| 2023-10-17 17:26:59,563 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:26:59,564 Model: "SequenceTagger( | |
| (embeddings): TransformerWordEmbeddings( | |
| (model): ElectraModel( | |
| (embeddings): ElectraEmbeddings( | |
| (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): ElectraEncoder( | |
| (layer): ModuleList( | |
| (0-11): 12 x ElectraLayer( | |
| (attention): ElectraAttention( | |
| (self): ElectraSelfAttention( | |
| (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): ElectraSelfOutput( | |
| (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): ElectraIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| (intermediate_act_fn): GELUActivation() | |
| ) | |
| (output): ElectraOutput( | |
| (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) | |
| ) | |
| ) | |
| ) | |
| ) | |
| ) | |
| ) | |
| (locked_dropout): LockedDropout(p=0.5) | |
| (linear): Linear(in_features=768, out_features=17, bias=True) | |
| (loss_function): CrossEntropyLoss() | |
| )" | |
| 2023-10-17 17:26:59,564 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:26:59,564 MultiCorpus: 1166 train + 165 dev + 415 test sentences | |
| - NER_HIPE_2022 Corpus: 1166 train + 165 dev + 415 test sentences - /root/.flair/datasets/ner_hipe_2022/v2.1/newseye/fi/with_doc_seperator | |
| 2023-10-17 17:26:59,564 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:26:59,564 Train: 1166 sentences | |
| 2023-10-17 17:26:59,564 (train_with_dev=False, train_with_test=False) | |
| 2023-10-17 17:26:59,565 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:26:59,565 Training Params: | |
| 2023-10-17 17:26:59,565 - learning_rate: "3e-05" | |
| 2023-10-17 17:26:59,565 - mini_batch_size: "4" | |
| 2023-10-17 17:26:59,565 - max_epochs: "10" | |
| 2023-10-17 17:26:59,565 - shuffle: "True" | |
| 2023-10-17 17:26:59,565 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:26:59,565 Plugins: | |
| 2023-10-17 17:26:59,565 - TensorboardLogger | |
| 2023-10-17 17:26:59,565 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-17 17:26:59,565 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:26:59,565 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-17 17:26:59,565 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-17 17:26:59,565 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:26:59,565 Computation: | |
| 2023-10-17 17:26:59,565 - compute on device: cuda:0 | |
| 2023-10-17 17:26:59,565 - embedding storage: none | |
| 2023-10-17 17:26:59,565 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:26:59,565 Model training base path: "hmbench-newseye/fi-hmteams/teams-base-historic-multilingual-discriminator-bs4-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-1" | |
| 2023-10-17 17:26:59,566 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:26:59,566 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:26:59,566 Logging anything other than scalars to TensorBoard is currently not supported. | |
| 2023-10-17 17:27:02,559 epoch 1 - iter 29/292 - loss 3.38067707 - time (sec): 2.99 - samples/sec: 1274.79 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 17:27:04,259 epoch 1 - iter 58/292 - loss 2.84271477 - time (sec): 4.69 - samples/sec: 1733.47 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 17:27:06,435 epoch 1 - iter 87/292 - loss 2.15025489 - time (sec): 6.87 - samples/sec: 2025.87 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 17:27:08,024 epoch 1 - iter 116/292 - loss 1.73892010 - time (sec): 8.46 - samples/sec: 2196.36 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 17:27:09,750 epoch 1 - iter 145/292 - loss 1.52932502 - time (sec): 10.18 - samples/sec: 2213.85 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 17:27:11,391 epoch 1 - iter 174/292 - loss 1.35737795 - time (sec): 11.82 - samples/sec: 2255.55 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 17:27:13,018 epoch 1 - iter 203/292 - loss 1.21956588 - time (sec): 13.45 - samples/sec: 2279.46 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 17:27:14,949 epoch 1 - iter 232/292 - loss 1.09424639 - time (sec): 15.38 - samples/sec: 2310.72 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 17:27:16,712 epoch 1 - iter 261/292 - loss 1.01634785 - time (sec): 17.14 - samples/sec: 2301.10 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 17:27:18,606 epoch 1 - iter 290/292 - loss 0.93625762 - time (sec): 19.04 - samples/sec: 2320.43 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-17 17:27:18,714 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:27:18,715 EPOCH 1 done: loss 0.9322 - lr: 0.000030 | |
| 2023-10-17 17:27:19,545 DEV : loss 0.19820411503314972 - f1-score (micro avg) 0.4404 | |
| 2023-10-17 17:27:19,551 saving best model | |
| 2023-10-17 17:27:19,982 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:27:21,872 epoch 2 - iter 29/292 - loss 0.22906131 - time (sec): 1.89 - samples/sec: 2440.74 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-17 17:27:23,585 epoch 2 - iter 58/292 - loss 0.20380503 - time (sec): 3.60 - samples/sec: 2427.27 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 17:27:25,351 epoch 2 - iter 87/292 - loss 0.19601726 - time (sec): 5.37 - samples/sec: 2453.85 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 17:27:27,325 epoch 2 - iter 116/292 - loss 0.18101298 - time (sec): 7.34 - samples/sec: 2492.83 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 17:27:29,067 epoch 2 - iter 145/292 - loss 0.17978471 - time (sec): 9.08 - samples/sec: 2536.20 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 17:27:30,696 epoch 2 - iter 174/292 - loss 0.17845205 - time (sec): 10.71 - samples/sec: 2574.15 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 17:27:32,232 epoch 2 - iter 203/292 - loss 0.18417685 - time (sec): 12.25 - samples/sec: 2562.26 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 17:27:33,820 epoch 2 - iter 232/292 - loss 0.19378925 - time (sec): 13.84 - samples/sec: 2538.03 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 17:27:35,628 epoch 2 - iter 261/292 - loss 0.19190160 - time (sec): 15.64 - samples/sec: 2570.21 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 17:27:37,313 epoch 2 - iter 290/292 - loss 0.18637235 - time (sec): 17.33 - samples/sec: 2554.65 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 17:27:37,418 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:27:37,419 EPOCH 2 done: loss 0.1866 - lr: 0.000027 | |
| 2023-10-17 17:27:38,858 DEV : loss 0.13132032752037048 - f1-score (micro avg) 0.6523 | |
| 2023-10-17 17:27:38,881 saving best model | |
| 2023-10-17 17:27:39,381 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:27:41,149 epoch 3 - iter 29/292 - loss 0.11668019 - time (sec): 1.76 - samples/sec: 2582.00 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 17:27:42,789 epoch 3 - iter 58/292 - loss 0.10524911 - time (sec): 3.40 - samples/sec: 2641.65 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 17:27:44,415 epoch 3 - iter 87/292 - loss 0.12104987 - time (sec): 5.03 - samples/sec: 2720.98 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 17:27:45,968 epoch 3 - iter 116/292 - loss 0.11755234 - time (sec): 6.58 - samples/sec: 2686.04 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 17:27:47,599 epoch 3 - iter 145/292 - loss 0.11284499 - time (sec): 8.21 - samples/sec: 2658.66 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 17:27:49,217 epoch 3 - iter 174/292 - loss 0.10811762 - time (sec): 9.83 - samples/sec: 2628.27 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 17:27:51,020 epoch 3 - iter 203/292 - loss 0.10863850 - time (sec): 11.63 - samples/sec: 2659.81 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 17:27:52,752 epoch 3 - iter 232/292 - loss 0.10627802 - time (sec): 13.37 - samples/sec: 2663.02 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 17:27:54,311 epoch 3 - iter 261/292 - loss 0.10575975 - time (sec): 14.93 - samples/sec: 2655.88 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 17:27:56,137 epoch 3 - iter 290/292 - loss 0.10736363 - time (sec): 16.75 - samples/sec: 2634.68 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 17:27:56,257 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:27:56,257 EPOCH 3 done: loss 0.1078 - lr: 0.000023 | |
| 2023-10-17 17:27:57,516 DEV : loss 0.1270725578069687 - f1-score (micro avg) 0.7313 | |
| 2023-10-17 17:27:57,521 saving best model | |
| 2023-10-17 17:27:57,991 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:27:59,500 epoch 4 - iter 29/292 - loss 0.11337783 - time (sec): 1.50 - samples/sec: 2364.25 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 17:28:01,109 epoch 4 - iter 58/292 - loss 0.09246785 - time (sec): 3.11 - samples/sec: 2522.43 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 17:28:03,000 epoch 4 - iter 87/292 - loss 0.07732073 - time (sec): 5.01 - samples/sec: 2562.90 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 17:28:04,764 epoch 4 - iter 116/292 - loss 0.07279139 - time (sec): 6.77 - samples/sec: 2578.42 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 17:28:06,391 epoch 4 - iter 145/292 - loss 0.06862627 - time (sec): 8.40 - samples/sec: 2594.33 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 17:28:08,168 epoch 4 - iter 174/292 - loss 0.06941418 - time (sec): 10.17 - samples/sec: 2623.37 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 17:28:09,936 epoch 4 - iter 203/292 - loss 0.07292749 - time (sec): 11.94 - samples/sec: 2633.95 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 17:28:11,626 epoch 4 - iter 232/292 - loss 0.07213824 - time (sec): 13.63 - samples/sec: 2620.05 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 17:28:13,204 epoch 4 - iter 261/292 - loss 0.07275720 - time (sec): 15.21 - samples/sec: 2641.76 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 17:28:14,908 epoch 4 - iter 290/292 - loss 0.07210992 - time (sec): 16.91 - samples/sec: 2611.71 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 17:28:15,014 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:28:15,015 EPOCH 4 done: loss 0.0719 - lr: 0.000020 | |
| 2023-10-17 17:28:16,266 DEV : loss 0.12534381449222565 - f1-score (micro avg) 0.7749 | |
| 2023-10-17 17:28:16,271 saving best model | |
| 2023-10-17 17:28:16,794 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:28:18,744 epoch 5 - iter 29/292 - loss 0.05953152 - time (sec): 1.95 - samples/sec: 2665.79 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 17:28:20,508 epoch 5 - iter 58/292 - loss 0.04305700 - time (sec): 3.71 - samples/sec: 2662.09 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 17:28:22,098 epoch 5 - iter 87/292 - loss 0.05274874 - time (sec): 5.30 - samples/sec: 2689.83 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 17:28:23,608 epoch 5 - iter 116/292 - loss 0.05816026 - time (sec): 6.81 - samples/sec: 2652.68 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 17:28:25,334 epoch 5 - iter 145/292 - loss 0.05818204 - time (sec): 8.54 - samples/sec: 2630.17 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 17:28:27,100 epoch 5 - iter 174/292 - loss 0.05810976 - time (sec): 10.30 - samples/sec: 2649.02 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 17:28:28,766 epoch 5 - iter 203/292 - loss 0.05835023 - time (sec): 11.97 - samples/sec: 2652.40 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 17:28:30,397 epoch 5 - iter 232/292 - loss 0.05556762 - time (sec): 13.60 - samples/sec: 2658.25 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 17:28:32,060 epoch 5 - iter 261/292 - loss 0.05489206 - time (sec): 15.26 - samples/sec: 2619.23 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 17:28:33,627 epoch 5 - iter 290/292 - loss 0.05276153 - time (sec): 16.83 - samples/sec: 2620.96 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 17:28:33,744 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:28:33,744 EPOCH 5 done: loss 0.0524 - lr: 0.000017 | |
| 2023-10-17 17:28:35,003 DEV : loss 0.1388275921344757 - f1-score (micro avg) 0.7404 | |
| 2023-10-17 17:28:35,007 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:28:36,580 epoch 6 - iter 29/292 - loss 0.04318866 - time (sec): 1.57 - samples/sec: 2847.50 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 17:28:38,085 epoch 6 - iter 58/292 - loss 0.04282065 - time (sec): 3.08 - samples/sec: 2629.42 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 17:28:39,949 epoch 6 - iter 87/292 - loss 0.04016784 - time (sec): 4.94 - samples/sec: 2609.49 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 17:28:41,597 epoch 6 - iter 116/292 - loss 0.04140804 - time (sec): 6.59 - samples/sec: 2608.75 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 17:28:43,095 epoch 6 - iter 145/292 - loss 0.04001813 - time (sec): 8.09 - samples/sec: 2562.13 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 17:28:44,814 epoch 6 - iter 174/292 - loss 0.03934836 - time (sec): 9.80 - samples/sec: 2549.72 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 17:28:46,650 epoch 6 - iter 203/292 - loss 0.03998330 - time (sec): 11.64 - samples/sec: 2553.75 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 17:28:48,456 epoch 6 - iter 232/292 - loss 0.03957101 - time (sec): 13.45 - samples/sec: 2559.54 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 17:28:50,115 epoch 6 - iter 261/292 - loss 0.03892236 - time (sec): 15.11 - samples/sec: 2565.17 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 17:28:51,917 epoch 6 - iter 290/292 - loss 0.03724276 - time (sec): 16.91 - samples/sec: 2618.81 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 17:28:52,008 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:28:52,008 EPOCH 6 done: loss 0.0373 - lr: 0.000013 | |
| 2023-10-17 17:28:53,260 DEV : loss 0.15327706933021545 - f1-score (micro avg) 0.7414 | |
| 2023-10-17 17:28:53,265 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:28:55,107 epoch 7 - iter 29/292 - loss 0.01499409 - time (sec): 1.84 - samples/sec: 2673.73 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 17:28:56,892 epoch 7 - iter 58/292 - loss 0.02746269 - time (sec): 3.63 - samples/sec: 2535.72 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 17:28:58,571 epoch 7 - iter 87/292 - loss 0.03058176 - time (sec): 5.31 - samples/sec: 2609.09 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 17:29:00,399 epoch 7 - iter 116/292 - loss 0.02783010 - time (sec): 7.13 - samples/sec: 2613.54 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 17:29:02,208 epoch 7 - iter 145/292 - loss 0.02763787 - time (sec): 8.94 - samples/sec: 2636.93 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 17:29:03,848 epoch 7 - iter 174/292 - loss 0.02864891 - time (sec): 10.58 - samples/sec: 2631.66 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 17:29:05,535 epoch 7 - iter 203/292 - loss 0.02705060 - time (sec): 12.27 - samples/sec: 2655.11 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 17:29:07,098 epoch 7 - iter 232/292 - loss 0.02619522 - time (sec): 13.83 - samples/sec: 2656.91 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 17:29:08,606 epoch 7 - iter 261/292 - loss 0.02763773 - time (sec): 15.34 - samples/sec: 2636.76 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 17:29:10,173 epoch 7 - iter 290/292 - loss 0.02674452 - time (sec): 16.91 - samples/sec: 2618.73 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 17:29:10,271 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:29:10,271 EPOCH 7 done: loss 0.0267 - lr: 0.000010 | |
| 2023-10-17 17:29:11,518 DEV : loss 0.16855847835540771 - f1-score (micro avg) 0.7511 | |
| 2023-10-17 17:29:11,523 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:29:13,452 epoch 8 - iter 29/292 - loss 0.02027046 - time (sec): 1.93 - samples/sec: 2456.17 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 17:29:15,350 epoch 8 - iter 58/292 - loss 0.02601394 - time (sec): 3.83 - samples/sec: 2461.62 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 17:29:17,197 epoch 8 - iter 87/292 - loss 0.02915936 - time (sec): 5.67 - samples/sec: 2511.81 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 17:29:18,764 epoch 8 - iter 116/292 - loss 0.02597150 - time (sec): 7.24 - samples/sec: 2514.51 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 17:29:20,355 epoch 8 - iter 145/292 - loss 0.02298947 - time (sec): 8.83 - samples/sec: 2498.33 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 17:29:21,943 epoch 8 - iter 174/292 - loss 0.02214849 - time (sec): 10.42 - samples/sec: 2477.29 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 17:29:23,569 epoch 8 - iter 203/292 - loss 0.02160627 - time (sec): 12.04 - samples/sec: 2515.45 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 17:29:25,193 epoch 8 - iter 232/292 - loss 0.01994902 - time (sec): 13.67 - samples/sec: 2512.24 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 17:29:27,208 epoch 8 - iter 261/292 - loss 0.02019007 - time (sec): 15.68 - samples/sec: 2572.58 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 17:29:28,717 epoch 8 - iter 290/292 - loss 0.02000299 - time (sec): 17.19 - samples/sec: 2580.42 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 17:29:28,810 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:29:28,811 EPOCH 8 done: loss 0.0200 - lr: 0.000007 | |
| 2023-10-17 17:29:30,046 DEV : loss 0.16279011964797974 - f1-score (micro avg) 0.7297 | |
| 2023-10-17 17:29:30,050 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:29:31,831 epoch 9 - iter 29/292 - loss 0.01144995 - time (sec): 1.78 - samples/sec: 2396.24 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 17:29:33,608 epoch 9 - iter 58/292 - loss 0.01623989 - time (sec): 3.56 - samples/sec: 2291.67 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 17:29:35,363 epoch 9 - iter 87/292 - loss 0.01401842 - time (sec): 5.31 - samples/sec: 2234.76 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 17:29:37,138 epoch 9 - iter 116/292 - loss 0.01205765 - time (sec): 7.09 - samples/sec: 2251.76 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 17:29:38,916 epoch 9 - iter 145/292 - loss 0.01173432 - time (sec): 8.86 - samples/sec: 2348.03 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 17:29:40,652 epoch 9 - iter 174/292 - loss 0.01383228 - time (sec): 10.60 - samples/sec: 2400.23 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 17:29:42,275 epoch 9 - iter 203/292 - loss 0.01267356 - time (sec): 12.22 - samples/sec: 2423.12 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 17:29:43,999 epoch 9 - iter 232/292 - loss 0.01196640 - time (sec): 13.95 - samples/sec: 2479.86 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 17:29:45,663 epoch 9 - iter 261/292 - loss 0.01366318 - time (sec): 15.61 - samples/sec: 2524.91 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 17:29:47,441 epoch 9 - iter 290/292 - loss 0.01473423 - time (sec): 17.39 - samples/sec: 2527.37 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 17:29:47,644 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:29:47,644 EPOCH 9 done: loss 0.0147 - lr: 0.000003 | |
| 2023-10-17 17:29:48,905 DEV : loss 0.175223708152771 - f1-score (micro avg) 0.7467 | |
| 2023-10-17 17:29:48,910 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:29:50,670 epoch 10 - iter 29/292 - loss 0.01438218 - time (sec): 1.76 - samples/sec: 2780.63 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 17:29:52,357 epoch 10 - iter 58/292 - loss 0.01415184 - time (sec): 3.45 - samples/sec: 2802.79 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 17:29:54,032 epoch 10 - iter 87/292 - loss 0.01816413 - time (sec): 5.12 - samples/sec: 2710.02 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 17:29:55,669 epoch 10 - iter 116/292 - loss 0.01481988 - time (sec): 6.76 - samples/sec: 2678.17 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 17:29:57,326 epoch 10 - iter 145/292 - loss 0.01203336 - time (sec): 8.41 - samples/sec: 2674.61 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 17:29:59,003 epoch 10 - iter 174/292 - loss 0.01214143 - time (sec): 10.09 - samples/sec: 2658.32 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 17:30:00,852 epoch 10 - iter 203/292 - loss 0.01276323 - time (sec): 11.94 - samples/sec: 2663.21 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 17:30:02,439 epoch 10 - iter 232/292 - loss 0.01297237 - time (sec): 13.53 - samples/sec: 2638.23 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 17:30:04,230 epoch 10 - iter 261/292 - loss 0.01231085 - time (sec): 15.32 - samples/sec: 2651.34 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-17 17:30:05,785 epoch 10 - iter 290/292 - loss 0.01144895 - time (sec): 16.87 - samples/sec: 2623.09 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-17 17:30:05,893 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:30:05,893 EPOCH 10 done: loss 0.0114 - lr: 0.000000 | |
| 2023-10-17 17:30:07,136 DEV : loss 0.17449024319648743 - f1-score (micro avg) 0.7387 | |
| 2023-10-17 17:30:07,536 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:30:07,537 Loading model from best epoch ... | |
| 2023-10-17 17:30:09,536 SequenceTagger predicts: Dictionary with 17 tags: O, S-LOC, B-LOC, E-LOC, I-LOC, S-PER, B-PER, E-PER, I-PER, S-ORG, B-ORG, E-ORG, I-ORG, S-HumanProd, B-HumanProd, E-HumanProd, I-HumanProd | |
| 2023-10-17 17:30:12,032 | |
| Results: | |
| - F-score (micro) 0.7261 | |
| - F-score (macro) 0.6066 | |
| - Accuracy 0.5897 | |
| By class: | |
| precision recall f1-score support | |
| PER 0.8437 0.8218 0.8326 348 | |
| LOC 0.6073 0.7701 0.6791 261 | |
| ORG 0.3077 0.2308 0.2637 52 | |
| HumanProd 0.6667 0.6364 0.6512 22 | |
| micro avg 0.7027 0.7511 0.7261 683 | |
| macro avg 0.6063 0.6148 0.6066 683 | |
| weighted avg 0.7068 0.7511 0.7248 683 | |
| 2023-10-17 17:30:12,032 ---------------------------------------------------------------------------------------------------- | |