| 2023-10-18 23:49:39,844 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 23:49:39,845 Model: "SequenceTagger( | |
| (embeddings): TransformerWordEmbeddings( | |
| (model): BertModel( | |
| (embeddings): BertEmbeddings( | |
| (word_embeddings): Embedding(31103, 768) | |
| (position_embeddings): Embedding(512, 768) | |
| (token_type_embeddings): Embedding(2, 768) | |
| (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (encoder): BertEncoder( | |
| (layer): ModuleList( | |
| (0-11): 12 x BertLayer( | |
| (attention): BertAttention( | |
| (self): BertSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): BertSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): BertIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| (intermediate_act_fn): GELUActivation() | |
| ) | |
| (output): BertOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| ) | |
| ) | |
| (pooler): BertPooler( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (activation): Tanh() | |
| ) | |
| ) | |
| ) | |
| (locked_dropout): LockedDropout(p=0.5) | |
| (linear): Linear(in_features=768, out_features=81, bias=True) | |
| (loss_function): CrossEntropyLoss() | |
| )" | |
| 2023-10-18 23:49:39,845 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 23:49:39,845 Corpus: 6900 train + 1576 dev + 1833 test sentences | |
| 2023-10-18 23:49:39,846 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 23:49:39,846 Train: 6900 sentences | |
| 2023-10-18 23:49:39,846 (train_with_dev=False, train_with_test=False) | |
| 2023-10-18 23:49:39,846 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 23:49:39,846 Training Params: | |
| 2023-10-18 23:49:39,846 - learning_rate: "5e-05" | |
| 2023-10-18 23:49:39,846 - mini_batch_size: "16" | |
| 2023-10-18 23:49:39,846 - max_epochs: "10" | |
| 2023-10-18 23:49:39,846 - shuffle: "True" | |
| 2023-10-18 23:49:39,846 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 23:49:39,846 Plugins: | |
| 2023-10-18 23:49:39,846 - TensorboardLogger | |
| 2023-10-18 23:49:39,846 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-18 23:49:39,846 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 23:49:39,846 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-18 23:49:39,846 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-18 23:49:39,846 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 23:49:39,846 Computation: | |
| 2023-10-18 23:49:39,846 - compute on device: cuda:0 | |
| 2023-10-18 23:49:39,847 - embedding storage: none | |
| 2023-10-18 23:49:39,847 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 23:49:39,847 Model training base path: "autotrain-flair-mobie-gbert_base-bs16-e10-lr5e-05-1" | |
| 2023-10-18 23:49:39,847 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 23:49:39,847 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 23:49:39,847 Logging anything other than scalars to TensorBoard is currently not supported. | |
| 2023-10-18 23:49:54,007 epoch 1 - iter 43/432 - loss 4.54226396 - time (sec): 14.16 - samples/sec: 427.65 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-18 23:50:08,103 epoch 1 - iter 86/432 - loss 3.39025495 - time (sec): 28.26 - samples/sec: 429.20 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-18 23:50:22,380 epoch 1 - iter 129/432 - loss 2.82298352 - time (sec): 42.53 - samples/sec: 431.35 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-18 23:50:35,740 epoch 1 - iter 172/432 - loss 2.47385817 - time (sec): 55.89 - samples/sec: 437.97 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-18 23:50:49,999 epoch 1 - iter 215/432 - loss 2.21787123 - time (sec): 70.15 - samples/sec: 433.61 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-18 23:51:03,183 epoch 1 - iter 258/432 - loss 2.00329484 - time (sec): 83.33 - samples/sec: 440.26 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-18 23:51:16,381 epoch 1 - iter 301/432 - loss 1.82489643 - time (sec): 96.53 - samples/sec: 447.14 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-18 23:51:30,192 epoch 1 - iter 344/432 - loss 1.69046523 - time (sec): 110.34 - samples/sec: 445.93 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-18 23:51:43,742 epoch 1 - iter 387/432 - loss 1.57702628 - time (sec): 123.89 - samples/sec: 444.99 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-18 23:51:58,002 epoch 1 - iter 430/432 - loss 1.47019726 - time (sec): 138.15 - samples/sec: 446.59 - lr: 0.000050 - momentum: 0.000000 | |
| 2023-10-18 23:51:58,500 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 23:51:58,501 EPOCH 1 done: loss 1.4681 - lr: 0.000050 | |
| 2023-10-18 23:52:10,741 DEV : loss 0.48693621158599854 - f1-score (micro avg) 0.7049 | |
| 2023-10-18 23:52:10,765 saving best model | |
| 2023-10-18 23:52:11,236 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 23:52:24,640 epoch 2 - iter 43/432 - loss 0.49120434 - time (sec): 13.40 - samples/sec: 475.14 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-18 23:52:37,470 epoch 2 - iter 86/432 - loss 0.47518885 - time (sec): 26.23 - samples/sec: 473.80 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-18 23:52:50,585 epoch 2 - iter 129/432 - loss 0.46930182 - time (sec): 39.35 - samples/sec: 467.10 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-18 23:53:03,976 epoch 2 - iter 172/432 - loss 0.45056911 - time (sec): 52.74 - samples/sec: 469.05 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-18 23:53:18,853 epoch 2 - iter 215/432 - loss 0.43792445 - time (sec): 67.62 - samples/sec: 458.89 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-18 23:53:32,607 epoch 2 - iter 258/432 - loss 0.43015339 - time (sec): 81.37 - samples/sec: 460.55 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-18 23:53:46,790 epoch 2 - iter 301/432 - loss 0.41739009 - time (sec): 95.55 - samples/sec: 457.84 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-18 23:54:00,936 epoch 2 - iter 344/432 - loss 0.40919722 - time (sec): 109.70 - samples/sec: 452.88 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-18 23:54:15,261 epoch 2 - iter 387/432 - loss 0.39789179 - time (sec): 124.02 - samples/sec: 448.77 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-18 23:54:30,460 epoch 2 - iter 430/432 - loss 0.39342103 - time (sec): 139.22 - samples/sec: 443.36 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-18 23:54:30,977 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 23:54:30,978 EPOCH 2 done: loss 0.3932 - lr: 0.000044 | |
| 2023-10-18 23:54:43,400 DEV : loss 0.3221401870250702 - f1-score (micro avg) 0.7999 | |
| 2023-10-18 23:54:43,424 saving best model | |
| 2023-10-18 23:54:44,719 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 23:54:58,597 epoch 3 - iter 43/432 - loss 0.26073780 - time (sec): 13.88 - samples/sec: 440.91 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-18 23:55:12,781 epoch 3 - iter 86/432 - loss 0.26640971 - time (sec): 28.06 - samples/sec: 433.46 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-18 23:55:27,533 epoch 3 - iter 129/432 - loss 0.25801074 - time (sec): 42.81 - samples/sec: 424.09 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-18 23:55:42,492 epoch 3 - iter 172/432 - loss 0.24957799 - time (sec): 57.77 - samples/sec: 421.11 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-18 23:55:57,651 epoch 3 - iter 215/432 - loss 0.25398995 - time (sec): 72.93 - samples/sec: 417.81 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-18 23:56:12,408 epoch 3 - iter 258/432 - loss 0.25510902 - time (sec): 87.69 - samples/sec: 421.63 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-18 23:56:27,276 epoch 3 - iter 301/432 - loss 0.25604031 - time (sec): 102.55 - samples/sec: 420.25 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-18 23:56:41,333 epoch 3 - iter 344/432 - loss 0.25487803 - time (sec): 116.61 - samples/sec: 424.44 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-18 23:56:55,954 epoch 3 - iter 387/432 - loss 0.25224648 - time (sec): 131.23 - samples/sec: 425.07 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-18 23:57:10,652 epoch 3 - iter 430/432 - loss 0.24985880 - time (sec): 145.93 - samples/sec: 422.88 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-18 23:57:11,301 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 23:57:11,301 EPOCH 3 done: loss 0.2495 - lr: 0.000039 | |
| 2023-10-18 23:57:24,474 DEV : loss 0.2786136269569397 - f1-score (micro avg) 0.8259 | |
| 2023-10-18 23:57:24,498 saving best model | |
| 2023-10-18 23:57:25,777 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 23:57:39,701 epoch 4 - iter 43/432 - loss 0.17159693 - time (sec): 13.92 - samples/sec: 472.47 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-18 23:57:55,199 epoch 4 - iter 86/432 - loss 0.17789331 - time (sec): 29.42 - samples/sec: 433.90 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-18 23:58:10,250 epoch 4 - iter 129/432 - loss 0.17886504 - time (sec): 44.47 - samples/sec: 428.99 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-18 23:58:24,351 epoch 4 - iter 172/432 - loss 0.17380496 - time (sec): 58.57 - samples/sec: 428.72 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-18 23:58:40,004 epoch 4 - iter 215/432 - loss 0.17639725 - time (sec): 74.23 - samples/sec: 426.47 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-18 23:58:55,251 epoch 4 - iter 258/432 - loss 0.17695320 - time (sec): 89.47 - samples/sec: 425.05 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-18 23:59:10,163 epoch 4 - iter 301/432 - loss 0.17433887 - time (sec): 104.39 - samples/sec: 422.34 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-18 23:59:24,925 epoch 4 - iter 344/432 - loss 0.17056141 - time (sec): 119.15 - samples/sec: 416.50 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-18 23:59:40,330 epoch 4 - iter 387/432 - loss 0.17233317 - time (sec): 134.55 - samples/sec: 414.20 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-18 23:59:55,682 epoch 4 - iter 430/432 - loss 0.17233952 - time (sec): 149.90 - samples/sec: 411.30 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-18 23:59:56,286 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 23:59:56,286 EPOCH 4 done: loss 0.1719 - lr: 0.000033 | |
| 2023-10-19 00:00:09,553 DEV : loss 0.3027258515357971 - f1-score (micro avg) 0.833 | |
| 2023-10-19 00:00:09,578 saving best model | |
| 2023-10-19 00:00:10,866 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 00:00:24,962 epoch 5 - iter 43/432 - loss 0.13224073 - time (sec): 14.09 - samples/sec: 412.85 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-19 00:00:40,762 epoch 5 - iter 86/432 - loss 0.12870566 - time (sec): 29.89 - samples/sec: 396.63 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-19 00:00:56,297 epoch 5 - iter 129/432 - loss 0.12680988 - time (sec): 45.43 - samples/sec: 391.33 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-19 00:01:11,298 epoch 5 - iter 172/432 - loss 0.12448631 - time (sec): 60.43 - samples/sec: 397.60 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-19 00:01:25,586 epoch 5 - iter 215/432 - loss 0.12976948 - time (sec): 74.72 - samples/sec: 400.65 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-19 00:01:40,737 epoch 5 - iter 258/432 - loss 0.13032162 - time (sec): 89.87 - samples/sec: 401.15 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-19 00:01:55,989 epoch 5 - iter 301/432 - loss 0.13168277 - time (sec): 105.12 - samples/sec: 405.48 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-19 00:02:09,035 epoch 5 - iter 344/432 - loss 0.13191984 - time (sec): 118.17 - samples/sec: 415.52 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-19 00:02:24,258 epoch 5 - iter 387/432 - loss 0.13139996 - time (sec): 133.39 - samples/sec: 414.77 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-19 00:02:40,019 epoch 5 - iter 430/432 - loss 0.13241412 - time (sec): 149.15 - samples/sec: 413.75 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-19 00:02:40,513 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 00:02:40,513 EPOCH 5 done: loss 0.1323 - lr: 0.000028 | |
| 2023-10-19 00:02:53,879 DEV : loss 0.3319297134876251 - f1-score (micro avg) 0.8275 | |
| 2023-10-19 00:02:53,909 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 00:03:09,440 epoch 6 - iter 43/432 - loss 0.08999368 - time (sec): 15.53 - samples/sec: 399.56 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-19 00:03:23,839 epoch 6 - iter 86/432 - loss 0.08539150 - time (sec): 29.93 - samples/sec: 429.70 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-19 00:03:38,488 epoch 6 - iter 129/432 - loss 0.09986893 - time (sec): 44.58 - samples/sec: 422.57 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-19 00:03:54,568 epoch 6 - iter 172/432 - loss 0.09913431 - time (sec): 60.66 - samples/sec: 415.33 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-19 00:04:09,161 epoch 6 - iter 215/432 - loss 0.09906129 - time (sec): 75.25 - samples/sec: 409.41 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-19 00:04:23,814 epoch 6 - iter 258/432 - loss 0.09924250 - time (sec): 89.90 - samples/sec: 411.32 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-19 00:04:38,652 epoch 6 - iter 301/432 - loss 0.10059479 - time (sec): 104.74 - samples/sec: 412.85 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-19 00:04:53,540 epoch 6 - iter 344/432 - loss 0.09936378 - time (sec): 119.63 - samples/sec: 413.63 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-19 00:05:08,991 epoch 6 - iter 387/432 - loss 0.09927245 - time (sec): 135.08 - samples/sec: 410.82 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-19 00:05:25,338 epoch 6 - iter 430/432 - loss 0.09843081 - time (sec): 151.43 - samples/sec: 407.47 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-19 00:05:25,876 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 00:05:25,876 EPOCH 6 done: loss 0.0985 - lr: 0.000022 | |
| 2023-10-19 00:05:39,277 DEV : loss 0.3483152687549591 - f1-score (micro avg) 0.8353 | |
| 2023-10-19 00:05:39,301 saving best model | |
| 2023-10-19 00:05:41,347 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 00:05:56,804 epoch 7 - iter 43/432 - loss 0.07646855 - time (sec): 15.46 - samples/sec: 383.21 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-19 00:06:12,246 epoch 7 - iter 86/432 - loss 0.07564571 - time (sec): 30.90 - samples/sec: 382.43 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-19 00:06:26,486 epoch 7 - iter 129/432 - loss 0.07414267 - time (sec): 45.14 - samples/sec: 405.53 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-19 00:06:41,108 epoch 7 - iter 172/432 - loss 0.07110179 - time (sec): 59.76 - samples/sec: 418.47 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-19 00:06:56,294 epoch 7 - iter 215/432 - loss 0.07443072 - time (sec): 74.95 - samples/sec: 413.30 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-19 00:07:10,672 epoch 7 - iter 258/432 - loss 0.07597555 - time (sec): 89.32 - samples/sec: 417.24 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-19 00:07:25,487 epoch 7 - iter 301/432 - loss 0.07746008 - time (sec): 104.14 - samples/sec: 417.75 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-19 00:07:40,229 epoch 7 - iter 344/432 - loss 0.07686569 - time (sec): 118.88 - samples/sec: 417.03 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-19 00:07:55,052 epoch 7 - iter 387/432 - loss 0.07546838 - time (sec): 133.70 - samples/sec: 413.79 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-19 00:08:09,443 epoch 7 - iter 430/432 - loss 0.07435736 - time (sec): 148.09 - samples/sec: 415.90 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-19 00:08:10,004 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 00:08:10,005 EPOCH 7 done: loss 0.0749 - lr: 0.000017 | |
| 2023-10-19 00:08:22,467 DEV : loss 0.35942888259887695 - f1-score (micro avg) 0.8395 | |
| 2023-10-19 00:08:22,492 saving best model | |
| 2023-10-19 00:08:23,780 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 00:08:37,812 epoch 8 - iter 43/432 - loss 0.05403566 - time (sec): 14.03 - samples/sec: 443.97 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-19 00:08:50,468 epoch 8 - iter 86/432 - loss 0.05416407 - time (sec): 26.69 - samples/sec: 465.48 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-19 00:09:05,136 epoch 8 - iter 129/432 - loss 0.05231093 - time (sec): 41.35 - samples/sec: 445.46 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-19 00:09:19,064 epoch 8 - iter 172/432 - loss 0.05332684 - time (sec): 55.28 - samples/sec: 439.02 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-19 00:09:32,357 epoch 8 - iter 215/432 - loss 0.05490906 - time (sec): 68.58 - samples/sec: 442.24 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-19 00:09:45,819 epoch 8 - iter 258/432 - loss 0.05470571 - time (sec): 82.04 - samples/sec: 445.59 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-19 00:09:59,775 epoch 8 - iter 301/432 - loss 0.05508927 - time (sec): 95.99 - samples/sec: 444.48 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-19 00:10:13,551 epoch 8 - iter 344/432 - loss 0.05696792 - time (sec): 109.77 - samples/sec: 443.76 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-19 00:10:28,569 epoch 8 - iter 387/432 - loss 0.05709499 - time (sec): 124.79 - samples/sec: 440.02 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-19 00:10:42,292 epoch 8 - iter 430/432 - loss 0.05606310 - time (sec): 138.51 - samples/sec: 445.16 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-19 00:10:42,821 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 00:10:42,821 EPOCH 8 done: loss 0.0560 - lr: 0.000011 | |
| 2023-10-19 00:10:55,201 DEV : loss 0.3855433464050293 - f1-score (micro avg) 0.8399 | |
| 2023-10-19 00:10:55,225 saving best model | |
| 2023-10-19 00:10:56,513 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 00:11:09,243 epoch 9 - iter 43/432 - loss 0.04130631 - time (sec): 12.73 - samples/sec: 503.43 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-19 00:11:22,023 epoch 9 - iter 86/432 - loss 0.03767518 - time (sec): 25.51 - samples/sec: 484.19 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-19 00:11:35,992 epoch 9 - iter 129/432 - loss 0.04012592 - time (sec): 39.48 - samples/sec: 467.91 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-19 00:11:50,170 epoch 9 - iter 172/432 - loss 0.03874753 - time (sec): 53.66 - samples/sec: 461.63 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-19 00:12:03,449 epoch 9 - iter 215/432 - loss 0.03749511 - time (sec): 66.93 - samples/sec: 465.10 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-19 00:12:17,477 epoch 9 - iter 258/432 - loss 0.03805076 - time (sec): 80.96 - samples/sec: 460.64 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-19 00:12:30,864 epoch 9 - iter 301/432 - loss 0.03919902 - time (sec): 94.35 - samples/sec: 462.58 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-19 00:12:45,129 epoch 9 - iter 344/432 - loss 0.04055903 - time (sec): 108.62 - samples/sec: 455.14 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-19 00:12:59,088 epoch 9 - iter 387/432 - loss 0.04016294 - time (sec): 122.57 - samples/sec: 452.94 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-19 00:13:12,844 epoch 9 - iter 430/432 - loss 0.04071803 - time (sec): 136.33 - samples/sec: 452.09 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-19 00:13:13,346 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 00:13:13,346 EPOCH 9 done: loss 0.0406 - lr: 0.000006 | |
| 2023-10-19 00:13:25,615 DEV : loss 0.398950457572937 - f1-score (micro avg) 0.8446 | |
| 2023-10-19 00:13:25,640 saving best model | |
| 2023-10-19 00:13:26,920 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 00:13:40,602 epoch 10 - iter 43/432 - loss 0.03991636 - time (sec): 13.68 - samples/sec: 438.30 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-19 00:13:54,198 epoch 10 - iter 86/432 - loss 0.03709518 - time (sec): 27.28 - samples/sec: 436.13 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-19 00:14:07,245 epoch 10 - iter 129/432 - loss 0.03665230 - time (sec): 40.32 - samples/sec: 453.56 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-19 00:14:21,656 epoch 10 - iter 172/432 - loss 0.03488483 - time (sec): 54.73 - samples/sec: 449.35 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-19 00:14:35,583 epoch 10 - iter 215/432 - loss 0.03260316 - time (sec): 68.66 - samples/sec: 449.20 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-19 00:14:50,542 epoch 10 - iter 258/432 - loss 0.03311250 - time (sec): 83.62 - samples/sec: 442.51 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-19 00:15:04,584 epoch 10 - iter 301/432 - loss 0.03267573 - time (sec): 97.66 - samples/sec: 440.01 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-19 00:15:20,118 epoch 10 - iter 344/432 - loss 0.03135514 - time (sec): 113.20 - samples/sec: 434.14 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-19 00:15:35,441 epoch 10 - iter 387/432 - loss 0.03196909 - time (sec): 128.52 - samples/sec: 431.63 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-19 00:15:50,021 epoch 10 - iter 430/432 - loss 0.03303907 - time (sec): 143.10 - samples/sec: 430.68 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-19 00:15:50,585 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 00:15:50,585 EPOCH 10 done: loss 0.0330 - lr: 0.000000 | |
| 2023-10-19 00:16:03,688 DEV : loss 0.41425013542175293 - f1-score (micro avg) 0.8446 | |
| 2023-10-19 00:16:03,714 saving best model | |
| 2023-10-19 00:16:05,498 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 00:16:05,500 Loading model from best epoch ... | |
| 2023-10-19 00:16:07,893 SequenceTagger predicts: Dictionary with 81 tags: O, S-location-route, B-location-route, E-location-route, I-location-route, S-location-stop, B-location-stop, E-location-stop, I-location-stop, S-trigger, B-trigger, E-trigger, I-trigger, S-organization-company, B-organization-company, E-organization-company, I-organization-company, S-location-city, B-location-city, E-location-city, I-location-city, S-location, B-location, E-location, I-location, S-event-cause, B-event-cause, E-event-cause, I-event-cause, S-location-street, B-location-street, E-location-street, I-location-street, S-time, B-time, E-time, I-time, S-date, B-date, E-date, I-date, S-number, B-number, E-number, I-number, S-duration, B-duration, E-duration, I-duration, S-organization | |
| 2023-10-19 00:16:25,689 | |
| Results: | |
| - F-score (micro) 0.7706 | |
| - F-score (macro) 0.5891 | |
| - Accuracy 0.6737 | |
| By class: | |
| precision recall f1-score support | |
| trigger 0.7277 0.6062 0.6614 833 | |
| location-stop 0.8421 0.8157 0.8287 765 | |
| location 0.8096 0.8376 0.8234 665 | |
| location-city 0.8068 0.8852 0.8441 566 | |
| date 0.9013 0.8579 0.8791 394 | |
| location-street 0.9417 0.8782 0.9088 386 | |
| time 0.7855 0.8867 0.8330 256 | |
| location-route 0.9053 0.7746 0.8349 284 | |
| organization-company 0.7838 0.6905 0.7342 252 | |
| distance 0.9882 1.0000 0.9940 167 | |
| number 0.6760 0.8121 0.7378 149 | |
| duration 0.3484 0.3313 0.3396 163 | |
| event-cause 0.0000 0.0000 0.0000 0 | |
| disaster-type 0.9310 0.3913 0.5510 69 | |
| organization 0.5769 0.5357 0.5556 28 | |
| person 0.5000 1.0000 0.6667 10 | |
| set 0.0000 0.0000 0.0000 0 | |
| org-position 0.0000 0.0000 0.0000 1 | |
| money 0.0000 0.0000 0.0000 0 | |
| micro avg 0.7637 0.7777 0.7706 4988 | |
| macro avg 0.6065 0.5949 0.5891 4988 | |
| weighted avg 0.8075 0.7777 0.7888 4988 | |
| 2023-10-19 00:16:25,690 ---------------------------------------------------------------------------------------------------- | |