iter 135/274 - loss 0.04792430 - samples/sec: 66.11 - lr: 0.100000 2022-11-01 13:14:26,815 epoch 6 - iter 162/274 - loss 0.04791153 - samples/sec: 69.70 - lr: 0.100000 2022-11-01 13:14:38,924 epoch 6 - iter 189/274 - loss 0.04811161 - samples/sec: 71.37 - lr: 0.100000 2022-11-01 13:14:50,571 epoch 6 - iter 216/274 - loss 0.04808548 - samples/sec: 74.20 - lr: 0.100000 2022-11-01 13:15:02,316 epoch 6 - iter 243/274 - loss 0.04851904 - samples/sec: 73.59 - lr: 0.100000 2022-11-01 13:15:15,000 epoch 6 - iter 270/274 - loss 0.04914944 - samples/sec: 68.13 - lr: 0.100000 2022-11-01 13:15:16,810 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:15:16,811 EPOCH 6 done: loss 0.0491 - lr 0.100000 2022-11-01 13:15:42,123 Evaluating as a multi-label problem: False 2022-11-01 13:15:42,139 TEST : loss 0.03993703052401543 - f1-score (micro avg) 0.8164 2022-11-01 13:15:42,191 BAD EPOCHS (no improvement): 0 2022-11-01 13:15:42,277 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:15:54,919 epoch 7 - iter 27/274 - loss 0.04702372 - samples/sec: 68.36 - lr: 0.100000 2022-11-01 13:16:08,351 epoch 7 - iter 54/274 - loss 0.04766522 - samples/sec: 64.34 - lr: 0.100000 2022-11-01 13:16:20,530 epoch 7 - iter 81/274 - loss 0.04786969 - samples/sec: 70.96 - lr: 0.100000 2022-11-01 13:16:33,124 epoch 7 - iter 108/274 - loss 0.04794053 - samples/sec: 68.62 - lr: 0.100000 2022-11-01 13:16:44,786 epoch 7 - iter 135/274 - loss 0.04732043 - samples/sec: 74.11 - lr: 0.100000 2022-11-01 13:16:56,876 epoch 7 - iter 162/274 - loss 0.04645068 - samples/sec: 71.48 - lr: 0.100000 2022-11-01 13:17:07,762 epoch 7 - iter 189/274 - loss 0.04566414 - samples/sec: 79.39 - lr: 0.100000 2022-11-01 13:17:20,361 epoch 7 - iter 216/274 - loss 0.04596395 - samples/sec: 68.59 - lr: 0.100000 2022-11-01 13:17:34,748 epoch 7 - iter 243/274 - loss 0.04585695 - samples/sec: 60.07 - lr: 0.100000 2022-11-01 13:17:46,833 epoch 7 - iter 270/274 - loss 0.04602936 - samples/sec: 71.51 - lr: 0.100000 2022-11-01 13:17:48,543 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:17:48,543 EPOCH 7 done: loss 0.0459 - lr 0.100000 2022-11-01 13:18:13,817 Evaluating as a multi-label problem: False 2022-11-01 13:18:13,832 TEST : loss 0.0414385087788105 - f1-score (micro avg) 0.8123 2022-11-01 13:18:13,885 BAD EPOCHS (no improvement): 0 2022-11-01 13:18:13,971 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:18:27,515 epoch 8 - iter 27/274 - loss 0.03864514 - samples/sec: 63.81 - lr: 0.100000 2022-11-01 13:18:40,798 epoch 8 - iter 54/274 - loss 0.04677644 - samples/sec: 65.07 - lr: 0.100000 2022-11-01 13:18:52,934 epoch 8 - iter 81/274 - loss 0.04564782 - samples/sec: 71.21 - lr: 0.100000 2022-11-01 13:19:04,156 epoch 8 - iter 108/274 - loss 0.04660204 - samples/sec: 77.01 - lr: 0.100000 2022-11-01 13:19:16,047 epoch 8 - iter 135/274 - loss 0.04492183 - samples/sec: 72.68 - lr: 0.100000 2022-11-01 13:19:28,142 epoch 8 - iter 162/274 - loss 0.04498433 - samples/sec: 71.45 - lr: 0.100000 2022-11-01 13:19:39,987 epoch 8 - iter 189/274 - loss 0.04445526 - samples/sec: 72.96 - lr: 0.100000 2022-11-01 13:19:53,894 epoch 8 - iter 216/274 - loss 0.04466556 - samples/sec: 62.14 - lr: 0.100000 2022-11-01 13:20:06,190 epoch 8 - iter 243/274 - loss 0.04424167 - samples/sec: 70.28 - lr: 0.100000 2022-11-01 13:20:18,046 epoch 8 - iter 270/274 - loss 0.04411825 - samples/sec: 72.90 - lr: 0.100000 2022-11-01 13:20:19,887 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:20:19,888 EPOCH 8 done: loss 0.0442 - lr 0.100000 2022-11-01 13:20:45,195 Evaluating as a multi-label problem: False 2022-11-01 13:20:45,210 TEST : loss 0.0352301225066185 - f1-score (micro avg) 0.8301 2022-11-01 13:20:45,262 BAD EPOCHS (no improvement): 0 2022-11-01 13:20:45,347 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:20:57,331 epoch 9 - iter 27/274 - loss 0.03421196 - samples/sec: 72.12 - lr: 0.100000 2022-11-01 13:21:11,143 epoch 9 - iter 54/274 - loss 0.03958776 - samples/sec: 62.57 - lr: 0.100000 2022-11-01 13:21:22,700 epoch 9 - iter 81/274 - loss 0.03861008 - samples/sec: 74.78 - lr: 0.100000 2022-11-01 13:21:34,844 epoch 9 - iter 108/274 - loss 0.03858464 - samples/sec: 71.16 - lr: 0.100000 2022-11-01 13:21:46,395 epoch 9 - iter 135/274 - loss 0.03857484 - samples/sec: 74.82 - lr: 0.100000 2022-11-01 13:21:58,479 epoch 9 - iter 162/274 - loss 0.03923221 - samples/sec: 71.51 - lr: 0.100000 2022-11-01 13:22:12,010 epoch 9 - iter 189/274 - loss 0.04032935 - samples/sec: 63.87 - lr: 0.100000 2022-11-01 13:22:24,283 epoch 9 - iter 216/274 - loss 0.03989000 - samples/sec: 70.42 - lr: 0.100000 2022-11-01 13:22:37,207 epoch 9 - iter 243/274 - loss 0.04033892 - samples/sec: 66.87 - lr: 0.100000 2022-11-01 13:22:49,535 epoch 9 - iter 270/274 - loss 0.04091413 - samples/sec: 70.11 - lr: 0.100000 2022-11-01 13:22:51,188 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:22:51,189 EPOCH 9 done: loss 0.0409 - lr 0.100000 2022-11-01 13:23:16,507 Evaluating as a multi-label problem: False 2022-11-01 13:23:16,522 TEST : loss 0.035973258316516876 - f1-score (micro avg) 0.8336 2022-11-01 13:23:16,574 BAD EPOCHS (no improvement): 0 2022-11-01 13:23:16,659 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:23:28,888 epoch 10 - iter 27/274 - loss 0.03551569 - samples/sec: 70.67 - lr: 0.100000 2022-11-01 13:23:40,651 epoch 10 - iter 54/274 - loss 0.03803901 - samples/sec: 73.47 - lr: 0.100000 2022-11-01 13:23:52,937 epoch 10 - iter 81/274 - loss 0.03866324 - samples/sec: 70.34 - lr: 0.100000 2022-11-01 13:24:04,214 epoch 10 - iter 108/274 - loss 0.03929714 - samples/sec: 76.64 - lr: 0.100000 2022-11-01 13:24:18,658 epoch 10 - iter 135/274 - loss 0.03798954 - samples/sec: 59.83 - lr: 0.100000 2022-11-01 13:24:31,144 epoch 10 - iter 162/274 - loss 0.03737353 - samples/sec: 69.21 - lr: 0.100000 2022-11-01 13:24:43,524 epoch 10 - iter 189/274 - loss 0.03819265 - samples/sec: 69.81 - lr: 0.100000 2022-11-01 13:24:55,975 epoch 10 - iter 216/274 - loss 0.03809318 - samples/sec: 69.41 - lr: 0.100000 2022-11-01 13:25:09,174 epoch 10 - iter 243/274 - loss 0.03795923 - samples/sec: 65.48 - lr: 0.100000 2022-11-01 13:25:21,702 epoch 10 - iter 270/274 - loss 0.03858601 - samples/sec: 68.98 - lr: 0.100000 2022-11-01 13:25:23,304 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:25:23,304 EPOCH 10 done: loss 0.0388 - lr 0.100000 2022-11-01 13:25:48,617 Evaluating as a multi-label problem: False 2022-11-01 13:25:48,633 TEST : loss 0.03315580636262894 - f1-score (micro avg) 0.8307 2022-11-01 13:25:48,683 BAD EPOCHS (no improvement): 0 2022-11-01 13:25:48,769 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:26:01,137 epoch 11 - iter 27/274 - loss 0.03336240 - samples/sec: 69.88 - lr: 0.100000 2022-11-01 13:26:14,421 epoch 11 - iter 54/274 - loss 0.03527565 - samples/sec: 65.06 - lr: 0.100000 2022-11-01 13:26:26,672 epoch 11 - iter 81/274 - loss 0.03575293 - samples/sec: 70.54 - lr: 0.100000 2022-11-01 13:26:39,936 epoch 11 - iter 108/274 - loss 0.03822032 - samples/sec: 65.15 - lr: 0.100000 2022-11-01 13:26:51,243 epoch 11 - iter 135/274 - loss 0.03800128 - samples/sec: 76.44 - lr: 0.100000 2022-11-01 13:27:03,276 epoch 11 - iter 162/274 - loss 0.03759663 - samples/sec: 71.82 - lr: 0.100000 2022-11-01 13:27:15,749 epoch 11 - iter 189/274 - loss 0.03792055 - samples/sec: 69.28 - lr: 0.100000 2022-11-01 13:27:28,611 epoch 11 - iter 216/274 - loss 0.03760377 - samples/sec: 67.19 - lr: 0.100000 2022-11-01 13:27:40,313 epoch 11 - iter 243/274 - loss 0.03749324 - samples/sec: 73.85 - lr: 0.100000 2022-11-01 13:27:53,182 epoch 11 - iter 270/274 - loss 0.03774304 - samples/sec: 67.15 - lr: 0.100000 2022-11-01 13:27:54,562 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:27:54,562 EPOCH 11 done: loss 0.0377 - lr 0.100000 2022-11-01 13:28:19,892 Evaluating as a multi-label problem: False 2022-11-01 13:28:19,908 TEST : loss 0.03283185511827469 - f1-score (micro avg) 0.8212 2022-11-01 13:28:19,960 BAD EPOCHS (no improvement): 0 2022-11-01 13:28:20,046 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:28:32,783 epoch 12 - iter 27/274 - loss 0.03750028 - samples/sec: 67.85 - lr: 0.100000 2022-11-01 13:28:45,843 epoch 12 - iter 54/274 - loss 0.03532475 - samples/sec: 66.17 - lr: 0.100000 2022-11-01 13:28:57,814 epoch 12 - iter 81/274 - loss 0.03713735 - samples/sec: 72.20 - lr: 0.100000 2022-11-01 13:29:09,768 epoch 12 - iter 108/274 - loss 0.03681510 - samples/sec: 72.30 - lr: 0.100000 2022-11-01 13:29:24,299 epoch 12 - iter 135/274 - loss 0.03831782 - samples/sec: 59.47 - lr: 0.100000 2022-11-01 13:29:35,963 epoch 12 - iter 162/274 - loss 0.03671352 - samples/sec: 74.10 - lr: 0.100000 2022-11-01 13:29:47,879 epoch 12 - iter 189/274 - loss 0.03644150 - samples/sec: 72.52 - lr: 0.100000 2022-11-01 13:30:01,084 epoch 12 - iter 216/274 - loss 0.03741624 - samples/sec: 65.45 - lr: 0.100000 2022-11-01 13:30:12,910 epoch 12 - iter 243/274 - loss 0.03760841 - samples/sec: 73.08 - lr: 0.100000 2022-11-01 13:30:24,282 epoch 12 - iter 270/274 - loss 0.03743746 - samples/sec: 76.00 - lr: 0.100000 2022-11-01 13:30:26,622 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:30:26,622 EPOCH 12 done: loss 0.0372 - lr 0.100000 2022-11-01 13:30:51,847 Evaluating as a multi-label problem: False 2022-11-01 13:30:51,862 TEST : loss 0.037361979484558105 - f1-score (micro avg) 0.8248 2022-11-01 13:30:51,915 BAD EPOCHS (no improvement): 0 2022-11-01 13:30:52,001 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:31:04,558 epoch 13 - iter 27/274 - loss 0.03512437 - samples/sec: 68.82 - lr: 0.100000 2022-11-01 13:31:15,671 epoch 13 - iter 54/274 - loss 0.03410457 - samples/sec: 77.77 - lr: 0.100000 2022-11-01 13:31:28,928 epoch 13 - iter 81/274 - loss 0.03664686 - samples/sec: 65.19 - lr: 0.100000 2022-11-01 13:31:41,194 epoch 13 - iter 108/274 - loss 0.03708780 - samples/sec: 70.46 - lr: 0.100000 2022-11-01 13:31:53,508 epoch 13 - iter 135/274 - loss 0.03597557 - samples/sec: 70.18 - lr: 0.100000 2022-11-01 13:32:05,194 epoch 13 - iter 162/274 - loss 0.03576194 - samples/sec: 73.95 - lr: 0.100000 2022-11-01 13:32:18,580 epoch 13 - iter 189/274 - loss 0.03517390 - samples/sec: 64.56 - lr: 0.100000 2022-11-01 13:32:31,865 epoch 13 - iter 216/274 - loss 0.03618700 - samples/sec: 65.05 - lr: 0.100000 2022-11-01 13:32:43,293 epoch 13 - iter 243/274 - loss 0.03653199 - samples/sec: 75.62 - lr: 0.100000 2022-11-01 13:32:55,873 epoch 13 - iter 270/274 - loss 0.03649977 - samples/sec: 68.70 - lr: 0.100000 2022-11-01 13:32:57,821 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:32:57,821 EPOCH 13 done: loss 0.0366 - lr 0.100000 2022-11-01 13:33:23,196 Evaluating as a multi-label problem: False 2022-11-01 13:33:23,211 TEST : loss 0.03093760274350643 - f1-score (micro avg) 0.8276 2022-11-01 13:33:23,262 BAD EPOCHS (no improvement): 0 2022-11-01 13:33:23,348 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:33:35,596 epoch 14 - iter 27/274 - loss 0.03587195 - samples/sec: 70.57 - lr: 0.100000 2022-11-01 13:33:47,961 epoch 14 - iter 54/274 - loss 0.03435583 - samples/sec: 69.89 - lr: 0.100000 2022-11-01 13:33:59,808 epoch 14 - iter 81/274 - loss 0.03350450 - samples/sec: 72.95 - lr: 0.100000 2022-11-01 13:34:11,390 epoch 14 - iter 108/274 - loss 0.03432252 - samples/sec: 74.62 - lr: 0.100000 2022-11-01 13:34:24,737 epoch 14 - iter 135/274 - loss 0.03559134 - samples/sec: 64.75 - lr: 0.100000 2022-11-01 13:34:37,434 epoch 14 - iter 162/274 - loss 0.03552331 - samples/sec: 68.06 - lr: 0.100000 2022-11-01 13:34:49,584 epoch 14 - iter 189/274 - loss 0.03506626 - samples/sec: 71.13 - lr: 0.100000 2022-11-01 13:35:03,212 epoch 14 - iter 216/274 - loss 0.03444676 - samples/sec: 63.41 - lr: 0.100000 2022-11-01 13:35:15,032 epoch 14 - iter 243/274 - loss 0.03434282 - samples/sec: 73.12 - lr: 0.100000 2022-11-01 13:35:27,648 epoch 14 - iter 270/274 - loss 0.03420688 - samples/sec: 68.50 - lr: 0.100000 2022-11-01 13:35:29,536 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:35:29,536 EPOCH 14 done: loss 0.0341 - lr 0.100000 2022-11-01 13:35:54,970 Evaluating as a multi-label problem: False 2022-11-01 13:35:54,985 TEST : loss 0.032740455120801926 - f1-score (micro avg) 0.8382 2022-11-01 13:35:55,038 BAD EPOCHS (no improvement): 0 2022-11-01 13:35:55,124 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:36:06,207 epoch 15 - iter 27/274 - loss 0.02621004 - samples/sec: 77.98 - lr: 0.100000 2022-11-01 13:36:18,117 epoch 15 - iter 54/274 - loss 0.03148500 - samples/sec: 72.56 - lr: 0.100000 2022-11-01 13:36:32,408 epoch 15 - iter 81/274 - loss 0.03283017 - samples/sec: 60.47 - lr: 0.100000 2022-11-01 13:36:44,413 epoch 15 - iter 108/274 - loss 0.03269024 - samples/sec: 72.00 - lr: 0.100000 2022-11-01 13:36:57,549 epoch 15 - iter 135/274 - loss 0.03234032 - samples/sec: 65.79 - lr: 0.100000 2022-11-01 13:37:09,569 epoch 15 - iter 162/274 - loss 0.03236532 - samples/sec: 71.90 - lr: 0.100000 2022-11-01 13:37:21,479 epoch 15 - iter 189/274 - loss 0.03211454 - samples/sec: 72.56 - lr: 0.100000 2022-11-01 13:37:33,192 epoch 15 - iter 216/274 - loss 0.03241047 - samples/sec: 73.78 - lr: 0.100000 2022-11-01 13:37:46,183 epoch 15 - iter 243/274 - loss 0.03314606 - samples/sec: 66.53 - lr: 0.100000 2022-11-01 13:37:58,664 epoch 15 - iter 270/274 - loss 0.03257262 - samples/sec: 69.24 - lr: 0.100000 2022-11-01 13:38:00,237 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:38:00,237 EPOCH 15 done: loss 0.0325 - lr 0.100000 2022-11-01 13:38:25,551 Evaluating as a multi-label problem: False 2022-11-01 13:38:25,566 TEST : loss 0.03659946471452713 - f1-score (micro avg) 0.8396 2022-11-01 13:38:25,619 BAD EPOCHS (no improvement): 0 2022-11-01 13:38:25,708 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:38:38,868 epoch 16 - iter 27/274 - loss 0.04310501 - samples/sec: 65.67 - lr: 0.100000 2022-11-01 13:38:51,141 epoch 16 - iter 54/274 - loss 0.03821968 - samples/sec: 70.42 - lr: 0.100000 2022-11-01 13:39:03,213 epoch 16 - iter 81/274 - loss 0.03601832 - samples/sec: 71.59 - lr: 0.100000 2022-11-01 13:39:15,515 epoch 16 - iter 108/274 - loss 0.03464665 - samples/sec: 70.25 - lr: 0.100000 2022-11-01 13:39:28,495 epoch 16 - iter 135/274 - loss 0.03385713 - samples/sec: 66.58 - lr: 0.100000 2022-11-01 13:39:42,428 epoch 16 - iter 162/274 - loss 0.03355248 - samples/sec: 62.02 - lr: 0.100000 2022-11-01 13:39:55,016 epoch 16 - iter 189/274 - loss 0.03305979 - samples/sec: 68.66 - lr: 0.100000 2022-11-01 13:40:06,660 epoch 16 - iter 216/274 - loss 0.03245928 - samples/sec: 74.22 - lr: 0.100000 2022-11-01 13:40:18,569 epoch 16 - iter 243/274 - loss 0.03229054 - samples/sec: 72.57 - lr: 0.100000 2022-11-01 13:40:29,519 epoch 16 - iter 270/274 - loss 0.03266463 - samples/sec: 78.93 - lr: 0.100000 2022-11-01 13:40:31,278 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:40:31,279 EPOCH 16 done: loss 0.0324 - lr 0.100000 2022-11-01 13:40:56,563 Evaluating as a multi-label problem: False 2022-11-01 13:40:56,579 TEST : loss 0.03419892117381096 - f1-score (micro avg) 0.8414 2022-11-01 13:40:56,630 BAD EPOCHS (no improvement): 0 2022-11-01 13:40:56,716 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:41:08,628 epoch 17 - iter 27/274 - loss 0.03131168 - samples/sec: 72.55 - lr: 0.100000 2022-11-01 13:41:20,642 epoch 17 - iter 54/274 - loss 0.03329973 - samples/sec: 71.94 - lr: 0.100000 2022-11-01 13:41:33,558 epoch 17 - iter 81/274 - loss 0.03205309 - samples/sec: 66.91 - lr: 0.100000 2022-11-01 13:41:46,746 epoch 17 - iter 108/274 - loss 0.03106228 - samples/sec: 65.53 - lr: 0.100000 2022-11-01 13:41:59,456 epoch 17 - iter 135/274 - loss 0.03205977 - samples/sec: 68.00 - lr: 0.100000 2022-11-01 13:42:10,814 epoch 17 - iter 162/274 - loss 0.03230744 - samples/sec: 76.09 - lr: 0.100000 2022-11-01 13:42:22,736 epoch 17 - iter 189/274 - loss 0.03217993 - samples/sec: 72.49 - lr: 0.100000 2022-11-01 13:42:35,185 epoch 17 - iter 216/274 - loss 0.03154261 - samples/sec: 69.42 - lr: 0.100000 2022-11-01 13:42:48,451 epoch 17 - iter 243/274 - loss 0.03218871 - samples/sec: 65.14 - lr: 0.100000 2022-11-01 13:43:00,903 epoch 17 - iter 270/274 - loss 0.03216961 - samples/sec: 69.40 - lr: 0.100000 2022-11-01 13:43:02,520 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:43:02,520 EPOCH 17 done: loss 0.0324 - lr 0.100000 2022-11-01 13:43:27,903 Evaluating as a multi-label problem: False 2022-11-01 13:43:27,919 TEST : loss 0.032121315598487854 - f1-score (micro avg) 0.8142 2022-11-01 13:43:27,973 BAD EPOCHS (no improvement): 0 2022-11-01 13:43:28,061 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:43:39,245 epoch 18 - iter 27/274 - loss 0.02828295 - samples/sec: 77.28 - lr: 0.100000 2022-11-01 13:43:51,970 epoch 18 - iter 54/274 - loss 0.02821400 - samples/sec: 67.91 - lr: 0.100000 2022-11-01 13:44:04,671 epoch 18 - iter 81/274 - loss 0.02895659 - samples/sec: 68.04 - lr: 0.100000 2022-11-01 13:44:17,750 epoch 18 - iter 108/274 - loss 0.02937219 - samples/sec: 66.08 - lr: 0.100000 2022-11-01 13:44:29,293 epoch 18 - iter 135/274 - loss 0.02969136 - samples/sec: 74.87 - lr: 0.100000 2022-11-01 13:44:41,423 epoch 18 - iter 162/274 - loss 0.03044366 - samples/sec: 71.25 - lr: 0.100000 2022-11-01 13:44:53,180 epoch 18 - iter 189/274 - loss 0.03033224 - samples/sec: 73.51 - lr: 0.100000 2022-11-01 13:45:05,434 epoch 18 - iter 216/274 - loss 0.03010129 - samples/sec: 70.52 - lr: 0.100000 2022-11-01 13:45:17,103 epoch 18 - iter 243/274 - loss 0.03031468 - samples/sec: 74.07 - lr: 0.100000 2022-11-01 13:45:31,926 epoch 18 - iter 270/274 - loss 0.03086624 - samples/sec: 58.30 - lr: 0.100000 2022-11-01 13:45:33,720 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:45:33,720 EPOCH 18 done: loss 0.0309 - lr 0.100000 2022-11-01 13:45:59,011 Evaluating as a multi-label problem: False 2022-11-01 13:45:59,027 TEST : loss 0.03097383677959442 - f1-score (micro avg) 0.8361 2022-11-01 13:45:59,081 BAD EPOCHS (no improvement): 0 2022-11-01 13:45:59,150 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:46:12,115 epoch 19 - iter 27/274 - loss 0.03291951 - samples/sec: 66.66 - lr: 0.100000 2022-11-01 13:46:24,726 epoch 19 - iter 54/274 - loss 0.03100127 - samples/sec: 68.53 - lr: 0.100000 2022-11-01 13:46:36,908 epoch 19 - iter 81/274 - loss 0.03008968 - samples/sec: 70.95 - lr: 0.100000 2022-11-01 13:46:49,567 epoch 19 - iter 108/274 - loss 0.02850661 - samples/sec: 68.36 - lr: 0.100000 2022-11-01 13:47:03,710 epoch 19 - iter 135/274 - loss 0.02973182 - samples/sec: 61.10 - lr: 0.100000 2022-11-01 13:47:15,650 epoch 19 - iter 162/274 - loss 0.03029075 - samples/sec: 72.38 - lr: 0.100000 2022-11-01 13:47:27,204 epoch 19 - iter 189/274 - loss 0.03061716 - samples/sec: 74.80 - lr: 0.100000 2022-11-01 13:47:39,709 epoch 19 - iter 216/274 - loss 0.03024609 - samples/sec: 69.11 - lr: 0.100000 2022-11-01 13:47:52,438 epoch 19 - iter 243/274 - loss 0.03075993 - samples/sec: 67.89 - lr: 0.100000 2022-11-01 13:48:04,395 epoch 19 - iter 270/274 - loss 0.03035569 - samples/sec: 72.28 - lr: 0.100000 2022-11-01 13:48:06,254 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:48:06,254 EPOCH 19 done: loss 0.0304 - lr 0.100000 2022-11-01 13:48:31,545 Evaluating as a multi-label problem: False 2022-11-01 13:48:31,560 TEST : loss 0.031058575958013535 - f1-score (micro avg) 0.8361 2022-11-01 13:48:31,612 BAD EPOCHS (no improvement): 0 2022-11-01 13:48:31,701 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:48:43,605 epoch 20 - iter 27/274 - loss 0.03341089 - samples/sec: 72.61 - lr: 0.100000 2022-11-01 13:48:56,331 epoch 20 - iter 54/274 - loss 0.02965002 - samples/sec: 67.91 - lr: 0.100000 2022-11-01 13:49:08,466 epoch 20 - iter 81/274 - loss 0.02936467 - samples/sec: 71.22 - lr: 0.100000 2022-11-01 13:49:20,359 epoch 20 - iter 108/274 - loss 0.02967577 - samples/sec: 72.67 - lr: 0.100000 2022-11-01 13:49:31,703 epoch 20 - iter 135/274 - loss 0.02962385 - samples/sec: 76.18 - lr: 0.100000 2022-11-01 13:49:45,689 epoch 20 - iter 162/274 - loss 0.03002445 - samples/sec: 61.79 - lr: 0.100000 2022-11-01 13:49:59,016 epoch 20 - iter 189/274 - loss 0.02979085 - samples/sec: 64.85 - lr: 0.100000 2022-11-01 13:50:11,482 epoch 20 - iter 216/274 - loss 0.03016882 - samples/sec: 69.33 - lr: 0.100000 2022-11-01 13:50:23,142 epoch 20 - iter 243/274 - loss 0.03053355 - samples/sec: 74.12 - lr: 0.100000 2022-11-01 13:50:35,085 epoch 20 - iter 270/274 - loss 0.03054658 - samples/sec: 72.37 - lr: 0.100000 2022-11-01 13:50:36,716 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:50:36,716 EPOCH 20 done: loss 0.0304 - lr 0.100000 2022-11-01 13:51:01,815 Evaluating as a multi-label problem: False 2022-11-01 13:51:01,830 TEST : loss 0.035328544676303864 - f1-score (micro avg) 0.8392 2022-11-01 13:51:01,882 BAD EPOCHS (no improvement): 1 2022-11-01 13:51:01,968 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:51:16,421 epoch 21 - iter 27/274 - loss 0.03241261 - samples/sec: 59.79 - lr: 0.100000 2022-11-01 13:51:28,464 epoch 21 - iter 54/274 - loss 0.03286965 - samples/sec: 71.76 - lr: 0.100000 2022-11-01 13:51:40,060 epoch 21 - iter 81/274 - loss 0.03240940 - samples/sec: 74.53 - lr: 0.100000 2022-11-01 13:51:52,405 epoch 21 - iter 108/274 - loss 0.03079412 - samples/sec: 70.01 - lr: 0.100000 2022-11-01 13:52:04,384 epoch 21 - iter 135/274 - loss 0.02985053 - samples/sec: 72.15 - lr: 0.100000 2022-11-01 13:52:16,601 epoch 21 - iter 162/274 - loss 0.02987171 - samples/sec: 70.74 - lr: 0.100000 2022-11-01 13:52:28,629 epoch 21 - iter 189/274 - loss 0.03085183 - samples/sec: 71.85 - lr: 0.100000 2022-11-01 13:52:40,275 epoch 21 - iter 216/274 - loss 0.03117974 - samples/sec: 74.21 - lr: 0.100000 2022-11-01 13:52:53,944 epoch 21 - iter 243/274 - loss 0.03112541 - samples/sec: 63.22 - lr: 0.100000 2022-11-01 13:53:05,688 epoch 21 - iter 270/274 - loss 0.03062103 - samples/sec: 73.59 - lr: 0.100000 2022-11-01 13:53:07,553 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:53:07,554 EPOCH 21 done: loss 0.0308 - lr 0.100000 2022-11-01 13:53:32,862 Evaluating as a multi-label problem: False 2022-11-01 13:53:32,877 TEST : loss 0.029285110533237457 - f1-score (micro avg) 0.8396 2022-11-01 13:53:32,929 BAD EPOCHS (no improvement): 2 2022-11-01 13:53:33,017 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:53:44,810 epoch 22 - iter 27/274 - loss 0.02903520 - samples/sec: 73.29 - lr: 0.100000 2022-11-01 13:53:57,359 epoch 22 - iter 54/274 - loss 0.02877626 - samples/sec: 68.87 - lr: 0.100000 2022-11-01 13:54:09,305 epoch 22 - iter 81/274 - loss 0.02903053 - samples/sec: 72.34 - lr: 0.100000 2022-11-01 13:54:22,177 epoch 22 - iter 108/274 - loss 0.02918162 - samples/sec: 67.14 - lr: 0.100000 2022-11-01 13:54:34,724 epoch 22 - iter 135/274 - loss 0.03022362 - samples/sec: 68.88 - lr: 0.100000 2022-11-01 13:54:47,100 epoch 22 - iter 162/274 - loss 0.02921564 - samples/sec: 69.83 - lr: 0.100000 2022-11-01 13:54:58,855 epoch 22 - iter 189/274 - loss 0.02907579 - samples/sec: 73.52 - lr: 0.100000 2022-11-01 13:55:11,841 epoch 22 - iter 216/274 - loss 0.02880394 - samples/sec: 66.55 - lr: 0.100000 2022-11-01 13:55:24,785 epoch 22 - iter 243/274 - loss 0.02882432 - samples/sec: 66.76 - lr: 0.100000 2022-11-01 13:55:35,994 epoch 22 - iter 270/274 - loss 0.02922647 - samples/sec: 77.11 - lr: 0.100000 2022-11-01 13:55:37,631 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:55:37,631 EPOCH 22 done: loss 0.0293 - lr 0.100000 2022-11-01 13:56:02,870 Evaluating as a multi-label problem: False 2022-11-01 13:56:02,885 TEST : loss 0.031731970608234406 - f1-score (micro avg) 0.8458 2022-11-01 13:56:02,937 BAD EPOCHS (no improvement): 0 2022-11-01 13:56:03,023 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:56:15,323 epoch 23 - iter 27/274 - loss 0.02954803 - samples/sec: 70.27 - lr: 0.100000 2022-11-01 13:56:27,494 epoch 23 - iter 54/274 - loss 0.02818459 - samples/sec: 71.01 - lr: 0.100000 2022-11-01 13:56:38,573 epoch 23 - iter 81/274 - loss 0.02966005 - samples/sec: 78.01 - lr: 0.100000 2022-11-01 13:56:52,151 epoch 23 - iter 108/274 - loss 0.02929197 - samples/sec: 63.65 - lr: 0.100000 2022-11-01 13:57:03,768 epoch 23 - iter 135/274 - loss 0.02938255 - samples/sec: 74.40 - lr: 0.100000 2022-11-01 13:57:16,576 epoch 23 - iter 162/274 - loss 0.02905523 - samples/sec: 67.48 - lr: 0.100000 2022-11-01 13:57:28,040 epoch 23 - iter 189/274 - loss 0.02845779 - samples/sec: 75.38 - lr: 0.100000 2022-11-01 13:57:41,003 epoch 23 - iter 216/274 - loss 0.02851665 - samples/sec: 66.67 - lr: 0.100000 2022-11-01 13:57:52,675 epoch 23 - iter 243/274 - loss 0.02836095 - samples/sec: 74.04 - lr: 0.100000 2022-11-01 13:58:05,834 epoch 23 - iter 270/274 - loss 0.02879719 - samples/sec: 65.68 - lr: 0.100000 2022-11-01 13:58:07,795 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:58:07,795 EPOCH 23 done: loss 0.0292 - lr 0.100000 2022-11-01 13:58:33,309 Evaluating as a multi-label problem: False 2022-11-01 13:58:33,324 TEST : loss 0.029490221291780472 - f1-score (micro avg) 0.8464 2022-11-01 13:58:33,376 BAD EPOCHS (no improvement): 0 2022-11-01 13:58:33,466 ---------------------------------------------------------------------------------------------------- 2022-11-01 13:58:47,010 epoch 24 - iter 27/274 - loss 0.03114330 - samples/sec: 63.81 - lr: 0.100000 2022-11-01 13:58:57,750 epoch 24 - iter 54/274 - loss 0.02934230 - samples/sec: 80.47 - lr: 0.100000 2022-11-01 13:59:10,428 epoch 24 - iter 81/274 - loss 0.02821868 - samples/sec: 68.17 - lr: 0.100000 2022-11-01 13:59:22,831 epoch 24 - iter 108/274 - loss 0.02736854 - samples/sec: 69.68 - lr: 0.100000 2022-11-01 13:59:34,154 epoch 24 - iter 135/274 - loss 0.02744987 - samples/sec: 76.33 - lr: 0.100000 2022-11-01 13:59:47,845 epoch 24 - iter 162/274 - loss 0.02721262 - samples/sec: 63.12 - lr: 0.100000 2022-11-01 14:00:00,436 epoch 24 - iter 189/274 - loss 0.02819192 - samples/sec: 68.64 - lr: 0.100000 2022-11-01 14:00:12,356 epoch 24 - iter 216/274 - loss 0.02808668 - samples/sec: 72.50 - lr: 0.100000 2022-11-01 14:00:24,554 epoch 24 - iter 243/274 - loss 0.02787150 - samples/sec: 70.85 - lr: 0.100000 2022-11-01 14:00:36,399 epoch 24 - iter 270/274 - loss 0.02806091 - samples/sec: 72.96 - lr: 0.100000 2022-11-01 14:00:38,397 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:00:38,397 EPOCH 24 done: loss 0.0281 - lr 0.100000 2022-11-01 14:01:03,905 Evaluating as a multi-label problem: False 2022-11-01 14:01:03,920 TEST : loss 0.03052011877298355 - f1-score (micro avg) 0.8427 2022-11-01 14:01:03,971 BAD EPOCHS (no improvement): 0 2022-11-01 14:01:04,039 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:01:15,033 epoch 25 - iter 27/274 - loss 0.02254447 - samples/sec: 78.61 - lr: 0.100000 2022-11-01 14:01:27,113 epoch 25 - iter 54/274 - loss 0.02958591 - samples/sec: 71.54 - lr: 0.100000 2022-11-01 14:01:39,053 epoch 25 - iter 81/274 - loss 0.02847044 - samples/sec: 72.39 - lr: 0.100000 2022-11-01 14:01:50,919 epoch 25 - iter 108/274 - loss 0.02739965 - samples/sec: 72.83 - lr: 0.100000 2022-11-01 14:02:02,867 epoch 25 - iter 135/274 - loss 0.02744808 - samples/sec: 72.33 - lr: 0.100000 2022-11-01 14:02:15,744 epoch 25 - iter 162/274 - loss 0.02698485 - samples/sec: 67.12 - lr: 0.100000 2022-11-01 14:02:27,495 epoch 25 - iter 189/274 - loss 0.02731846 - samples/sec: 73.54 - lr: 0.100000 2022-11-01 14:02:40,427 epoch 25 - iter 216/274 - loss 0.02843243 - samples/sec: 66.83 - lr: 0.100000 2022-11-01 14:02:54,788 epoch 25 - iter 243/274 - loss 0.02862498 - samples/sec: 60.18 - lr: 0.100000 2022-11-01 14:03:08,086 epoch 25 - iter 270/274 - loss 0.02826127 - samples/sec: 64.99 - lr: 0.100000 2022-11-01 14:03:09,433 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:03:09,434 EPOCH 25 done: loss 0.0284 - lr 0.100000 2022-11-01 14:03:34,594 Evaluating as a multi-label problem: False 2022-11-01 14:03:34,610 TEST : loss 0.029107416048645973 - f1-score (micro avg) 0.8389 2022-11-01 14:03:34,662 BAD EPOCHS (no improvement): 1 2022-11-01 14:03:34,750 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:03:46,841 epoch 26 - iter 27/274 - loss 0.02811300 - samples/sec: 71.48 - lr: 0.100000 2022-11-01 14:03:59,602 epoch 26 - iter 54/274 - loss 0.02743337 - samples/sec: 67.72 - lr: 0.100000 2022-11-01 14:04:11,887 epoch 26 - iter 81/274 - loss 0.02763661 - samples/sec: 70.35 - lr: 0.100000 2022-11-01 14:04:25,712 epoch 26 - iter 108/274 - loss 0.02912647 - samples/sec: 62.51 - lr: 0.100000 2022-11-01 14:04:37,325 epoch 26 - iter 135/274 - loss 0.02824420 - samples/sec: 74.42 - lr: 0.100000 2022-11-01 14:04:50,074 epoch 26 - iter 162/274 - loss 0.02814963 - samples/sec: 67.79 - lr: 0.100000 2022-11-01 14:05:02,658 epoch 26 - iter 189/274 - loss 0.02796098 - samples/sec: 68.68 - lr: 0.100000 2022-11-01 14:05:15,161 epoch 26 - iter 216/274 - loss 0.02806696 - samples/sec: 69.12 - lr: 0.100000 2022-11-01 14:05:26,292 epoch 26 - iter 243/274 - loss 0.02822794 - samples/sec: 77.65 - lr: 0.100000 2022-11-01 14:05:38,777 epoch 26 - iter 270/274 - loss 0.02796632 - samples/sec: 69.22 - lr: 0.100000 2022-11-01 14:05:40,413 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:05:40,413 EPOCH 26 done: loss 0.0280 - lr 0.100000 2022-11-01 14:06:05,568 Evaluating as a multi-label problem: False 2022-11-01 14:06:05,583 TEST : loss 0.028921490535140038 - f1-score (micro avg) 0.8499 2022-11-01 14:06:05,635 BAD EPOCHS (no improvement): 0 2022-11-01 14:06:05,720 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:06:17,118 epoch 27 - iter 27/274 - loss 0.03035630 - samples/sec: 75.83 - lr: 0.100000 2022-11-01 14:06:28,418 epoch 27 - iter 54/274 - loss 0.02636220 - samples/sec: 76.48 - lr: 0.100000 2022-11-01 14:06:40,920 epoch 27 - iter 81/274 - loss 0.02716773 - samples/sec: 69.13 - lr: 0.100000 2022-11-01 14:06:53,020 epoch 27 - iter 108/274 - loss 0.02817490 - samples/sec: 71.43 - lr: 0.100000 2022-11-01 14:07:06,130 epoch 27 - iter 135/274 - loss 0.02905628 - samples/sec: 65.92 - lr: 0.100000 2022-11-01 14:07:19,646 epoch 27 - iter 162/274 - loss 0.02789546 - samples/sec: 63.94 - lr: 0.100000 2022-11-01 14:07:31,413 epoch 27 - iter 189/274 - loss 0.02750674 - samples/sec: 73.44 - lr: 0.100000 2022-11-01 14:07:43,807 epoch 27 - iter 216/274 - loss 0.02740534 - samples/sec: 69.73 - lr: 0.100000 2022-11-01 14:07:57,071 epoch 27 - iter 243/274 - loss 0.02788272 - samples/sec: 65.15 - lr: 0.100000 2022-11-01 14:08:09,097 epoch 27 - iter 270/274 - loss 0.02804086 - samples/sec: 71.86 - lr: 0.100000 2022-11-01 14:08:10,721 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:08:10,721 EPOCH 27 done: loss 0.0279 - lr 0.100000 2022-11-01 14:08:35,996 Evaluating as a multi-label problem: False 2022-11-01 14:08:36,011 TEST : loss 0.02727373316884041 - f1-score (micro avg) 0.8495 2022-11-01 14:08:36,063 BAD EPOCHS (no improvement): 0 2022-11-01 14:08:36,151 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:08:48,729 epoch 28 - iter 27/274 - loss 0.02792706 - samples/sec: 68.72 - lr: 0.100000 2022-11-01 14:09:00,474 epoch 28 - iter 54/274 - loss 0.02712818 - samples/sec: 73.58 - lr: 0.100000 2022-11-01 14:09:13,998 epoch 28 - iter 81/274 - loss 0.02881006 - samples/sec: 63.90 - lr: 0.100000 2022-11-01 14:09:26,897 epoch 28 - iter 108/274 - loss 0.02790622 - samples/sec: 66.99 - lr: 0.100000 2022-11-01 14:09:39,353 epoch 28 - iter 135/274 - loss 0.02765454 - samples/sec: 69.38 - lr: 0.100000 2022-11-01 14:09:51,992 epoch 28 - iter 162/274 - loss 0.02686081 - samples/sec: 68.38 - lr: 0.100000 2022-11-01 14:10:05,064 epoch 28 - iter 189/274 - loss 0.02634890 - samples/sec: 66.11 - lr: 0.100000 2022-11-01 14:10:16,714 epoch 28 - iter 216/274 - loss 0.02655923 - samples/sec: 74.18 - lr: 0.100000 2022-11-01 14:10:29,815 epoch 28 - iter 243/274 - loss 0.02663561 - samples/sec: 65.96 - lr: 0.100000 2022-11-01 14:10:41,079 epoch 28 - iter 270/274 - loss 0.02647144 - samples/sec: 76.72 - lr: 0.100000 2022-11-01 14:10:42,579 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:10:42,580 EPOCH 28 done: loss 0.0267 - lr 0.100000 2022-11-01 14:11:07,885 Evaluating as a multi-label problem: False 2022-11-01 14:11:07,901 TEST : loss 0.029852760955691338 - f1-score (micro avg) 0.8372 2022-11-01 14:11:07,953 BAD EPOCHS (no improvement): 0 2022-11-01 14:11:08,041 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:11:20,409 epoch 29 - iter 27/274 - loss 0.02518790 - samples/sec: 69.88 - lr: 0.100000 2022-11-01 14:11:32,626 epoch 29 - iter 54/274 - loss 0.02805683 - samples/sec: 70.74 - lr: 0.100000 2022-11-01 14:11:45,533 epoch 29 - iter 81/274 - loss 0.02825807 - samples/sec: 66.96 - lr: 0.100000 2022-11-01 14:11:57,137 epoch 29 - iter 108/274 - loss 0.02799206 - samples/sec: 74.48 - lr: 0.100000 2022-11-01 14:12:08,601 epoch 29 - iter 135/274 - loss 0.02755879 - samples/sec: 75.38 - lr: 0.100000 2022-11-01 14:12:21,338 epoch 29 - iter 162/274 - loss 0.02685576 - samples/sec: 67.85 - lr: 0.100000 2022-11-01 14:12:33,835 epoch 29 - iter 189/274 - loss 0.02594996 - samples/sec: 69.16 - lr: 0.100000 2022-11-01 14:12:46,797 epoch 29 - iter 216/274 - loss 0.02550550 - samples/sec: 66.67 - lr: 0.100000 2022-11-01 14:12:59,038 epoch 29 - iter 243/274 - loss 0.02644877 - samples/sec: 70.60 - lr: 0.100000 2022-11-01 14:13:12,139 epoch 29 - iter 270/274 - loss 0.02627661 - samples/sec: 65.96 - lr: 0.100000 2022-11-01 14:13:13,801 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:13:13,801 EPOCH 29 done: loss 0.0265 - lr 0.100000 2022-11-01 14:13:39,155 Evaluating as a multi-label problem: False 2022-11-01 14:13:39,171 TEST : loss 0.02927403524518013 - f1-score (micro avg) 0.8443 2022-11-01 14:13:39,223 BAD EPOCHS (no improvement): 0 2022-11-01 14:13:39,311 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:13:51,641 epoch 30 - iter 27/274 - loss 0.02423251 - samples/sec: 70.10 - lr: 0.100000 2022-11-01 14:14:05,415 epoch 30 - iter 54/274 - loss 0.02348831 - samples/sec: 62.74 - lr: 0.100000 2022-11-01 14:14:18,177 epoch 30 - iter 81/274 - loss 0.02264011 - samples/sec: 67.72 - lr: 0.100000 2022-11-01 14:14:29,311 epoch 30 - iter 108/274 - loss 0.02290510 - samples/sec: 77.62 - lr: 0.100000 2022-11-01 14:14:40,278 epoch 30 - iter 135/274 - loss 0.02305872 - samples/sec: 78.81 - lr: 0.100000 2022-11-01 14:14:52,410 epoch 30 - iter 162/274 - loss 0.02371256 - samples/sec: 71.23 - lr: 0.100000 2022-11-01 14:15:05,697 epoch 30 - iter 189/274 - loss 0.02443210 - samples/sec: 65.04 - lr: 0.100000 2022-11-01 14:15:18,878 epoch 30 - iter 216/274 - loss 0.02487402 - samples/sec: 65.56 - lr: 0.100000 2022-11-01 14:15:31,181 epoch 30 - iter 243/274 - loss 0.02547667 - samples/sec: 70.25 - lr: 0.100000 2022-11-01 14:15:44,553 epoch 30 - iter 270/274 - loss 0.02573419 - samples/sec: 64.63 - lr: 0.100000 2022-11-01 14:15:46,184 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:15:46,184 EPOCH 30 done: loss 0.0257 - lr 0.100000 2022-11-01 14:16:11,386 Evaluating as a multi-label problem: False 2022-11-01 14:16:11,401 TEST : loss 0.030005231499671936 - f1-score (micro avg) 0.8523 2022-11-01 14:16:11,453 BAD EPOCHS (no improvement): 0 2022-11-01 14:16:11,541 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:16:23,665 epoch 31 - iter 27/274 - loss 0.02769051 - samples/sec: 71.29 - lr: 0.100000 2022-11-01 14:16:35,224 epoch 31 - iter 54/274 - loss 0.02615510 - samples/sec: 74.77 - lr: 0.100000 2022-11-01 14:16:46,401 epoch 31 - iter 81/274 - loss 0.02630420 - samples/sec: 77.32 - lr: 0.100000 2022-11-01 14:16:59,281 epoch 31 - iter 108/274 - loss 0.02469976 - samples/sec: 67.10 - lr: 0.100000 2022-11-01 14:17:11,971 epoch 31 - iter 135/274 - loss 0.02533977 - samples/sec: 68.10 - lr: 0.100000 2022-11-01 14:17:25,008 epoch 31 - iter 162/274 - loss 0.02569860 - samples/sec: 66.29 - lr: 0.100000 2022-11-01 14:17:38,425 epoch 31 - iter 189/274 - loss 0.02582364 - samples/sec: 64.41 - lr: 0.100000 2022-11-01 14:17:50,083 epoch 31 - iter 216/274 - loss 0.02617259 - samples/sec: 74.13 - lr: 0.100000 2022-11-01 14:18:02,399 epoch 31 - iter 243/274 - loss 0.02593181 - samples/sec: 70.17 - lr: 0.100000 2022-11-01 14:18:14,787 epoch 31 - iter 270/274 - loss 0.02601068 - samples/sec: 69.77 - lr: 0.100000 2022-11-01 14:18:16,416 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:18:16,416 EPOCH 31 done: loss 0.0260 - lr 0.100000 2022-11-01 14:18:41,696 Evaluating as a multi-label problem: False 2022-11-01 14:18:41,712 TEST : loss 0.029843807220458984 - f1-score (micro avg) 0.8272 2022-11-01 14:18:41,764 BAD EPOCHS (no improvement): 1 2022-11-01 14:18:41,849 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:18:54,631 epoch 32 - iter 27/274 - loss 0.02580945 - samples/sec: 67.62 - lr: 0.100000 2022-11-01 14:19:05,986 epoch 32 - iter 54/274 - loss 0.02640680 - samples/sec: 76.11 - lr: 0.100000 2022-11-01 14:19:18,468 epoch 32 - iter 81/274 - loss 0.02720723 - samples/sec: 69.24 - lr: 0.100000 2022-11-01 14:19:31,021 epoch 32 - iter 108/274 - loss 0.02758148 - samples/sec: 68.85 - lr: 0.100000 2022-11-01 14:19:42,993 epoch 32 - iter 135/274 - loss 0.02673017 - samples/sec: 72.19 - lr: 0.100000 2022-11-01 14:19:54,726 epoch 32 - iter 162/274 - loss 0.02549280 - samples/sec: 73.66 - lr: 0.100000 2022-11-01 14:20:07,180 epoch 32 - iter 189/274 - loss 0.02547213 - samples/sec: 69.39 - lr: 0.100000 2022-11-01 14:20:19,997 epoch 32 - iter 216/274 - loss 0.02544760 - samples/sec: 67.43 - lr: 0.100000 2022-11-01 14:20:32,141 epoch 32 - iter 243/274 - loss 0.02578350 - samples/sec: 71.16 - lr: 0.100000 2022-11-01 14:20:45,434 epoch 32 - iter 270/274 - loss 0.02555593 - samples/sec: 65.02 - lr: 0.100000 2022-11-01 14:20:47,150 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:20:47,150 EPOCH 32 done: loss 0.0256 - lr 0.100000 2022-11-01 14:21:12,438 Evaluating as a multi-label problem: False 2022-11-01 14:21:12,453 TEST : loss 0.032904475927352905 - f1-score (micro avg) 0.8416 2022-11-01 14:21:12,505 BAD EPOCHS (no improvement): 0 2022-11-01 14:21:12,594 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:21:24,196 epoch 33 - iter 27/274 - loss 0.02139107 - samples/sec: 74.49 - lr: 0.100000 2022-11-01 14:21:35,808 epoch 33 - iter 54/274 - loss 0.02249589 - samples/sec: 74.43 - lr: 0.100000 2022-11-01 14:21:48,551 epoch 33 - iter 81/274 - loss 0.02273499 - samples/sec: 67.82 - lr: 0.100000 2022-11-01 14:22:00,045 epoch 33 - iter 108/274 - loss 0.02313428 - samples/sec: 75.19 - lr: 0.100000 2022-11-01 14:22:12,913 epoch 33 - iter 135/274 - loss 0.02465351 - samples/sec: 67.16 - lr: 0.100000 2022-11-01 14:22:25,998 epoch 33 - iter 162/274 - loss 0.02561604 - samples/sec: 66.04 - lr: 0.100000 2022-11-01 14:22:39,478 epoch 33 - iter 189/274 - loss 0.02617891 - samples/sec: 64.11 - lr: 0.100000 2022-11-01 14:22:52,040 epoch 33 - iter 216/274 - loss 0.02625557 - samples/sec: 68.80 - lr: 0.100000 2022-11-01 14:23:05,286 epoch 33 - iter 243/274 - loss 0.02610092 - samples/sec: 65.24 - lr: 0.100000 2022-11-01 14:23:17,260 epoch 33 - iter 270/274 - loss 0.02604854 - samples/sec: 72.18 - lr: 0.100000 2022-11-01 14:23:18,711 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:23:18,711 EPOCH 33 done: loss 0.0261 - lr 0.100000 2022-11-01 14:23:44,069 Evaluating as a multi-label problem: False 2022-11-01 14:23:44,084 TEST : loss 0.028233280405402184 - f1-score (micro avg) 0.8391 2022-11-01 14:23:44,136 BAD EPOCHS (no improvement): 1 2022-11-01 14:23:44,226 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:23:56,465 epoch 34 - iter 27/274 - loss 0.02246222 - samples/sec: 70.62 - lr: 0.100000 2022-11-01 14:24:07,833 epoch 34 - iter 54/274 - loss 0.02635074 - samples/sec: 76.03 - lr: 0.100000 2022-11-01 14:24:20,691 epoch 34 - iter 81/274 - loss 0.02508465 - samples/sec: 67.21 - lr: 0.100000 2022-11-01 14:24:33,435 epoch 34 - iter 108/274 - loss 0.02542733 - samples/sec: 67.81 - lr: 0.100000 2022-11-01 14:24:45,896 epoch 34 - iter 135/274 - loss 0.02499971 - samples/sec: 69.35 - lr: 0.100000 2022-11-01 14:24:59,505 epoch 34 - iter 162/274 - loss 0.02484198 - samples/sec: 63.50 - lr: 0.100000 2022-11-01 14:25:11,652 epoch 34 - iter 189/274 - loss 0.02512618 - samples/sec: 71.14 - lr: 0.100000 2022-11-01 14:25:22,940 epoch 34 - iter 216/274 - loss 0.02466030 - samples/sec: 76.57 - lr: 0.100000 2022-11-01 14:25:35,198 epoch 34 - iter 243/274 - loss 0.02485847 - samples/sec: 70.50 - lr: 0.100000 2022-11-01 14:25:47,307 epoch 34 - iter 270/274 - loss 0.02483982 - samples/sec: 71.37 - lr: 0.100000 2022-11-01 14:25:49,659 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:25:49,660 EPOCH 34 done: loss 0.0251 - lr 0.100000 2022-11-01 14:26:14,991 Evaluating as a multi-label problem: False 2022-11-01 14:26:15,007 TEST : loss 0.03128255903720856 - f1-score (micro avg) 0.8362 2022-11-01 14:26:15,058 BAD EPOCHS (no improvement): 0 2022-11-01 14:26:15,146 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:26:27,562 epoch 35 - iter 27/274 - loss 0.02694894 - samples/sec: 69.61 - lr: 0.100000 2022-11-01 14:26:40,795 epoch 35 - iter 54/274 - loss 0.02622403 - samples/sec: 65.31 - lr: 0.100000 2022-11-01 14:26:53,932 epoch 35 - iter 81/274 - loss 0.02467823 - samples/sec: 65.78 - lr: 0.100000 2022-11-01 14:27:08,552 epoch 35 - iter 108/274 - loss 0.02345882 - samples/sec: 59.11 - lr: 0.100000 2022-11-01 14:27:21,143 epoch 35 - iter 135/274 - loss 0.02558701 - samples/sec: 68.63 - lr: 0.100000 2022-11-01 14:27:33,403 epoch 35 - iter 162/274 - loss 0.02581309 - samples/sec: 70.49 - lr: 0.100000 2022-11-01 14:27:45,796 epoch 35 - iter 189/274 - loss 0.02556739 - samples/sec: 69.73 - lr: 0.100000 2022-11-01 14:27:57,067 epoch 35 - iter 216/274 - loss 0.02550404 - samples/sec: 76.68 - lr: 0.100000 2022-11-01 14:28:08,594 epoch 35 - iter 243/274 - loss 0.02550350 - samples/sec: 74.98 - lr: 0.100000 2022-11-01 14:28:20,638 epoch 35 - iter 270/274 - loss 0.02552577 - samples/sec: 71.76 - lr: 0.100000 2022-11-01 14:28:22,286 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:28:22,286 EPOCH 35 done: loss 0.0256 - lr 0.100000 2022-11-01 14:28:47,480 Evaluating as a multi-label problem: False 2022-11-01 14:28:47,496 TEST : loss 0.02886551432311535 - f1-score (micro avg) 0.839 2022-11-01 14:28:47,547 BAD EPOCHS (no improvement): 1 2022-11-01 14:28:47,616 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:28:58,605 epoch 36 - iter 27/274 - loss 0.02300676 - samples/sec: 78.66 - lr: 0.100000 2022-11-01 14:29:11,051 epoch 36 - iter 54/274 - loss 0.02499267 - samples/sec: 69.43 - lr: 0.100000 2022-11-01 14:29:23,960 epoch 36 - iter 81/274 - loss 0.02491617 - samples/sec: 66.95 - lr: 0.100000 2022-11-01 14:29:35,980 epoch 36 - iter 108/274 - loss 0.02491462 - samples/sec: 71.90 - lr: 0.100000 2022-11-01 14:29:48,361 epoch 36 - iter 135/274 - loss 0.02460620 - samples/sec: 69.80 - lr: 0.100000 2022-11-01 14:30:00,925 epoch 36 - iter 162/274 - loss 0.02530639 - samples/sec: 68.78 - lr: 0.100000 2022-11-01 14:30:13,191 epoch 36 - iter 189/274 - loss 0.02488329 - samples/sec: 70.46 - lr: 0.100000 2022-11-01 14:30:26,975 epoch 36 - iter 216/274 - loss 0.02498352 - samples/sec: 62.70 - lr: 0.100000 2022-11-01 14:30:39,154 epoch 36 - iter 243/274 - loss 0.02518749 - samples/sec: 70.96 - lr: 0.100000 2022-11-01 14:30:51,430 epoch 36 - iter 270/274 - loss 0.02540258 - samples/sec: 70.40 - lr: 0.100000 2022-11-01 14:30:53,449 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:30:53,449 EPOCH 36 done: loss 0.0254 - lr 0.100000 2022-11-01 14:31:18,697 Evaluating as a multi-label problem: False 2022-11-01 14:31:18,712 TEST : loss 0.02905181795358658 - f1-score (micro avg) 0.8424 2022-11-01 14:31:18,763 BAD EPOCHS (no improvement): 2 2022-11-01 14:31:18,855 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:31:31,289 epoch 37 - iter 27/274 - loss 0.02678495 - samples/sec: 69.51 - lr: 0.100000 2022-11-01 14:31:43,065 epoch 37 - iter 54/274 - loss 0.02523053 - samples/sec: 73.39 - lr: 0.100000 2022-11-01 14:31:55,883 epoch 37 - iter 81/274 - loss 0.02558693 - samples/sec: 67.42 - lr: 0.100000 2022-11-01 14:32:07,760 epoch 37 - iter 108/274 - loss 0.02555196 - samples/sec: 72.76 - lr: 0.100000 2022-11-01 14:32:19,739 epoch 37 - iter 135/274 - loss 0.02508545 - samples/sec: 72.15 - lr: 0.100000 2022-11-01 14:32:33,968 epoch 37 - iter 162/274 - loss 0.02481853 - samples/sec: 60.74 - lr: 0.100000 2022-11-01 14:32:45,715 epoch 37 - iter 189/274 - loss 0.02523619 - samples/sec: 73.57 - lr: 0.100000 2022-11-01 14:32:58,842 epoch 37 - iter 216/274 - loss 0.02533995 - samples/sec: 65.84 - lr: 0.100000 2022-11-01 14:33:09,872 epoch 37 - iter 243/274 - loss 0.02496223 - samples/sec: 78.35 - lr: 0.100000 2022-11-01 14:33:22,337 epoch 37 - iter 270/274 - loss 0.02494492 - samples/sec: 69.33 - lr: 0.100000 2022-11-01 14:33:23,784 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:33:23,784 EPOCH 37 done: loss 0.0248 - lr 0.100000 2022-11-01 14:33:49,123 Evaluating as a multi-label problem: False 2022-11-01 14:33:49,139 TEST : loss 0.03083939664065838 - f1-score (micro avg) 0.8404 2022-11-01 14:33:49,191 BAD EPOCHS (no improvement): 0 2022-11-01 14:33:49,284 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:34:01,480 epoch 38 - iter 27/274 - loss 0.02325190 - samples/sec: 70.86 - lr: 0.100000 2022-11-01 14:34:15,709 epoch 38 - iter 54/274 - loss 0.02240111 - samples/sec: 60.73 - lr: 0.100000 2022-11-01 14:34:28,421 epoch 38 - iter 81/274 - loss 0.02339176 - samples/sec: 67.99 - lr: 0.100000 2022-11-01 14:34:40,651 epoch 38 - iter 108/274 - loss 0.02383358 - samples/sec: 70.66 - lr: 0.100000 2022-11-01 14:34:52,869 epoch 38 - iter 135/274 - loss 0.02355411 - samples/sec: 70.74 - lr: 0.100000 2022-11-01 14:35:05,634 epoch 38 - iter 162/274 - loss 0.02436854 - samples/sec: 67.70 - lr: 0.100000 2022-11-01 14:35:18,016 epoch 38 - iter 189/274 - loss 0.02461991 - samples/sec: 69.80 - lr: 0.100000 2022-11-01 14:35:30,070 epoch 38 - iter 216/274 - loss 0.02434924 - samples/sec: 71.70 - lr: 0.100000 2022-11-01 14:35:40,955 epoch 38 - iter 243/274 - loss 0.02462337 - samples/sec: 79.39 - lr: 0.100000 2022-11-01 14:35:53,586 epoch 38 - iter 270/274 - loss 0.02484028 - samples/sec: 68.42 - lr: 0.100000 2022-11-01 14:35:55,289 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:35:55,289 EPOCH 38 done: loss 0.0247 - lr 0.100000 2022-11-01 14:36:20,583 Evaluating as a multi-label problem: False 2022-11-01 14:36:20,598 TEST : loss 0.029346710070967674 - f1-score (micro avg) 0.8482 2022-11-01 14:36:20,650 BAD EPOCHS (no improvement): 0 2022-11-01 14:36:20,721 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:36:32,585 epoch 39 - iter 27/274 - loss 0.02562557 - samples/sec: 72.85 - lr: 0.100000 2022-11-01 14:36:43,852 epoch 39 - iter 54/274 - loss 0.02372105 - samples/sec: 76.71 - lr: 0.100000 2022-11-01 14:36:57,929 epoch 39 - iter 81/274 - loss 0.02352530 - samples/sec: 61.39 - lr: 0.100000 2022-11-01 14:37:11,034 epoch 39 - iter 108/274 - loss 0.02507286 - samples/sec: 65.95 - lr: 0.100000 2022-11-01 14:37:22,672 epoch 39 - iter 135/274 - loss 0.02526471 - samples/sec: 74.26 - lr: 0.100000 2022-11-01 14:37:35,165 epoch 39 - iter 162/274 - loss 0.02549320 - samples/sec: 69.18 - lr: 0.100000 2022-11-01 14:37:46,859 epoch 39 - iter 189/274 - loss 0.02480664 - samples/sec: 73.90 - lr: 0.100000 2022-11-01 14:37:58,698 epoch 39 - iter 216/274 - loss 0.02442860 - samples/sec: 73.00 - lr: 0.100000 2022-11-01 14:38:11,976 epoch 39 - iter 243/274 - loss 0.02518608 - samples/sec: 65.09 - lr: 0.100000 2022-11-01 14:38:23,528 epoch 39 - iter 270/274 - loss 0.02512607 - samples/sec: 74.82 - lr: 0.100000 2022-11-01 14:38:25,272 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:38:25,272 EPOCH 39 done: loss 0.0252 - lr 0.100000 2022-11-01 14:38:50,637 Evaluating as a multi-label problem: False 2022-11-01 14:38:50,652 TEST : loss 0.030634140595793724 - f1-score (micro avg) 0.8477 2022-11-01 14:38:50,704 BAD EPOCHS (no improvement): 1 2022-11-01 14:38:50,781 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:39:02,083 epoch 40 - iter 27/274 - loss 0.02303791 - samples/sec: 76.47 - lr: 0.100000 2022-11-01 14:39:15,907 epoch 40 - iter 54/274 - loss 0.02221891 - samples/sec: 62.52 - lr: 0.100000 2022-11-01 14:39:27,953 epoch 40 - iter 81/274 - loss 0.02304378 - samples/sec: 71.74 - lr: 0.100000 2022-11-01 14:39:40,530 epoch 40 - iter 108/274 - loss 0.02335194 - samples/sec: 68.72 - lr: 0.100000 2022-11-01 14:39:52,052 epoch 40 - iter 135/274 - loss 0.02327292 - samples/sec: 75.01 - lr: 0.100000 2022-11-01 14:40:04,816 epoch 40 - iter 162/274 - loss 0.02340847 - samples/sec: 67.71 - lr: 0.100000 2022-11-01 14:40:17,337 epoch 40 - iter 189/274 - loss 0.02348761 - samples/sec: 69.02 - lr: 0.100000 2022-11-01 14:40:30,638 epoch 40 - iter 216/274 - loss 0.02364579 - samples/sec: 64.97 - lr: 0.100000 2022-11-01 14:40:41,862 epoch 40 - iter 243/274 - loss 0.02363918 - samples/sec: 77.00 - lr: 0.100000 2022-11-01 14:40:54,205 epoch 40 - iter 270/274 - loss 0.02364620 - samples/sec: 70.02 - lr: 0.100000 2022-11-01 14:40:56,428 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:40:56,428 EPOCH 40 done: loss 0.0239 - lr 0.100000 2022-11-01 14:41:21,842 Evaluating as a multi-label problem: False 2022-11-01 14:41:21,858 TEST : loss 0.02772146463394165 - f1-score (micro avg) 0.8367 2022-11-01 14:41:21,910 BAD EPOCHS (no improvement): 0 2022-11-01 14:41:21,980 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:41:34,373 epoch 41 - iter 27/274 - loss 0.02218261 - samples/sec: 69.74 - lr: 0.100000 2022-11-01 14:41:46,713 epoch 41 - iter 54/274 - loss 0.02452946 - samples/sec: 70.04 - lr: 0.100000 2022-11-01 14:42:00,067 epoch 41 - iter 81/274 - loss 0.02464984 - samples/sec: 64.71 - lr: 0.100000 2022-11-01 14:42:13,175 epoch 41 - iter 108/274 - loss 0.02478733 - samples/sec: 65.93 - lr: 0.100000 2022-11-01 14:42:24,582 epoch 41 - iter 135/274 - loss 0.02416254 - samples/sec: 75.77 - lr: 0.100000 2022-11-01 14:42:37,182 epoch 41 - iter 162/274 - loss 0.02418863 - samples/sec: 68.59 - lr: 0.100000 2022-11-01 14:42:48,979 epoch 41 - iter 189/274 - loss 0.02391712 - samples/sec: 73.26 - lr: 0.100000 2022-11-01 14:43:01,479 epoch 41 - iter 216/274 - loss 0.02390674 - samples/sec: 69.14 - lr: 0.100000 2022-11-01 14:43:13,157 epoch 41 - iter 243/274 - loss 0.02392243 - samples/sec: 74.01 - lr: 0.100000 2022-11-01 14:43:25,639 epoch 41 - iter 270/274 - loss 0.02412327 - samples/sec: 69.24 - lr: 0.100000 2022-11-01 14:43:27,265 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:43:27,265 EPOCH 41 done: loss 0.0239 - lr 0.100000 2022-11-01 14:43:52,553 Evaluating as a multi-label problem: False 2022-11-01 14:43:52,568 TEST : loss 0.03169442340731621 - f1-score (micro avg) 0.8514 2022-11-01 14:43:52,619 BAD EPOCHS (no improvement): 0 2022-11-01 14:43:52,707 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:44:04,877 epoch 42 - iter 27/274 - loss 0.02433022 - samples/sec: 71.02 - lr: 0.100000 2022-11-01 14:44:17,429 epoch 42 - iter 54/274 - loss 0.02389634 - samples/sec: 68.85 - lr: 0.100000 2022-11-01 14:44:29,618 epoch 42 - iter 81/274 - loss 0.02250941 - samples/sec: 70.90 - lr: 0.100000 2022-11-01 14:44:41,866 epoch 42 - iter 108/274 - loss 0.02211868 - samples/sec: 70.56 - lr: 0.100000 2022-11-01 14:44:55,665 epoch 42 - iter 135/274 - loss 0.02233769 - samples/sec: 62.63 - lr: 0.100000 2022-11-01 14:45:07,849 epoch 42 - iter 162/274 - loss 0.02328487 - samples/sec: 70.93 - lr: 0.100000 2022-11-01 14:45:18,733 epoch 42 - iter 189/274 - loss 0.02313874 - samples/sec: 79.41 - lr: 0.100000 2022-11-01 14:45:31,192 epoch 42 - iter 216/274 - loss 0.02357150 - samples/sec: 69.37 - lr: 0.100000 2022-11-01 14:45:44,209 epoch 42 - iter 243/274 - loss 0.02391369 - samples/sec: 66.39 - lr: 0.100000 2022-11-01 14:45:55,304 epoch 42 - iter 270/274 - loss 0.02365274 - samples/sec: 77.90 - lr: 0.100000 2022-11-01 14:45:57,120 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:45:57,120 EPOCH 42 done: loss 0.0235 - lr 0.100000 2022-11-01 14:46:22,560 Evaluating as a multi-label problem: False 2022-11-01 14:46:22,576 TEST : loss 0.03278948739171028 - f1-score (micro avg) 0.8516 2022-11-01 14:46:22,628 BAD EPOCHS (no improvement): 0 2022-11-01 14:46:22,717 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:46:38,002 epoch 43 - iter 27/274 - loss 0.02368651 - samples/sec: 56.54 - lr: 0.100000 2022-11-01 14:46:49,976 epoch 43 - iter 54/274 - loss 0.02517416 - samples/sec: 72.18 - lr: 0.100000 2022-11-01 14:47:01,138 epoch 43 - iter 81/274 - loss 0.02256523 - samples/sec: 77.43 - lr: 0.100000 2022-11-01 14:47:14,006 epoch 43 - iter 108/274 - loss 0.02355001 - samples/sec: 67.16 - lr: 0.100000 2022-11-01 14:47:26,796 epoch 43 - iter 135/274 - loss 0.02396305 - samples/sec: 67.57 - lr: 0.100000 2022-11-01 14:47:40,342 epoch 43 - iter 162/274 - loss 0.02362844 - samples/sec: 63.80 - lr: 0.100000 2022-11-01 14:47:51,127 epoch 43 - iter 189/274 - loss 0.02289074 - samples/sec: 80.14 - lr: 0.100000 2022-11-01 14:48:04,379 epoch 43 - iter 216/274 - loss 0.02336316 - samples/sec: 65.21 - lr: 0.100000 2022-11-01 14:48:16,059 epoch 43 - iter 243/274 - loss 0.02362543 - samples/sec: 73.99 - lr: 0.100000 2022-11-01 14:48:28,117 epoch 43 - iter 270/274 - loss 0.02350817 - samples/sec: 71.67 - lr: 0.100000 2022-11-01 14:48:29,903 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:48:29,903 EPOCH 43 done: loss 0.0235 - lr 0.100000 2022-11-01 14:48:55,144 Evaluating as a multi-label problem: False 2022-11-01 14:48:55,160 TEST : loss 0.032541219145059586 - f1-score (micro avg) 0.8499 2022-11-01 14:48:55,213 BAD EPOCHS (no improvement): 0 2022-11-01 14:48:55,302 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:49:08,036 epoch 44 - iter 27/274 - loss 0.02069038 - samples/sec: 67.87 - lr: 0.100000 2022-11-01 14:49:20,182 epoch 44 - iter 54/274 - loss 0.02151187 - samples/sec: 71.15 - lr: 0.100000 2022-11-01 14:49:30,865 epoch 44 - iter 81/274 - loss 0.02143477 - samples/sec: 80.90 - lr: 0.100000 2022-11-01 14:49:42,537 epoch 44 - iter 108/274 - loss 0.02245272 - samples/sec: 74.05 - lr: 0.100000 2022-11-01 14:49:54,536 epoch 44 - iter 135/274 - loss 0.02279972 - samples/sec: 72.02 - lr: 0.100000 2022-11-01 14:50:05,597 epoch 44 - iter 162/274 - loss 0.02322081 - samples/sec: 78.14 - lr: 0.100000 2022-11-01 14:50:18,330 epoch 44 - iter 189/274 - loss 0.02353130 - samples/sec: 67.87 - lr: 0.100000 2022-11-01 14:50:32,304 epoch 44 - iter 216/274 - loss 0.02377507 - samples/sec: 61.84 - lr: 0.100000 2022-11-01 14:50:44,805 epoch 44 - iter 243/274 - loss 0.02373147 - samples/sec: 69.13 - lr: 0.100000 2022-11-01 14:50:57,854 epoch 44 - iter 270/274 - loss 0.02373160 - samples/sec: 66.31 - lr: 0.100000 2022-11-01 14:50:59,998 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:50:59,998 EPOCH 44 done: loss 0.0238 - lr 0.100000 2022-11-01 14:51:26,134 Evaluating as a multi-label problem: False 2022-11-01 14:51:26,149 TEST : loss 0.02845124527812004 - f1-score (micro avg) 0.8465 2022-11-01 14:51:26,200 BAD EPOCHS (no improvement): 1 2022-11-01 14:51:26,269 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:51:39,451 epoch 45 - iter 27/274 - loss 0.02757102 - samples/sec: 65.56 - lr: 0.100000 2022-11-01 14:51:52,057 epoch 45 - iter 54/274 - loss 0.02555338 - samples/sec: 68.56 - lr: 0.100000 2022-11-01 14:52:03,835 epoch 45 - iter 81/274 - loss 0.02440811 - samples/sec: 73.38 - lr: 0.100000 2022-11-01 14:52:15,975 epoch 45 - iter 108/274 - loss 0.02504033 - samples/sec: 71.19 - lr: 0.100000 2022-11-01 14:52:28,608 epoch 45 - iter 135/274 - loss 0.02481827 - samples/sec: 68.41 - lr: 0.100000 2022-11-01 14:52:40,182 epoch 45 - iter 162/274 - loss 0.02464289 - samples/sec: 74.67 - lr: 0.100000 2022-11-01 14:52:53,060 epoch 45 - iter 189/274 - loss 0.02493790 - samples/sec: 67.11 - lr: 0.100000 2022-11-01 14:53:05,153 epoch 45 - iter 216/274 - loss 0.02455552 - samples/sec: 71.47 - lr: 0.100000 2022-11-01 14:53:17,930 epoch 45 - iter 243/274 - loss 0.02398309 - samples/sec: 67.64 - lr: 0.100000 2022-11-01 14:53:30,733 epoch 45 - iter 270/274 - loss 0.02374604 - samples/sec: 67.50 - lr: 0.100000 2022-11-01 14:53:33,008 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:53:33,008 EPOCH 45 done: loss 0.0238 - lr 0.100000 2022-11-01 14:53:58,283 Evaluating as a multi-label problem: False 2022-11-01 14:53:58,299 TEST : loss 0.029735716059803963 - f1-score (micro avg) 0.8508 2022-11-01 14:53:58,351 BAD EPOCHS (no improvement): 2 2022-11-01 14:53:58,435 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:54:09,817 epoch 46 - iter 27/274 - loss 0.02467951 - samples/sec: 75.94 - lr: 0.100000 2022-11-01 14:54:21,873 epoch 46 - iter 54/274 - loss 0.02596354 - samples/sec: 71.69 - lr: 0.100000 2022-11-01 14:54:34,441 epoch 46 - iter 81/274 - loss 0.02400549 - samples/sec: 68.76 - lr: 0.100000 2022-11-01 14:54:47,134 epoch 46 - iter 108/274 - loss 0.02389095 - samples/sec: 68.09 - lr: 0.100000 2022-11-01 14:55:01,103 epoch 46 - iter 135/274 - loss 0.02373190 - samples/sec: 61.87 - lr: 0.100000 2022-11-01 14:55:13,471 epoch 46 - iter 162/274 - loss 0.02343819 - samples/sec: 69.88 - lr: 0.100000 2022-11-01 14:55:25,101 epoch 46 - iter 189/274 - loss 0.02343376 - samples/sec: 74.31 - lr: 0.100000 2022-11-01 14:55:38,007 epoch 46 - iter 216/274 - loss 0.02403790 - samples/sec: 66.96 - lr: 0.100000 2022-11-01 14:55:50,576 epoch 46 - iter 243/274 - loss 0.02399389 - samples/sec: 68.76 - lr: 0.100000 2022-11-01 14:56:02,258 epoch 46 - iter 270/274 - loss 0.02418122 - samples/sec: 73.98 - lr: 0.100000 2022-11-01 14:56:04,273 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:56:04,274 EPOCH 46 done: loss 0.0243 - lr 0.100000 2022-11-01 14:56:29,683 Evaluating as a multi-label problem: False 2022-11-01 14:56:29,698 TEST : loss 0.028860261663794518 - f1-score (micro avg) 0.8483 2022-11-01 14:56:29,751 BAD EPOCHS (no improvement): 3 2022-11-01 14:56:29,837 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:56:42,570 epoch 47 - iter 27/274 - loss 0.03313505 - samples/sec: 67.88 - lr: 0.100000 2022-11-01 14:56:54,775 epoch 47 - iter 54/274 - loss 0.02904664 - samples/sec: 70.81 - lr: 0.100000 2022-11-01 14:57:07,973 epoch 47 - iter 81/274 - loss 0.02655091 - samples/sec: 65.48 - lr: 0.100000 2022-11-01 14:57:20,344 epoch 47 - iter 108/274 - loss 0.02502254 - samples/sec: 69.86 - lr: 0.100000 2022-11-01 14:57:33,689 epoch 47 - iter 135/274 - loss 0.02387354 - samples/sec: 64.76 - lr: 0.100000 2022-11-01 14:57:47,202 epoch 47 - iter 162/274 - loss 0.02337203 - samples/sec: 63.96 - lr: 0.100000 2022-11-01 14:57:59,283 epoch 47 - iter 189/274 - loss 0.02311901 - samples/sec: 71.53 - lr: 0.100000 2022-11-01 14:58:10,345 epoch 47 - iter 216/274 - loss 0.02312254 - samples/sec: 78.13 - lr: 0.100000 2022-11-01 14:58:22,536 epoch 47 - iter 243/274 - loss 0.02276797 - samples/sec: 70.89 - lr: 0.100000 2022-11-01 14:58:35,257 epoch 47 - iter 270/274 - loss 0.02288939 - samples/sec: 67.94 - lr: 0.100000 2022-11-01 14:58:36,750 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:58:36,750 EPOCH 47 done: loss 0.0228 - lr 0.100000 2022-11-01 14:59:01,933 Evaluating as a multi-label problem: False 2022-11-01 14:59:01,949 TEST : loss 0.02934456616640091 - f1-score (micro avg) 0.85 2022-11-01 14:59:02,000 BAD EPOCHS (no improvement): 0 2022-11-01 14:59:02,087 ---------------------------------------------------------------------------------------------------- 2022-11-01 14:59:14,890 epoch 48 - iter 27/274 - loss 0.02641052 - samples/sec: 67.51 - lr: 0.100000 2022-11-01 14:59:27,300 epoch 48 - iter 54/274 - loss 0.02458621 - samples/sec: 69.64 - lr: 0.100000 2022-11-01 14:59:41,623 epoch 48 - iter 81/274 - loss 0.02492918 - samples/sec: 60.34 - lr: 0.100000 2022-11-01 14:59:53,214 epoch 48 - iter 108/274 - loss 0.02434256 - samples/sec: 74.56 - lr: 0.100000 2022-11-01 15:00:05,218 epoch 48 - iter 135/274 - loss 0.02440883 - samples/sec: 72.00 - lr: 0.100000 2022-11-01 15:00:17,655 epoch 48 - iter 162/274 - loss 0.02434351 - samples/sec: 69.49 - lr: 0.100000 2022-11-01 15:00:29,358 epoch 48 - iter 189/274 - loss 0.02453602 - samples/sec: 73.85 - lr: 0.100000 2022-11-01 15:00:41,290 epoch 48 - iter 216/274 - loss 0.02403384 - samples/sec: 72.43 - lr: 0.100000 2022-11-01 15:00:52,879 epoch 48 - iter 243/274 - loss 0.02357749 - samples/sec: 74.57 - lr: 0.100000 2022-11-01 15:01:06,810 epoch 48 - iter 270/274 - loss 0.02325659 - samples/sec: 62.04 - lr: 0.100000 2022-11-01 15:01:08,920 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:01:08,921 EPOCH 48 done: loss 0.0233 - lr 0.100000 2022-11-01 15:01:34,433 Evaluating as a multi-label problem: False 2022-11-01 15:01:34,449 TEST : loss 0.027938606217503548 - f1-score (micro avg) 0.8443 2022-11-01 15:01:34,500 BAD EPOCHS (no improvement): 1 2022-11-01 15:01:34,588 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:01:46,854 epoch 49 - iter 27/274 - loss 0.01956175 - samples/sec: 70.46 - lr: 0.100000 2022-11-01 15:01:59,605 epoch 49 - iter 54/274 - loss 0.02219700 - samples/sec: 67.78 - lr: 0.100000 2022-11-01 15:02:11,513 epoch 49 - iter 81/274 - loss 0.02216077 - samples/sec: 72.57 - lr: 0.100000 2022-11-01 15:02:23,884 epoch 49 - iter 108/274 - loss 0.02166043 - samples/sec: 69.86 - lr: 0.100000 2022-11-01 15:02:35,018 epoch 49 - iter 135/274 - loss 0.02214609 - samples/sec: 77.62 - lr: 0.100000 2022-11-01 15:02:47,703 epoch 49 - iter 162/274 - loss 0.02230819 - samples/sec: 68.13 - lr: 0.100000 2022-11-01 15:03:00,160 epoch 49 - iter 189/274 - loss 0.02220722 - samples/sec: 69.38 - lr: 0.100000 2022-11-01 15:03:13,972 epoch 49 - iter 216/274 - loss 0.02222522 - samples/sec: 62.57 - lr: 0.100000 2022-11-01 15:03:26,882 epoch 49 - iter 243/274 - loss 0.02219608 - samples/sec: 66.94 - lr: 0.100000 2022-11-01 15:03:38,015 epoch 49 - iter 270/274 - loss 0.02232361 - samples/sec: 77.63 - lr: 0.100000 2022-11-01 15:03:39,771 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:03:39,772 EPOCH 49 done: loss 0.0224 - lr 0.100000 2022-11-01 15:04:05,093 Evaluating as a multi-label problem: False 2022-11-01 15:04:05,108 TEST : loss 0.02850373275578022 - f1-score (micro avg) 0.8468 2022-11-01 15:04:05,160 BAD EPOCHS (no improvement): 0 2022-11-01 15:04:05,249 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:04:19,274 epoch 50 - iter 27/274 - loss 0.02281989 - samples/sec: 61.62 - lr: 0.100000 2022-11-01 15:04:32,085 epoch 50 - iter 54/274 - loss 0.02177090 - samples/sec: 67.46 - lr: 0.100000 2022-11-01 15:04:44,255 epoch 50 - iter 81/274 - loss 0.02148794 - samples/sec: 71.01 - lr: 0.100000 2022-11-01 15:04:55,864 epoch 50 - iter 108/274 - loss 0.02172616 - samples/sec: 74.44 - lr: 0.100000 2022-11-01 15:05:08,711 epoch 50 - iter 135/274 - loss 0.02248392 - samples/sec: 67.27 - lr: 0.100000 2022-11-01 15:05:19,943 epoch 50 - iter 162/274 - loss 0.02202995 - samples/sec: 76.95 - lr: 0.100000 2022-11-01 15:05:31,349 epoch 50 - iter 189/274 - loss 0.02290603 - samples/sec: 75.77 - lr: 0.100000 2022-11-01 15:05:43,290 epoch 50 - iter 216/274 - loss 0.02253406 - samples/sec: 72.38 - lr: 0.100000 2022-11-01 15:05:54,958 epoch 50 - iter 243/274 - loss 0.02223297 - samples/sec: 74.07 - lr: 0.100000 2022-11-01 15:06:08,209 epoch 50 - iter 270/274 - loss 0.02262291 - samples/sec: 65.22 - lr: 0.100000 2022-11-01 15:06:10,014 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:06:10,015 EPOCH 50 done: loss 0.0226 - lr 0.100000 2022-11-01 15:06:34,955 Evaluating as a multi-label problem: False 2022-11-01 15:06:34,970 TEST : loss 0.028627894818782806 - f1-score (micro avg) 0.8454 2022-11-01 15:06:35,022 BAD EPOCHS (no improvement): 1 2022-11-01 15:06:35,107 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:06:48,507 epoch 51 - iter 27/274 - loss 0.02238933 - samples/sec: 64.49 - lr: 0.100000 2022-11-01 15:07:02,021 epoch 51 - iter 54/274 - loss 0.02462189 - samples/sec: 63.95 - lr: 0.100000 2022-11-01 15:07:14,430 epoch 51 - iter 81/274 - loss 0.02400550 - samples/sec: 69.65 - lr: 0.100000 2022-11-01 15:07:26,726 epoch 51 - iter 108/274 - loss 0.02311522 - samples/sec: 70.29 - lr: 0.100000 2022-11-01 15:07:37,629 epoch 51 - iter 135/274 - loss 0.02300795 - samples/sec: 79.27 - lr: 0.100000 2022-11-01 15:07:50,615 epoch 51 - iter 162/274 - loss 0.02348605 - samples/sec: 66.55 - lr: 0.100000 2022-11-01 15:08:02,430 epoch 51 - iter 189/274 - loss 0.02283313 - samples/sec: 73.15 - lr: 0.100000 2022-11-01 15:08:14,790 epoch 51 - iter 216/274 - loss 0.02245246 - samples/sec: 69.92 - lr: 0.100000 2022-11-01 15:08:26,827 epoch 51 - iter 243/274 - loss 0.02276332 - samples/sec: 71.80 - lr: 0.100000 2022-11-01 15:08:40,356 epoch 51 - iter 270/274 - loss 0.02279572 - samples/sec: 63.88 - lr: 0.100000 2022-11-01 15:08:41,992 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:08:41,992 EPOCH 51 done: loss 0.0228 - lr 0.100000 2022-11-01 15:09:07,240 Evaluating as a multi-label problem: False 2022-11-01 15:09:07,255 TEST : loss 0.030040256679058075 - f1-score (micro avg) 0.8562 2022-11-01 15:09:07,307 BAD EPOCHS (no improvement): 2 2022-11-01 15:09:07,396 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:09:19,681 epoch 52 - iter 27/274 - loss 0.02043969 - samples/sec: 70.35 - lr: 0.100000 2022-11-01 15:09:34,320 epoch 52 - iter 54/274 - loss 0.02200447 - samples/sec: 59.03 - lr: 0.100000 2022-11-01 15:09:47,331 epoch 52 - iter 81/274 - loss 0.02239819 - samples/sec: 66.42 - lr: 0.100000 2022-11-01 15:10:00,542 epoch 52 - iter 108/274 - loss 0.02195955 - samples/sec: 65.41 - lr: 0.100000 2022-11-01 15:10:12,733 epoch 52 - iter 135/274 - loss 0.02255437 - samples/sec: 70.89 - lr: 0.100000 2022-11-01 15:10:24,202 epoch 52 - iter 162/274 - loss 0.02364029 - samples/sec: 75.36 - lr: 0.100000 2022-11-01 15:10:35,444 epoch 52 - iter 189/274 - loss 0.02373332 - samples/sec: 76.87 - lr: 0.100000 2022-11-01 15:10:47,265 epoch 52 - iter 216/274 - loss 0.02396143 - samples/sec: 73.11 - lr: 0.100000 2022-11-01 15:10:59,460 epoch 52 - iter 243/274 - loss 0.02381229 - samples/sec: 70.87 - lr: 0.100000 2022-11-01 15:11:12,304 epoch 52 - iter 270/274 - loss 0.02388624 - samples/sec: 67.28 - lr: 0.100000 2022-11-01 15:11:13,703 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:11:13,703 EPOCH 52 done: loss 0.0240 - lr 0.100000 2022-11-01 15:11:38,949 Evaluating as a multi-label problem: False 2022-11-01 15:11:38,965 TEST : loss 0.02899007685482502 - f1-score (micro avg) 0.8496 2022-11-01 15:11:39,015 BAD EPOCHS (no improvement): 3 2022-11-01 15:11:39,107 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:11:50,967 epoch 53 - iter 27/274 - loss 0.02453654 - samples/sec: 72.87 - lr: 0.100000 2022-11-01 15:12:06,441 epoch 53 - iter 54/274 - loss 0.02250028 - samples/sec: 55.85 - lr: 0.100000 2022-11-01 15:12:18,855 epoch 53 - iter 81/274 - loss 0.02251377 - samples/sec: 69.62 - lr: 0.100000 2022-11-01 15:12:31,007 epoch 53 - iter 108/274 - loss 0.02219599 - samples/sec: 71.12 - lr: 0.100000 2022-11-01 15:12:43,529 epoch 53 - iter 135/274 - loss 0.02197082 - samples/sec: 69.02 - lr: 0.100000 2022-11-01 15:12:55,036 epoch 53 - iter 162/274 - loss 0.02234258 - samples/sec: 75.11 - lr: 0.100000 2022-11-01 15:13:06,569 epoch 53 - iter 189/274 - loss 0.02253575 - samples/sec: 74.94 - lr: 0.100000 2022-11-01 15:13:17,608 epoch 53 - iter 216/274 - loss 0.02244875 - samples/sec: 78.29 - lr: 0.100000 2022-11-01 15:13:30,157 epoch 53 - iter 243/274 - loss 0.02246492 - samples/sec: 68.87 - lr: 0.100000 2022-11-01 15:13:43,481 epoch 53 - iter 270/274 - loss 0.02199013 - samples/sec: 64.86 - lr: 0.100000 2022-11-01 15:13:45,316 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:13:45,317 EPOCH 53 done: loss 0.0219 - lr 0.100000 2022-11-01 15:14:10,521 Evaluating as a multi-label problem: False 2022-11-01 15:14:10,536 TEST : loss 0.031025480479002 - f1-score (micro avg) 0.8497 2022-11-01 15:14:10,589 BAD EPOCHS (no improvement): 0 2022-11-01 15:14:10,684 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:14:23,106 epoch 54 - iter 27/274 - loss 0.02366044 - samples/sec: 69.58 - lr: 0.100000 2022-11-01 15:14:35,723 epoch 54 - iter 54/274 - loss 0.02131955 - samples/sec: 68.50 - lr: 0.100000 2022-11-01 15:14:47,667 epoch 54 - iter 81/274 - loss 0.02241648 - samples/sec: 72.36 - lr: 0.100000 2022-11-01 15:15:01,117 epoch 54 - iter 108/274 - loss 0.02264243 - samples/sec: 64.25 - lr: 0.100000 2022-11-01 15:15:13,721 epoch 54 - iter 135/274 - loss 0.02298791 - samples/sec: 68.57 - lr: 0.100000 2022-11-01 15:15:25,955 epoch 54 - iter 162/274 - loss 0.02242851 - samples/sec: 70.64 - lr: 0.100000 2022-11-01 15:15:38,384 epoch 54 - iter 189/274 - loss 0.02235910 - samples/sec: 69.54 - lr: 0.100000 2022-11-01 15:15:50,640 epoch 54 - iter 216/274 - loss 0.02201195 - samples/sec: 70.51 - lr: 0.100000 2022-11-01 15:16:03,803 epoch 54 - iter 243/274 - loss 0.02225472 - samples/sec: 65.66 - lr: 0.100000 2022-11-01 15:16:15,823 epoch 54 - iter 270/274 - loss 0.02218903 - samples/sec: 71.90 - lr: 0.100000 2022-11-01 15:16:17,612 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:16:17,612 EPOCH 54 done: loss 0.0222 - lr 0.100000 2022-11-01 15:16:42,914 Evaluating as a multi-label problem: False 2022-11-01 15:16:42,930 TEST : loss 0.030233900994062424 - f1-score (micro avg) 0.8454 2022-11-01 15:16:42,983 BAD EPOCHS (no improvement): 1 2022-11-01 15:16:43,079 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:16:55,349 epoch 55 - iter 27/274 - loss 0.02055602 - samples/sec: 70.44 - lr: 0.100000 2022-11-01 15:17:08,468 epoch 55 - iter 54/274 - loss 0.01923870 - samples/sec: 65.88 - lr: 0.100000 2022-11-01 15:17:23,027 epoch 55 - iter 81/274 - loss 0.02096547 - samples/sec: 59.36 - lr: 0.100000 2022-11-01 15:17:34,938 epoch 55 - iter 108/274 - loss 0.02099036 - samples/sec: 72.56 - lr: 0.100000 2022-11-01 15:17:47,602 epoch 55 - iter 135/274 - loss 0.02078503 - samples/sec: 68.24 - lr: 0.100000 2022-11-01 15:17:59,080 epoch 55 - iter 162/274 - loss 0.02148538 - samples/sec: 75.30 - lr: 0.100000 2022-11-01 15:18:11,657 epoch 55 - iter 189/274 - loss 0.02214461 - samples/sec: 68.71 - lr: 0.100000 2022-11-01 15:18:23,508 epoch 55 - iter 216/274 - loss 0.02190890 - samples/sec: 72.93 - lr: 0.100000 2022-11-01 15:18:36,762 epoch 55 - iter 243/274 - loss 0.02249219 - samples/sec: 65.20 - lr: 0.100000 2022-11-01 15:18:48,843 epoch 55 - iter 270/274 - loss 0.02234599 - samples/sec: 71.54 - lr: 0.100000 2022-11-01 15:18:50,379 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:18:50,379 EPOCH 55 done: loss 0.0224 - lr 0.100000 2022-11-01 15:19:15,651 Evaluating as a multi-label problem: False 2022-11-01 15:19:15,666 TEST : loss 0.02768951654434204 - f1-score (micro avg) 0.856 2022-11-01 15:19:15,719 BAD EPOCHS (no improvement): 2 2022-11-01 15:19:15,811 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:19:28,337 epoch 56 - iter 27/274 - loss 0.01954876 - samples/sec: 69.00 - lr: 0.100000 2022-11-01 15:19:40,046 epoch 56 - iter 54/274 - loss 0.02032311 - samples/sec: 73.81 - lr: 0.100000 2022-11-01 15:19:52,765 epoch 56 - iter 81/274 - loss 0.02087417 - samples/sec: 67.95 - lr: 0.100000 2022-11-01 15:20:04,834 epoch 56 - iter 108/274 - loss 0.02048386 - samples/sec: 71.61 - lr: 0.100000 2022-11-01 15:20:17,273 epoch 56 - iter 135/274 - loss 0.02064770 - samples/sec: 69.47 - lr: 0.100000 2022-11-01 15:20:28,798 epoch 56 - iter 162/274 - loss 0.02112385 - samples/sec: 74.99 - lr: 0.100000 2022-11-01 15:20:40,648 epoch 56 - iter 189/274 - loss 0.02075702 - samples/sec: 72.93 - lr: 0.100000 2022-11-01 15:20:53,632 epoch 56 - iter 216/274 - loss 0.02239268 - samples/sec: 66.56 - lr: 0.100000 2022-11-01 15:21:06,045 epoch 56 - iter 243/274 - loss 0.02240334 - samples/sec: 69.62 - lr: 0.100000 2022-11-01 15:21:18,551 epoch 56 - iter 270/274 - loss 0.02264396 - samples/sec: 69.11 - lr: 0.100000 2022-11-01 15:21:19,946 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:21:19,946 EPOCH 56 done: loss 0.0228 - lr 0.100000 2022-11-01 15:21:45,321 Evaluating as a multi-label problem: False 2022-11-01 15:21:45,337 TEST : loss 0.0304726455360651 - f1-score (micro avg) 0.8554 2022-11-01 15:21:45,388 BAD EPOCHS (no improvement): 3 2022-11-01 15:21:45,480 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:21:59,285 epoch 57 - iter 27/274 - loss 0.01858226 - samples/sec: 62.60 - lr: 0.100000 2022-11-01 15:22:12,050 epoch 57 - iter 54/274 - loss 0.02101951 - samples/sec: 67.70 - lr: 0.100000 2022-11-01 15:22:23,465 epoch 57 - iter 81/274 - loss 0.02165109 - samples/sec: 75.71 - lr: 0.100000 2022-11-01 15:22:37,035 epoch 57 - iter 108/274 - loss 0.02113920 - samples/sec: 63.68 - lr: 0.100000 2022-11-01 15:22:49,205 epoch 57 - iter 135/274 - loss 0.02123264 - samples/sec: 71.01 - lr: 0.100000 2022-11-01 15:23:01,492 epoch 57 - iter 162/274 - loss 0.02134561 - samples/sec: 70.34 - lr: 0.100000 2022-11-01 15:23:12,834 epoch 57 - iter 189/274 - loss 0.02164682 - samples/sec: 76.20 - lr: 0.100000 2022-11-01 15:23:25,219 epoch 57 - iter 216/274 - loss 0.02181912 - samples/sec: 69.78 - lr: 0.100000 2022-11-01 15:23:37,457 epoch 57 - iter 243/274 - loss 0.02190306 - samples/sec: 70.62 - lr: 0.100000 2022-11-01 15:23:49,705 epoch 57 - iter 270/274 - loss 0.02153457 - samples/sec: 70.56 - lr: 0.100000 2022-11-01 15:23:51,568 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:23:51,569 EPOCH 57 done: loss 0.0218 - lr 0.100000 2022-11-01 15:24:16,774 Evaluating as a multi-label problem: False 2022-11-01 15:24:16,790 TEST : loss 0.029483051970601082 - f1-score (micro avg) 0.851 2022-11-01 15:24:16,842 BAD EPOCHS (no improvement): 0 2022-11-01 15:24:16,934 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:24:27,696 epoch 58 - iter 27/274 - loss 0.01840180 - samples/sec: 80.31 - lr: 0.100000 2022-11-01 15:24:40,903 epoch 58 - iter 54/274 - loss 0.01832122 - samples/sec: 65.43 - lr: 0.100000 2022-11-01 15:24:53,761 epoch 58 - iter 81/274 - loss 0.02185904 - samples/sec: 67.21 - lr: 0.100000 2022-11-01 15:25:06,320 epoch 58 - iter 108/274 - loss 0.02212350 - samples/sec: 68.81 - lr: 0.100000 2022-11-01 15:25:17,127 epoch 58 - iter 135/274 - loss 0.02206877 - samples/sec: 79.97 - lr: 0.100000 2022-11-01 15:25:28,855 epoch 58 - iter 162/274 - loss 0.02272453 - samples/sec: 73.69 - lr: 0.100000 2022-11-01 15:25:42,309 epoch 58 - iter 189/274 - loss 0.02193286 - samples/sec: 64.23 - lr: 0.100000 2022-11-01 15:25:56,457 epoch 58 - iter 216/274 - loss 0.02243499 - samples/sec: 61.08 - lr: 0.100000 2022-11-01 15:26:08,686 epoch 58 - iter 243/274 - loss 0.02276000 - samples/sec: 70.67 - lr: 0.100000 2022-11-01 15:26:21,274 epoch 58 - iter 270/274 - loss 0.02265005 - samples/sec: 68.65 - lr: 0.100000 2022-11-01 15:26:22,976 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:26:22,976 EPOCH 58 done: loss 0.0227 - lr 0.100000 2022-11-01 15:26:48,369 Evaluating as a multi-label problem: False 2022-11-01 15:26:48,384 TEST : loss 0.03021113947033882 - f1-score (micro avg) 0.8549 2022-11-01 15:26:48,438 BAD EPOCHS (no improvement): 1 2022-11-01 15:26:48,531 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:26:59,892 epoch 59 - iter 27/274 - loss 0.02035532 - samples/sec: 76.07 - lr: 0.100000 2022-11-01 15:27:11,943 epoch 59 - iter 54/274 - loss 0.02086338 - samples/sec: 71.71 - lr: 0.100000 2022-11-01 15:27:25,608 epoch 59 - iter 81/274 - loss 0.02163636 - samples/sec: 63.24 - lr: 0.100000 2022-11-01 15:27:37,361 epoch 59 - iter 108/274 - loss 0.02209525 - samples/sec: 73.53 - lr: 0.100000 2022-11-01 15:27:50,299 epoch 59 - iter 135/274 - loss 0.02206673 - samples/sec: 66.80 - lr: 0.100000 2022-11-01 15:28:03,802 epoch 59 - iter 162/274 - loss 0.02266218 - samples/sec: 64.00 - lr: 0.100000 2022-11-01 15:28:17,186 epoch 59 - iter 189/274 - loss 0.02225368 - samples/sec: 64.57 - lr: 0.100000 2022-11-01 15:28:28,801 epoch 59 - iter 216/274 - loss 0.02210266 - samples/sec: 74.40 - lr: 0.100000 2022-11-01 15:28:41,114 epoch 59 - iter 243/274 - loss 0.02192757 - samples/sec: 70.19 - lr: 0.100000 2022-11-01 15:28:53,424 epoch 59 - iter 270/274 - loss 0.02161121 - samples/sec: 70.20 - lr: 0.100000 2022-11-01 15:28:54,871 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:28:54,871 EPOCH 59 done: loss 0.0217 - lr 0.100000 2022-11-01 15:29:20,109 Evaluating as a multi-label problem: False 2022-11-01 15:29:20,124 TEST : loss 0.03019784763455391 - f1-score (micro avg) 0.8518 2022-11-01 15:29:20,177 BAD EPOCHS (no improvement): 0 2022-11-01 15:29:20,268 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:29:33,582 epoch 60 - iter 27/274 - loss 0.02266229 - samples/sec: 64.91 - lr: 0.100000 2022-11-01 15:29:44,822 epoch 60 - iter 54/274 - loss 0.02097862 - samples/sec: 76.89 - lr: 0.100000 2022-11-01 15:29:58,299 epoch 60 - iter 81/274 - loss 0.02103717 - samples/sec: 64.12 - lr: 0.100000 2022-11-01 15:30:10,428 epoch 60 - iter 108/274 - loss 0.02157194 - samples/sec: 71.25 - lr: 0.100000 2022-11-01 15:30:23,316 epoch 60 - iter 135/274 - loss 0.02176278 - samples/sec: 67.06 - lr: 0.100000 2022-11-01 15:30:35,025 epoch 60 - iter 162/274 - loss 0.02124505 - samples/sec: 73.81 - lr: 0.100000 2022-11-01 15:30:47,845 epoch 60 - iter 189/274 - loss 0.02133995 - samples/sec: 67.41 - lr: 0.100000 2022-11-01 15:31:00,017 epoch 60 - iter 216/274 - loss 0.02152520 - samples/sec: 71.00 - lr: 0.100000 2022-11-01 15:31:12,827 epoch 60 - iter 243/274 - loss 0.02134036 - samples/sec: 67.46 - lr: 0.100000 2022-11-01 15:31:24,440 epoch 60 - iter 270/274 - loss 0.02164276 - samples/sec: 74.42 - lr: 0.100000 2022-11-01 15:31:25,992 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:31:25,992 EPOCH 60 done: loss 0.0216 - lr 0.100000 2022-11-01 15:31:51,314 Evaluating as a multi-label problem: False 2022-11-01 15:31:51,329 TEST : loss 0.030309708788990974 - f1-score (micro avg) 0.8446 2022-11-01 15:31:51,382 BAD EPOCHS (no improvement): 0 2022-11-01 15:31:51,474 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:32:04,475 epoch 61 - iter 27/274 - loss 0.02131620 - samples/sec: 66.48 - lr: 0.100000 2022-11-01 15:32:16,775 epoch 61 - iter 54/274 - loss 0.01755958 - samples/sec: 70.26 - lr: 0.100000 2022-11-01 15:32:29,944 epoch 61 - iter 81/274 - loss 0.01785219 - samples/sec: 65.63 - lr: 0.100000 2022-11-01 15:32:42,291 epoch 61 - iter 108/274 - loss 0.01927462 - samples/sec: 69.99 - lr: 0.100000 2022-11-01 15:32:53,782 epoch 61 - iter 135/274 - loss 0.01932511 - samples/sec: 75.21 - lr: 0.100000 2022-11-01 15:33:05,138 epoch 61 - iter 162/274 - loss 0.02022663 - samples/sec: 76.10 - lr: 0.100000 2022-11-01 15:33:18,348 epoch 61 - iter 189/274 - loss 0.02152986 - samples/sec: 65.42 - lr: 0.100000 2022-11-01 15:33:30,173 epoch 61 - iter 216/274 - loss 0.02153104 - samples/sec: 73.08 - lr: 0.100000 2022-11-01 15:33:42,662 epoch 61 - iter 243/274 - loss 0.02155148 - samples/sec: 69.20 - lr: 0.100000 2022-11-01 15:33:54,579 epoch 61 - iter 270/274 - loss 0.02144034 - samples/sec: 72.53 - lr: 0.100000 2022-11-01 15:33:56,381 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:33:56,381 EPOCH 61 done: loss 0.0215 - lr 0.100000 2022-11-01 15:34:21,677 Evaluating as a multi-label problem: False 2022-11-01 15:34:21,693 TEST : loss 0.028495075181126595 - f1-score (micro avg) 0.8491 2022-11-01 15:34:21,745 BAD EPOCHS (no improvement): 0 2022-11-01 15:34:21,837 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:34:34,938 epoch 62 - iter 27/274 - loss 0.01744152 - samples/sec: 65.97 - lr: 0.100000 2022-11-01 15:34:47,972 epoch 62 - iter 54/274 - loss 0.02095425 - samples/sec: 66.30 - lr: 0.100000 2022-11-01 15:35:00,121 epoch 62 - iter 81/274 - loss 0.02182806 - samples/sec: 71.14 - lr: 0.100000 2022-11-01 15:35:12,065 epoch 62 - iter 108/274 - loss 0.02200592 - samples/sec: 72.36 - lr: 0.100000 2022-11-01 15:35:24,838 epoch 62 - iter 135/274 - loss 0.02188164 - samples/sec: 67.66 - lr: 0.100000 2022-11-01 15:35:36,484 epoch 62 - iter 162/274 - loss 0.02140413 - samples/sec: 74.21 - lr: 0.100000 2022-11-01 15:35:49,425 epoch 62 - iter 189/274 - loss 0.02147430 - samples/sec: 66.78 - lr: 0.100000 2022-11-01 15:36:01,416 epoch 62 - iter 216/274 - loss 0.02079022 - samples/sec: 72.07 - lr: 0.100000 2022-11-01 15:36:14,073 epoch 62 - iter 243/274 - loss 0.02100848 - samples/sec: 68.28 - lr: 0.100000 2022-11-01 15:36:25,958 epoch 62 - iter 270/274 - loss 0.02117302 - samples/sec: 72.71 - lr: 0.100000 2022-11-01 15:36:27,489 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:36:27,489 EPOCH 62 done: loss 0.0211 - lr 0.100000 2022-11-01 15:36:52,787 Evaluating as a multi-label problem: False 2022-11-01 15:36:52,803 TEST : loss 0.03227972984313965 - f1-score (micro avg) 0.8455 2022-11-01 15:36:52,856 BAD EPOCHS (no improvement): 0 2022-11-01 15:36:52,948 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:37:04,831 epoch 63 - iter 27/274 - loss 0.02126119 - samples/sec: 72.73 - lr: 0.100000 2022-11-01 15:37:18,535 epoch 63 - iter 54/274 - loss 0.01942961 - samples/sec: 63.06 - lr: 0.100000 2022-11-01 15:37:31,254 epoch 63 - iter 81/274 - loss 0.02012420 - samples/sec: 67.94 - lr: 0.100000 2022-11-01 15:37:42,705 epoch 63 - iter 108/274 - loss 0.02029080 - samples/sec: 75.48 - lr: 0.100000 2022-11-01 15:37:55,699 epoch 63 - iter 135/274 - loss 0.02042011 - samples/sec: 66.51 - lr: 0.100000 2022-11-01 15:38:08,123 epoch 63 - iter 162/274 - loss 0.02065848 - samples/sec: 69.56 - lr: 0.100000 2022-11-01 15:38:19,533 epoch 63 - iter 189/274 - loss 0.02095013 - samples/sec: 75.74 - lr: 0.100000 2022-11-01 15:38:33,075 epoch 63 - iter 216/274 - loss 0.02097885 - samples/sec: 63.82 - lr: 0.100000 2022-11-01 15:38:45,108 epoch 63 - iter 243/274 - loss 0.02113682 - samples/sec: 71.82 - lr: 0.100000 2022-11-01 15:38:57,147 epoch 63 - iter 270/274 - loss 0.02136165 - samples/sec: 71.79 - lr: 0.100000 2022-11-01 15:38:58,754 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:38:58,754 EPOCH 63 done: loss 0.0214 - lr 0.100000 2022-11-01 15:39:24,602 Evaluating as a multi-label problem: False 2022-11-01 15:39:24,617 TEST : loss 0.029485132545232773 - f1-score (micro avg) 0.8442 2022-11-01 15:39:24,671 BAD EPOCHS (no improvement): 1 2022-11-01 15:39:24,745 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:39:35,637 epoch 64 - iter 27/274 - loss 0.01890757 - samples/sec: 79.35 - lr: 0.100000 2022-11-01 15:39:49,308 epoch 64 - iter 54/274 - loss 0.01938230 - samples/sec: 63.21 - lr: 0.100000 2022-11-01 15:40:02,928 epoch 64 - iter 81/274 - loss 0.02217057 - samples/sec: 63.45 - lr: 0.100000 2022-11-01 15:40:15,391 epoch 64 - iter 108/274 - loss 0.02165389 - samples/sec: 69.34 - lr: 0.100000 2022-11-01 15:40:26,951 epoch 64 - iter 135/274 - loss 0.02168174 - samples/sec: 74.76 - lr: 0.100000 2022-11-01 15:40:38,848 epoch 64 - iter 162/274 - loss 0.02134826 - samples/sec: 72.64 - lr: 0.100000 2022-11-01 15:40:50,875 epoch 64 - iter 189/274 - loss 0.02080389 - samples/sec: 71.86 - lr: 0.100000 2022-11-01 15:41:03,888 epoch 64 - iter 216/274 - loss 0.02074878 - samples/sec: 66.41 - lr: 0.100000 2022-11-01 15:41:16,800 epoch 64 - iter 243/274 - loss 0.02043543 - samples/sec: 66.93 - lr: 0.100000 2022-11-01 15:41:29,886 epoch 64 - iter 270/274 - loss 0.02087130 - samples/sec: 66.04 - lr: 0.100000 2022-11-01 15:41:31,399 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:41:31,399 EPOCH 64 done: loss 0.0209 - lr 0.100000 2022-11-01 15:41:56,819 Evaluating as a multi-label problem: False 2022-11-01 15:41:56,835 TEST : loss 0.030096804723143578 - f1-score (micro avg) 0.8446 2022-11-01 15:41:56,887 BAD EPOCHS (no improvement): 0 2022-11-01 15:41:56,980 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:42:11,007 epoch 65 - iter 27/274 - loss 0.02540958 - samples/sec: 61.61 - lr: 0.100000 2022-11-01 15:42:23,241 epoch 65 - iter 54/274 - loss 0.02236285 - samples/sec: 70.64 - lr: 0.100000 2022-11-01 15:42:35,599 epoch 65 - iter 81/274 - loss 0.02219879 - samples/sec: 69.93 - lr: 0.100000 2022-11-01 15:42:47,630 epoch 65 - iter 108/274 - loss 0.02127425 - samples/sec: 71.83 - lr: 0.100000 2022-11-01 15:43:00,252 epoch 65 - iter 135/274 - loss 0.02210803 - samples/sec: 68.47 - lr: 0.100000 2022-11-01 15:43:12,079 epoch 65 - iter 162/274 - loss 0.02161108 - samples/sec: 73.07 - lr: 0.100000 2022-11-01 15:43:23,801 epoch 65 - iter 189/274 - loss 0.02206507 - samples/sec: 73.73 - lr: 0.100000 2022-11-01 15:43:34,832 epoch 65 - iter 216/274 - loss 0.02203354 - samples/sec: 78.35 - lr: 0.100000 2022-11-01 15:43:47,550 epoch 65 - iter 243/274 - loss 0.02200313 - samples/sec: 67.95 - lr: 0.100000 2022-11-01 15:44:00,620 epoch 65 - iter 270/274 - loss 0.02150743 - samples/sec: 66.12 - lr: 0.100000 2022-11-01 15:44:02,372 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:44:02,372 EPOCH 65 done: loss 0.0214 - lr 0.100000 2022-11-01 15:44:28,137 Evaluating as a multi-label problem: False 2022-11-01 15:44:28,153 TEST : loss 0.02994183637201786 - f1-score (micro avg) 0.8534 2022-11-01 15:44:28,205 BAD EPOCHS (no improvement): 1 2022-11-01 15:44:28,291 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:44:40,467 epoch 66 - iter 27/274 - loss 0.01805836 - samples/sec: 70.98 - lr: 0.100000 2022-11-01 15:44:53,328 epoch 66 - iter 54/274 - loss 0.01872092 - samples/sec: 67.20 - lr: 0.100000 2022-11-01 15:45:06,350 epoch 66 - iter 81/274 - loss 0.02087662 - samples/sec: 66.37 - lr: 0.100000 2022-11-01 15:45:17,576 epoch 66 - iter 108/274 - loss 0.02057641 - samples/sec: 76.99 - lr: 0.100000 2022-11-01 15:45:29,056 epoch 66 - iter 135/274 - loss 0.01985161 - samples/sec: 75.28 - lr: 0.100000 2022-11-01 15:45:42,760 epoch 66 - iter 162/274 - loss 0.02047046 - samples/sec: 63.06 - lr: 0.100000 2022-11-01 15:45:56,009 epoch 66 - iter 189/274 - loss 0.02016785 - samples/sec: 65.23 - lr: 0.100000 2022-11-01 15:46:07,489 epoch 66 - iter 216/274 - loss 0.02021241 - samples/sec: 75.28 - lr: 0.100000 2022-11-01 15:46:19,392 epoch 66 - iter 243/274 - loss 0.02018700 - samples/sec: 72.61 - lr: 0.100000 2022-11-01 15:46:32,830 epoch 66 - iter 270/274 - loss 0.02057448 - samples/sec: 64.31 - lr: 0.100000 2022-11-01 15:46:34,491 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:46:34,491 EPOCH 66 done: loss 0.0205 - lr 0.100000 2022-11-01 15:46:59,926 Evaluating as a multi-label problem: False 2022-11-01 15:46:59,942 TEST : loss 0.02977355383336544 - f1-score (micro avg) 0.8492 2022-11-01 15:46:59,994 BAD EPOCHS (no improvement): 0 2022-11-01 15:47:00,080 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:47:12,481 epoch 67 - iter 27/274 - loss 0.02224031 - samples/sec: 69.69 - lr: 0.100000 2022-11-01 15:47:26,274 epoch 67 - iter 54/274 - loss 0.01948851 - samples/sec: 62.66 - lr: 0.100000 2022-11-01 15:47:37,830 epoch 67 - iter 81/274 - loss 0.02039320 - samples/sec: 74.79 - lr: 0.100000 2022-11-01 15:47:49,569 epoch 67 - iter 108/274 - loss 0.02151655 - samples/sec: 73.62 - lr: 0.100000 2022-11-01 15:48:01,705 epoch 67 - iter 135/274 - loss 0.02094293 - samples/sec: 71.21 - lr: 0.100000 2022-11-01 15:48:14,965 epoch 67 - iter 162/274 - loss 0.02077230 - samples/sec: 65.18 - lr: 0.100000 2022-11-01 15:48:27,654 epoch 67 - iter 189/274 - loss 0.02084305 - samples/sec: 68.11 - lr: 0.100000 2022-11-01 15:48:39,855 epoch 67 - iter 216/274 - loss 0.02079591 - samples/sec: 70.83 - lr: 0.100000 2022-11-01 15:48:51,410 epoch 67 - iter 243/274 - loss 0.02046085 - samples/sec: 74.80 - lr: 0.100000 2022-11-01 15:49:05,305 epoch 67 - iter 270/274 - loss 0.02023832 - samples/sec: 62.19 - lr: 0.100000 2022-11-01 15:49:07,162 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:49:07,162 EPOCH 67 done: loss 0.0203 - lr 0.100000 2022-11-01 15:49:32,558 Evaluating as a multi-label problem: False 2022-11-01 15:49:32,574 TEST : loss 0.030972706153988838 - f1-score (micro avg) 0.8543 2022-11-01 15:49:32,627 BAD EPOCHS (no improvement): 0 2022-11-01 15:49:32,723 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:49:46,088 epoch 68 - iter 27/274 - loss 0.02133801 - samples/sec: 64.67 - lr: 0.100000 2022-11-01 15:49:58,017 epoch 68 - iter 54/274 - loss 0.02034460 - samples/sec: 72.45 - lr: 0.100000 2022-11-01 15:50:11,523 epoch 68 - iter 81/274 - loss 0.02022263 - samples/sec: 63.98 - lr: 0.100000 2022-11-01 15:50:24,462 epoch 68 - iter 108/274 - loss 0.02108536 - samples/sec: 66.79 - lr: 0.100000 2022-11-01 15:50:37,223 epoch 68 - iter 135/274 - loss 0.02035431 - samples/sec: 67.73 - lr: 0.100000 2022-11-01 15:50:49,548 epoch 68 - iter 162/274 - loss 0.02128033 - samples/sec: 70.12 - lr: 0.100000 2022-11-01 15:51:01,472 epoch 68 - iter 189/274 - loss 0.02080314 - samples/sec: 72.48 - lr: 0.100000 2022-11-01 15:51:13,417 epoch 68 - iter 216/274 - loss 0.02127075 - samples/sec: 72.35 - lr: 0.100000 2022-11-01 15:51:25,660 epoch 68 - iter 243/274 - loss 0.02066568 - samples/sec: 70.59 - lr: 0.100000 2022-11-01 15:51:37,327 epoch 68 - iter 270/274 - loss 0.02080117 - samples/sec: 74.07 - lr: 0.100000 2022-11-01 15:51:38,889 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:51:38,889 EPOCH 68 done: loss 0.0208 - lr 0.100000 2022-11-01 15:52:04,255 Evaluating as a multi-label problem: False 2022-11-01 15:52:04,271 TEST : loss 0.030792292207479477 - f1-score (micro avg) 0.8528 2022-11-01 15:52:04,323 BAD EPOCHS (no improvement): 1 2022-11-01 15:52:04,414 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:52:16,801 epoch 69 - iter 27/274 - loss 0.02075958 - samples/sec: 69.77 - lr: 0.100000 2022-11-01 15:52:28,377 epoch 69 - iter 54/274 - loss 0.02100983 - samples/sec: 74.66 - lr: 0.100000 2022-11-01 15:52:40,744 epoch 69 - iter 81/274 - loss 0.01987977 - samples/sec: 69.88 - lr: 0.100000 2022-11-01 15:52:52,969 epoch 69 - iter 108/274 - loss 0.01993851 - samples/sec: 70.70 - lr: 0.100000 2022-11-01 15:53:04,669 epoch 69 - iter 135/274 - loss 0.01973035 - samples/sec: 73.87 - lr: 0.100000 2022-11-01 15:53:16,071 epoch 69 - iter 162/274 - loss 0.01921936 - samples/sec: 75.80 - lr: 0.100000 2022-11-01 15:53:27,126 epoch 69 - iter 189/274 - loss 0.01975087 - samples/sec: 78.17 - lr: 0.100000 2022-11-01 15:53:39,655 epoch 69 - iter 216/274 - loss 0.02017193 - samples/sec: 68.98 - lr: 0.100000 2022-11-01 15:53:53,330 epoch 69 - iter 243/274 - loss 0.01998366 - samples/sec: 63.19 - lr: 0.100000 2022-11-01 15:54:06,348 epoch 69 - iter 270/274 - loss 0.01994459 - samples/sec: 66.39 - lr: 0.100000 2022-11-01 15:54:08,088 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:54:08,088 EPOCH 69 done: loss 0.0199 - lr 0.100000 2022-11-01 15:54:33,789 Evaluating as a multi-label problem: False 2022-11-01 15:54:33,804 TEST : loss 0.031563375145196915 - f1-score (micro avg) 0.8505 2022-11-01 15:54:33,856 BAD EPOCHS (no improvement): 0 2022-11-01 15:54:33,947 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:54:47,227 epoch 70 - iter 27/274 - loss 0.01858086 - samples/sec: 65.08 - lr: 0.100000 2022-11-01 15:54:58,681 epoch 70 - iter 54/274 - loss 0.01935509 - samples/sec: 75.45 - lr: 0.100000 2022-11-01 15:55:10,707 epoch 70 - iter 81/274 - loss 0.01941681 - samples/sec: 71.87 - lr: 0.100000 2022-11-01 15:55:24,092 epoch 70 - iter 108/274 - loss 0.02029023 - samples/sec: 64.56 - lr: 0.100000 2022-11-01 15:55:36,306 epoch 70 - iter 135/274 - loss 0.02080017 - samples/sec: 70.76 - lr: 0.100000 2022-11-01 15:55:48,483 epoch 70 - iter 162/274 - loss 0.02105265 - samples/sec: 70.97 - lr: 0.100000 2022-11-01 15:56:01,367 epoch 70 - iter 189/274 - loss 0.02042653 - samples/sec: 67.08 - lr: 0.100000 2022-11-01 15:56:13,179 epoch 70 - iter 216/274 - loss 0.02107873 - samples/sec: 73.17 - lr: 0.100000 2022-11-01 15:56:26,980 epoch 70 - iter 243/274 - loss 0.02108922 - samples/sec: 62.62 - lr: 0.100000 2022-11-01 15:56:40,787 epoch 70 - iter 270/274 - loss 0.02127791 - samples/sec: 62.59 - lr: 0.100000 2022-11-01 15:56:42,391 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:56:42,391 EPOCH 70 done: loss 0.0212 - lr 0.100000 2022-11-01 15:57:07,366 Evaluating as a multi-label problem: False 2022-11-01 15:57:07,382 TEST : loss 0.03166978433728218 - f1-score (micro avg) 0.8539 2022-11-01 15:57:07,435 BAD EPOCHS (no improvement): 1 2022-11-01 15:57:07,525 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:57:18,588 epoch 71 - iter 27/274 - loss 0.02212426 - samples/sec: 78.12 - lr: 0.100000 2022-11-01 15:57:30,305 epoch 71 - iter 54/274 - loss 0.02025799 - samples/sec: 73.76 - lr: 0.100000 2022-11-01 15:57:42,033 epoch 71 - iter 81/274 - loss 0.02065372 - samples/sec: 73.69 - lr: 0.100000 2022-11-01 15:57:54,142 epoch 71 - iter 108/274 - loss 0.02128302 - samples/sec: 71.37 - lr: 0.100000 2022-11-01 15:58:07,073 epoch 71 - iter 135/274 - loss 0.02181676 - samples/sec: 66.83 - lr: 0.100000 2022-11-01 15:58:20,111 epoch 71 - iter 162/274 - loss 0.02132020 - samples/sec: 66.28 - lr: 0.100000 2022-11-01 15:58:32,485 epoch 71 - iter 189/274 - loss 0.02050799 - samples/sec: 69.84 - lr: 0.100000 2022-11-01 15:58:43,824 epoch 71 - iter 216/274 - loss 0.01992917 - samples/sec: 76.22 - lr: 0.100000 2022-11-01 15:58:56,979 epoch 71 - iter 243/274 - loss 0.02030662 - samples/sec: 65.69 - lr: 0.100000 2022-11-01 15:59:09,144 epoch 71 - iter 270/274 - loss 0.02021591 - samples/sec: 71.04 - lr: 0.100000 2022-11-01 15:59:11,568 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:59:11,568 EPOCH 71 done: loss 0.0204 - lr 0.100000 2022-11-01 15:59:37,390 Evaluating as a multi-label problem: False 2022-11-01 15:59:37,406 TEST : loss 0.03054458275437355 - f1-score (micro avg) 0.854 2022-11-01 15:59:37,458 BAD EPOCHS (no improvement): 2 2022-11-01 15:59:37,554 ---------------------------------------------------------------------------------------------------- 2022-11-01 15:59:49,256 epoch 72 - iter 27/274 - loss 0.02002288 - samples/sec: 73.86 - lr: 0.100000 2022-11-01 16:00:01,291 epoch 72 - iter 54/274 - loss 0.01804290 - samples/sec: 71.81 - lr: 0.100000 2022-11-01 16:00:13,882 epoch 72 - iter 81/274 - loss 0.01876863 - samples/sec: 68.63 - lr: 0.100000 2022-11-01 16:00:25,965 epoch 72 - iter 108/274 - loss 0.01891240 - samples/sec: 71.53 - lr: 0.100000 2022-11-01 16:00:39,081 epoch 72 - iter 135/274 - loss 0.01882314 - samples/sec: 65.89 - lr: 0.100000 2022-11-01 16:00:51,215 epoch 72 - iter 162/274 - loss 0.01888338 - samples/sec: 71.23 - lr: 0.100000 2022-11-01 16:01:02,822 epoch 72 - iter 189/274 - loss 0.01859963 - samples/sec: 74.45 - lr: 0.100000 2022-11-01 16:01:15,001 epoch 72 - iter 216/274 - loss 0.01894609 - samples/sec: 70.96 - lr: 0.100000 2022-11-01 16:01:28,410 epoch 72 - iter 243/274 - loss 0.01937545 - samples/sec: 64.45 - lr: 0.100000 2022-11-01 16:01:42,428 epoch 72 - iter 270/274 - loss 0.02020000 - samples/sec: 61.65 - lr: 0.100000 2022-11-01 16:01:43,954 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:01:43,955 EPOCH 72 done: loss 0.0201 - lr 0.100000 2022-11-01 16:02:09,347 Evaluating as a multi-label problem: False 2022-11-01 16:02:09,363 TEST : loss 0.029515517875552177 - f1-score (micro avg) 0.8582 2022-11-01 16:02:09,415 BAD EPOCHS (no improvement): 3 2022-11-01 16:02:09,508 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:02:23,043 epoch 73 - iter 27/274 - loss 0.02220240 - samples/sec: 63.85 - lr: 0.100000 2022-11-01 16:02:34,503 epoch 73 - iter 54/274 - loss 0.02184526 - samples/sec: 75.42 - lr: 0.100000 2022-11-01 16:02:47,677 epoch 73 - iter 81/274 - loss 0.02129952 - samples/sec: 65.60 - lr: 0.100000 2022-11-01 16:03:00,508 epoch 73 - iter 108/274 - loss 0.02092159 - samples/sec: 67.35 - lr: 0.100000 2022-11-01 16:03:11,713 epoch 73 - iter 135/274 - loss 0.02135403 - samples/sec: 77.13 - lr: 0.100000 2022-11-01 16:03:23,418 epoch 73 - iter 162/274 - loss 0.02121899 - samples/sec: 73.84 - lr: 0.100000 2022-11-01 16:03:35,824 epoch 73 - iter 189/274 - loss 0.02072249 - samples/sec: 69.66 - lr: 0.100000 2022-11-01 16:03:48,819 epoch 73 - iter 216/274 - loss 0.02100808 - samples/sec: 66.50 - lr: 0.100000 2022-11-01 16:04:01,462 epoch 73 - iter 243/274 - loss 0.02116109 - samples/sec: 68.36 - lr: 0.100000 2022-11-01 16:04:14,781 epoch 73 - iter 270/274 - loss 0.02126688 - samples/sec: 64.88 - lr: 0.100000 2022-11-01 16:04:16,334 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:04:16,334 EPOCH 73 done: loss 0.0212 - lr 0.100000 2022-11-01 16:04:41,564 Evaluating as a multi-label problem: False 2022-11-01 16:04:41,579 TEST : loss 0.0294826440513134 - f1-score (micro avg) 0.8499 2022-11-01 16:04:41,631 Epoch 73: reducing learning rate of group 0 to 5.0000e-02. 2022-11-01 16:04:41,632 BAD EPOCHS (no improvement): 4 2022-11-01 16:04:41,723 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:04:54,382 epoch 74 - iter 27/274 - loss 0.01699297 - samples/sec: 68.27 - lr: 0.050000 2022-11-01 16:05:07,038 epoch 74 - iter 54/274 - loss 0.01847639 - samples/sec: 68.28 - lr: 0.050000 2022-11-01 16:05:18,943 epoch 74 - iter 81/274 - loss 0.01896710 - samples/sec: 72.59 - lr: 0.050000 2022-11-01 16:05:30,232 epoch 74 - iter 108/274 - loss 0.01856741 - samples/sec: 76.56 - lr: 0.050000 2022-11-01 16:05:42,326 epoch 74 - iter 135/274 - loss 0.01911050 - samples/sec: 71.46 - lr: 0.050000 2022-11-01 16:05:53,721 epoch 74 - iter 162/274 - loss 0.01893491 - samples/sec: 75.85 - lr: 0.050000 2022-11-01 16:06:05,986 epoch 74 - iter 189/274 - loss 0.01976027 - samples/sec: 70.47 - lr: 0.050000 2022-11-01 16:06:18,737 epoch 74 - iter 216/274 - loss 0.01995122 - samples/sec: 67.77 - lr: 0.050000 2022-11-01 16:06:31,727 epoch 74 - iter 243/274 - loss 0.01949284 - samples/sec: 66.53 - lr: 0.050000 2022-11-01 16:06:44,209 epoch 74 - iter 270/274 - loss 0.01943572 - samples/sec: 69.24 - lr: 0.050000 2022-11-01 16:06:46,178 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:06:46,179 EPOCH 74 done: loss 0.0194 - lr 0.050000 2022-11-01 16:07:11,505 Evaluating as a multi-label problem: False 2022-11-01 16:07:11,520 TEST : loss 0.030243773013353348 - f1-score (micro avg) 0.8508 2022-11-01 16:07:11,574 BAD EPOCHS (no improvement): 0 2022-11-01 16:07:11,666 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:07:24,777 epoch 75 - iter 27/274 - loss 0.01546676 - samples/sec: 65.92 - lr: 0.050000 2022-11-01 16:07:36,355 epoch 75 - iter 54/274 - loss 0.01834654 - samples/sec: 74.65 - lr: 0.050000 2022-11-01 16:07:48,021 epoch 75 - iter 81/274 - loss 0.01790446 - samples/sec: 74.08 - lr: 0.050000 2022-11-01 16:07:59,523 epoch 75 - iter 108/274 - loss 0.01785671 - samples/sec: 75.14 - lr: 0.050000 2022-11-01 16:08:12,431 epoch 75 - iter 135/274 - loss 0.01831446 - samples/sec: 66.95 - lr: 0.050000 2022-11-01 16:08:25,527 epoch 75 - iter 162/274 - loss 0.01826631 - samples/sec: 65.99 - lr: 0.050000 2022-11-01 16:08:37,958 epoch 75 - iter 189/274 - loss 0.01816669 - samples/sec: 69.52 - lr: 0.050000 2022-11-01 16:08:51,537 epoch 75 - iter 216/274 - loss 0.01861337 - samples/sec: 63.64 - lr: 0.050000 2022-11-01 16:09:03,481 epoch 75 - iter 243/274 - loss 0.01881745 - samples/sec: 72.36 - lr: 0.050000 2022-11-01 16:09:16,590 epoch 75 - iter 270/274 - loss 0.01870689 - samples/sec: 65.93 - lr: 0.050000 2022-11-01 16:09:18,295 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:09:18,295 EPOCH 75 done: loss 0.0188 - lr 0.050000 2022-11-01 16:09:43,737 Evaluating as a multi-label problem: False 2022-11-01 16:09:43,752 TEST : loss 0.02911132387816906 - f1-score (micro avg) 0.8527 2022-11-01 16:09:43,804 BAD EPOCHS (no improvement): 0 2022-11-01 16:09:43,895 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:09:56,178 epoch 76 - iter 27/274 - loss 0.01445317 - samples/sec: 70.36 - lr: 0.050000 2022-11-01 16:10:08,517 epoch 76 - iter 54/274 - loss 0.01648596 - samples/sec: 70.04 - lr: 0.050000 2022-11-01 16:10:20,368 epoch 76 - iter 81/274 - loss 0.01698888 - samples/sec: 72.93 - lr: 0.050000 2022-11-01 16:10:32,873 epoch 76 - iter 108/274 - loss 0.01756096 - samples/sec: 69.11 - lr: 0.050000 2022-11-01 16:10:46,907 epoch 76 - iter 135/274 - loss 0.01762281 - samples/sec: 61.58 - lr: 0.050000 2022-11-01 16:10:58,979 epoch 76 - iter 162/274 - loss 0.01732201 - samples/sec: 71.60 - lr: 0.050000 2022-11-01 16:11:11,759 epoch 76 - iter 189/274 - loss 0.01751176 - samples/sec: 67.62 - lr: 0.050000 2022-11-01 16:11:23,975 epoch 76 - iter 216/274 - loss 0.01766946 - samples/sec: 70.74 - lr: 0.050000 2022-11-01 16:11:35,773 epoch 76 - iter 243/274 - loss 0.01783327 - samples/sec: 73.25 - lr: 0.050000 2022-11-01 16:11:48,911 epoch 76 - iter 270/274 - loss 0.01793928 - samples/sec: 65.78 - lr: 0.050000 2022-11-01 16:11:50,891 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:11:50,892 EPOCH 76 done: loss 0.0180 - lr 0.050000 2022-11-01 16:12:16,332 Evaluating as a multi-label problem: False 2022-11-01 16:12:16,347 TEST : loss 0.02934643253684044 - f1-score (micro avg) 0.857 2022-11-01 16:12:16,399 BAD EPOCHS (no improvement): 0 2022-11-01 16:12:16,490 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:12:28,007 epoch 77 - iter 27/274 - loss 0.01524350 - samples/sec: 75.04 - lr: 0.050000 2022-11-01 16:12:40,880 epoch 77 - iter 54/274 - loss 0.01741012 - samples/sec: 67.14 - lr: 0.050000 2022-11-01 16:12:53,126 epoch 77 - iter 81/274 - loss 0.01776495 - samples/sec: 70.57 - lr: 0.050000 2022-11-01 16:13:04,214 epoch 77 - iter 108/274 - loss 0.01764313 - samples/sec: 77.95 - lr: 0.050000 2022-11-01 16:13:18,011 epoch 77 - iter 135/274 - loss 0.01765748 - samples/sec: 62.63 - lr: 0.050000 2022-11-01 16:13:29,621 epoch 77 - iter 162/274 - loss 0.01771770 - samples/sec: 74.44 - lr: 0.050000 2022-11-01 16:13:43,414 epoch 77 - iter 189/274 - loss 0.01796879 - samples/sec: 62.65 - lr: 0.050000 2022-11-01 16:13:54,588 epoch 77 - iter 216/274 - loss 0.01797517 - samples/sec: 77.35 - lr: 0.050000 2022-11-01 16:14:07,007 epoch 77 - iter 243/274 - loss 0.01790936 - samples/sec: 69.59 - lr: 0.050000 2022-11-01 16:14:20,191 epoch 77 - iter 270/274 - loss 0.01865935 - samples/sec: 65.55 - lr: 0.050000 2022-11-01 16:14:22,147 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:14:22,148 EPOCH 77 done: loss 0.0186 - lr 0.050000 2022-11-01 16:14:47,277 Evaluating as a multi-label problem: False 2022-11-01 16:14:47,293 TEST : loss 0.028807329013943672 - f1-score (micro avg) 0.8581 2022-11-01 16:14:47,347 BAD EPOCHS (no improvement): 1 2022-11-01 16:14:47,439 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:14:59,483 epoch 78 - iter 27/274 - loss 0.01491909 - samples/sec: 71.76 - lr: 0.050000 2022-11-01 16:15:11,094 epoch 78 - iter 54/274 - loss 0.01479802 - samples/sec: 74.43 - lr: 0.050000 2022-11-01 16:15:23,177 epoch 78 - iter 81/274 - loss 0.01800552 - samples/sec: 71.53 - lr: 0.050000 2022-11-01 16:15:35,961 epoch 78 - iter 108/274 - loss 0.01651022 - samples/sec: 67.60 - lr: 0.050000 2022-11-01 16:15:48,569 epoch 78 - iter 135/274 - loss 0.01727430 - samples/sec: 68.55 - lr: 0.050000 2022-11-01 16:16:02,945 epoch 78 - iter 162/274 - loss 0.01702202 - samples/sec: 60.12 - lr: 0.050000 2022-11-01 16:16:15,222 epoch 78 - iter 189/274 - loss 0.01711726 - samples/sec: 70.39 - lr: 0.050000 2022-11-01 16:16:27,068 epoch 78 - iter 216/274 - loss 0.01707427 - samples/sec: 72.95 - lr: 0.050000 2022-11-01 16:16:39,506 epoch 78 - iter 243/274 - loss 0.01700401 - samples/sec: 69.48 - lr: 0.050000 2022-11-01 16:16:52,570 epoch 78 - iter 270/274 - loss 0.01712211 - samples/sec: 66.15 - lr: 0.050000 2022-11-01 16:16:54,130 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:16:54,131 EPOCH 78 done: loss 0.0171 - lr 0.050000 2022-11-01 16:17:19,592 Evaluating as a multi-label problem: False 2022-11-01 16:17:19,608 TEST : loss 0.03133295476436615 - f1-score (micro avg) 0.8528 2022-11-01 16:17:19,662 BAD EPOCHS (no improvement): 0 2022-11-01 16:17:19,735 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:17:31,215 epoch 79 - iter 27/274 - loss 0.01593943 - samples/sec: 75.29 - lr: 0.050000 2022-11-01 16:17:43,239 epoch 79 - iter 54/274 - loss 0.01816389 - samples/sec: 71.87 - lr: 0.050000 2022-11-01 16:17:54,562 epoch 79 - iter 81/274 - loss 0.01802346 - samples/sec: 76.33 - lr: 0.050000 2022-11-01 16:18:07,895 epoch 79 - iter 108/274 - loss 0.01903539 - samples/sec: 64.82 - lr: 0.050000 2022-11-01 16:18:20,020 epoch 79 - iter 135/274 - loss 0.01855551 - samples/sec: 71.28 - lr: 0.050000 2022-11-01 16:18:33,472 epoch 79 - iter 162/274 - loss 0.01859544 - samples/sec: 64.24 - lr: 0.050000 2022-11-01 16:18:45,736 epoch 79 - iter 189/274 - loss 0.01866095 - samples/sec: 70.47 - lr: 0.050000 2022-11-01 16:18:58,137 epoch 79 - iter 216/274 - loss 0.01866639 - samples/sec: 69.69 - lr: 0.050000 2022-11-01 16:19:10,045 epoch 79 - iter 243/274 - loss 0.01811509 - samples/sec: 72.57 - lr: 0.050000 2022-11-01 16:19:23,548 epoch 79 - iter 270/274 - loss 0.01832024 - samples/sec: 64.00 - lr: 0.050000 2022-11-01 16:19:25,173 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:19:25,174 EPOCH 79 done: loss 0.0184 - lr 0.050000 2022-11-01 16:19:50,600 Evaluating as a multi-label problem: False 2022-11-01 16:19:50,616 TEST : loss 0.03068099543452263 - f1-score (micro avg) 0.8506 2022-11-01 16:19:50,669 BAD EPOCHS (no improvement): 1 2022-11-01 16:19:50,760 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:20:01,772 epoch 80 - iter 27/274 - loss 0.01991148 - samples/sec: 78.49 - lr: 0.050000 2022-11-01 16:20:16,433 epoch 80 - iter 54/274 - loss 0.01871553 - samples/sec: 58.94 - lr: 0.050000 2022-11-01 16:20:28,629 epoch 80 - iter 81/274 - loss 0.01907954 - samples/sec: 70.86 - lr: 0.050000 2022-11-01 16:20:40,218 epoch 80 - iter 108/274 - loss 0.01834093 - samples/sec: 74.58 - lr: 0.050000 2022-11-01 16:20:53,091 epoch 80 - iter 135/274 - loss 0.01859223 - samples/sec: 67.14 - lr: 0.050000 2022-11-01 16:21:04,356 epoch 80 - iter 162/274 - loss 0.01827675 - samples/sec: 76.72 - lr: 0.050000 2022-11-01 16:21:17,001 epoch 80 - iter 189/274 - loss 0.01822210 - samples/sec: 68.34 - lr: 0.050000 2022-11-01 16:21:28,675 epoch 80 - iter 216/274 - loss 0.01827311 - samples/sec: 74.03 - lr: 0.050000 2022-11-01 16:21:42,235 epoch 80 - iter 243/274 - loss 0.01796925 - samples/sec: 63.73 - lr: 0.050000 2022-11-01 16:21:54,314 epoch 80 - iter 270/274 - loss 0.01791834 - samples/sec: 71.55 - lr: 0.050000 2022-11-01 16:21:56,353 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:21:56,353 EPOCH 80 done: loss 0.0180 - lr 0.050000 2022-11-01 16:22:21,823 Evaluating as a multi-label problem: False 2022-11-01 16:22:21,839 TEST : loss 0.03157917782664299 - f1-score (micro avg) 0.8551 2022-11-01 16:22:21,892 BAD EPOCHS (no improvement): 2 2022-11-01 16:22:21,984 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:22:34,097 epoch 81 - iter 27/274 - loss 0.01705883 - samples/sec: 71.36 - lr: 0.050000 2022-11-01 16:22:45,629 epoch 81 - iter 54/274 - loss 0.01676405 - samples/sec: 74.94 - lr: 0.050000 2022-11-01 16:22:57,336 epoch 81 - iter 81/274 - loss 0.01739874 - samples/sec: 73.83 - lr: 0.050000 2022-11-01 16:23:08,562 epoch 81 - iter 108/274 - loss 0.01762212 - samples/sec: 76.98 - lr: 0.050000 2022-11-01 16:23:21,574 epoch 81 - iter 135/274 - loss 0.01782749 - samples/sec: 66.42 - lr: 0.050000 2022-11-01 16:23:35,270 epoch 81 - iter 162/274 - loss 0.01828249 - samples/sec: 63.10 - lr: 0.050000 2022-11-01 16:23:48,300 epoch 81 - iter 189/274 - loss 0.01813256 - samples/sec: 66.32 - lr: 0.050000 2022-11-01 16:24:01,404 epoch 81 - iter 216/274 - loss 0.01802512 - samples/sec: 65.95 - lr: 0.050000 2022-11-01 16:24:12,505 epoch 81 - iter 243/274 - loss 0.01793248 - samples/sec: 77.85 - lr: 0.050000 2022-11-01 16:24:24,473 epoch 81 - iter 270/274 - loss 0.01780714 - samples/sec: 72.21 - lr: 0.050000 2022-11-01 16:24:26,323 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:24:26,323 EPOCH 81 done: loss 0.0179 - lr 0.050000 2022-11-01 16:24:51,950 Evaluating as a multi-label problem: False 2022-11-01 16:24:51,966 TEST : loss 0.029629342257976532 - f1-score (micro avg) 0.8565 2022-11-01 16:24:52,017 BAD EPOCHS (no improvement): 3 2022-11-01 16:24:52,108 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:25:03,673 epoch 82 - iter 27/274 - loss 0.01517411 - samples/sec: 74.73 - lr: 0.050000 2022-11-01 16:25:15,248 epoch 82 - iter 54/274 - loss 0.01566208 - samples/sec: 74.67 - lr: 0.050000 2022-11-01 16:25:28,531 epoch 82 - iter 81/274 - loss 0.01767380 - samples/sec: 65.06 - lr: 0.050000 2022-11-01 16:25:40,413 epoch 82 - iter 108/274 - loss 0.01710010 - samples/sec: 72.74 - lr: 0.050000 2022-11-01 16:25:52,805 epoch 82 - iter 135/274 - loss 0.01665061 - samples/sec: 69.74 - lr: 0.050000 2022-11-01 16:26:05,721 epoch 82 - iter 162/274 - loss 0.01717756 - samples/sec: 66.91 - lr: 0.050000 2022-11-01 16:26:18,213 epoch 82 - iter 189/274 - loss 0.01790767 - samples/sec: 69.18 - lr: 0.050000 2022-11-01 16:26:30,435 epoch 82 - iter 216/274 - loss 0.01790503 - samples/sec: 70.71 - lr: 0.050000 2022-11-01 16:26:44,476 epoch 82 - iter 243/274 - loss 0.01773968 - samples/sec: 61.55 - lr: 0.050000 2022-11-01 16:26:56,279 epoch 82 - iter 270/274 - loss 0.01752431 - samples/sec: 73.22 - lr: 0.050000 2022-11-01 16:26:57,790 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:26:57,790 EPOCH 82 done: loss 0.0176 - lr 0.050000 2022-11-01 16:27:23,088 Evaluating as a multi-label problem: False 2022-11-01 16:27:23,103 TEST : loss 0.02843180112540722 - f1-score (micro avg) 0.8544 2022-11-01 16:27:23,156 Epoch 82: reducing learning rate of group 0 to 2.5000e-02. 2022-11-01 16:27:23,156 BAD EPOCHS (no improvement): 4 2022-11-01 16:27:23,248 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:27:35,196 epoch 83 - iter 27/274 - loss 0.01636089 - samples/sec: 72.33 - lr: 0.025000 2022-11-01 16:27:46,808 epoch 83 - iter 54/274 - loss 0.01606208 - samples/sec: 74.43 - lr: 0.025000 2022-11-01 16:27:59,607 epoch 83 - iter 81/274 - loss 0.01687172 - samples/sec: 67.52 - lr: 0.025000 2022-11-01 16:28:12,576 epoch 83 - iter 108/274 - loss 0.01773665 - samples/sec: 66.64 - lr: 0.025000 2022-11-01 16:28:25,607 epoch 83 - iter 135/274 - loss 0.01707393 - samples/sec: 66.32 - lr: 0.025000 2022-11-01 16:28:37,893 epoch 83 - iter 162/274 - loss 0.01671065 - samples/sec: 70.35 - lr: 0.025000 2022-11-01 16:28:50,691 epoch 83 - iter 189/274 - loss 0.01697125 - samples/sec: 67.53 - lr: 0.025000 2022-11-01 16:29:03,462 epoch 83 - iter 216/274 - loss 0.01688751 - samples/sec: 67.67 - lr: 0.025000 2022-11-01 16:29:15,237 epoch 83 - iter 243/274 - loss 0.01724621 - samples/sec: 73.39 - lr: 0.025000 2022-11-01 16:29:27,912 epoch 83 - iter 270/274 - loss 0.01744322 - samples/sec: 68.18 - lr: 0.025000 2022-11-01 16:29:29,629 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:29:29,629 EPOCH 83 done: loss 0.0173 - lr 0.025000 2022-11-01 16:29:54,787 Evaluating as a multi-label problem: False 2022-11-01 16:29:54,803 TEST : loss 0.029316166415810585 - f1-score (micro avg) 0.8533 2022-11-01 16:29:54,856 BAD EPOCHS (no improvement): 1 2022-11-01 16:29:54,951 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:30:06,126 epoch 84 - iter 27/274 - loss 0.01576658 - samples/sec: 77.34 - lr: 0.025000 2022-11-01 16:30:18,356 epoch 84 - iter 54/274 - loss 0.01510948 - samples/sec: 70.67 - lr: 0.025000 2022-11-01 16:30:30,897 epoch 84 - iter 81/274 - loss 0.01509003 - samples/sec: 68.91 - lr: 0.025000 2022-11-01 16:30:44,239 epoch 84 - iter 108/274 - loss 0.01485943 - samples/sec: 64.77 - lr: 0.025000 2022-11-01 16:30:57,506 epoch 84 - iter 135/274 - loss 0.01553865 - samples/sec: 65.14 - lr: 0.025000 2022-11-01 16:31:08,699 epoch 84 - iter 162/274 - loss 0.01580709 - samples/sec: 77.21 - lr: 0.025000 2022-11-01 16:31:21,826 epoch 84 - iter 189/274 - loss 0.01591768 - samples/sec: 65.84 - lr: 0.025000 2022-11-01 16:31:35,047 epoch 84 - iter 216/274 - loss 0.01610133 - samples/sec: 65.36 - lr: 0.025000 2022-11-01 16:31:47,076 epoch 84 - iter 243/274 - loss 0.01600053 - samples/sec: 71.85 - lr: 0.025000 2022-11-01 16:31:59,719 epoch 84 - iter 270/274 - loss 0.01628348 - samples/sec: 68.36 - lr: 0.025000 2022-11-01 16:32:01,717 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:32:01,717 EPOCH 84 done: loss 0.0164 - lr 0.025000 2022-11-01 16:32:27,343 Evaluating as a multi-label problem: False 2022-11-01 16:32:27,359 TEST : loss 0.029401035979390144 - f1-score (micro avg) 0.8506 2022-11-01 16:32:27,411 BAD EPOCHS (no improvement): 0 2022-11-01 16:32:27,507 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:32:39,216 epoch 85 - iter 27/274 - loss 0.01603222 - samples/sec: 73.81 - lr: 0.025000 2022-11-01 16:32:51,063 epoch 85 - iter 54/274 - loss 0.01741225 - samples/sec: 72.95 - lr: 0.025000 2022-11-01 16:33:04,348 epoch 85 - iter 81/274 - loss 0.01696731 - samples/sec: 65.05 - lr: 0.025000 2022-11-01 16:33:17,167 epoch 85 - iter 108/274 - loss 0.01676102 - samples/sec: 67.42 - lr: 0.025000 2022-11-01 16:33:30,885 epoch 85 - iter 135/274 - loss 0.01643452 - samples/sec: 63.00 - lr: 0.025000 2022-11-01 16:33:42,958 epoch 85 - iter 162/274 - loss 0.01683062 - samples/sec: 71.58 - lr: 0.025000 2022-11-01 16:33:54,584 epoch 85 - iter 189/274 - loss 0.01661397 - samples/sec: 74.34 - lr: 0.025000 2022-11-01 16:34:08,124 epoch 85 - iter 216/274 - loss 0.01674394 - samples/sec: 63.83 - lr: 0.025000 2022-11-01 16:34:19,185 epoch 85 - iter 243/274 - loss 0.01673404 - samples/sec: 78.14 - lr: 0.025000 2022-11-01 16:34:30,584 epoch 85 - iter 270/274 - loss 0.01678524 - samples/sec: 75.82 - lr: 0.025000 2022-11-01 16:34:32,416 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:34:32,416 EPOCH 85 done: loss 0.0167 - lr 0.025000 2022-11-01 16:34:57,702 Evaluating as a multi-label problem: False 2022-11-01 16:34:57,717 TEST : loss 0.030953796580433846 - f1-score (micro avg) 0.8556 2022-11-01 16:34:57,769 BAD EPOCHS (no improvement): 1 2022-11-01 16:34:57,860 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:35:10,313 epoch 86 - iter 27/274 - loss 0.01832310 - samples/sec: 69.40 - lr: 0.025000 2022-11-01 16:35:24,124 epoch 86 - iter 54/274 - loss 0.01662775 - samples/sec: 62.57 - lr: 0.025000 2022-11-01 16:35:35,622 epoch 86 - iter 81/274 - loss 0.01593853 - samples/sec: 75.17 - lr: 0.025000 2022-11-01 16:35:48,105 epoch 86 - iter 108/274 - loss 0.01677397 - samples/sec: 69.23 - lr: 0.025000 2022-11-01 16:35:59,618 epoch 86 - iter 135/274 - loss 0.01677152 - samples/sec: 75.07 - lr: 0.025000 2022-11-01 16:36:11,947 epoch 86 - iter 162/274 - loss 0.01687084 - samples/sec: 70.10 - lr: 0.025000 2022-11-01 16:36:25,305 epoch 86 - iter 189/274 - loss 0.01703050 - samples/sec: 64.70 - lr: 0.025000 2022-11-01 16:36:37,864 epoch 86 - iter 216/274 - loss 0.01682995 - samples/sec: 68.81 - lr: 0.025000 2022-11-01 16:36:48,783 epoch 86 - iter 243/274 - loss 0.01675319 - samples/sec: 79.15 - lr: 0.025000 2022-11-01 16:36:59,918 epoch 86 - iter 270/274 - loss 0.01679931 - samples/sec: 77.62 - lr: 0.025000 2022-11-01 16:37:01,938 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:37:01,938 EPOCH 86 done: loss 0.0170 - lr 0.025000 2022-11-01 16:37:27,319 Evaluating as a multi-label problem: False 2022-11-01 16:37:27,335 TEST : loss 0.030635029077529907 - f1-score (micro avg) 0.8537 2022-11-01 16:37:27,388 BAD EPOCHS (no improvement): 2 2022-11-01 16:37:27,480 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:37:39,899 epoch 87 - iter 27/274 - loss 0.01457488 - samples/sec: 69.60 - lr: 0.025000 2022-11-01 16:37:53,247 epoch 87 - iter 54/274 - loss 0.01425651 - samples/sec: 64.74 - lr: 0.025000 2022-11-01 16:38:06,024 epoch 87 - iter 81/274 - loss 0.01547111 - samples/sec: 67.64 - lr: 0.025000 2022-11-01 16:38:19,260 epoch 87 - iter 108/274 - loss 0.01529546 - samples/sec: 65.29 - lr: 0.025000 2022-11-01 16:38:31,312 epoch 87 - iter 135/274 - loss 0.01584319 - samples/sec: 71.71 - lr: 0.025000 2022-11-01 16:38:43,662 epoch 87 - iter 162/274 - loss 0.01590420 - samples/sec: 69.98 - lr: 0.025000 2022-11-01 16:38:56,177 epoch 87 - iter 189/274 - loss 0.01631382 - samples/sec: 69.05 - lr: 0.025000 2022-11-01 16:39:08,261 epoch 87 - iter 216/274 - loss 0.01628017 - samples/sec: 71.52 - lr: 0.025000 2022-11-01 16:39:20,371 epoch 87 - iter 243/274 - loss 0.01615643 - samples/sec: 71.37 - lr: 0.025000 2022-11-01 16:39:33,177 epoch 87 - iter 270/274 - loss 0.01590582 - samples/sec: 67.48 - lr: 0.025000 2022-11-01 16:39:34,790 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:39:34,790 EPOCH 87 done: loss 0.0159 - lr 0.025000 2022-11-01 16:40:00,078 Evaluating as a multi-label problem: False 2022-11-01 16:40:00,093 TEST : loss 0.03055056370794773 - f1-score (micro avg) 0.8535 2022-11-01 16:40:00,146 BAD EPOCHS (no improvement): 0 2022-11-01 16:40:00,238 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:40:11,140 epoch 88 - iter 27/274 - loss 0.01375907 - samples/sec: 79.28 - lr: 0.025000 2022-11-01 16:40:24,674 epoch 88 - iter 54/274 - loss 0.01666760 - samples/sec: 63.86 - lr: 0.025000 2022-11-01 16:40:36,121 epoch 88 - iter 81/274 - loss 0.01668721 - samples/sec: 75.50 - lr: 0.025000 2022-11-01 16:40:48,625 epoch 88 - iter 108/274 - loss 0.01569771 - samples/sec: 69.12 - lr: 0.025000 2022-11-01 16:41:02,221 epoch 88 - iter 135/274 - loss 0.01541809 - samples/sec: 63.56 - lr: 0.025000 2022-11-01 16:41:13,833 epoch 88 - iter 162/274 - loss 0.01572390 - samples/sec: 74.43 - lr: 0.025000 2022-11-01 16:41:26,394 epoch 88 - iter 189/274 - loss 0.01613422 - samples/sec: 68.80 - lr: 0.025000 2022-11-01 16:41:39,138 epoch 88 - iter 216/274 - loss 0.01597918 - samples/sec: 67.81 - lr: 0.025000 2022-11-01 16:41:50,987 epoch 88 - iter 243/274 - loss 0.01610632 - samples/sec: 72.94 - lr: 0.025000 2022-11-01 16:42:04,017 epoch 88 - iter 270/274 - loss 0.01642128 - samples/sec: 66.33 - lr: 0.025000 2022-11-01 16:42:05,883 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:42:05,883 EPOCH 88 done: loss 0.0166 - lr 0.025000 2022-11-01 16:42:30,656 Evaluating as a multi-label problem: False 2022-11-01 16:42:30,672 TEST : loss 0.029628725722432137 - f1-score (micro avg) 0.8577 2022-11-01 16:42:30,726 BAD EPOCHS (no improvement): 1 2022-11-01 16:42:30,799 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:42:43,593 epoch 89 - iter 27/274 - loss 0.01806551 - samples/sec: 67.55 - lr: 0.025000 2022-11-01 16:42:56,549 epoch 89 - iter 54/274 - loss 0.01773860 - samples/sec: 66.70 - lr: 0.025000 2022-11-01 16:43:07,563 epoch 89 - iter 81/274 - loss 0.01752078 - samples/sec: 78.47 - lr: 0.025000 2022-11-01 16:43:18,722 epoch 89 - iter 108/274 - loss 0.01689594 - samples/sec: 77.45 - lr: 0.025000 2022-11-01 16:43:31,342 epoch 89 - iter 135/274 - loss 0.01681539 - samples/sec: 68.48 - lr: 0.025000 2022-11-01 16:43:43,326 epoch 89 - iter 162/274 - loss 0.01672993 - samples/sec: 72.12 - lr: 0.025000 2022-11-01 16:43:55,437 epoch 89 - iter 189/274 - loss 0.01699377 - samples/sec: 71.36 - lr: 0.025000 2022-11-01 16:44:07,633 epoch 89 - iter 216/274 - loss 0.01664312 - samples/sec: 70.86 - lr: 0.025000 2022-11-01 16:44:21,310 epoch 89 - iter 243/274 - loss 0.01652580 - samples/sec: 63.19 - lr: 0.025000 2022-11-01 16:44:34,524 epoch 89 - iter 270/274 - loss 0.01646223 - samples/sec: 65.40 - lr: 0.025000 2022-11-01 16:44:36,018 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:44:36,018 EPOCH 89 done: loss 0.0164 - lr 0.025000 2022-11-01 16:45:01,028 Evaluating as a multi-label problem: False 2022-11-01 16:45:01,044 TEST : loss 0.030412347987294197 - f1-score (micro avg) 0.8557 2022-11-01 16:45:01,101 BAD EPOCHS (no improvement): 2 2022-11-01 16:45:01,197 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:45:13,274 epoch 90 - iter 27/274 - loss 0.01564131 - samples/sec: 71.56 - lr: 0.025000 2022-11-01 16:45:25,179 epoch 90 - iter 54/274 - loss 0.01582138 - samples/sec: 72.60 - lr: 0.025000 2022-11-01 16:45:37,427 epoch 90 - iter 81/274 - loss 0.01540488 - samples/sec: 70.56 - lr: 0.025000 2022-11-01 16:45:48,993 epoch 90 - iter 108/274 - loss 0.01637324 - samples/sec: 74.73 - lr: 0.025000 2022-11-01 16:46:01,317 epoch 90 - iter 135/274 - loss 0.01632562 - samples/sec: 70.13 - lr: 0.025000 2022-11-01 16:46:13,570 epoch 90 - iter 162/274 - loss 0.01599840 - samples/sec: 70.53 - lr: 0.025000 2022-11-01 16:46:26,019 epoch 90 - iter 189/274 - loss 0.01599910 - samples/sec: 69.43 - lr: 0.025000 2022-11-01 16:46:38,827 epoch 90 - iter 216/274 - loss 0.01613755 - samples/sec: 67.47 - lr: 0.025000 2022-11-01 16:46:50,421 epoch 90 - iter 243/274 - loss 0.01621818 - samples/sec: 74.55 - lr: 0.025000 2022-11-01 16:47:03,939 epoch 90 - iter 270/274 - loss 0.01603622 - samples/sec: 63.93 - lr: 0.025000 2022-11-01 16:47:06,316 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:47:06,316 EPOCH 90 done: loss 0.0160 - lr 0.025000 2022-11-01 16:47:31,676 Evaluating as a multi-label problem: False 2022-11-01 16:47:31,692 TEST : loss 0.029919512569904327 - f1-score (micro avg) 0.8499 2022-11-01 16:47:31,746 BAD EPOCHS (no improvement): 3 2022-11-01 16:47:31,838 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:47:44,697 epoch 91 - iter 27/274 - loss 0.01229596 - samples/sec: 67.21 - lr: 0.025000 2022-11-01 16:47:57,004 epoch 91 - iter 54/274 - loss 0.01415102 - samples/sec: 70.22 - lr: 0.025000 2022-11-01 16:48:09,090 epoch 91 - iter 81/274 - loss 0.01421652 - samples/sec: 71.50 - lr: 0.025000 2022-11-01 16:48:21,585 epoch 91 - iter 108/274 - loss 0.01502545 - samples/sec: 69.17 - lr: 0.025000 2022-11-01 16:48:35,360 epoch 91 - iter 135/274 - loss 0.01534741 - samples/sec: 62.74 - lr: 0.025000 2022-11-01 16:48:47,558 epoch 91 - iter 162/274 - loss 0.01576136 - samples/sec: 70.85 - lr: 0.025000 2022-11-01 16:49:00,013 epoch 91 - iter 189/274 - loss 0.01573564 - samples/sec: 69.39 - lr: 0.025000 2022-11-01 16:49:12,613 epoch 91 - iter 216/274 - loss 0.01610894 - samples/sec: 68.59 - lr: 0.025000 2022-11-01 16:49:23,671 epoch 91 - iter 243/274 - loss 0.01583706 - samples/sec: 78.15 - lr: 0.025000 2022-11-01 16:49:37,477 epoch 91 - iter 270/274 - loss 0.01585399 - samples/sec: 62.60 - lr: 0.025000 2022-11-01 16:49:39,134 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:49:39,135 EPOCH 91 done: loss 0.0158 - lr 0.025000 2022-11-01 16:50:04,527 Evaluating as a multi-label problem: False 2022-11-01 16:50:04,542 TEST : loss 0.029802754521369934 - f1-score (micro avg) 0.8562 2022-11-01 16:50:04,594 BAD EPOCHS (no improvement): 0 2022-11-01 16:50:04,667 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:50:17,801 epoch 92 - iter 27/274 - loss 0.01424113 - samples/sec: 65.80 - lr: 0.025000 2022-11-01 16:50:30,363 epoch 92 - iter 54/274 - loss 0.01557183 - samples/sec: 68.80 - lr: 0.025000 2022-11-01 16:50:43,821 epoch 92 - iter 81/274 - loss 0.01633458 - samples/sec: 64.21 - lr: 0.025000 2022-11-01 16:50:55,674 epoch 92 - iter 108/274 - loss 0.01687727 - samples/sec: 72.92 - lr: 0.025000 2022-11-01 16:51:08,718 epoch 92 - iter 135/274 - loss 0.01594242 - samples/sec: 66.25 - lr: 0.025000 2022-11-01 16:51:20,596 epoch 92 - iter 162/274 - loss 0.01612769 - samples/sec: 72.76 - lr: 0.025000 2022-11-01 16:51:32,683 epoch 92 - iter 189/274 - loss 0.01619242 - samples/sec: 71.50 - lr: 0.025000 2022-11-01 16:51:45,275 epoch 92 - iter 216/274 - loss 0.01641394 - samples/sec: 68.63 - lr: 0.025000 2022-11-01 16:51:57,544 epoch 92 - iter 243/274 - loss 0.01626312 - samples/sec: 70.44 - lr: 0.025000 2022-11-01 16:52:09,360 epoch 92 - iter 270/274 - loss 0.01581703 - samples/sec: 73.14 - lr: 0.025000 2022-11-01 16:52:11,253 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:52:11,254 EPOCH 92 done: loss 0.0158 - lr 0.025000 2022-11-01 16:52:36,332 Evaluating as a multi-label problem: False 2022-11-01 16:52:36,347 TEST : loss 0.031193019822239876 - f1-score (micro avg) 0.852 2022-11-01 16:52:36,399 BAD EPOCHS (no improvement): 0 2022-11-01 16:52:36,495 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:52:47,868 epoch 93 - iter 27/274 - loss 0.01514042 - samples/sec: 75.99 - lr: 0.025000 2022-11-01 16:52:59,621 epoch 93 - iter 54/274 - loss 0.01608344 - samples/sec: 73.54 - lr: 0.025000 2022-11-01 16:53:12,802 epoch 93 - iter 81/274 - loss 0.01633994 - samples/sec: 65.56 - lr: 0.025000 2022-11-01 16:53:26,430 epoch 93 - iter 108/274 - loss 0.01694982 - samples/sec: 63.41 - lr: 0.025000 2022-11-01 16:53:39,222 epoch 93 - iter 135/274 - loss 0.01595774 - samples/sec: 67.56 - lr: 0.025000 2022-11-01 16:53:51,426 epoch 93 - iter 162/274 - loss 0.01608164 - samples/sec: 70.81 - lr: 0.025000 2022-11-01 16:54:03,857 epoch 93 - iter 189/274 - loss 0.01616575 - samples/sec: 69.52 - lr: 0.025000 2022-11-01 16:54:16,142 epoch 93 - iter 216/274 - loss 0.01606524 - samples/sec: 70.35 - lr: 0.025000 2022-11-01 16:54:28,972 epoch 93 - iter 243/274 - loss 0.01602004 - samples/sec: 67.36 - lr: 0.025000 2022-11-01 16:54:41,141 epoch 93 - iter 270/274 - loss 0.01552356 - samples/sec: 71.02 - lr: 0.025000 2022-11-01 16:54:42,851 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:54:42,852 EPOCH 93 done: loss 0.0155 - lr 0.025000 2022-11-01 16:55:08,139 Evaluating as a multi-label problem: False 2022-11-01 16:55:08,154 TEST : loss 0.03080672211945057 - f1-score (micro avg) 0.8551 2022-11-01 16:55:08,208 BAD EPOCHS (no improvement): 0 2022-11-01 16:55:08,300 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:55:20,564 epoch 94 - iter 27/274 - loss 0.01833471 - samples/sec: 70.47 - lr: 0.025000 2022-11-01 16:55:33,934 epoch 94 - iter 54/274 - loss 0.01785616 - samples/sec: 64.64 - lr: 0.025000 2022-11-01 16:55:46,048 epoch 94 - iter 81/274 - loss 0.01756784 - samples/sec: 71.34 - lr: 0.025000 2022-11-01 16:55:59,581 epoch 94 - iter 108/274 - loss 0.01710252 - samples/sec: 63.86 - lr: 0.025000 2022-11-01 16:56:11,194 epoch 94 - iter 135/274 - loss 0.01640143 - samples/sec: 74.42 - lr: 0.025000 2022-11-01 16:56:24,892 epoch 94 - iter 162/274 - loss 0.01595753 - samples/sec: 63.09 - lr: 0.025000 2022-11-01 16:56:37,887 epoch 94 - iter 189/274 - loss 0.01589872 - samples/sec: 66.50 - lr: 0.025000 2022-11-01 16:56:48,846 epoch 94 - iter 216/274 - loss 0.01636018 - samples/sec: 78.87 - lr: 0.025000 2022-11-01 16:57:00,547 epoch 94 - iter 243/274 - loss 0.01639244 - samples/sec: 73.86 - lr: 0.025000 2022-11-01 16:57:12,390 epoch 94 - iter 270/274 - loss 0.01644462 - samples/sec: 72.98 - lr: 0.025000 2022-11-01 16:57:13,913 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:57:13,913 EPOCH 94 done: loss 0.0164 - lr 0.025000 2022-11-01 16:57:39,655 Evaluating as a multi-label problem: False 2022-11-01 16:57:39,671 TEST : loss 0.030662264674901962 - f1-score (micro avg) 0.8553 2022-11-01 16:57:39,722 BAD EPOCHS (no improvement): 1 2022-11-01 16:57:39,814 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:57:52,162 epoch 95 - iter 27/274 - loss 0.01688978 - samples/sec: 70.00 - lr: 0.025000 2022-11-01 16:58:05,022 epoch 95 - iter 54/274 - loss 0.01534652 - samples/sec: 67.20 - lr: 0.025000 2022-11-01 16:58:16,780 epoch 95 - iter 81/274 - loss 0.01469917 - samples/sec: 73.50 - lr: 0.025000 2022-11-01 16:58:28,997 epoch 95 - iter 108/274 - loss 0.01583896 - samples/sec: 70.74 - lr: 0.025000 2022-11-01 16:58:40,603 epoch 95 - iter 135/274 - loss 0.01604019 - samples/sec: 74.46 - lr: 0.025000 2022-11-01 16:58:52,272 epoch 95 - iter 162/274 - loss 0.01560099 - samples/sec: 74.07 - lr: 0.025000 2022-11-01 16:59:05,106 epoch 95 - iter 189/274 - loss 0.01566128 - samples/sec: 67.33 - lr: 0.025000 2022-11-01 16:59:16,292 epoch 95 - iter 216/274 - loss 0.01538281 - samples/sec: 77.27 - lr: 0.025000 2022-11-01 16:59:30,105 epoch 95 - iter 243/274 - loss 0.01595071 - samples/sec: 62.56 - lr: 0.025000 2022-11-01 16:59:42,530 epoch 95 - iter 270/274 - loss 0.01587799 - samples/sec: 69.55 - lr: 0.025000 2022-11-01 16:59:44,417 ---------------------------------------------------------------------------------------------------- 2022-11-01 16:59:44,417 EPOCH 95 done: loss 0.0158 - lr 0.025000 2022-11-01 17:00:09,855 Evaluating as a multi-label problem: False 2022-11-01 17:00:09,870 TEST : loss 0.030545346438884735 - f1-score (micro avg) 0.8545 2022-11-01 17:00:09,923 BAD EPOCHS (no improvement): 2 2022-11-01 17:00:10,015 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:00:23,419 epoch 96 - iter 27/274 - loss 0.01242489 - samples/sec: 64.48 - lr: 0.025000 2022-11-01 17:00:35,238 epoch 96 - iter 54/274 - loss 0.01448475 - samples/sec: 73.12 - lr: 0.025000 2022-11-01 17:00:48,022 epoch 96 - iter 81/274 - loss 0.01561201 - samples/sec: 67.60 - lr: 0.025000 2022-11-01 17:01:00,345 epoch 96 - iter 108/274 - loss 0.01621416 - samples/sec: 70.13 - lr: 0.025000 2022-11-01 17:01:13,192 epoch 96 - iter 135/274 - loss 0.01632154 - samples/sec: 67.27 - lr: 0.025000 2022-11-01 17:01:24,671 epoch 96 - iter 162/274 - loss 0.01572867 - samples/sec: 75.29 - lr: 0.025000 2022-11-01 17:01:36,808 epoch 96 - iter 189/274 - loss 0.01559104 - samples/sec: 71.21 - lr: 0.025000 2022-11-01 17:01:50,027 epoch 96 - iter 216/274 - loss 0.01589267 - samples/sec: 65.38 - lr: 0.025000 2022-11-01 17:02:03,405 epoch 96 - iter 243/274 - loss 0.01604069 - samples/sec: 64.60 - lr: 0.025000 2022-11-01 17:02:14,570 epoch 96 - iter 270/274 - loss 0.01609900 - samples/sec: 77.40 - lr: 0.025000 2022-11-01 17:02:16,458 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:02:16,458 EPOCH 96 done: loss 0.0161 - lr 0.025000 2022-11-01 17:02:41,425 Evaluating as a multi-label problem: False 2022-11-01 17:02:41,440 TEST : loss 0.031394150108098984 - f1-score (micro avg) 0.8584 2022-11-01 17:02:41,493 BAD EPOCHS (no improvement): 3 2022-11-01 17:02:41,585 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:02:54,710 epoch 97 - iter 27/274 - loss 0.01492072 - samples/sec: 65.85 - lr: 0.025000 2022-11-01 17:03:05,770 epoch 97 - iter 54/274 - loss 0.01396878 - samples/sec: 78.14 - lr: 0.025000 2022-11-01 17:03:17,619 epoch 97 - iter 81/274 - loss 0.01413726 - samples/sec: 72.94 - lr: 0.025000 2022-11-01 17:03:31,104 epoch 97 - iter 108/274 - loss 0.01427275 - samples/sec: 64.09 - lr: 0.025000 2022-11-01 17:03:43,566 epoch 97 - iter 135/274 - loss 0.01438317 - samples/sec: 69.35 - lr: 0.025000 2022-11-01 17:03:56,029 epoch 97 - iter 162/274 - loss 0.01508738 - samples/sec: 69.34 - lr: 0.025000 2022-11-01 17:04:07,750 epoch 97 - iter 189/274 - loss 0.01543147 - samples/sec: 73.73 - lr: 0.025000 2022-11-01 17:04:21,673 epoch 97 - iter 216/274 - loss 0.01514577 - samples/sec: 62.07 - lr: 0.025000 2022-11-01 17:04:35,162 epoch 97 - iter 243/274 - loss 0.01554633 - samples/sec: 64.07 - lr: 0.025000 2022-11-01 17:04:47,543 epoch 97 - iter 270/274 - loss 0.01594045 - samples/sec: 69.80 - lr: 0.025000 2022-11-01 17:04:49,266 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:04:49,267 EPOCH 97 done: loss 0.0161 - lr 0.025000 2022-11-01 17:05:14,559 Evaluating as a multi-label problem: False 2022-11-01 17:05:14,575 TEST : loss 0.031141091138124466 - f1-score (micro avg) 0.8548 2022-11-01 17:05:14,626 Epoch 97: reducing learning rate of group 0 to 1.2500e-02. 2022-11-01 17:05:14,626 BAD EPOCHS (no improvement): 4 2022-11-01 17:05:14,718 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:05:27,619 epoch 98 - iter 27/274 - loss 0.01684552 - samples/sec: 66.99 - lr: 0.012500 2022-11-01 17:05:40,712 epoch 98 - iter 54/274 - loss 0.01617953 - samples/sec: 66.00 - lr: 0.012500 2022-11-01 17:05:52,535 epoch 98 - iter 81/274 - loss 0.01694288 - samples/sec: 73.10 - lr: 0.012500 2022-11-01 17:06:04,021 epoch 98 - iter 108/274 - loss 0.01581446 - samples/sec: 75.25 - lr: 0.012500 2022-11-01 17:06:16,731 epoch 98 - iter 135/274 - loss 0.01504212 - samples/sec: 68.00 - lr: 0.012500 2022-11-01 17:06:28,406 epoch 98 - iter 162/274 - loss 0.01514386 - samples/sec: 74.02 - lr: 0.012500 2022-11-01 17:06:40,061 epoch 98 - iter 189/274 - loss 0.01497497 - samples/sec: 74.15 - lr: 0.012500 2022-11-01 17:06:51,963 epoch 98 - iter 216/274 - loss 0.01510213 - samples/sec: 72.61 - lr: 0.012500 2022-11-01 17:07:04,163 epoch 98 - iter 243/274 - loss 0.01520530 - samples/sec: 70.84 - lr: 0.012500 2022-11-01 17:07:18,137 epoch 98 - iter 270/274 - loss 0.01495979 - samples/sec: 61.84 - lr: 0.012500 2022-11-01 17:07:19,938 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:07:19,938 EPOCH 98 done: loss 0.0150 - lr 0.012500 2022-11-01 17:07:45,296 Evaluating as a multi-label problem: False 2022-11-01 17:07:45,312 TEST : loss 0.0315224826335907 - f1-score (micro avg) 0.8517 2022-11-01 17:07:45,364 BAD EPOCHS (no improvement): 0 2022-11-01 17:07:45,457 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:07:59,107 epoch 99 - iter 27/274 - loss 0.01568841 - samples/sec: 63.31 - lr: 0.012500 2022-11-01 17:08:11,036 epoch 99 - iter 54/274 - loss 0.01701872 - samples/sec: 72.45 - lr: 0.012500 2022-11-01 17:08:22,893 epoch 99 - iter 81/274 - loss 0.01531658 - samples/sec: 72.89 - lr: 0.012500 2022-11-01 17:08:34,443 epoch 99 - iter 108/274 - loss 0.01571024 - samples/sec: 74.83 - lr: 0.012500 2022-11-01 17:08:45,990 epoch 99 - iter 135/274 - loss 0.01567341 - samples/sec: 74.85 - lr: 0.012500 2022-11-01 17:08:58,358 epoch 99 - iter 162/274 - loss 0.01522725 - samples/sec: 69.88 - lr: 0.012500 2022-11-01 17:09:10,655 epoch 99 - iter 189/274 - loss 0.01517455 - samples/sec: 70.28 - lr: 0.012500 2022-11-01 17:09:24,581 epoch 99 - iter 216/274 - loss 0.01501352 - samples/sec: 62.06 - lr: 0.012500 2022-11-01 17:09:36,581 epoch 99 - iter 243/274 - loss 0.01514386 - samples/sec: 72.02 - lr: 0.012500 2022-11-01 17:09:48,961 epoch 99 - iter 270/274 - loss 0.01501936 - samples/sec: 69.81 - lr: 0.012500 2022-11-01 17:09:50,696 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:09:50,696 EPOCH 99 done: loss 0.0149 - lr 0.012500 2022-11-01 17:10:16,131 Evaluating as a multi-label problem: False 2022-11-01 17:10:16,146 TEST : loss 0.032214682549238205 - f1-score (micro avg) 0.8528 2022-11-01 17:10:16,198 BAD EPOCHS (no improvement): 0 2022-11-01 17:10:16,290 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:10:28,380 epoch 100 - iter 27/274 - loss 0.01049140 - samples/sec: 71.49 - lr: 0.012500 2022-11-01 17:10:41,052 epoch 100 - iter 54/274 - loss 0.01500905 - samples/sec: 68.20 - lr: 0.012500 2022-11-01 17:10:53,501 epoch 100 - iter 81/274 - loss 0.01512699 - samples/sec: 69.42 - lr: 0.012500 2022-11-01 17:11:05,018 epoch 100 - iter 108/274 - loss 0.01472317 - samples/sec: 75.04 - lr: 0.012500 2022-11-01 17:11:16,311 epoch 100 - iter 135/274 - loss 0.01471632 - samples/sec: 76.53 - lr: 0.012500 2022-11-01 17:11:28,068 epoch 100 - iter 162/274 - loss 0.01508426 - samples/sec: 73.51 - lr: 0.012500 2022-11-01 17:11:42,352 epoch 100 - iter 189/274 - loss 0.01528565 - samples/sec: 60.50 - lr: 0.012500 2022-11-01 17:11:54,868 epoch 100 - iter 216/274 - loss 0.01551813 - samples/sec: 69.05 - lr: 0.012500 2022-11-01 17:12:09,315 epoch 100 - iter 243/274 - loss 0.01560369 - samples/sec: 59.82 - lr: 0.012500 2022-11-01 17:12:20,899 epoch 100 - iter 270/274 - loss 0.01542870 - samples/sec: 74.61 - lr: 0.012500 2022-11-01 17:12:22,620 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:12:22,620 EPOCH 100 done: loss 0.0153 - lr 0.012500 2022-11-01 17:12:47,951 Evaluating as a multi-label problem: False 2022-11-01 17:12:47,966 TEST : loss 0.03205437958240509 - f1-score (micro avg) 0.8544 2022-11-01 17:12:48,018 BAD EPOCHS (no improvement): 1 2022-11-01 17:12:48,109 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:13:00,180 epoch 101 - iter 27/274 - loss 0.01378529 - samples/sec: 71.60 - lr: 0.012500 2022-11-01 17:13:12,215 epoch 101 - iter 54/274 - loss 0.01337199 - samples/sec: 71.81 - lr: 0.012500 2022-11-01 17:13:25,504 epoch 101 - iter 81/274 - loss 0.01404534 - samples/sec: 65.03 - lr: 0.012500 2022-11-01 17:13:36,981 epoch 101 - iter 108/274 - loss 0.01373175 - samples/sec: 75.30 - lr: 0.012500 2022-11-01 17:13:48,891 epoch 101 - iter 135/274 - loss 0.01451741 - samples/sec: 72.56 - lr: 0.012500 2022-11-01 17:14:01,244 epoch 101 - iter 162/274 - loss 0.01501925 - samples/sec: 69.96 - lr: 0.012500 2022-11-01 17:14:14,210 epoch 101 - iter 189/274 - loss 0.01503842 - samples/sec: 66.65 - lr: 0.012500 2022-11-01 17:14:26,461 epoch 101 - iter 216/274 - loss 0.01533271 - samples/sec: 70.55 - lr: 0.012500 2022-11-01 17:14:38,050 epoch 101 - iter 243/274 - loss 0.01542822 - samples/sec: 74.57 - lr: 0.012500 2022-11-01 17:14:52,728 epoch 101 - iter 270/274 - loss 0.01542944 - samples/sec: 58.88 - lr: 0.012500 2022-11-01 17:14:54,387 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:14:54,387 EPOCH 101 done: loss 0.0153 - lr 0.012500 2022-11-01 17:15:19,832 Evaluating as a multi-label problem: False 2022-11-01 17:15:19,847 TEST : loss 0.03180859610438347 - f1-score (micro avg) 0.8518 2022-11-01 17:15:19,900 BAD EPOCHS (no improvement): 2 2022-11-01 17:15:19,996 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:15:30,919 epoch 102 - iter 27/274 - loss 0.01367323 - samples/sec: 79.13 - lr: 0.012500 2022-11-01 17:15:42,942 epoch 102 - iter 54/274 - loss 0.01496790 - samples/sec: 71.88 - lr: 0.012500 2022-11-01 17:15:54,982 epoch 102 - iter 81/274 - loss 0.01427020 - samples/sec: 71.78 - lr: 0.012500 2022-11-01 17:16:07,360 epoch 102 - iter 108/274 - loss 0.01451117 - samples/sec: 69.82 - lr: 0.012500 2022-11-01 17:16:19,150 epoch 102 - iter 135/274 - loss 0.01477473 - samples/sec: 73.31 - lr: 0.012500 2022-11-01 17:16:32,137 epoch 102 - iter 162/274 - loss 0.01509181 - samples/sec: 66.54 - lr: 0.012500 2022-11-01 17:16:44,150 epoch 102 - iter 189/274 - loss 0.01558677 - samples/sec: 71.94 - lr: 0.012500 2022-11-01 17:16:55,429 epoch 102 - iter 216/274 - loss 0.01557646 - samples/sec: 76.63 - lr: 0.012500 2022-11-01 17:17:08,071 epoch 102 - iter 243/274 - loss 0.01558887 - samples/sec: 68.36 - lr: 0.012500 2022-11-01 17:17:21,624 epoch 102 - iter 270/274 - loss 0.01573576 - samples/sec: 63.77 - lr: 0.012500 2022-11-01 17:17:24,639 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:17:24,640 EPOCH 102 done: loss 0.0157 - lr 0.012500 2022-11-01 17:17:49,335 Evaluating as a multi-label problem: False 2022-11-01 17:17:49,351 TEST : loss 0.03114163875579834 - f1-score (micro avg) 0.8522 2022-11-01 17:17:49,402 BAD EPOCHS (no improvement): 3 2022-11-01 17:17:49,497 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:18:01,427 epoch 103 - iter 27/274 - loss 0.01511439 - samples/sec: 72.45 - lr: 0.012500 2022-11-01 17:18:13,288 epoch 103 - iter 54/274 - loss 0.01521225 - samples/sec: 72.87 - lr: 0.012500 2022-11-01 17:18:27,608 epoch 103 - iter 81/274 - loss 0.01588243 - samples/sec: 60.35 - lr: 0.012500 2022-11-01 17:18:40,062 epoch 103 - iter 108/274 - loss 0.01620946 - samples/sec: 69.39 - lr: 0.012500 2022-11-01 17:18:53,137 epoch 103 - iter 135/274 - loss 0.01627265 - samples/sec: 66.10 - lr: 0.012500 2022-11-01 17:19:05,918 epoch 103 - iter 162/274 - loss 0.01616743 - samples/sec: 67.62 - lr: 0.012500 2022-11-01 17:19:18,579 epoch 103 - iter 189/274 - loss 0.01595910 - samples/sec: 68.26 - lr: 0.012500 2022-11-01 17:19:30,844 epoch 103 - iter 216/274 - loss 0.01601796 - samples/sec: 70.46 - lr: 0.012500 2022-11-01 17:19:42,438 epoch 103 - iter 243/274 - loss 0.01586805 - samples/sec: 74.54 - lr: 0.012500 2022-11-01 17:19:54,280 epoch 103 - iter 270/274 - loss 0.01587716 - samples/sec: 72.98 - lr: 0.012500 2022-11-01 17:19:55,910 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:19:55,910 EPOCH 103 done: loss 0.0159 - lr 0.012500 2022-11-01 17:20:21,470 Evaluating as a multi-label problem: False 2022-11-01 17:20:21,486 TEST : loss 0.03149925917387009 - f1-score (micro avg) 0.8538 2022-11-01 17:20:21,538 Epoch 103: reducing learning rate of group 0 to 6.2500e-03. 2022-11-01 17:20:21,539 BAD EPOCHS (no improvement): 4 2022-11-01 17:20:21,631 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:20:34,090 epoch 104 - iter 27/274 - loss 0.01498141 - samples/sec: 69.37 - lr: 0.006250 2022-11-01 17:20:46,629 epoch 104 - iter 54/274 - loss 0.01501934 - samples/sec: 68.92 - lr: 0.006250 2022-11-01 17:20:57,980 epoch 104 - iter 81/274 - loss 0.01434988 - samples/sec: 76.14 - lr: 0.006250 2022-11-01 17:21:09,792 epoch 104 - iter 108/274 - loss 0.01473952 - samples/sec: 73.17 - lr: 0.006250 2022-11-01 17:21:23,026 epoch 104 - iter 135/274 - loss 0.01529435 - samples/sec: 65.30 - lr: 0.006250 2022-11-01 17:21:36,383 epoch 104 - iter 162/274 - loss 0.01527378 - samples/sec: 64.70 - lr: 0.006250 2022-11-01 17:21:50,064 epoch 104 - iter 189/274 - loss 0.01508563 - samples/sec: 63.17 - lr: 0.006250 2022-11-01 17:22:02,774 epoch 104 - iter 216/274 - loss 0.01520574 - samples/sec: 68.00 - lr: 0.006250 2022-11-01 17:22:14,747 epoch 104 - iter 243/274 - loss 0.01531841 - samples/sec: 72.18 - lr: 0.006250 2022-11-01 17:22:25,810 epoch 104 - iter 270/274 - loss 0.01495468 - samples/sec: 78.12 - lr: 0.006250 2022-11-01 17:22:27,314 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:22:27,314 EPOCH 104 done: loss 0.0150 - lr 0.006250 2022-11-01 17:22:52,615 Evaluating as a multi-label problem: False 2022-11-01 17:22:52,631 TEST : loss 0.03160782903432846 - f1-score (micro avg) 0.8545 2022-11-01 17:22:52,682 BAD EPOCHS (no improvement): 1 2022-11-01 17:22:52,774 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:23:04,512 epoch 105 - iter 27/274 - loss 0.01478439 - samples/sec: 73.63 - lr: 0.006250 2022-11-01 17:23:17,554 epoch 105 - iter 54/274 - loss 0.01580731 - samples/sec: 66.26 - lr: 0.006250 2022-11-01 17:23:29,786 epoch 105 - iter 81/274 - loss 0.01527523 - samples/sec: 70.66 - lr: 0.006250 2022-11-01 17:23:42,262 epoch 105 - iter 108/274 - loss 0.01556524 - samples/sec: 69.27 - lr: 0.006250 2022-11-01 17:23:53,798 epoch 105 - iter 135/274 - loss 0.01510414 - samples/sec: 74.92 - lr: 0.006250 2022-11-01 17:24:05,883 epoch 105 - iter 162/274 - loss 0.01499963 - samples/sec: 71.52 - lr: 0.006250 2022-11-01 17:24:18,145 epoch 105 - iter 189/274 - loss 0.01459439 - samples/sec: 70.48 - lr: 0.006250 2022-11-01 17:24:31,529 epoch 105 - iter 216/274 - loss 0.01450208 - samples/sec: 64.57 - lr: 0.006250 2022-11-01 17:24:44,094 epoch 105 - iter 243/274 - loss 0.01431071 - samples/sec: 68.78 - lr: 0.006250 2022-11-01 17:24:56,610 epoch 105 - iter 270/274 - loss 0.01451876 - samples/sec: 69.05 - lr: 0.006250 2022-11-01 17:24:58,538 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:24:58,539 EPOCH 105 done: loss 0.0145 - lr 0.006250 2022-11-01 17:25:24,716 Evaluating as a multi-label problem: False 2022-11-01 17:25:24,732 TEST : loss 0.031382638961076736 - f1-score (micro avg) 0.8549 2022-11-01 17:25:24,783 BAD EPOCHS (no improvement): 0 2022-11-01 17:25:24,878 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:25:37,729 epoch 106 - iter 27/274 - loss 0.01310063 - samples/sec: 67.26 - lr: 0.006250 2022-11-01 17:25:49,473 epoch 106 - iter 54/274 - loss 0.01383816 - samples/sec: 73.59 - lr: 0.006250 2022-11-01 17:26:02,132 epoch 106 - iter 81/274 - loss 0.01373350 - samples/sec: 68.27 - lr: 0.006250 2022-11-01 17:26:14,016 epoch 106 - iter 108/274 - loss 0.01442718 - samples/sec: 72.72 - lr: 0.006250 2022-11-01 17:26:26,053 epoch 106 - iter 135/274 - loss 0.01401087 - samples/sec: 71.80 - lr: 0.006250 2022-11-01 17:26:38,918 epoch 106 - iter 162/274 - loss 0.01399659 - samples/sec: 67.18 - lr: 0.006250 2022-11-01 17:26:51,716 epoch 106 - iter 189/274 - loss 0.01399994 - samples/sec: 67.53 - lr: 0.006250 2022-11-01 17:27:04,149 epoch 106 - iter 216/274 - loss 0.01436065 - samples/sec: 69.51 - lr: 0.006250 2022-11-01 17:27:16,644 epoch 106 - iter 243/274 - loss 0.01474534 - samples/sec: 69.17 - lr: 0.006250 2022-11-01 17:27:28,686 epoch 106 - iter 270/274 - loss 0.01480237 - samples/sec: 71.77 - lr: 0.006250 2022-11-01 17:27:30,054 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:27:30,054 EPOCH 106 done: loss 0.0147 - lr 0.006250 2022-11-01 17:27:55,476 Evaluating as a multi-label problem: False 2022-11-01 17:27:55,492 TEST : loss 0.03141792118549347 - f1-score (micro avg) 0.8558 2022-11-01 17:27:55,546 BAD EPOCHS (no improvement): 1 2022-11-01 17:27:55,639 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:28:08,177 epoch 107 - iter 27/274 - loss 0.01872842 - samples/sec: 68.93 - lr: 0.006250 2022-11-01 17:28:19,630 epoch 107 - iter 54/274 - loss 0.01616813 - samples/sec: 75.46 - lr: 0.006250 2022-11-01 17:28:32,113 epoch 107 - iter 81/274 - loss 0.01536312 - samples/sec: 69.23 - lr: 0.006250 2022-11-01 17:28:44,519 epoch 107 - iter 108/274 - loss 0.01581316 - samples/sec: 69.67 - lr: 0.006250 2022-11-01 17:28:57,543 epoch 107 - iter 135/274 - loss 0.01573153 - samples/sec: 66.35 - lr: 0.006250 2022-11-01 17:29:09,596 epoch 107 - iter 162/274 - loss 0.01590482 - samples/sec: 71.71 - lr: 0.006250 2022-11-01 17:29:21,223 epoch 107 - iter 189/274 - loss 0.01568356 - samples/sec: 74.32 - lr: 0.006250 2022-11-01 17:29:35,337 epoch 107 - iter 216/274 - loss 0.01557378 - samples/sec: 61.23 - lr: 0.006250 2022-11-01 17:29:47,568 epoch 107 - iter 243/274 - loss 0.01547147 - samples/sec: 70.66 - lr: 0.006250 2022-11-01 17:30:00,199 epoch 107 - iter 270/274 - loss 0.01556995 - samples/sec: 68.42 - lr: 0.006250 2022-11-01 17:30:02,023 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:30:02,024 EPOCH 107 done: loss 0.0156 - lr 0.006250 2022-11-01 17:30:26,714 Evaluating as a multi-label problem: False 2022-11-01 17:30:26,729 TEST : loss 0.031312357634305954 - f1-score (micro avg) 0.8558 2022-11-01 17:30:26,780 BAD EPOCHS (no improvement): 2 2022-11-01 17:30:26,872 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:30:39,718 epoch 108 - iter 27/274 - loss 0.01390738 - samples/sec: 67.28 - lr: 0.006250 2022-11-01 17:30:52,052 epoch 108 - iter 54/274 - loss 0.01439151 - samples/sec: 70.07 - lr: 0.006250 2022-11-01 17:31:05,111 epoch 108 - iter 81/274 - loss 0.01442134 - samples/sec: 66.17 - lr: 0.006250 2022-11-01 17:31:16,827 epoch 108 - iter 108/274 - loss 0.01435974 - samples/sec: 73.77 - lr: 0.006250 2022-11-01 17:31:29,153 epoch 108 - iter 135/274 - loss 0.01387339 - samples/sec: 70.11 - lr: 0.006250 2022-11-01 17:31:43,801 epoch 108 - iter 162/274 - loss 0.01425564 - samples/sec: 59.00 - lr: 0.006250 2022-11-01 17:31:55,727 epoch 108 - iter 189/274 - loss 0.01421163 - samples/sec: 72.46 - lr: 0.006250 2022-11-01 17:32:07,607 epoch 108 - iter 216/274 - loss 0.01410484 - samples/sec: 72.75 - lr: 0.006250 2022-11-01 17:32:20,751 epoch 108 - iter 243/274 - loss 0.01457425 - samples/sec: 65.75 - lr: 0.006250 2022-11-01 17:32:32,581 epoch 108 - iter 270/274 - loss 0.01465172 - samples/sec: 73.05 - lr: 0.006250 2022-11-01 17:32:34,099 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:32:34,100 EPOCH 108 done: loss 0.0148 - lr 0.006250 2022-11-01 17:32:58,961 Evaluating as a multi-label problem: False 2022-11-01 17:32:58,977 TEST : loss 0.031135080382227898 - f1-score (micro avg) 0.8554 2022-11-01 17:32:59,030 BAD EPOCHS (no improvement): 3 2022-11-01 17:32:59,122 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:33:12,240 epoch 109 - iter 27/274 - loss 0.01912379 - samples/sec: 65.88 - lr: 0.006250 2022-11-01 17:33:24,444 epoch 109 - iter 54/274 - loss 0.01804758 - samples/sec: 70.82 - lr: 0.006250 2022-11-01 17:33:37,289 epoch 109 - iter 81/274 - loss 0.01646409 - samples/sec: 67.28 - lr: 0.006250 2022-11-01 17:33:49,388 epoch 109 - iter 108/274 - loss 0.01560171 - samples/sec: 71.43 - lr: 0.006250 2022-11-01 17:34:01,172 epoch 109 - iter 135/274 - loss 0.01511687 - samples/sec: 73.34 - lr: 0.006250 2022-11-01 17:34:12,746 epoch 109 - iter 162/274 - loss 0.01504958 - samples/sec: 74.68 - lr: 0.006250 2022-11-01 17:34:25,860 epoch 109 - iter 189/274 - loss 0.01522205 - samples/sec: 65.90 - lr: 0.006250 2022-11-01 17:34:38,292 epoch 109 - iter 216/274 - loss 0.01524269 - samples/sec: 69.52 - lr: 0.006250 2022-11-01 17:34:51,412 epoch 109 - iter 243/274 - loss 0.01492633 - samples/sec: 65.87 - lr: 0.006250 2022-11-01 17:35:04,115 epoch 109 - iter 270/274 - loss 0.01465676 - samples/sec: 68.04 - lr: 0.006250 2022-11-01 17:35:05,583 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:35:05,583 EPOCH 109 done: loss 0.0147 - lr 0.006250 2022-11-01 17:35:30,502 Evaluating as a multi-label problem: False 2022-11-01 17:35:30,517 TEST : loss 0.031781088560819626 - f1-score (micro avg) 0.8552 2022-11-01 17:35:30,570 Epoch 109: reducing learning rate of group 0 to 3.1250e-03. 2022-11-01 17:35:30,571 BAD EPOCHS (no improvement): 4 2022-11-01 17:35:30,662 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:35:43,277 epoch 110 - iter 27/274 - loss 0.01618152 - samples/sec: 68.51 - lr: 0.003125 2022-11-01 17:35:57,703 epoch 110 - iter 54/274 - loss 0.01398249 - samples/sec: 59.91 - lr: 0.003125 2022-11-01 17:36:11,539 epoch 110 - iter 81/274 - loss 0.01436806 - samples/sec: 62.46 - lr: 0.003125 2022-11-01 17:36:23,687 epoch 110 - iter 108/274 - loss 0.01402755 - samples/sec: 71.14 - lr: 0.003125 2022-11-01 17:36:35,831 epoch 110 - iter 135/274 - loss 0.01429670 - samples/sec: 71.17 - lr: 0.003125 2022-11-01 17:36:47,885 epoch 110 - iter 162/274 - loss 0.01429064 - samples/sec: 71.69 - lr: 0.003125 2022-11-01 17:36:59,675 epoch 110 - iter 189/274 - loss 0.01471822 - samples/sec: 73.30 - lr: 0.003125 2022-11-01 17:37:12,360 epoch 110 - iter 216/274 - loss 0.01430368 - samples/sec: 68.13 - lr: 0.003125 2022-11-01 17:37:23,509 epoch 110 - iter 243/274 - loss 0.01448710 - samples/sec: 77.52 - lr: 0.003125 2022-11-01 17:37:35,507 epoch 110 - iter 270/274 - loss 0.01446019 - samples/sec: 72.03 - lr: 0.003125 2022-11-01 17:37:37,495 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:37:37,495 EPOCH 110 done: loss 0.0144 - lr 0.003125 2022-11-01 17:38:02,941 Evaluating as a multi-label problem: False 2022-11-01 17:38:02,956 TEST : loss 0.031605690717697144 - f1-score (micro avg) 0.8551 2022-11-01 17:38:03,011 BAD EPOCHS (no improvement): 0 2022-11-01 17:38:03,085 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:38:15,036 epoch 111 - iter 27/274 - loss 0.01596760 - samples/sec: 72.32 - lr: 0.003125 2022-11-01 17:38:28,050 epoch 111 - iter 54/274 - loss 0.01611072 - samples/sec: 66.40 - lr: 0.003125 2022-11-01 17:38:41,281 epoch 111 - iter 81/274 - loss 0.01586174 - samples/sec: 65.32 - lr: 0.003125 2022-11-01 17:38:54,263 epoch 111 - iter 108/274 - loss 0.01557685 - samples/sec: 66.57 - lr: 0.003125 2022-11-01 17:39:08,244 epoch 111 - iter 135/274 - loss 0.01580835 - samples/sec: 61.81 - lr: 0.003125 2022-11-01 17:39:19,514 epoch 111 - iter 162/274 - loss 0.01606974 - samples/sec: 76.68 - lr: 0.003125 2022-11-01 17:39:31,520 epoch 111 - iter 189/274 - loss 0.01547722 - samples/sec: 71.98 - lr: 0.003125 2022-11-01 17:39:42,815 epoch 111 - iter 216/274 - loss 0.01515104 - samples/sec: 76.52 - lr: 0.003125 2022-11-01 17:39:54,557 epoch 111 - iter 243/274 - loss 0.01496053 - samples/sec: 73.60 - lr: 0.003125 2022-11-01 17:40:07,087 epoch 111 - iter 270/274 - loss 0.01483213 - samples/sec: 68.97 - lr: 0.003125 2022-11-01 17:40:08,469 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:40:08,469 EPOCH 111 done: loss 0.0149 - lr 0.003125 2022-11-01 17:40:33,329 Evaluating as a multi-label problem: False 2022-11-01 17:40:33,344 TEST : loss 0.031536173075437546 - f1-score (micro avg) 0.8541 2022-11-01 17:40:33,396 BAD EPOCHS (no improvement): 1 2022-11-01 17:40:33,470 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:40:46,575 epoch 112 - iter 27/274 - loss 0.01439567 - samples/sec: 65.95 - lr: 0.003125 2022-11-01 17:40:58,836 epoch 112 - iter 54/274 - loss 0.01354366 - samples/sec: 70.48 - lr: 0.003125 2022-11-01 17:41:10,562 epoch 112 - iter 81/274 - loss 0.01444438 - samples/sec: 73.70 - lr: 0.003125 2022-11-01 17:41:24,112 epoch 112 - iter 108/274 - loss 0.01493261 - samples/sec: 63.78 - lr: 0.003125 2022-11-01 17:41:35,909 epoch 112 - iter 135/274 - loss 0.01562564 - samples/sec: 73.26 - lr: 0.003125 2022-11-01 17:41:48,092 epoch 112 - iter 162/274 - loss 0.01544606 - samples/sec: 70.94 - lr: 0.003125 2022-11-01 17:42:00,153 epoch 112 - iter 189/274 - loss 0.01543938 - samples/sec: 71.65 - lr: 0.003125 2022-11-01 17:42:12,466 epoch 112 - iter 216/274 - loss 0.01503371 - samples/sec: 70.19 - lr: 0.003125 2022-11-01 17:42:24,873 epoch 112 - iter 243/274 - loss 0.01527409 - samples/sec: 69.66 - lr: 0.003125 2022-11-01 17:42:37,180 epoch 112 - iter 270/274 - loss 0.01508578 - samples/sec: 70.22 - lr: 0.003125 2022-11-01 17:42:38,763 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:42:38,763 EPOCH 112 done: loss 0.0151 - lr 0.003125 2022-11-01 17:43:04,124 Evaluating as a multi-label problem: False 2022-11-01 17:43:04,139 TEST : loss 0.031474340707063675 - f1-score (micro avg) 0.855 2022-11-01 17:43:04,191 BAD EPOCHS (no improvement): 2 2022-11-01 17:43:04,280 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:43:16,911 epoch 113 - iter 27/274 - loss 0.01609706 - samples/sec: 68.43 - lr: 0.003125 2022-11-01 17:43:29,310 epoch 113 - iter 54/274 - loss 0.01433556 - samples/sec: 69.70 - lr: 0.003125 2022-11-01 17:43:42,128 epoch 113 - iter 81/274 - loss 0.01434582 - samples/sec: 67.42 - lr: 0.003125 2022-11-01 17:43:55,192 epoch 113 - iter 108/274 - loss 0.01474083 - samples/sec: 66.16 - lr: 0.003125 2022-11-01 17:44:07,374 epoch 113 - iter 135/274 - loss 0.01445667 - samples/sec: 70.94 - lr: 0.003125 2022-11-01 17:44:19,671 epoch 113 - iter 162/274 - loss 0.01481096 - samples/sec: 70.28 - lr: 0.003125 2022-11-01 17:44:31,736 epoch 113 - iter 189/274 - loss 0.01481574 - samples/sec: 71.64 - lr: 0.003125 2022-11-01 17:44:45,034 epoch 113 - iter 216/274 - loss 0.01524675 - samples/sec: 64.99 - lr: 0.003125 2022-11-01 17:44:58,586 epoch 113 - iter 243/274 - loss 0.01492049 - samples/sec: 63.77 - lr: 0.003125 2022-11-01 17:45:09,603 epoch 113 - iter 270/274 - loss 0.01468932 - samples/sec: 78.45 - lr: 0.003125 2022-11-01 17:45:11,032 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:45:11,032 EPOCH 113 done: loss 0.0147 - lr 0.003125 2022-11-01 17:45:36,455 Evaluating as a multi-label problem: False 2022-11-01 17:45:36,471 TEST : loss 0.031519342213869095 - f1-score (micro avg) 0.8545 2022-11-01 17:45:36,523 BAD EPOCHS (no improvement): 3 2022-11-01 17:45:36,616 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:45:49,215 epoch 114 - iter 27/274 - loss 0.01487123 - samples/sec: 68.60 - lr: 0.003125 2022-11-01 17:46:00,350 epoch 114 - iter 54/274 - loss 0.01485395 - samples/sec: 77.61 - lr: 0.003125 2022-11-01 17:46:13,743 epoch 114 - iter 81/274 - loss 0.01571063 - samples/sec: 64.53 - lr: 0.003125 2022-11-01 17:46:25,662 epoch 114 - iter 108/274 - loss 0.01471453 - samples/sec: 72.51 - lr: 0.003125 2022-11-01 17:46:38,373 epoch 114 - iter 135/274 - loss 0.01512168 - samples/sec: 67.99 - lr: 0.003125 2022-11-01 17:46:50,844 epoch 114 - iter 162/274 - loss 0.01516243 - samples/sec: 69.30 - lr: 0.003125 2022-11-01 17:47:04,008 epoch 114 - iter 189/274 - loss 0.01502249 - samples/sec: 65.65 - lr: 0.003125 2022-11-01 17:47:15,595 epoch 114 - iter 216/274 - loss 0.01471831 - samples/sec: 74.58 - lr: 0.003125 2022-11-01 17:47:29,477 epoch 114 - iter 243/274 - loss 0.01445627 - samples/sec: 62.25 - lr: 0.003125 2022-11-01 17:47:40,993 epoch 114 - iter 270/274 - loss 0.01491303 - samples/sec: 75.05 - lr: 0.003125 2022-11-01 17:47:43,070 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:47:43,070 EPOCH 114 done: loss 0.0150 - lr 0.003125 2022-11-01 17:48:08,286 Evaluating as a multi-label problem: False 2022-11-01 17:48:08,302 TEST : loss 0.031727951020002365 - f1-score (micro avg) 0.8533 2022-11-01 17:48:08,354 Epoch 114: reducing learning rate of group 0 to 1.5625e-03. 2022-11-01 17:48:08,354 BAD EPOCHS (no improvement): 4 2022-11-01 17:48:08,429 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:48:21,757 epoch 115 - iter 27/274 - loss 0.01438955 - samples/sec: 64.85 - lr: 0.001563 2022-11-01 17:48:35,019 epoch 115 - iter 54/274 - loss 0.01465102 - samples/sec: 65.16 - lr: 0.001563 2022-11-01 17:48:48,715 epoch 115 - iter 81/274 - loss 0.01452675 - samples/sec: 63.10 - lr: 0.001563 2022-11-01 17:49:00,439 epoch 115 - iter 108/274 - loss 0.01446702 - samples/sec: 73.71 - lr: 0.001563 2022-11-01 17:49:13,470 epoch 115 - iter 135/274 - loss 0.01355820 - samples/sec: 66.32 - lr: 0.001563 2022-11-01 17:49:26,293 epoch 115 - iter 162/274 - loss 0.01370481 - samples/sec: 67.40 - lr: 0.001563 2022-11-01 17:49:38,891 epoch 115 - iter 189/274 - loss 0.01345347 - samples/sec: 68.60 - lr: 0.001563 2022-11-01 17:49:50,147 epoch 115 - iter 216/274 - loss 0.01344039 - samples/sec: 76.78 - lr: 0.001563 2022-11-01 17:50:01,283 epoch 115 - iter 243/274 - loss 0.01399875 - samples/sec: 77.61 - lr: 0.001563 2022-11-01 17:50:14,106 epoch 115 - iter 270/274 - loss 0.01443076 - samples/sec: 67.40 - lr: 0.001563 2022-11-01 17:50:15,622 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:50:15,622 EPOCH 115 done: loss 0.0146 - lr 0.001563 2022-11-01 17:50:40,571 Evaluating as a multi-label problem: False 2022-11-01 17:50:40,587 TEST : loss 0.03165162727236748 - f1-score (micro avg) 0.8539 2022-11-01 17:50:40,639 BAD EPOCHS (no improvement): 1 2022-11-01 17:50:40,731 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:50:54,027 epoch 116 - iter 27/274 - loss 0.01425236 - samples/sec: 65.00 - lr: 0.001563 2022-11-01 17:51:06,232 epoch 116 - iter 54/274 - loss 0.01383829 - samples/sec: 70.81 - lr: 0.001563 2022-11-01 17:51:18,685 epoch 116 - iter 81/274 - loss 0.01359765 - samples/sec: 69.40 - lr: 0.001563 2022-11-01 17:51:29,472 epoch 116 - iter 108/274 - loss 0.01347194 - samples/sec: 80.12 - lr: 0.001563 2022-11-01 17:51:42,835 epoch 116 - iter 135/274 - loss 0.01379473 - samples/sec: 64.67 - lr: 0.001563 2022-11-01 17:51:55,231 epoch 116 - iter 162/274 - loss 0.01379061 - samples/sec: 69.72 - lr: 0.001563 2022-11-01 17:52:08,602 epoch 116 - iter 189/274 - loss 0.01405799 - samples/sec: 64.63 - lr: 0.001563 2022-11-01 17:52:19,838 epoch 116 - iter 216/274 - loss 0.01425247 - samples/sec: 76.92 - lr: 0.001563 2022-11-01 17:52:33,205 epoch 116 - iter 243/274 - loss 0.01416433 - samples/sec: 64.65 - lr: 0.001563 2022-11-01 17:52:45,518 epoch 116 - iter 270/274 - loss 0.01401386 - samples/sec: 70.19 - lr: 0.001563 2022-11-01 17:52:46,821 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:52:46,821 EPOCH 116 done: loss 0.0141 - lr 0.001563 2022-11-01 17:53:11,731 Evaluating as a multi-label problem: False 2022-11-01 17:53:11,746 TEST : loss 0.03173290938138962 - f1-score (micro avg) 0.8549 2022-11-01 17:53:11,799 BAD EPOCHS (no improvement): 0 2022-11-01 17:53:11,891 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:53:24,606 epoch 117 - iter 27/274 - loss 0.01300331 - samples/sec: 67.97 - lr: 0.001563 2022-11-01 17:53:36,989 epoch 117 - iter 54/274 - loss 0.01595312 - samples/sec: 69.79 - lr: 0.001563 2022-11-01 17:53:48,545 epoch 117 - iter 81/274 - loss 0.01527940 - samples/sec: 74.79 - lr: 0.001563 2022-11-01 17:54:00,263 epoch 117 - iter 108/274 - loss 0.01460286 - samples/sec: 73.76 - lr: 0.001563 2022-11-01 17:54:12,584 epoch 117 - iter 135/274 - loss 0.01422859 - samples/sec: 70.14 - lr: 0.001563 2022-11-01 17:54:25,742 epoch 117 - iter 162/274 - loss 0.01434427 - samples/sec: 65.68 - lr: 0.001563 2022-11-01 17:54:38,379 epoch 117 - iter 189/274 - loss 0.01401961 - samples/sec: 68.39 - lr: 0.001563 2022-11-01 17:54:51,636 epoch 117 - iter 216/274 - loss 0.01447595 - samples/sec: 65.19 - lr: 0.001563 2022-11-01 17:55:04,763 epoch 117 - iter 243/274 - loss 0.01405447 - samples/sec: 65.84 - lr: 0.001563 2022-11-01 17:55:17,004 epoch 117 - iter 270/274 - loss 0.01409952 - samples/sec: 70.60 - lr: 0.001563 2022-11-01 17:55:18,621 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:55:18,621 EPOCH 117 done: loss 0.0141 - lr 0.001563 2022-11-01 17:55:43,762 Evaluating as a multi-label problem: False 2022-11-01 17:55:43,777 TEST : loss 0.03180387616157532 - f1-score (micro avg) 0.8554 2022-11-01 17:55:43,830 BAD EPOCHS (no improvement): 0 2022-11-01 17:55:43,922 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:55:55,269 epoch 118 - iter 27/274 - loss 0.01405596 - samples/sec: 76.17 - lr: 0.001563 2022-11-01 17:56:06,720 epoch 118 - iter 54/274 - loss 0.01339267 - samples/sec: 75.48 - lr: 0.001563 2022-11-01 17:56:20,308 epoch 118 - iter 81/274 - loss 0.01339778 - samples/sec: 63.60 - lr: 0.001563 2022-11-01 17:56:32,577 epoch 118 - iter 108/274 - loss 0.01319099 - samples/sec: 70.44 - lr: 0.001563 2022-11-01 17:56:44,998 epoch 118 - iter 135/274 - loss 0.01301660 - samples/sec: 69.58 - lr: 0.001563 2022-11-01 17:56:56,910 epoch 118 - iter 162/274 - loss 0.01359261 - samples/sec: 72.55 - lr: 0.001563 2022-11-01 17:57:08,695 epoch 118 - iter 189/274 - loss 0.01402305 - samples/sec: 73.33 - lr: 0.001563 2022-11-01 17:57:20,558 epoch 118 - iter 216/274 - loss 0.01374466 - samples/sec: 72.85 - lr: 0.001563 2022-11-01 17:57:33,907 epoch 118 - iter 243/274 - loss 0.01374517 - samples/sec: 64.74 - lr: 0.001563 2022-11-01 17:57:46,542 epoch 118 - iter 270/274 - loss 0.01403553 - samples/sec: 68.40 - lr: 0.001563 2022-11-01 17:57:47,973 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:57:47,973 EPOCH 118 done: loss 0.0140 - lr 0.001563 2022-11-01 17:58:13,100 Evaluating as a multi-label problem: False 2022-11-01 17:58:13,116 TEST : loss 0.03177444264292717 - f1-score (micro avg) 0.8549 2022-11-01 17:58:13,167 BAD EPOCHS (no improvement): 0 2022-11-01 17:58:13,258 ---------------------------------------------------------------------------------------------------- 2022-11-01 17:58:25,375 epoch 119 - iter 27/274 - loss 0.01538861 - samples/sec: 71.33 - lr: 0.001563 2022-11-01 17:58:38,665 epoch 119 - iter 54/274 - loss 0.01428429 - samples/sec: 65.03 - lr: 0.001563 2022-11-01 17:58:50,968 epoch 119 - iter 81/274 - loss 0.01545027 - samples/sec: 70.24 - lr: 0.001563 2022-11-01 17:59:03,236 epoch 119 - iter 108/274 - loss 0.01576570 - samples/sec: 70.45 - lr: 0.001563 2022-11-01 17:59:15,846 epoch 119 - iter 135/274 - loss 0.01500808 - samples/sec: 68.53 - lr: 0.001563 2022-11-01 17:59:28,587 epoch 119 - iter 162/274 - loss 0.01529803 - samples/sec: 67.83 - lr: 0.001563 2022-11-01 17:59:40,199 epoch 119 - iter 189/274 - loss 0.01492457 - samples/sec: 74.43 - lr: 0.001563 2022-11-01 17:59:53,221 epoch 119 - iter 216/274 - loss 0.01480307 - samples/sec: 66.37 - lr: 0.001563 2022-11-01 18:00:05,989 epoch 119 - iter 243/274 - loss 0.01461764 - samples/sec: 67.69 - lr: 0.001563 2022-11-01 18:00:18,288 epoch 119 - iter 270/274 - loss 0.01486278 - samples/sec: 70.27 - lr: 0.001563 2022-11-01 18:00:19,889 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:00:19,889 EPOCH 119 done: loss 0.0150 - lr 0.001563 2022-11-01 18:00:45,262 Evaluating as a multi-label problem: False 2022-11-01 18:00:45,278 TEST : loss 0.03172260522842407 - f1-score (micro avg) 0.8543 2022-11-01 18:00:45,330 BAD EPOCHS (no improvement): 1 2022-11-01 18:00:45,422 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:00:57,044 epoch 120 - iter 27/274 - loss 0.00899055 - samples/sec: 74.37 - lr: 0.001563 2022-11-01 18:01:09,522 epoch 120 - iter 54/274 - loss 0.01259727 - samples/sec: 69.26 - lr: 0.001563 2022-11-01 18:01:22,694 epoch 120 - iter 81/274 - loss 0.01366828 - samples/sec: 65.61 - lr: 0.001563 2022-11-01 18:01:34,264 epoch 120 - iter 108/274 - loss 0.01391092 - samples/sec: 74.69 - lr: 0.001563 2022-11-01 18:01:45,942 epoch 120 - iter 135/274 - loss 0.01388514 - samples/sec: 74.00 - lr: 0.001563 2022-11-01 18:01:58,326 epoch 120 - iter 162/274 - loss 0.01440931 - samples/sec: 69.79 - lr: 0.001563 2022-11-01 18:02:11,386 epoch 120 - iter 189/274 - loss 0.01447825 - samples/sec: 66.17 - lr: 0.001563 2022-11-01 18:02:24,050 epoch 120 - iter 216/274 - loss 0.01423748 - samples/sec: 68.24 - lr: 0.001563 2022-11-01 18:02:35,638 epoch 120 - iter 243/274 - loss 0.01403297 - samples/sec: 74.58 - lr: 0.001563 2022-11-01 18:02:49,124 epoch 120 - iter 270/274 - loss 0.01421427 - samples/sec: 64.08 - lr: 0.001563 2022-11-01 18:02:51,039 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:02:51,039 EPOCH 120 done: loss 0.0142 - lr 0.001563 2022-11-01 18:03:16,381 Evaluating as a multi-label problem: False 2022-11-01 18:03:16,397 TEST : loss 0.031805865466594696 - f1-score (micro avg) 0.8541 2022-11-01 18:03:16,449 BAD EPOCHS (no improvement): 2 2022-11-01 18:03:16,534 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:03:28,361 epoch 121 - iter 27/274 - loss 0.01605437 - samples/sec: 73.07 - lr: 0.001563 2022-11-01 18:03:40,389 epoch 121 - iter 54/274 - loss 0.01495214 - samples/sec: 71.86 - lr: 0.001563 2022-11-01 18:03:52,570 epoch 121 - iter 81/274 - loss 0.01478860 - samples/sec: 70.95 - lr: 0.001563 2022-11-01 18:04:05,835 epoch 121 - iter 108/274 - loss 0.01482221 - samples/sec: 65.15 - lr: 0.001563 2022-11-01 18:04:19,311 epoch 121 - iter 135/274 - loss 0.01481010 - samples/sec: 64.13 - lr: 0.001563 2022-11-01 18:04:31,812 epoch 121 - iter 162/274 - loss 0.01420799 - samples/sec: 69.13 - lr: 0.001563 2022-11-01 18:04:45,297 epoch 121 - iter 189/274 - loss 0.01428585 - samples/sec: 64.09 - lr: 0.001563 2022-11-01 18:04:56,845 epoch 121 - iter 216/274 - loss 0.01414983 - samples/sec: 74.84 - lr: 0.001563 2022-11-01 18:05:10,343 epoch 121 - iter 243/274 - loss 0.01463416 - samples/sec: 64.02 - lr: 0.001563 2022-11-01 18:05:22,196 epoch 121 - iter 270/274 - loss 0.01435355 - samples/sec: 72.92 - lr: 0.001563 2022-11-01 18:05:23,959 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:05:23,959 EPOCH 121 done: loss 0.0143 - lr 0.001563 2022-11-01 18:05:49,338 Evaluating as a multi-label problem: False 2022-11-01 18:05:49,354 TEST : loss 0.03179682791233063 - f1-score (micro avg) 0.8553 2022-11-01 18:05:49,405 BAD EPOCHS (no improvement): 3 2022-11-01 18:05:49,496 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:06:02,504 epoch 122 - iter 27/274 - loss 0.01348554 - samples/sec: 66.44 - lr: 0.001563 2022-11-01 18:06:15,580 epoch 122 - iter 54/274 - loss 0.01432921 - samples/sec: 66.10 - lr: 0.001563 2022-11-01 18:06:28,964 epoch 122 - iter 81/274 - loss 0.01316887 - samples/sec: 64.57 - lr: 0.001563 2022-11-01 18:06:40,994 epoch 122 - iter 108/274 - loss 0.01422191 - samples/sec: 71.84 - lr: 0.001563 2022-11-01 18:06:52,690 epoch 122 - iter 135/274 - loss 0.01408750 - samples/sec: 73.89 - lr: 0.001563 2022-11-01 18:07:04,944 epoch 122 - iter 162/274 - loss 0.01386067 - samples/sec: 70.53 - lr: 0.001563 2022-11-01 18:07:17,208 epoch 122 - iter 189/274 - loss 0.01357114 - samples/sec: 70.47 - lr: 0.001563 2022-11-01 18:07:29,672 epoch 122 - iter 216/274 - loss 0.01412466 - samples/sec: 69.33 - lr: 0.001563 2022-11-01 18:07:42,807 epoch 122 - iter 243/274 - loss 0.01395056 - samples/sec: 65.79 - lr: 0.001563 2022-11-01 18:07:55,077 epoch 122 - iter 270/274 - loss 0.01399248 - samples/sec: 70.44 - lr: 0.001563 2022-11-01 18:07:57,015 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:07:57,015 EPOCH 122 done: loss 0.0140 - lr 0.001563 2022-11-01 18:08:22,422 Evaluating as a multi-label problem: False 2022-11-01 18:08:22,438 TEST : loss 0.03200670704245567 - f1-score (micro avg) 0.8546 2022-11-01 18:08:22,489 BAD EPOCHS (no improvement): 0 2022-11-01 18:08:22,581 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:08:35,223 epoch 123 - iter 27/274 - loss 0.01535170 - samples/sec: 68.37 - lr: 0.001563 2022-11-01 18:08:46,897 epoch 123 - iter 54/274 - loss 0.01369532 - samples/sec: 74.03 - lr: 0.001563 2022-11-01 18:08:59,453 epoch 123 - iter 81/274 - loss 0.01398782 - samples/sec: 68.83 - lr: 0.001563 2022-11-01 18:09:11,954 epoch 123 - iter 108/274 - loss 0.01383519 - samples/sec: 69.13 - lr: 0.001563 2022-11-01 18:09:26,337 epoch 123 - iter 135/274 - loss 0.01394853 - samples/sec: 60.08 - lr: 0.001563 2022-11-01 18:09:37,371 epoch 123 - iter 162/274 - loss 0.01390282 - samples/sec: 78.33 - lr: 0.001563 2022-11-01 18:09:49,682 epoch 123 - iter 189/274 - loss 0.01422790 - samples/sec: 70.20 - lr: 0.001563 2022-11-01 18:10:02,333 epoch 123 - iter 216/274 - loss 0.01462927 - samples/sec: 68.31 - lr: 0.001563 2022-11-01 18:10:13,694 epoch 123 - iter 243/274 - loss 0.01470027 - samples/sec: 76.07 - lr: 0.001563 2022-11-01 18:10:26,453 epoch 123 - iter 270/274 - loss 0.01468566 - samples/sec: 67.73 - lr: 0.001563 2022-11-01 18:10:28,284 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:10:28,284 EPOCH 123 done: loss 0.0147 - lr 0.001563 2022-11-01 18:10:53,622 Evaluating as a multi-label problem: False 2022-11-01 18:10:53,638 TEST : loss 0.03187215328216553 - f1-score (micro avg) 0.8541 2022-11-01 18:10:53,691 BAD EPOCHS (no improvement): 1 2022-11-01 18:10:53,786 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:11:07,362 epoch 124 - iter 27/274 - loss 0.01179336 - samples/sec: 63.66 - lr: 0.001563 2022-11-01 18:11:19,048 epoch 124 - iter 54/274 - loss 0.01307793 - samples/sec: 73.95 - lr: 0.001563 2022-11-01 18:11:31,062 epoch 124 - iter 81/274 - loss 0.01339808 - samples/sec: 71.94 - lr: 0.001563 2022-11-01 18:11:42,429 epoch 124 - iter 108/274 - loss 0.01306621 - samples/sec: 76.03 - lr: 0.001563 2022-11-01 18:11:54,785 epoch 124 - iter 135/274 - loss 0.01296568 - samples/sec: 69.94 - lr: 0.001563 2022-11-01 18:12:06,411 epoch 124 - iter 162/274 - loss 0.01327152 - samples/sec: 74.34 - lr: 0.001563 2022-11-01 18:12:18,715 epoch 124 - iter 189/274 - loss 0.01373990 - samples/sec: 70.24 - lr: 0.001563 2022-11-01 18:12:31,980 epoch 124 - iter 216/274 - loss 0.01394854 - samples/sec: 65.15 - lr: 0.001563 2022-11-01 18:12:44,200 epoch 124 - iter 243/274 - loss 0.01405277 - samples/sec: 70.73 - lr: 0.001563 2022-11-01 18:12:57,416 epoch 124 - iter 270/274 - loss 0.01405971 - samples/sec: 65.39 - lr: 0.001563 2022-11-01 18:12:59,384 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:12:59,384 EPOCH 124 done: loss 0.0141 - lr 0.001563 2022-11-01 18:13:24,782 Evaluating as a multi-label problem: False 2022-11-01 18:13:24,798 TEST : loss 0.03188449889421463 - f1-score (micro avg) 0.8543 2022-11-01 18:13:24,850 BAD EPOCHS (no improvement): 2 2022-11-01 18:13:24,945 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:13:37,316 epoch 125 - iter 27/274 - loss 0.01168586 - samples/sec: 69.86 - lr: 0.001563 2022-11-01 18:13:51,327 epoch 125 - iter 54/274 - loss 0.01431803 - samples/sec: 61.68 - lr: 0.001563 2022-11-01 18:14:03,919 epoch 125 - iter 81/274 - loss 0.01415967 - samples/sec: 68.63 - lr: 0.001563 2022-11-01 18:14:16,961 epoch 125 - iter 108/274 - loss 0.01380225 - samples/sec: 66.26 - lr: 0.001563 2022-11-01 18:14:28,811 epoch 125 - iter 135/274 - loss 0.01381803 - samples/sec: 72.93 - lr: 0.001563 2022-11-01 18:14:41,675 epoch 125 - iter 162/274 - loss 0.01389812 - samples/sec: 67.18 - lr: 0.001563 2022-11-01 18:14:53,191 epoch 125 - iter 189/274 - loss 0.01408517 - samples/sec: 75.05 - lr: 0.001563 2022-11-01 18:15:05,054 epoch 125 - iter 216/274 - loss 0.01435856 - samples/sec: 72.85 - lr: 0.001563 2022-11-01 18:15:17,052 epoch 125 - iter 243/274 - loss 0.01424790 - samples/sec: 72.04 - lr: 0.001563 2022-11-01 18:15:29,655 epoch 125 - iter 270/274 - loss 0.01424784 - samples/sec: 68.57 - lr: 0.001563 2022-11-01 18:15:31,485 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:15:31,485 EPOCH 125 done: loss 0.0142 - lr 0.001563 2022-11-01 18:15:56,846 Evaluating as a multi-label problem: False 2022-11-01 18:15:56,861 TEST : loss 0.03190324455499649 - f1-score (micro avg) 0.8544 2022-11-01 18:15:56,915 BAD EPOCHS (no improvement): 3 2022-11-01 18:15:57,007 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:16:10,448 epoch 126 - iter 27/274 - loss 0.01233038 - samples/sec: 64.30 - lr: 0.001563 2022-11-01 18:16:22,275 epoch 126 - iter 54/274 - loss 0.01381905 - samples/sec: 73.07 - lr: 0.001563 2022-11-01 18:16:34,930 epoch 126 - iter 81/274 - loss 0.01419482 - samples/sec: 68.30 - lr: 0.001563 2022-11-01 18:16:46,563 epoch 126 - iter 108/274 - loss 0.01483839 - samples/sec: 74.29 - lr: 0.001563 2022-11-01 18:16:58,287 epoch 126 - iter 135/274 - loss 0.01521833 - samples/sec: 73.72 - lr: 0.001563 2022-11-01 18:17:09,874 epoch 126 - iter 162/274 - loss 0.01466584 - samples/sec: 74.59 - lr: 0.001563 2022-11-01 18:17:24,081 epoch 126 - iter 189/274 - loss 0.01470213 - samples/sec: 60.83 - lr: 0.001563 2022-11-01 18:17:36,797 epoch 126 - iter 216/274 - loss 0.01444898 - samples/sec: 67.96 - lr: 0.001563 2022-11-01 18:17:48,690 epoch 126 - iter 243/274 - loss 0.01437726 - samples/sec: 72.67 - lr: 0.001563 2022-11-01 18:18:00,074 epoch 126 - iter 270/274 - loss 0.01456913 - samples/sec: 75.92 - lr: 0.001563 2022-11-01 18:18:01,780 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:18:01,780 EPOCH 126 done: loss 0.0145 - lr 0.001563 2022-11-01 18:18:27,195 Evaluating as a multi-label problem: False 2022-11-01 18:18:27,211 TEST : loss 0.031878840178251266 - f1-score (micro avg) 0.8544 2022-11-01 18:18:27,263 Epoch 126: reducing learning rate of group 0 to 7.8125e-04. 2022-11-01 18:18:27,263 BAD EPOCHS (no improvement): 4 2022-11-01 18:18:27,356 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:18:38,405 epoch 127 - iter 27/274 - loss 0.01214851 - samples/sec: 78.22 - lr: 0.000781 2022-11-01 18:18:51,529 epoch 127 - iter 54/274 - loss 0.01322803 - samples/sec: 65.85 - lr: 0.000781 2022-11-01 18:19:03,957 epoch 127 - iter 81/274 - loss 0.01371365 - samples/sec: 69.54 - lr: 0.000781 2022-11-01 18:19:17,792 epoch 127 - iter 108/274 - loss 0.01357113 - samples/sec: 62.46 - lr: 0.000781 2022-11-01 18:19:30,305 epoch 127 - iter 135/274 - loss 0.01397682 - samples/sec: 69.07 - lr: 0.000781 2022-11-01 18:19:44,368 epoch 127 - iter 162/274 - loss 0.01396536 - samples/sec: 61.45 - lr: 0.000781 2022-11-01 18:19:55,789 epoch 127 - iter 189/274 - loss 0.01376907 - samples/sec: 75.68 - lr: 0.000781 2022-11-01 18:20:09,810 epoch 127 - iter 216/274 - loss 0.01406742 - samples/sec: 61.64 - lr: 0.000781 2022-11-01 18:20:20,817 epoch 127 - iter 243/274 - loss 0.01420367 - samples/sec: 78.52 - lr: 0.000781 2022-11-01 18:20:32,276 epoch 127 - iter 270/274 - loss 0.01427245 - samples/sec: 75.42 - lr: 0.000781 2022-11-01 18:20:33,974 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:20:33,975 EPOCH 127 done: loss 0.0141 - lr 0.000781 2022-11-01 18:20:59,316 Evaluating as a multi-label problem: False 2022-11-01 18:20:59,332 TEST : loss 0.031853314489126205 - f1-score (micro avg) 0.8541 2022-11-01 18:20:59,384 BAD EPOCHS (no improvement): 1 2022-11-01 18:20:59,476 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:21:12,554 epoch 128 - iter 27/274 - loss 0.01442018 - samples/sec: 66.08 - lr: 0.000781 2022-11-01 18:21:25,402 epoch 128 - iter 54/274 - loss 0.01455128 - samples/sec: 67.26 - lr: 0.000781 2022-11-01 18:21:37,344 epoch 128 - iter 81/274 - loss 0.01443058 - samples/sec: 72.37 - lr: 0.000781 2022-11-01 18:21:49,031 epoch 128 - iter 108/274 - loss 0.01426873 - samples/sec: 73.95 - lr: 0.000781 2022-11-01 18:22:01,548 epoch 128 - iter 135/274 - loss 0.01495891 - samples/sec: 69.04 - lr: 0.000781 2022-11-01 18:22:13,136 epoch 128 - iter 162/274 - loss 0.01507623 - samples/sec: 74.58 - lr: 0.000781 2022-11-01 18:22:25,508 epoch 128 - iter 189/274 - loss 0.01498890 - samples/sec: 69.85 - lr: 0.000781 2022-11-01 18:22:38,731 epoch 128 - iter 216/274 - loss 0.01477757 - samples/sec: 65.36 - lr: 0.000781 2022-11-01 18:22:52,156 epoch 128 - iter 243/274 - loss 0.01465474 - samples/sec: 64.37 - lr: 0.000781 2022-11-01 18:23:04,893 epoch 128 - iter 270/274 - loss 0.01489369 - samples/sec: 67.85 - lr: 0.000781 2022-11-01 18:23:06,594 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:23:06,594 EPOCH 128 done: loss 0.0149 - lr 0.000781 2022-11-01 18:23:31,895 Evaluating as a multi-label problem: False 2022-11-01 18:23:31,911 TEST : loss 0.0317995622754097 - f1-score (micro avg) 0.8545 2022-11-01 18:23:31,962 BAD EPOCHS (no improvement): 2 2022-11-01 18:23:32,056 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:23:44,890 epoch 129 - iter 27/274 - loss 0.01701574 - samples/sec: 67.34 - lr: 0.000781 2022-11-01 18:23:56,118 epoch 129 - iter 54/274 - loss 0.01559604 - samples/sec: 76.98 - lr: 0.000781 2022-11-01 18:24:08,335 epoch 129 - iter 81/274 - loss 0.01464102 - samples/sec: 70.74 - lr: 0.000781 2022-11-01 18:24:21,755 epoch 129 - iter 108/274 - loss 0.01516544 - samples/sec: 64.39 - lr: 0.000781 2022-11-01 18:24:34,920 epoch 129 - iter 135/274 - loss 0.01553544 - samples/sec: 65.65 - lr: 0.000781 2022-11-01 18:24:46,816 epoch 129 - iter 162/274 - loss 0.01577649 - samples/sec: 72.65 - lr: 0.000781 2022-11-01 18:24:59,344 epoch 129 - iter 189/274 - loss 0.01573528 - samples/sec: 68.98 - lr: 0.000781 2022-11-01 18:25:12,318 epoch 129 - iter 216/274 - loss 0.01545947 - samples/sec: 66.61 - lr: 0.000781 2022-11-01 18:25:23,959 epoch 129 - iter 243/274 - loss 0.01549187 - samples/sec: 74.24 - lr: 0.000781 2022-11-01 18:25:36,740 epoch 129 - iter 270/274 - loss 0.01594032 - samples/sec: 67.62 - lr: 0.000781 2022-11-01 18:25:38,294 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:25:38,295 EPOCH 129 done: loss 0.0159 - lr 0.000781 2022-11-01 18:26:03,654 Evaluating as a multi-label problem: False 2022-11-01 18:26:03,669 TEST : loss 0.031778719276189804 - f1-score (micro avg) 0.8547 2022-11-01 18:26:03,722 BAD EPOCHS (no improvement): 3 2022-11-01 18:26:03,813 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:26:15,664 epoch 130 - iter 27/274 - loss 0.01545049 - samples/sec: 72.93 - lr: 0.000781 2022-11-01 18:26:28,299 epoch 130 - iter 54/274 - loss 0.01380701 - samples/sec: 68.40 - lr: 0.000781 2022-11-01 18:26:41,697 epoch 130 - iter 81/274 - loss 0.01339731 - samples/sec: 64.50 - lr: 0.000781 2022-11-01 18:26:54,110 epoch 130 - iter 108/274 - loss 0.01311691 - samples/sec: 69.62 - lr: 0.000781 2022-11-01 18:27:06,825 epoch 130 - iter 135/274 - loss 0.01372726 - samples/sec: 67.97 - lr: 0.000781 2022-11-01 18:27:18,546 epoch 130 - iter 162/274 - loss 0.01377890 - samples/sec: 73.74 - lr: 0.000781 2022-11-01 18:27:29,845 epoch 130 - iter 189/274 - loss 0.01383286 - samples/sec: 76.49 - lr: 0.000781 2022-11-01 18:27:43,698 epoch 130 - iter 216/274 - loss 0.01401131 - samples/sec: 62.39 - lr: 0.000781 2022-11-01 18:27:55,900 epoch 130 - iter 243/274 - loss 0.01402296 - samples/sec: 70.83 - lr: 0.000781 2022-11-01 18:28:07,241 epoch 130 - iter 270/274 - loss 0.01396332 - samples/sec: 76.21 - lr: 0.000781 2022-11-01 18:28:08,598 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:28:08,598 EPOCH 130 done: loss 0.0140 - lr 0.000781 2022-11-01 18:28:33,883 Evaluating as a multi-label problem: False 2022-11-01 18:28:33,898 TEST : loss 0.031718671321868896 - f1-score (micro avg) 0.8547 2022-11-01 18:28:33,952 BAD EPOCHS (no improvement): 0 2022-11-01 18:28:34,043 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:28:45,979 epoch 131 - iter 27/274 - loss 0.01307243 - samples/sec: 72.41 - lr: 0.000781 2022-11-01 18:28:58,110 epoch 131 - iter 54/274 - loss 0.01315823 - samples/sec: 71.24 - lr: 0.000781 2022-11-01 18:29:11,717 epoch 131 - iter 81/274 - loss 0.01382737 - samples/sec: 63.51 - lr: 0.000781 2022-11-01 18:29:24,334 epoch 131 - iter 108/274 - loss 0.01367923 - samples/sec: 68.50 - lr: 0.000781 2022-11-01 18:29:36,846 epoch 131 - iter 135/274 - loss 0.01293479 - samples/sec: 69.07 - lr: 0.000781 2022-11-01 18:29:49,418 epoch 131 - iter 162/274 - loss 0.01360035 - samples/sec: 68.74 - lr: 0.000781 2022-11-01 18:30:00,934 epoch 131 - iter 189/274 - loss 0.01349732 - samples/sec: 75.05 - lr: 0.000781 2022-11-01 18:30:13,375 epoch 131 - iter 216/274 - loss 0.01383598 - samples/sec: 69.47 - lr: 0.000781 2022-11-01 18:30:25,302 epoch 131 - iter 243/274 - loss 0.01377255 - samples/sec: 72.46 - lr: 0.000781 2022-11-01 18:30:37,001 epoch 131 - iter 270/274 - loss 0.01388772 - samples/sec: 73.88 - lr: 0.000781 2022-11-01 18:30:38,646 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:30:38,646 EPOCH 131 done: loss 0.0138 - lr 0.000781 2022-11-01 18:31:04,103 Evaluating as a multi-label problem: False 2022-11-01 18:31:04,119 TEST : loss 0.03182306885719299 - f1-score (micro avg) 0.8546 2022-11-01 18:31:04,173 BAD EPOCHS (no improvement): 0 2022-11-01 18:31:04,247 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:31:16,478 epoch 132 - iter 27/274 - loss 0.01766349 - samples/sec: 70.66 - lr: 0.000781 2022-11-01 18:31:28,684 epoch 132 - iter 54/274 - loss 0.01453588 - samples/sec: 70.80 - lr: 0.000781 2022-11-01 18:31:40,661 epoch 132 - iter 81/274 - loss 0.01396542 - samples/sec: 72.16 - lr: 0.000781 2022-11-01 18:31:53,393 epoch 132 - iter 108/274 - loss 0.01430618 - samples/sec: 67.88 - lr: 0.000781 2022-11-01 18:32:06,520 epoch 132 - iter 135/274 - loss 0.01439286 - samples/sec: 65.83 - lr: 0.000781 2022-11-01 18:32:19,528 epoch 132 - iter 162/274 - loss 0.01473819 - samples/sec: 66.43 - lr: 0.000781 2022-11-01 18:32:31,572 epoch 132 - iter 189/274 - loss 0.01429222 - samples/sec: 71.76 - lr: 0.000781 2022-11-01 18:32:43,127 epoch 132 - iter 216/274 - loss 0.01431037 - samples/sec: 74.79 - lr: 0.000781 2022-11-01 18:32:57,838 epoch 132 - iter 243/274 - loss 0.01464379 - samples/sec: 58.75 - lr: 0.000781 2022-11-01 18:33:10,135 epoch 132 - iter 270/274 - loss 0.01477125 - samples/sec: 70.28 - lr: 0.000781 2022-11-01 18:33:12,056 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:33:12,056 EPOCH 132 done: loss 0.0148 - lr 0.000781 2022-11-01 18:33:37,535 Evaluating as a multi-label problem: False 2022-11-01 18:33:37,551 TEST : loss 0.03184701129794121 - f1-score (micro avg) 0.8546 2022-11-01 18:33:37,601 BAD EPOCHS (no improvement): 1 2022-11-01 18:33:37,697 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:33:50,117 epoch 133 - iter 27/274 - loss 0.01314103 - samples/sec: 69.59 - lr: 0.000781 2022-11-01 18:34:02,137 epoch 133 - iter 54/274 - loss 0.01319767 - samples/sec: 71.90 - lr: 0.000781 2022-11-01 18:34:15,737 epoch 133 - iter 81/274 - loss 0.01357056 - samples/sec: 63.55 - lr: 0.000781 2022-11-01 18:34:27,341 epoch 133 - iter 108/274 - loss 0.01377149 - samples/sec: 74.48 - lr: 0.000781 2022-11-01 18:34:39,606 epoch 133 - iter 135/274 - loss 0.01401248 - samples/sec: 70.46 - lr: 0.000781 2022-11-01 18:34:53,225 epoch 133 - iter 162/274 - loss 0.01435865 - samples/sec: 63.46 - lr: 0.000781 2022-11-01 18:35:05,127 epoch 133 - iter 189/274 - loss 0.01460999 - samples/sec: 72.61 - lr: 0.000781 2022-11-01 18:35:17,438 epoch 133 - iter 216/274 - loss 0.01523430 - samples/sec: 70.20 - lr: 0.000781 2022-11-01 18:35:30,196 epoch 133 - iter 243/274 - loss 0.01523406 - samples/sec: 67.74 - lr: 0.000781 2022-11-01 18:35:42,029 epoch 133 - iter 270/274 - loss 0.01521377 - samples/sec: 73.03 - lr: 0.000781 2022-11-01 18:35:43,607 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:35:43,607 EPOCH 133 done: loss 0.0151 - lr 0.000781 2022-11-01 18:36:09,113 Evaluating as a multi-label problem: False 2022-11-01 18:36:09,129 TEST : loss 0.03188365697860718 - f1-score (micro avg) 0.8546 2022-11-01 18:36:09,182 BAD EPOCHS (no improvement): 2 2022-11-01 18:36:09,268 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:36:21,391 epoch 134 - iter 27/274 - loss 0.01570005 - samples/sec: 71.29 - lr: 0.000781 2022-11-01 18:36:34,709 epoch 134 - iter 54/274 - loss 0.01353171 - samples/sec: 64.89 - lr: 0.000781 2022-11-01 18:36:47,667 epoch 134 - iter 81/274 - loss 0.01290484 - samples/sec: 66.70 - lr: 0.000781 2022-11-01 18:36:59,759 epoch 134 - iter 108/274 - loss 0.01333661 - samples/sec: 71.47 - lr: 0.000781 2022-11-01 18:37:12,839 epoch 134 - iter 135/274 - loss 0.01340435 - samples/sec: 66.07 - lr: 0.000781 2022-11-01 18:37:25,282 epoch 134 - iter 162/274 - loss 0.01310120 - samples/sec: 69.45 - lr: 0.000781 2022-11-01 18:37:37,095 epoch 134 - iter 189/274 - loss 0.01362252 - samples/sec: 73.16 - lr: 0.000781 2022-11-01 18:37:49,281 epoch 134 - iter 216/274 - loss 0.01378086 - samples/sec: 70.92 - lr: 0.000781 2022-11-01 18:38:01,142 epoch 134 - iter 243/274 - loss 0.01385806 - samples/sec: 72.87 - lr: 0.000781 2022-11-01 18:38:14,124 epoch 134 - iter 270/274 - loss 0.01414799 - samples/sec: 66.57 - lr: 0.000781 2022-11-01 18:38:15,844 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:38:15,844 EPOCH 134 done: loss 0.0142 - lr 0.000781 2022-11-01 18:38:41,212 Evaluating as a multi-label problem: False 2022-11-01 18:38:41,227 TEST : loss 0.03192955255508423 - f1-score (micro avg) 0.8538 2022-11-01 18:38:41,279 BAD EPOCHS (no improvement): 3 2022-11-01 18:38:41,364 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:38:54,723 epoch 135 - iter 27/274 - loss 0.01327526 - samples/sec: 64.69 - lr: 0.000781 2022-11-01 18:39:07,129 epoch 135 - iter 54/274 - loss 0.01409919 - samples/sec: 69.67 - lr: 0.000781 2022-11-01 18:39:19,915 epoch 135 - iter 81/274 - loss 0.01531283 - samples/sec: 67.59 - lr: 0.000781 2022-11-01 18:39:32,995 epoch 135 - iter 108/274 - loss 0.01543934 - samples/sec: 66.07 - lr: 0.000781 2022-11-01 18:39:45,099 epoch 135 - iter 135/274 - loss 0.01553804 - samples/sec: 71.41 - lr: 0.000781 2022-11-01 18:39:58,722 epoch 135 - iter 162/274 - loss 0.01537747 - samples/sec: 63.44 - lr: 0.000781 2022-11-01 18:40:10,924 epoch 135 - iter 189/274 - loss 0.01505536 - samples/sec: 70.82 - lr: 0.000781 2022-11-01 18:40:22,920 epoch 135 - iter 216/274 - loss 0.01518738 - samples/sec: 72.05 - lr: 0.000781 2022-11-01 18:40:34,740 epoch 135 - iter 243/274 - loss 0.01497708 - samples/sec: 73.12 - lr: 0.000781 2022-11-01 18:40:47,071 epoch 135 - iter 270/274 - loss 0.01503585 - samples/sec: 70.08 - lr: 0.000781 2022-11-01 18:40:48,750 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:40:48,750 EPOCH 135 done: loss 0.0152 - lr 0.000781 2022-11-01 18:41:13,738 Evaluating as a multi-label problem: False 2022-11-01 18:41:13,753 TEST : loss 0.031969308853149414 - f1-score (micro avg) 0.8544 2022-11-01 18:41:13,805 Epoch 135: reducing learning rate of group 0 to 3.9063e-04. 2022-11-01 18:41:13,805 BAD EPOCHS (no improvement): 4 2022-11-01 18:41:13,900 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:41:26,650 epoch 136 - iter 27/274 - loss 0.01290276 - samples/sec: 67.79 - lr: 0.000391 2022-11-01 18:41:39,459 epoch 136 - iter 54/274 - loss 0.01299663 - samples/sec: 67.47 - lr: 0.000391 2022-11-01 18:41:51,985 epoch 136 - iter 81/274 - loss 0.01282157 - samples/sec: 68.99 - lr: 0.000391 2022-11-01 18:42:06,560 epoch 136 - iter 108/274 - loss 0.01339859 - samples/sec: 59.30 - lr: 0.000391 2022-11-01 18:42:18,770 epoch 136 - iter 135/274 - loss 0.01366404 - samples/sec: 70.78 - lr: 0.000391 2022-11-01 18:42:32,008 epoch 136 - iter 162/274 - loss 0.01492463 - samples/sec: 65.28 - lr: 0.000391 2022-11-01 18:42:42,929 epoch 136 - iter 189/274 - loss 0.01462456 - samples/sec: 79.14 - lr: 0.000391 2022-11-01 18:42:55,591 epoch 136 - iter 216/274 - loss 0.01414258 - samples/sec: 68.26 - lr: 0.000391 2022-11-01 18:43:07,774 epoch 136 - iter 243/274 - loss 0.01382027 - samples/sec: 70.93 - lr: 0.000391 2022-11-01 18:43:19,311 epoch 136 - iter 270/274 - loss 0.01399665 - samples/sec: 74.91 - lr: 0.000391 2022-11-01 18:43:20,917 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:43:20,917 EPOCH 136 done: loss 0.0140 - lr 0.000391 2022-11-01 18:43:46,411 Evaluating as a multi-label problem: False 2022-11-01 18:43:46,426 TEST : loss 0.0319695845246315 - f1-score (micro avg) 0.855 2022-11-01 18:43:46,478 BAD EPOCHS (no improvement): 1 2022-11-01 18:43:46,571 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:43:59,477 epoch 137 - iter 27/274 - loss 0.01202838 - samples/sec: 66.96 - lr: 0.000391 2022-11-01 18:44:12,382 epoch 137 - iter 54/274 - loss 0.01280634 - samples/sec: 66.97 - lr: 0.000391 2022-11-01 18:44:23,487 epoch 137 - iter 81/274 - loss 0.01300539 - samples/sec: 77.82 - lr: 0.000391 2022-11-01 18:44:35,621 epoch 137 - iter 108/274 - loss 0.01354442 - samples/sec: 71.22 - lr: 0.000391 2022-11-01 18:44:47,256 epoch 137 - iter 135/274 - loss 0.01373392 - samples/sec: 74.28 - lr: 0.000391 2022-11-01 18:44:59,898 epoch 137 - iter 162/274 - loss 0.01416349 - samples/sec: 68.36 - lr: 0.000391 2022-11-01 18:45:13,470 epoch 137 - iter 189/274 - loss 0.01416036 - samples/sec: 63.67 - lr: 0.000391 2022-11-01 18:45:27,207 epoch 137 - iter 216/274 - loss 0.01452940 - samples/sec: 62.91 - lr: 0.000391 2022-11-01 18:45:39,752 epoch 137 - iter 243/274 - loss 0.01448564 - samples/sec: 68.89 - lr: 0.000391 2022-11-01 18:45:51,493 epoch 137 - iter 270/274 - loss 0.01453954 - samples/sec: 73.61 - lr: 0.000391 2022-11-01 18:45:53,154 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:45:53,154 EPOCH 137 done: loss 0.0145 - lr 0.000391 2022-11-01 18:46:18,540 Evaluating as a multi-label problem: False 2022-11-01 18:46:18,556 TEST : loss 0.03197849541902542 - f1-score (micro avg) 0.8548 2022-11-01 18:46:18,609 BAD EPOCHS (no improvement): 2 2022-11-01 18:46:18,701 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:46:32,629 epoch 138 - iter 27/274 - loss 0.01287313 - samples/sec: 62.05 - lr: 0.000391 2022-11-01 18:46:44,889 epoch 138 - iter 54/274 - loss 0.01411019 - samples/sec: 70.49 - lr: 0.000391 2022-11-01 18:46:57,085 epoch 138 - iter 81/274 - loss 0.01373632 - samples/sec: 70.86 - lr: 0.000391 2022-11-01 18:47:10,008 epoch 138 - iter 108/274 - loss 0.01368310 - samples/sec: 66.88 - lr: 0.000391 2022-11-01 18:47:22,002 epoch 138 - iter 135/274 - loss 0.01385494 - samples/sec: 72.05 - lr: 0.000391 2022-11-01 18:47:34,426 epoch 138 - iter 162/274 - loss 0.01378742 - samples/sec: 69.56 - lr: 0.000391 2022-11-01 18:47:46,756 epoch 138 - iter 189/274 - loss 0.01386216 - samples/sec: 70.09 - lr: 0.000391 2022-11-01 18:47:58,425 epoch 138 - iter 216/274 - loss 0.01407536 - samples/sec: 74.06 - lr: 0.000391 2022-11-01 18:48:10,418 epoch 138 - iter 243/274 - loss 0.01377845 - samples/sec: 72.06 - lr: 0.000391 2022-11-01 18:48:22,138 epoch 138 - iter 270/274 - loss 0.01386241 - samples/sec: 73.74 - lr: 0.000391 2022-11-01 18:48:24,823 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:48:24,823 EPOCH 138 done: loss 0.0137 - lr 0.000391 2022-11-01 18:48:50,296 Evaluating as a multi-label problem: False 2022-11-01 18:48:50,312 TEST : loss 0.03200221434235573 - f1-score (micro avg) 0.8548 2022-11-01 18:48:50,364 BAD EPOCHS (no improvement): 0 2022-11-01 18:48:50,457 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:49:02,999 epoch 139 - iter 27/274 - loss 0.01582375 - samples/sec: 68.91 - lr: 0.000391 2022-11-01 18:49:15,457 epoch 139 - iter 54/274 - loss 0.01495674 - samples/sec: 69.37 - lr: 0.000391 2022-11-01 18:49:28,117 epoch 139 - iter 81/274 - loss 0.01450503 - samples/sec: 68.26 - lr: 0.000391 2022-11-01 18:49:40,212 epoch 139 - iter 108/274 - loss 0.01445288 - samples/sec: 71.45 - lr: 0.000391 2022-11-01 18:49:53,995 epoch 139 - iter 135/274 - loss 0.01467858 - samples/sec: 62.70 - lr: 0.000391 2022-11-01 18:50:06,504 epoch 139 - iter 162/274 - loss 0.01471299 - samples/sec: 69.08 - lr: 0.000391 2022-11-01 18:50:19,341 epoch 139 - iter 189/274 - loss 0.01431085 - samples/sec: 67.32 - lr: 0.000391 2022-11-01 18:50:30,753 epoch 139 - iter 216/274 - loss 0.01414775 - samples/sec: 75.73 - lr: 0.000391 2022-11-01 18:50:43,649 epoch 139 - iter 243/274 - loss 0.01416123 - samples/sec: 67.01 - lr: 0.000391 2022-11-01 18:50:56,349 epoch 139 - iter 270/274 - loss 0.01429129 - samples/sec: 68.05 - lr: 0.000391 2022-11-01 18:50:57,846 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:50:57,846 EPOCH 139 done: loss 0.0142 - lr 0.000391 2022-11-01 18:51:23,229 Evaluating as a multi-label problem: False 2022-11-01 18:51:23,244 TEST : loss 0.03198350593447685 - f1-score (micro avg) 0.8544 2022-11-01 18:51:23,296 BAD EPOCHS (no improvement): 1 2022-11-01 18:51:23,387 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:51:36,170 epoch 140 - iter 27/274 - loss 0.01491385 - samples/sec: 67.61 - lr: 0.000391 2022-11-01 18:51:48,603 epoch 140 - iter 54/274 - loss 0.01542907 - samples/sec: 69.51 - lr: 0.000391 2022-11-01 18:52:02,681 epoch 140 - iter 81/274 - loss 0.01483332 - samples/sec: 61.39 - lr: 0.000391 2022-11-01 18:52:14,616 epoch 140 - iter 108/274 - loss 0.01461136 - samples/sec: 72.41 - lr: 0.000391 2022-11-01 18:52:26,886 epoch 140 - iter 135/274 - loss 0.01441321 - samples/sec: 70.44 - lr: 0.000391 2022-11-01 18:52:38,892 epoch 140 - iter 162/274 - loss 0.01482984 - samples/sec: 71.98 - lr: 0.000391 2022-11-01 18:52:51,513 epoch 140 - iter 189/274 - loss 0.01465169 - samples/sec: 68.48 - lr: 0.000391 2022-11-01 18:53:03,540 epoch 140 - iter 216/274 - loss 0.01454677 - samples/sec: 71.86 - lr: 0.000391 2022-11-01 18:53:17,309 epoch 140 - iter 243/274 - loss 0.01465699 - samples/sec: 62.77 - lr: 0.000391 2022-11-01 18:53:29,003 epoch 140 - iter 270/274 - loss 0.01447624 - samples/sec: 73.91 - lr: 0.000391 2022-11-01 18:53:30,881 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:53:30,881 EPOCH 140 done: loss 0.0146 - lr 0.000391 2022-11-01 18:53:56,246 Evaluating as a multi-label problem: False 2022-11-01 18:53:56,262 TEST : loss 0.03198152035474777 - f1-score (micro avg) 0.8548 2022-11-01 18:53:56,314 BAD EPOCHS (no improvement): 2 2022-11-01 18:53:56,401 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:54:07,635 epoch 141 - iter 27/274 - loss 0.01380211 - samples/sec: 76.94 - lr: 0.000391 2022-11-01 18:54:20,777 epoch 141 - iter 54/274 - loss 0.01299416 - samples/sec: 65.76 - lr: 0.000391 2022-11-01 18:54:32,989 epoch 141 - iter 81/274 - loss 0.01288500 - samples/sec: 70.77 - lr: 0.000391 2022-11-01 18:54:44,408 epoch 141 - iter 108/274 - loss 0.01280394 - samples/sec: 75.69 - lr: 0.000391 2022-11-01 18:54:56,270 epoch 141 - iter 135/274 - loss 0.01294786 - samples/sec: 72.86 - lr: 0.000391 2022-11-01 18:55:09,407 epoch 141 - iter 162/274 - loss 0.01290578 - samples/sec: 65.78 - lr: 0.000391 2022-11-01 18:55:21,882 epoch 141 - iter 189/274 - loss 0.01312051 - samples/sec: 69.28 - lr: 0.000391 2022-11-01 18:55:33,330 epoch 141 - iter 216/274 - loss 0.01338580 - samples/sec: 75.50 - lr: 0.000391 2022-11-01 18:55:47,281 epoch 141 - iter 243/274 - loss 0.01371702 - samples/sec: 61.94 - lr: 0.000391 2022-11-01 18:55:59,370 epoch 141 - iter 270/274 - loss 0.01411856 - samples/sec: 71.49 - lr: 0.000391 2022-11-01 18:56:01,282 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:56:01,282 EPOCH 141 done: loss 0.0141 - lr 0.000391 2022-11-01 18:56:26,636 Evaluating as a multi-label problem: False 2022-11-01 18:56:26,651 TEST : loss 0.032018985599279404 - f1-score (micro avg) 0.8544 2022-11-01 18:56:26,705 BAD EPOCHS (no improvement): 3 2022-11-01 18:56:26,796 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:56:38,798 epoch 142 - iter 27/274 - loss 0.01461087 - samples/sec: 72.01 - lr: 0.000391 2022-11-01 18:56:50,263 epoch 142 - iter 54/274 - loss 0.01406950 - samples/sec: 75.38 - lr: 0.000391 2022-11-01 18:57:01,513 epoch 142 - iter 81/274 - loss 0.01326957 - samples/sec: 76.82 - lr: 0.000391 2022-11-01 18:57:13,833 epoch 142 - iter 108/274 - loss 0.01459213 - samples/sec: 70.15 - lr: 0.000391 2022-11-01 18:57:25,595 epoch 142 - iter 135/274 - loss 0.01422328 - samples/sec: 73.48 - lr: 0.000391 2022-11-01 18:57:39,117 epoch 142 - iter 162/274 - loss 0.01387491 - samples/sec: 63.91 - lr: 0.000391 2022-11-01 18:57:53,314 epoch 142 - iter 189/274 - loss 0.01399542 - samples/sec: 60.87 - lr: 0.000391 2022-11-01 18:58:06,060 epoch 142 - iter 216/274 - loss 0.01406924 - samples/sec: 67.80 - lr: 0.000391 2022-11-01 18:58:18,871 epoch 142 - iter 243/274 - loss 0.01429993 - samples/sec: 67.46 - lr: 0.000391 2022-11-01 18:58:32,342 epoch 142 - iter 270/274 - loss 0.01424921 - samples/sec: 64.15 - lr: 0.000391 2022-11-01 18:58:34,122 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:58:34,122 EPOCH 142 done: loss 0.0142 - lr 0.000391 2022-11-01 18:58:59,595 Evaluating as a multi-label problem: False 2022-11-01 18:58:59,611 TEST : loss 0.03204723075032234 - f1-score (micro avg) 0.8541 2022-11-01 18:58:59,664 Epoch 142: reducing learning rate of group 0 to 1.9531e-04. 2022-11-01 18:58:59,664 BAD EPOCHS (no improvement): 4 2022-11-01 18:58:59,757 ---------------------------------------------------------------------------------------------------- 2022-11-01 18:59:12,947 epoch 143 - iter 27/274 - loss 0.01607101 - samples/sec: 65.52 - lr: 0.000195 2022-11-01 18:59:25,410 epoch 143 - iter 54/274 - loss 0.01551964 - samples/sec: 69.34 - lr: 0.000195 2022-11-01 18:59:37,705 epoch 143 - iter 81/274 - loss 0.01508179 - samples/sec: 70.29 - lr: 0.000195 2022-11-01 18:59:50,633 epoch 143 - iter 108/274 - loss 0.01503203 - samples/sec: 66.85 - lr: 0.000195 2022-11-01 19:00:02,333 epoch 143 - iter 135/274 - loss 0.01500703 - samples/sec: 73.87 - lr: 0.000195 2022-11-01 19:00:15,575 epoch 143 - iter 162/274 - loss 0.01451339 - samples/sec: 65.26 - lr: 0.000195 2022-11-01 19:00:29,024 epoch 143 - iter 189/274 - loss 0.01453377 - samples/sec: 64.26 - lr: 0.000195 2022-11-01 19:00:40,418 epoch 143 - iter 216/274 - loss 0.01460606 - samples/sec: 75.85 - lr: 0.000195 2022-11-01 19:00:53,208 epoch 143 - iter 243/274 - loss 0.01465891 - samples/sec: 67.57 - lr: 0.000195 2022-11-01 19:01:05,277 epoch 143 - iter 270/274 - loss 0.01452026 - samples/sec: 71.61 - lr: 0.000195 2022-11-01 19:01:06,801 ---------------------------------------------------------------------------------------------------- 2022-11-01 19:01:06,801 EPOCH 143 done: loss 0.0145 - lr 0.000195 2022-11-01 19:01:32,286 Evaluating as a multi-label problem: False 2022-11-01 19:01:32,301 TEST : loss 0.03204527124762535 - f1-score (micro avg) 0.8544 2022-11-01 19:01:32,353 BAD EPOCHS (no improvement): 1 2022-11-01 19:01:32,446 ---------------------------------------------------------------------------------------------------- 2022-11-01 19:01:43,483 epoch 144 - iter 27/274 - loss 0.01275661 - samples/sec: 78.31 - lr: 0.000195 2022-11-01 19:01:55,891 epoch 144 - iter 54/274 - loss 0.01255751 - samples/sec: 69.65 - lr: 0.000195 2022-11-01 19:02:08,138 epoch 144 - iter 81/274 - loss 0.01352715 - samples/sec: 70.57 - lr: 0.000195 2022-11-01 19:02:20,657 epoch 144 - iter 108/274 - loss 0.01424597 - samples/sec: 69.03 - lr: 0.000195 2022-11-01 19:02:32,689 epoch 144 - iter 135/274 - loss 0.01388532 - samples/sec: 71.83 - lr: 0.000195 2022-11-01 19:02:46,254 epoch 144 - iter 162/274 - loss 0.01418345 - samples/sec: 63.71 - lr: 0.000195 2022-11-01 19:02:58,873 epoch 144 - iter 189/274 - loss 0.01401984 - samples/sec: 68.49 - lr: 0.000195 2022-11-01 19:03:10,582 epoch 144 - iter 216/274 - loss 0.01378628 - samples/sec: 73.81 - lr: 0.000195 2022-11-01 19:03:23,555 epoch 144 - iter 243/274 - loss 0.01386198 - samples/sec: 66.62 - lr: 0.000195 2022-11-01 19:03:37,102 epoch 144 - iter 270/274 - loss 0.01403064 - samples/sec: 63.79 - lr: 0.000195 2022-11-01 19:03:38,807 ---------------------------------------------------------------------------------------------------- 2022-11-01 19:03:38,807 EPOCH 144 done: loss 0.0141 - lr 0.000195 2022-11-01 19:04:04,183 Evaluating as a multi-label problem: False 2022-11-01 19:04:04,199 TEST : loss 0.03205322101712227 - f1-score (micro avg) 0.8544 2022-11-01 19:04:04,251 BAD EPOCHS (no improvement): 2 2022-11-01 19:04:04,337 ---------------------------------------------------------------------------------------------------- 2022-11-01 19:04:15,584 epoch 145 - iter 27/274 - loss 0.01196807 - samples/sec: 76.84 - lr: 0.000195 2022-11-01 19:04:27,733 epoch 145 - iter 54/274 - loss 0.01428555 - samples/sec: 71.14 - lr: 0.000195 2022-11-01 19:04:39,618 epoch 145 - iter 81/274 - loss 0.01458192 - samples/sec: 72.72 - lr: 0.000195 2022-11-01 19:04:52,925 epoch 145 - iter 108/274 - loss 0.01460566 - samples/sec: 64.95 - lr: 0.000195 2022-11-01 19:05:04,454 epoch 145 - iter 135/274 - loss 0.01511987 - samples/sec: 74.96 - lr: 0.000195 2022-11-01 19:05:16,725 epoch 145 - iter 162/274 - loss 0.01514862 - samples/sec: 70.43 - lr: 0.000195 2022-11-01 19:05:29,601 epoch 145 - iter 189/274 - loss 0.01476270 - samples/sec: 67.12 - lr: 0.000195 2022-11-01 19:05:42,378 epoch 145 - iter 216/274 - loss 0.01491464 - samples/sec: 67.64 - lr: 0.000195 2022-11-01 19:05:54,791 epoch 145 - iter 243/274 - loss 0.01472325 - samples/sec: 69.62 - lr: 0.000195 2022-11-01 19:06:08,380 epoch 145 - iter 270/274 - loss 0.01450260 - samples/sec: 63.59 - lr: 0.000195 2022-11-01 19:06:10,102 ---------------------------------------------------------------------------------------------------- 2022-11-01 19:06:10,103 EPOCH 145 done: loss 0.0145 - lr 0.000195 2022-11-01 19:06:35,540 Evaluating as a multi-label problem: False 2022-11-01 19:06:35,556 TEST : loss 0.03206166997551918 - f1-score (micro avg) 0.8544 2022-11-01 19:06:35,609 BAD EPOCHS (no improvement): 3 2022-11-01 19:06:35,703 ---------------------------------------------------------------------------------------------------- 2022-11-01 19:06:48,592 epoch 146 - iter 27/274 - loss 0.01138730 - samples/sec: 67.06 - lr: 0.000195 2022-11-01 19:07:00,468 epoch 146 - iter 54/274 - loss 0.01167755 - samples/sec: 72.77 - lr: 0.000195 2022-11-01 19:07:12,555 epoch 146 - iter 81/274 - loss 0.01291096 - samples/sec: 71.50 - lr: 0.000195 2022-11-01 19:07:25,188 epoch 146 - iter 108/274 - loss 0.01365870 - samples/sec: 68.41 - lr: 0.000195 2022-11-01 19:07:39,012 epoch 146 - iter 135/274 - loss 0.01360006 - samples/sec: 62.51 - lr: 0.000195 2022-11-01 19:07:50,620 epoch 146 - iter 162/274 - loss 0.01400603 - samples/sec: 74.45 - lr: 0.000195 2022-11-01 19:08:02,972 epoch 146 - iter 189/274 - loss 0.01390354 - samples/sec: 69.97 - lr: 0.000195 2022-11-01 19:08:15,150 epoch 146 - iter 216/274 - loss 0.01413519 - samples/sec: 70.96 - lr: 0.000195 2022-11-01 19:08:27,039 epoch 146 - iter 243/274 - loss 0.01425737 - samples/sec: 72.69 - lr: 0.000195 2022-11-01 19:08:38,896 epoch 146 - iter 270/274 - loss 0.01407049 - samples/sec: 72.89 - lr: 0.000195 2022-11-01 19:08:41,119 ---------------------------------------------------------------------------------------------------- 2022-11-01 19:08:41,119 EPOCH 146 done: loss 0.0140 - lr 0.000195 2022-11-01 19:09:06,382 Evaluating as a multi-label problem: False 2022-11-01 19:09:06,397 TEST : loss 0.032056890428066254 - f1-score (micro avg) 0.8544 2022-11-01 19:09:06,450 Epoch 146: reducing learning rate of group 0 to 9.7656e-05. 2022-11-01 19:09:06,451 BAD EPOCHS (no improvement): 4 2022-11-01 19:09:06,524 ---------------------------------------------------------------------------------------------------- 2022-11-01 19:09:06,524 ---------------------------------------------------------------------------------------------------- 2022-11-01 19:09:06,524 learning rate too small - quitting training! 2022-11-01 19:09:06,524 ---------------------------------------------------------------------------------------------------- 2022-11-01 19:09:06,599 ---------------------------------------------------------------------------------------------------- 2022-11-01 19:09:06,599 Testing using last state of model ... 2022-11-01 19:09:31,767 Evaluating as a multi-label problem: False 2022-11-01 19:09:31,783 0.8572 0.8516 0.8544 0.798 2022-11-01 19:09:31,783 Results: - F-score (micro) 0.8544 - F-score (macro) 0.7406 - Accuracy 0.798 By class: precision recall f1-score support PERS 0.9231 0.9374 0.9302 1678 LOC 0.8204 0.8429 0.8315 401 ORG 0.6708 0.6245 0.6468 261 MISC 0.6029 0.5125 0.5541 240 micro avg 0.8572 0.8516 0.8544 2580 macro avg 0.7543 0.7293 0.7406 2580 weighted avg 0.8518 0.8516 0.8512 2580 2022-11-01 19:09:31,783 ----------------------------------------------------------------------------------------------------