| 2023-10-17 16:18:49,833 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:18:49,834 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=13, bias=True) | |
| (loss_function): CrossEntropyLoss() | |
| )" | |
| 2023-10-17 16:18:49,834 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:18:49,834 MultiCorpus: 5777 train + 722 dev + 723 test sentences | |
| - NER_ICDAR_EUROPEANA Corpus: 5777 train + 722 dev + 723 test sentences - /root/.flair/datasets/ner_icdar_europeana/nl | |
| 2023-10-17 16:18:49,835 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:18:49,835 Train: 5777 sentences | |
| 2023-10-17 16:18:49,835 (train_with_dev=False, train_with_test=False) | |
| 2023-10-17 16:18:49,835 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:18:49,835 Training Params: | |
| 2023-10-17 16:18:49,835 - learning_rate: "5e-05" | |
| 2023-10-17 16:18:49,835 - mini_batch_size: "4" | |
| 2023-10-17 16:18:49,835 - max_epochs: "10" | |
| 2023-10-17 16:18:49,835 - shuffle: "True" | |
| 2023-10-17 16:18:49,835 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:18:49,835 Plugins: | |
| 2023-10-17 16:18:49,835 - TensorboardLogger | |
| 2023-10-17 16:18:49,835 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-17 16:18:49,835 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:18:49,835 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-17 16:18:49,835 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-17 16:18:49,835 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:18:49,835 Computation: | |
| 2023-10-17 16:18:49,835 - compute on device: cuda:0 | |
| 2023-10-17 16:18:49,835 - embedding storage: none | |
| 2023-10-17 16:18:49,835 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:18:49,835 Model training base path: "hmbench-icdar/nl-hmteams/teams-base-historic-multilingual-discriminator-bs4-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-2" | |
| 2023-10-17 16:18:49,835 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:18:49,835 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:18:49,835 Logging anything other than scalars to TensorBoard is currently not supported. | |
| 2023-10-17 16:18:56,849 epoch 1 - iter 144/1445 - loss 2.13705809 - time (sec): 7.01 - samples/sec: 2602.15 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 16:19:03,750 epoch 1 - iter 288/1445 - loss 1.21878406 - time (sec): 13.91 - samples/sec: 2562.25 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 16:19:10,804 epoch 1 - iter 432/1445 - loss 0.90739784 - time (sec): 20.97 - samples/sec: 2498.56 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 16:19:17,974 epoch 1 - iter 576/1445 - loss 0.72044535 - time (sec): 28.14 - samples/sec: 2490.68 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 16:19:25,043 epoch 1 - iter 720/1445 - loss 0.60080964 - time (sec): 35.21 - samples/sec: 2512.23 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 16:19:31,904 epoch 1 - iter 864/1445 - loss 0.52771699 - time (sec): 42.07 - samples/sec: 2513.55 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-17 16:19:38,848 epoch 1 - iter 1008/1445 - loss 0.47241003 - time (sec): 49.01 - samples/sec: 2521.27 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-17 16:19:45,917 epoch 1 - iter 1152/1445 - loss 0.42720095 - time (sec): 56.08 - samples/sec: 2519.40 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-17 16:19:52,870 epoch 1 - iter 1296/1445 - loss 0.39375757 - time (sec): 63.03 - samples/sec: 2509.51 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-17 16:19:59,869 epoch 1 - iter 1440/1445 - loss 0.36718281 - time (sec): 70.03 - samples/sec: 2509.84 - lr: 0.000050 - momentum: 0.000000 | |
| 2023-10-17 16:20:00,093 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:20:00,093 EPOCH 1 done: loss 0.3666 - lr: 0.000050 | |
| 2023-10-17 16:20:02,889 DEV : loss 0.0853525772690773 - f1-score (micro avg) 0.8262 | |
| 2023-10-17 16:20:02,908 saving best model | |
| 2023-10-17 16:20:03,241 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:20:09,898 epoch 2 - iter 144/1445 - loss 0.13163265 - time (sec): 6.65 - samples/sec: 2487.09 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-17 16:20:16,952 epoch 2 - iter 288/1445 - loss 0.11859313 - time (sec): 13.71 - samples/sec: 2444.56 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-17 16:20:24,250 epoch 2 - iter 432/1445 - loss 0.10993065 - time (sec): 21.01 - samples/sec: 2427.99 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-17 16:20:31,667 epoch 2 - iter 576/1445 - loss 0.10512844 - time (sec): 28.42 - samples/sec: 2425.61 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-17 16:20:38,916 epoch 2 - iter 720/1445 - loss 0.10132998 - time (sec): 35.67 - samples/sec: 2409.57 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-17 16:20:46,181 epoch 2 - iter 864/1445 - loss 0.09827432 - time (sec): 42.94 - samples/sec: 2449.22 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-17 16:20:53,243 epoch 2 - iter 1008/1445 - loss 0.09734789 - time (sec): 50.00 - samples/sec: 2461.18 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-17 16:21:00,233 epoch 2 - iter 1152/1445 - loss 0.09616555 - time (sec): 56.99 - samples/sec: 2456.82 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-17 16:21:07,398 epoch 2 - iter 1296/1445 - loss 0.09677640 - time (sec): 64.15 - samples/sec: 2465.71 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-17 16:21:14,472 epoch 2 - iter 1440/1445 - loss 0.09633877 - time (sec): 71.23 - samples/sec: 2467.41 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-17 16:21:14,703 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:21:14,703 EPOCH 2 done: loss 0.0963 - lr: 0.000044 | |
| 2023-10-17 16:21:19,008 DEV : loss 0.09023821353912354 - f1-score (micro avg) 0.8362 | |
| 2023-10-17 16:21:19,040 saving best model | |
| 2023-10-17 16:21:19,492 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:21:26,867 epoch 3 - iter 144/1445 - loss 0.07639569 - time (sec): 7.37 - samples/sec: 2469.85 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-17 16:21:33,792 epoch 3 - iter 288/1445 - loss 0.07289280 - time (sec): 14.30 - samples/sec: 2474.87 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-17 16:21:41,036 epoch 3 - iter 432/1445 - loss 0.07369285 - time (sec): 21.54 - samples/sec: 2526.94 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-17 16:21:47,971 epoch 3 - iter 576/1445 - loss 0.07352607 - time (sec): 28.48 - samples/sec: 2503.52 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-17 16:21:55,171 epoch 3 - iter 720/1445 - loss 0.07225890 - time (sec): 35.68 - samples/sec: 2486.81 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-17 16:22:02,381 epoch 3 - iter 864/1445 - loss 0.06938398 - time (sec): 42.88 - samples/sec: 2494.71 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-17 16:22:09,345 epoch 3 - iter 1008/1445 - loss 0.07054082 - time (sec): 49.85 - samples/sec: 2475.72 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-17 16:22:16,271 epoch 3 - iter 1152/1445 - loss 0.07020152 - time (sec): 56.78 - samples/sec: 2463.08 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-17 16:22:23,487 epoch 3 - iter 1296/1445 - loss 0.07093905 - time (sec): 63.99 - samples/sec: 2465.29 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-17 16:22:30,787 epoch 3 - iter 1440/1445 - loss 0.07220694 - time (sec): 71.29 - samples/sec: 2462.25 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-17 16:22:31,037 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:22:31,038 EPOCH 3 done: loss 0.0723 - lr: 0.000039 | |
| 2023-10-17 16:22:34,317 DEV : loss 0.09389135241508484 - f1-score (micro avg) 0.8522 | |
| 2023-10-17 16:22:34,334 saving best model | |
| 2023-10-17 16:22:34,794 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:22:41,916 epoch 4 - iter 144/1445 - loss 0.03934107 - time (sec): 7.12 - samples/sec: 2501.87 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-17 16:22:48,884 epoch 4 - iter 288/1445 - loss 0.04960378 - time (sec): 14.09 - samples/sec: 2474.30 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-17 16:22:55,742 epoch 4 - iter 432/1445 - loss 0.04967966 - time (sec): 20.95 - samples/sec: 2464.10 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-17 16:23:02,583 epoch 4 - iter 576/1445 - loss 0.05239601 - time (sec): 27.79 - samples/sec: 2472.89 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-17 16:23:10,050 epoch 4 - iter 720/1445 - loss 0.05481533 - time (sec): 35.25 - samples/sec: 2459.94 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-17 16:23:17,233 epoch 4 - iter 864/1445 - loss 0.05681795 - time (sec): 42.44 - samples/sec: 2473.57 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-17 16:23:24,313 epoch 4 - iter 1008/1445 - loss 0.05672883 - time (sec): 49.52 - samples/sec: 2478.78 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-17 16:23:31,477 epoch 4 - iter 1152/1445 - loss 0.05481502 - time (sec): 56.68 - samples/sec: 2477.63 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-17 16:23:38,544 epoch 4 - iter 1296/1445 - loss 0.05437627 - time (sec): 63.75 - samples/sec: 2479.36 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-17 16:23:45,784 epoch 4 - iter 1440/1445 - loss 0.05419519 - time (sec): 70.99 - samples/sec: 2475.65 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-17 16:23:46,031 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:23:46,032 EPOCH 4 done: loss 0.0541 - lr: 0.000033 | |
| 2023-10-17 16:23:49,286 DEV : loss 0.10415765643119812 - f1-score (micro avg) 0.8558 | |
| 2023-10-17 16:23:49,302 saving best model | |
| 2023-10-17 16:23:49,759 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:23:56,689 epoch 5 - iter 144/1445 - loss 0.05670271 - time (sec): 6.93 - samples/sec: 2374.53 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-17 16:24:03,688 epoch 5 - iter 288/1445 - loss 0.04436221 - time (sec): 13.93 - samples/sec: 2443.03 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-17 16:24:10,773 epoch 5 - iter 432/1445 - loss 0.04616850 - time (sec): 21.01 - samples/sec: 2458.36 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-17 16:24:17,711 epoch 5 - iter 576/1445 - loss 0.04352124 - time (sec): 27.95 - samples/sec: 2426.81 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-17 16:24:25,343 epoch 5 - iter 720/1445 - loss 0.04411388 - time (sec): 35.58 - samples/sec: 2418.81 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-17 16:24:32,451 epoch 5 - iter 864/1445 - loss 0.04402856 - time (sec): 42.69 - samples/sec: 2426.02 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-17 16:24:39,891 epoch 5 - iter 1008/1445 - loss 0.04635845 - time (sec): 50.13 - samples/sec: 2442.79 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 16:24:47,269 epoch 5 - iter 1152/1445 - loss 0.04510679 - time (sec): 57.51 - samples/sec: 2459.29 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 16:24:54,254 epoch 5 - iter 1296/1445 - loss 0.04387905 - time (sec): 64.49 - samples/sec: 2467.17 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 16:25:00,944 epoch 5 - iter 1440/1445 - loss 0.04340737 - time (sec): 71.18 - samples/sec: 2466.49 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 16:25:01,206 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:25:01,206 EPOCH 5 done: loss 0.0434 - lr: 0.000028 | |
| 2023-10-17 16:25:04,542 DEV : loss 0.14961402118206024 - f1-score (micro avg) 0.7955 | |
| 2023-10-17 16:25:04,563 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:25:11,913 epoch 6 - iter 144/1445 - loss 0.05786667 - time (sec): 7.35 - samples/sec: 2503.05 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 16:25:18,998 epoch 6 - iter 288/1445 - loss 0.03941575 - time (sec): 14.43 - samples/sec: 2463.13 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 16:25:25,910 epoch 6 - iter 432/1445 - loss 0.03463529 - time (sec): 21.35 - samples/sec: 2477.92 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 16:25:32,830 epoch 6 - iter 576/1445 - loss 0.03145162 - time (sec): 28.27 - samples/sec: 2487.21 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 16:25:39,923 epoch 6 - iter 720/1445 - loss 0.02986732 - time (sec): 35.36 - samples/sec: 2501.74 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 16:25:46,695 epoch 6 - iter 864/1445 - loss 0.02915652 - time (sec): 42.13 - samples/sec: 2533.84 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 16:25:53,428 epoch 6 - iter 1008/1445 - loss 0.02815790 - time (sec): 48.86 - samples/sec: 2551.88 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 16:26:00,418 epoch 6 - iter 1152/1445 - loss 0.02863677 - time (sec): 55.85 - samples/sec: 2527.10 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 16:26:07,287 epoch 6 - iter 1296/1445 - loss 0.02857277 - time (sec): 62.72 - samples/sec: 2519.48 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 16:26:14,266 epoch 6 - iter 1440/1445 - loss 0.02901616 - time (sec): 69.70 - samples/sec: 2518.37 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 16:26:14,559 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:26:14,559 EPOCH 6 done: loss 0.0289 - lr: 0.000022 | |
| 2023-10-17 16:26:17,754 DEV : loss 0.15008436143398285 - f1-score (micro avg) 0.8202 | |
| 2023-10-17 16:26:17,770 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:26:24,700 epoch 7 - iter 144/1445 - loss 0.02000359 - time (sec): 6.93 - samples/sec: 2656.70 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 16:26:31,753 epoch 7 - iter 288/1445 - loss 0.01569030 - time (sec): 13.98 - samples/sec: 2590.17 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 16:26:39,001 epoch 7 - iter 432/1445 - loss 0.01782813 - time (sec): 21.23 - samples/sec: 2505.61 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 16:26:46,180 epoch 7 - iter 576/1445 - loss 0.01964390 - time (sec): 28.41 - samples/sec: 2499.50 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 16:26:53,381 epoch 7 - iter 720/1445 - loss 0.01835474 - time (sec): 35.61 - samples/sec: 2499.50 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 16:27:00,040 epoch 7 - iter 864/1445 - loss 0.01866023 - time (sec): 42.27 - samples/sec: 2508.78 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 16:27:07,184 epoch 7 - iter 1008/1445 - loss 0.01877361 - time (sec): 49.41 - samples/sec: 2486.61 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 16:27:13,862 epoch 7 - iter 1152/1445 - loss 0.01962775 - time (sec): 56.09 - samples/sec: 2498.38 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 16:27:20,488 epoch 7 - iter 1296/1445 - loss 0.01955537 - time (sec): 62.72 - samples/sec: 2507.44 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 16:27:27,403 epoch 7 - iter 1440/1445 - loss 0.02047548 - time (sec): 69.63 - samples/sec: 2522.27 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 16:27:27,637 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:27:27,637 EPOCH 7 done: loss 0.0204 - lr: 0.000017 | |
| 2023-10-17 16:27:31,016 DEV : loss 0.14934930205345154 - f1-score (micro avg) 0.8585 | |
| 2023-10-17 16:27:31,032 saving best model | |
| 2023-10-17 16:27:31,496 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:27:38,491 epoch 8 - iter 144/1445 - loss 0.01993635 - time (sec): 6.99 - samples/sec: 2446.12 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 16:27:45,557 epoch 8 - iter 288/1445 - loss 0.01529310 - time (sec): 14.06 - samples/sec: 2434.12 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 16:27:52,729 epoch 8 - iter 432/1445 - loss 0.01421649 - time (sec): 21.23 - samples/sec: 2451.36 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 16:27:59,839 epoch 8 - iter 576/1445 - loss 0.01275077 - time (sec): 28.34 - samples/sec: 2445.92 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 16:28:06,792 epoch 8 - iter 720/1445 - loss 0.01099475 - time (sec): 35.29 - samples/sec: 2421.95 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 16:28:14,048 epoch 8 - iter 864/1445 - loss 0.01053576 - time (sec): 42.55 - samples/sec: 2442.96 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 16:28:21,295 epoch 8 - iter 1008/1445 - loss 0.01107931 - time (sec): 49.80 - samples/sec: 2455.05 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 16:28:28,360 epoch 8 - iter 1152/1445 - loss 0.01295286 - time (sec): 56.86 - samples/sec: 2453.26 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 16:28:35,774 epoch 8 - iter 1296/1445 - loss 0.01309587 - time (sec): 64.28 - samples/sec: 2455.43 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 16:28:43,046 epoch 8 - iter 1440/1445 - loss 0.01319627 - time (sec): 71.55 - samples/sec: 2454.86 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 16:28:43,274 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:28:43,274 EPOCH 8 done: loss 0.0134 - lr: 0.000011 | |
| 2023-10-17 16:28:46,569 DEV : loss 0.16947199404239655 - f1-score (micro avg) 0.8524 | |
| 2023-10-17 16:28:46,602 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:28:53,623 epoch 9 - iter 144/1445 - loss 0.00899269 - time (sec): 7.02 - samples/sec: 2577.61 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 16:29:01,060 epoch 9 - iter 288/1445 - loss 0.01406469 - time (sec): 14.46 - samples/sec: 2548.89 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 16:29:08,313 epoch 9 - iter 432/1445 - loss 0.01182979 - time (sec): 21.71 - samples/sec: 2487.70 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 16:29:15,658 epoch 9 - iter 576/1445 - loss 0.01105186 - time (sec): 29.06 - samples/sec: 2453.24 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 16:29:22,816 epoch 9 - iter 720/1445 - loss 0.01186549 - time (sec): 36.21 - samples/sec: 2470.18 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 16:29:30,151 epoch 9 - iter 864/1445 - loss 0.01072237 - time (sec): 43.55 - samples/sec: 2460.49 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 16:29:37,289 epoch 9 - iter 1008/1445 - loss 0.01098163 - time (sec): 50.69 - samples/sec: 2446.11 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 16:29:44,787 epoch 9 - iter 1152/1445 - loss 0.01023991 - time (sec): 58.18 - samples/sec: 2426.10 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 16:29:52,556 epoch 9 - iter 1296/1445 - loss 0.01014140 - time (sec): 65.95 - samples/sec: 2401.36 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 16:30:00,822 epoch 9 - iter 1440/1445 - loss 0.00966526 - time (sec): 74.22 - samples/sec: 2365.25 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 16:30:01,060 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:30:01,060 EPOCH 9 done: loss 0.0096 - lr: 0.000006 | |
| 2023-10-17 16:30:04,778 DEV : loss 0.15933012962341309 - f1-score (micro avg) 0.8648 | |
| 2023-10-17 16:30:04,794 saving best model | |
| 2023-10-17 16:30:05,250 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:30:13,087 epoch 10 - iter 144/1445 - loss 0.00391485 - time (sec): 7.83 - samples/sec: 2316.86 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 16:30:20,360 epoch 10 - iter 288/1445 - loss 0.00316501 - time (sec): 15.11 - samples/sec: 2309.41 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 16:30:27,734 epoch 10 - iter 432/1445 - loss 0.00358503 - time (sec): 22.48 - samples/sec: 2231.35 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 16:30:35,048 epoch 10 - iter 576/1445 - loss 0.00564098 - time (sec): 29.80 - samples/sec: 2274.25 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 16:30:43,390 epoch 10 - iter 720/1445 - loss 0.00548837 - time (sec): 38.14 - samples/sec: 2249.40 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 16:30:51,087 epoch 10 - iter 864/1445 - loss 0.00552389 - time (sec): 45.83 - samples/sec: 2243.93 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 16:30:59,119 epoch 10 - iter 1008/1445 - loss 0.00560035 - time (sec): 53.87 - samples/sec: 2241.21 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 16:31:07,014 epoch 10 - iter 1152/1445 - loss 0.00546225 - time (sec): 61.76 - samples/sec: 2241.91 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 16:31:14,728 epoch 10 - iter 1296/1445 - loss 0.00603445 - time (sec): 69.48 - samples/sec: 2258.14 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 16:31:21,998 epoch 10 - iter 1440/1445 - loss 0.00608040 - time (sec): 76.75 - samples/sec: 2289.15 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-17 16:31:22,229 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:31:22,230 EPOCH 10 done: loss 0.0061 - lr: 0.000000 | |
| 2023-10-17 16:31:25,469 DEV : loss 0.15785089135169983 - f1-score (micro avg) 0.8684 | |
| 2023-10-17 16:31:25,485 saving best model | |
| 2023-10-17 16:31:26,269 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 16:31:26,270 Loading model from best epoch ... | |
| 2023-10-17 16:31:27,631 SequenceTagger predicts: Dictionary with 13 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 | |
| 2023-10-17 16:31:30,393 | |
| Results: | |
| - F-score (micro) 0.8444 | |
| - F-score (macro) 0.7376 | |
| - Accuracy 0.7372 | |
| By class: | |
| precision recall f1-score support | |
| PER 0.8584 0.8299 0.8439 482 | |
| LOC 0.9402 0.8581 0.8973 458 | |
| ORG 0.5370 0.4203 0.4715 69 | |
| micro avg 0.8763 0.8147 0.8444 1009 | |
| macro avg 0.7785 0.7027 0.7376 1009 | |
| weighted avg 0.8735 0.8147 0.8426 1009 | |
| 2023-10-17 16:31:30,393 ---------------------------------------------------------------------------------------------------- | |