| 2023-10-13 22:21:32,062 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:21:32,063 Model: "SequenceTagger( | |
| (embeddings): TransformerWordEmbeddings( | |
| (model): BertModel( | |
| (embeddings): BertEmbeddings( | |
| (word_embeddings): Embedding(32001, 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=13, bias=True) | |
| (loss_function): CrossEntropyLoss() | |
| )" | |
| 2023-10-13 22:21:32,063 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:21:32,063 MultiCorpus: 7936 train + 992 dev + 992 test sentences | |
| - NER_ICDAR_EUROPEANA Corpus: 7936 train + 992 dev + 992 test sentences - /root/.flair/datasets/ner_icdar_europeana/fr | |
| 2023-10-13 22:21:32,063 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:21:32,063 Train: 7936 sentences | |
| 2023-10-13 22:21:32,063 (train_with_dev=False, train_with_test=False) | |
| 2023-10-13 22:21:32,063 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:21:32,064 Training Params: | |
| 2023-10-13 22:21:32,064 - learning_rate: "3e-05" | |
| 2023-10-13 22:21:32,064 - mini_batch_size: "8" | |
| 2023-10-13 22:21:32,064 - max_epochs: "10" | |
| 2023-10-13 22:21:32,064 - shuffle: "True" | |
| 2023-10-13 22:21:32,064 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:21:32,064 Plugins: | |
| 2023-10-13 22:21:32,064 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-13 22:21:32,064 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:21:32,064 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-13 22:21:32,064 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-13 22:21:32,064 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:21:32,064 Computation: | |
| 2023-10-13 22:21:32,064 - compute on device: cuda:0 | |
| 2023-10-13 22:21:32,064 - embedding storage: none | |
| 2023-10-13 22:21:32,064 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:21:32,064 Model training base path: "hmbench-icdar/fr-dbmdz/bert-base-historic-multilingual-cased-bs8-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-2" | |
| 2023-10-13 22:21:32,064 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:21:32,064 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:21:38,226 epoch 1 - iter 99/992 - loss 2.33299355 - time (sec): 6.16 - samples/sec: 2821.27 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-13 22:21:43,899 epoch 1 - iter 198/992 - loss 1.45654399 - time (sec): 11.83 - samples/sec: 2803.24 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-13 22:21:49,704 epoch 1 - iter 297/992 - loss 1.08734806 - time (sec): 17.64 - samples/sec: 2777.39 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-13 22:21:55,475 epoch 1 - iter 396/992 - loss 0.87857029 - time (sec): 23.41 - samples/sec: 2773.46 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-13 22:22:01,199 epoch 1 - iter 495/992 - loss 0.74066449 - time (sec): 29.13 - samples/sec: 2783.19 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-13 22:22:07,235 epoch 1 - iter 594/992 - loss 0.64158469 - time (sec): 35.17 - samples/sec: 2778.31 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-13 22:22:12,920 epoch 1 - iter 693/992 - loss 0.57302135 - time (sec): 40.86 - samples/sec: 2782.79 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-13 22:22:18,655 epoch 1 - iter 792/992 - loss 0.51792287 - time (sec): 46.59 - samples/sec: 2794.99 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-13 22:22:24,750 epoch 1 - iter 891/992 - loss 0.47364366 - time (sec): 52.68 - samples/sec: 2790.38 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-13 22:22:30,602 epoch 1 - iter 990/992 - loss 0.43807375 - time (sec): 58.54 - samples/sec: 2793.01 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-13 22:22:30,750 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:22:30,750 EPOCH 1 done: loss 0.4368 - lr: 0.000030 | |
| 2023-10-13 22:22:33,919 DEV : loss 0.09895769506692886 - f1-score (micro avg) 0.6992 | |
| 2023-10-13 22:22:33,940 saving best model | |
| 2023-10-13 22:22:34,356 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:22:40,079 epoch 2 - iter 99/992 - loss 0.10440393 - time (sec): 5.72 - samples/sec: 2716.33 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-13 22:22:45,944 epoch 2 - iter 198/992 - loss 0.10904220 - time (sec): 11.59 - samples/sec: 2709.89 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-13 22:22:52,058 epoch 2 - iter 297/992 - loss 0.10445266 - time (sec): 17.70 - samples/sec: 2738.80 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-13 22:22:57,812 epoch 2 - iter 396/992 - loss 0.10543564 - time (sec): 23.45 - samples/sec: 2776.19 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-13 22:23:03,822 epoch 2 - iter 495/992 - loss 0.10401639 - time (sec): 29.46 - samples/sec: 2761.40 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-13 22:23:09,512 epoch 2 - iter 594/992 - loss 0.10324383 - time (sec): 35.16 - samples/sec: 2769.06 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-13 22:23:15,203 epoch 2 - iter 693/992 - loss 0.10117912 - time (sec): 40.85 - samples/sec: 2773.98 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-13 22:23:21,294 epoch 2 - iter 792/992 - loss 0.10187508 - time (sec): 46.94 - samples/sec: 2770.45 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-13 22:23:27,242 epoch 2 - iter 891/992 - loss 0.10186016 - time (sec): 52.89 - samples/sec: 2763.64 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-13 22:23:33,244 epoch 2 - iter 990/992 - loss 0.10129833 - time (sec): 58.89 - samples/sec: 2778.25 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-13 22:23:33,369 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:23:33,370 EPOCH 2 done: loss 0.1012 - lr: 0.000027 | |
| 2023-10-13 22:23:36,856 DEV : loss 0.09443922340869904 - f1-score (micro avg) 0.7469 | |
| 2023-10-13 22:23:36,889 saving best model | |
| 2023-10-13 22:23:37,421 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:23:44,041 epoch 3 - iter 99/992 - loss 0.07835091 - time (sec): 6.62 - samples/sec: 2418.55 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-13 22:23:49,988 epoch 3 - iter 198/992 - loss 0.07452825 - time (sec): 12.57 - samples/sec: 2565.06 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-13 22:23:55,653 epoch 3 - iter 297/992 - loss 0.06912775 - time (sec): 18.23 - samples/sec: 2646.29 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-13 22:24:01,450 epoch 3 - iter 396/992 - loss 0.07019004 - time (sec): 24.03 - samples/sec: 2688.30 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-13 22:24:07,403 epoch 3 - iter 495/992 - loss 0.06908856 - time (sec): 29.98 - samples/sec: 2698.01 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-13 22:24:13,363 epoch 3 - iter 594/992 - loss 0.06956091 - time (sec): 35.94 - samples/sec: 2710.32 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-13 22:24:19,337 epoch 3 - iter 693/992 - loss 0.07164602 - time (sec): 41.91 - samples/sec: 2708.74 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-13 22:24:25,264 epoch 3 - iter 792/992 - loss 0.07204638 - time (sec): 47.84 - samples/sec: 2726.73 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-13 22:24:31,199 epoch 3 - iter 891/992 - loss 0.07025467 - time (sec): 53.78 - samples/sec: 2740.60 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-13 22:24:37,045 epoch 3 - iter 990/992 - loss 0.06972650 - time (sec): 59.62 - samples/sec: 2746.36 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-13 22:24:37,147 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:24:37,147 EPOCH 3 done: loss 0.0697 - lr: 0.000023 | |
| 2023-10-13 22:24:40,552 DEV : loss 0.10710007697343826 - f1-score (micro avg) 0.7477 | |
| 2023-10-13 22:24:40,575 saving best model | |
| 2023-10-13 22:24:41,077 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:24:46,925 epoch 4 - iter 99/992 - loss 0.04664656 - time (sec): 5.84 - samples/sec: 2741.14 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-13 22:24:53,063 epoch 4 - iter 198/992 - loss 0.04715979 - time (sec): 11.98 - samples/sec: 2768.98 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-13 22:24:59,015 epoch 4 - iter 297/992 - loss 0.04504200 - time (sec): 17.93 - samples/sec: 2753.00 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-13 22:25:04,781 epoch 4 - iter 396/992 - loss 0.04552468 - time (sec): 23.70 - samples/sec: 2777.07 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-13 22:25:10,615 epoch 4 - iter 495/992 - loss 0.04550867 - time (sec): 29.53 - samples/sec: 2791.41 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-13 22:25:16,451 epoch 4 - iter 594/992 - loss 0.04745191 - time (sec): 35.37 - samples/sec: 2789.76 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-13 22:25:22,220 epoch 4 - iter 693/992 - loss 0.04806225 - time (sec): 41.14 - samples/sec: 2786.19 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-13 22:25:28,218 epoch 4 - iter 792/992 - loss 0.04807101 - time (sec): 47.14 - samples/sec: 2781.22 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-13 22:25:33,783 epoch 4 - iter 891/992 - loss 0.04884662 - time (sec): 52.70 - samples/sec: 2795.26 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-13 22:25:39,847 epoch 4 - iter 990/992 - loss 0.04904023 - time (sec): 58.77 - samples/sec: 2783.19 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-13 22:25:39,971 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:25:39,972 EPOCH 4 done: loss 0.0491 - lr: 0.000020 | |
| 2023-10-13 22:25:43,378 DEV : loss 0.1333416849374771 - f1-score (micro avg) 0.7489 | |
| 2023-10-13 22:25:43,398 saving best model | |
| 2023-10-13 22:25:44,266 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:25:50,041 epoch 5 - iter 99/992 - loss 0.03508164 - time (sec): 5.77 - samples/sec: 2761.94 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-13 22:25:55,794 epoch 5 - iter 198/992 - loss 0.03490154 - time (sec): 11.52 - samples/sec: 2811.59 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-13 22:26:01,520 epoch 5 - iter 297/992 - loss 0.03554118 - time (sec): 17.25 - samples/sec: 2835.25 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-13 22:26:07,492 epoch 5 - iter 396/992 - loss 0.03723271 - time (sec): 23.22 - samples/sec: 2830.39 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-13 22:26:13,620 epoch 5 - iter 495/992 - loss 0.03770116 - time (sec): 29.35 - samples/sec: 2814.86 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-13 22:26:19,504 epoch 5 - iter 594/992 - loss 0.03766517 - time (sec): 35.23 - samples/sec: 2797.30 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-13 22:26:25,285 epoch 5 - iter 693/992 - loss 0.03805744 - time (sec): 41.01 - samples/sec: 2792.03 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-13 22:26:31,050 epoch 5 - iter 792/992 - loss 0.03684000 - time (sec): 46.78 - samples/sec: 2788.99 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-13 22:26:37,088 epoch 5 - iter 891/992 - loss 0.03834438 - time (sec): 52.82 - samples/sec: 2790.28 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-13 22:26:42,739 epoch 5 - iter 990/992 - loss 0.03863747 - time (sec): 58.47 - samples/sec: 2796.55 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-13 22:26:42,895 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:26:42,895 EPOCH 5 done: loss 0.0386 - lr: 0.000017 | |
| 2023-10-13 22:26:46,395 DEV : loss 0.1474953144788742 - f1-score (micro avg) 0.7697 | |
| 2023-10-13 22:26:46,416 saving best model | |
| 2023-10-13 22:26:46,900 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:26:52,655 epoch 6 - iter 99/992 - loss 0.03066144 - time (sec): 5.75 - samples/sec: 2870.08 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-13 22:26:58,650 epoch 6 - iter 198/992 - loss 0.02576809 - time (sec): 11.75 - samples/sec: 2842.92 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-13 22:27:04,479 epoch 6 - iter 297/992 - loss 0.02640387 - time (sec): 17.58 - samples/sec: 2865.75 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-13 22:27:10,420 epoch 6 - iter 396/992 - loss 0.02662851 - time (sec): 23.52 - samples/sec: 2839.78 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-13 22:27:16,188 epoch 6 - iter 495/992 - loss 0.02679061 - time (sec): 29.28 - samples/sec: 2812.92 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-13 22:27:22,018 epoch 6 - iter 594/992 - loss 0.02779911 - time (sec): 35.12 - samples/sec: 2804.97 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-13 22:27:27,615 epoch 6 - iter 693/992 - loss 0.02793110 - time (sec): 40.71 - samples/sec: 2789.84 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-13 22:27:33,725 epoch 6 - iter 792/992 - loss 0.02849861 - time (sec): 46.82 - samples/sec: 2800.86 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-13 22:27:39,500 epoch 6 - iter 891/992 - loss 0.03003150 - time (sec): 52.60 - samples/sec: 2796.36 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-13 22:27:45,315 epoch 6 - iter 990/992 - loss 0.02931730 - time (sec): 58.41 - samples/sec: 2799.63 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-13 22:27:45,439 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:27:45,439 EPOCH 6 done: loss 0.0294 - lr: 0.000013 | |
| 2023-10-13 22:27:48,830 DEV : loss 0.18882010877132416 - f1-score (micro avg) 0.7443 | |
| 2023-10-13 22:27:48,850 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:27:54,585 epoch 7 - iter 99/992 - loss 0.01843936 - time (sec): 5.73 - samples/sec: 2830.51 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-13 22:28:00,478 epoch 7 - iter 198/992 - loss 0.01884112 - time (sec): 11.63 - samples/sec: 2775.82 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-13 22:28:07,139 epoch 7 - iter 297/992 - loss 0.02033178 - time (sec): 18.29 - samples/sec: 2712.51 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-13 22:28:13,151 epoch 7 - iter 396/992 - loss 0.02087243 - time (sec): 24.30 - samples/sec: 2732.06 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-13 22:28:19,012 epoch 7 - iter 495/992 - loss 0.02087418 - time (sec): 30.16 - samples/sec: 2747.66 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-13 22:28:24,686 epoch 7 - iter 594/992 - loss 0.02171817 - time (sec): 35.83 - samples/sec: 2751.03 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-13 22:28:30,346 epoch 7 - iter 693/992 - loss 0.02240224 - time (sec): 41.49 - samples/sec: 2767.35 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-13 22:28:36,072 epoch 7 - iter 792/992 - loss 0.02183838 - time (sec): 47.22 - samples/sec: 2779.85 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-13 22:28:41,868 epoch 7 - iter 891/992 - loss 0.02200465 - time (sec): 53.02 - samples/sec: 2773.88 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-13 22:28:47,905 epoch 7 - iter 990/992 - loss 0.02214401 - time (sec): 59.05 - samples/sec: 2773.37 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-13 22:28:48,003 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:28:48,003 EPOCH 7 done: loss 0.0221 - lr: 0.000010 | |
| 2023-10-13 22:28:51,462 DEV : loss 0.18745747208595276 - f1-score (micro avg) 0.7648 | |
| 2023-10-13 22:28:51,483 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:28:57,625 epoch 8 - iter 99/992 - loss 0.01733595 - time (sec): 6.14 - samples/sec: 2687.32 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-13 22:29:03,732 epoch 8 - iter 198/992 - loss 0.01451052 - time (sec): 12.25 - samples/sec: 2732.96 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-13 22:29:09,698 epoch 8 - iter 297/992 - loss 0.01458980 - time (sec): 18.21 - samples/sec: 2747.88 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-13 22:29:15,627 epoch 8 - iter 396/992 - loss 0.01434329 - time (sec): 24.14 - samples/sec: 2786.27 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-13 22:29:21,451 epoch 8 - iter 495/992 - loss 0.01589815 - time (sec): 29.97 - samples/sec: 2787.43 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-13 22:29:27,300 epoch 8 - iter 594/992 - loss 0.01547773 - time (sec): 35.82 - samples/sec: 2772.84 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-13 22:29:33,240 epoch 8 - iter 693/992 - loss 0.01546711 - time (sec): 41.76 - samples/sec: 2752.58 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-13 22:29:39,317 epoch 8 - iter 792/992 - loss 0.01554967 - time (sec): 47.83 - samples/sec: 2748.23 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-13 22:29:45,154 epoch 8 - iter 891/992 - loss 0.01624295 - time (sec): 53.67 - samples/sec: 2751.29 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-13 22:29:51,001 epoch 8 - iter 990/992 - loss 0.01584456 - time (sec): 59.52 - samples/sec: 2752.74 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-13 22:29:51,101 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:29:51,101 EPOCH 8 done: loss 0.0160 - lr: 0.000007 | |
| 2023-10-13 22:29:54,567 DEV : loss 0.19708073139190674 - f1-score (micro avg) 0.7606 | |
| 2023-10-13 22:29:54,588 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:30:00,193 epoch 9 - iter 99/992 - loss 0.00851250 - time (sec): 5.60 - samples/sec: 2638.38 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-13 22:30:05,871 epoch 9 - iter 198/992 - loss 0.01387637 - time (sec): 11.28 - samples/sec: 2720.77 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-13 22:30:11,835 epoch 9 - iter 297/992 - loss 0.01335263 - time (sec): 17.25 - samples/sec: 2715.07 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-13 22:30:17,685 epoch 9 - iter 396/992 - loss 0.01153281 - time (sec): 23.10 - samples/sec: 2735.71 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-13 22:30:23,804 epoch 9 - iter 495/992 - loss 0.01105092 - time (sec): 29.21 - samples/sec: 2740.26 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-13 22:30:29,756 epoch 9 - iter 594/992 - loss 0.01139772 - time (sec): 35.17 - samples/sec: 2748.28 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-13 22:30:35,469 epoch 9 - iter 693/992 - loss 0.01125951 - time (sec): 40.88 - samples/sec: 2762.21 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-13 22:30:41,410 epoch 9 - iter 792/992 - loss 0.01144688 - time (sec): 46.82 - samples/sec: 2773.64 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-13 22:30:47,347 epoch 9 - iter 891/992 - loss 0.01171083 - time (sec): 52.76 - samples/sec: 2778.18 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-13 22:30:53,864 epoch 9 - iter 990/992 - loss 0.01160068 - time (sec): 59.27 - samples/sec: 2759.87 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-13 22:30:53,972 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:30:53,972 EPOCH 9 done: loss 0.0116 - lr: 0.000003 | |
| 2023-10-13 22:30:57,399 DEV : loss 0.21158859133720398 - f1-score (micro avg) 0.7642 | |
| 2023-10-13 22:30:57,420 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:31:03,143 epoch 10 - iter 99/992 - loss 0.01294454 - time (sec): 5.72 - samples/sec: 2871.83 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-13 22:31:09,337 epoch 10 - iter 198/992 - loss 0.01174616 - time (sec): 11.92 - samples/sec: 2875.49 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-13 22:31:14,913 epoch 10 - iter 297/992 - loss 0.01070740 - time (sec): 17.49 - samples/sec: 2844.70 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-13 22:31:20,657 epoch 10 - iter 396/992 - loss 0.01045205 - time (sec): 23.24 - samples/sec: 2850.69 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-13 22:31:26,862 epoch 10 - iter 495/992 - loss 0.01098101 - time (sec): 29.44 - samples/sec: 2830.26 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-13 22:31:32,596 epoch 10 - iter 594/992 - loss 0.01073008 - time (sec): 35.18 - samples/sec: 2824.57 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-13 22:31:38,266 epoch 10 - iter 693/992 - loss 0.01015657 - time (sec): 40.85 - samples/sec: 2806.63 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-13 22:31:44,347 epoch 10 - iter 792/992 - loss 0.00973608 - time (sec): 46.93 - samples/sec: 2792.56 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-13 22:31:50,396 epoch 10 - iter 891/992 - loss 0.00928079 - time (sec): 52.98 - samples/sec: 2788.54 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-13 22:31:56,043 epoch 10 - iter 990/992 - loss 0.00889257 - time (sec): 58.62 - samples/sec: 2792.15 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-13 22:31:56,156 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:31:56,156 EPOCH 10 done: loss 0.0089 - lr: 0.000000 | |
| 2023-10-13 22:31:59,648 DEV : loss 0.21550461649894714 - f1-score (micro avg) 0.7694 | |
| 2023-10-13 22:32:00,091 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 22:32:00,092 Loading model from best epoch ... | |
| 2023-10-13 22:32:01,548 SequenceTagger predicts: Dictionary with 13 tags: O, S-PER, B-PER, E-PER, I-PER, S-LOC, B-LOC, E-LOC, I-LOC, S-ORG, B-ORG, E-ORG, I-ORG | |
| 2023-10-13 22:32:04,837 | |
| Results: | |
| - F-score (micro) 0.7902 | |
| - F-score (macro) 0.7068 | |
| - Accuracy 0.6763 | |
| By class: | |
| precision recall f1-score support | |
| LOC 0.8268 0.8748 0.8501 655 | |
| PER 0.7026 0.8475 0.7683 223 | |
| ORG 0.5259 0.4803 0.5021 127 | |
| micro avg 0.7635 0.8189 0.7902 1005 | |
| macro avg 0.6851 0.7342 0.7068 1005 | |
| weighted avg 0.7612 0.8189 0.7880 1005 | |
| 2023-10-13 22:32:04,837 ---------------------------------------------------------------------------------------------------- | |