| 2023-10-17 17:51:15,725 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:51:15,726 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 17:51:15,726 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:51:15,727 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 17:51:15,727 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:51:15,727 Train: 1166 sentences | |
| 2023-10-17 17:51:15,727 (train_with_dev=False, train_with_test=False) | |
| 2023-10-17 17:51:15,727 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:51:15,727 Training Params: | |
| 2023-10-17 17:51:15,727 - learning_rate: "5e-05" | |
| 2023-10-17 17:51:15,727 - mini_batch_size: "8" | |
| 2023-10-17 17:51:15,727 - max_epochs: "10" | |
| 2023-10-17 17:51:15,727 - shuffle: "True" | |
| 2023-10-17 17:51:15,727 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:51:15,727 Plugins: | |
| 2023-10-17 17:51:15,727 - TensorboardLogger | |
| 2023-10-17 17:51:15,727 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-17 17:51:15,727 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:51:15,727 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-17 17:51:15,727 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-17 17:51:15,727 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:51:15,727 Computation: | |
| 2023-10-17 17:51:15,727 - compute on device: cuda:0 | |
| 2023-10-17 17:51:15,727 - embedding storage: none | |
| 2023-10-17 17:51:15,727 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:51:15,727 Model training base path: "hmbench-newseye/fi-hmteams/teams-base-historic-multilingual-discriminator-bs8-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-2" | |
| 2023-10-17 17:51:15,727 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:51:15,727 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:51:15,728 Logging anything other than scalars to TensorBoard is currently not supported. | |
| 2023-10-17 17:51:17,221 epoch 1 - iter 14/146 - loss 3.64932727 - time (sec): 1.49 - samples/sec: 2867.39 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 17:51:18,616 epoch 1 - iter 28/146 - loss 3.24147358 - time (sec): 2.89 - samples/sec: 3050.04 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 17:51:20,366 epoch 1 - iter 42/146 - loss 2.52637762 - time (sec): 4.64 - samples/sec: 2820.99 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 17:51:21,662 epoch 1 - iter 56/146 - loss 2.07805214 - time (sec): 5.93 - samples/sec: 2843.80 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 17:51:22,860 epoch 1 - iter 70/146 - loss 1.82936614 - time (sec): 7.13 - samples/sec: 2864.60 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 17:51:24,170 epoch 1 - iter 84/146 - loss 1.60733726 - time (sec): 8.44 - samples/sec: 2875.49 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 17:51:25,653 epoch 1 - iter 98/146 - loss 1.41652938 - time (sec): 9.92 - samples/sec: 2901.33 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-17 17:51:26,915 epoch 1 - iter 112/146 - loss 1.29603818 - time (sec): 11.19 - samples/sec: 2910.85 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-17 17:51:28,301 epoch 1 - iter 126/146 - loss 1.18560723 - time (sec): 12.57 - samples/sec: 2914.11 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-17 17:51:30,183 epoch 1 - iter 140/146 - loss 1.07325034 - time (sec): 14.45 - samples/sec: 2922.08 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-17 17:51:31,007 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:51:31,008 EPOCH 1 done: loss 1.0409 - lr: 0.000048 | |
| 2023-10-17 17:51:31,833 DEV : loss 0.19442486763000488 - f1-score (micro avg) 0.4893 | |
| 2023-10-17 17:51:31,838 saving best model | |
| 2023-10-17 17:51:32,169 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:51:33,822 epoch 2 - iter 14/146 - loss 0.28292930 - time (sec): 1.65 - samples/sec: 2889.28 - lr: 0.000050 - momentum: 0.000000 | |
| 2023-10-17 17:51:35,067 epoch 2 - iter 28/146 - loss 0.25593623 - time (sec): 2.90 - samples/sec: 2924.31 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-17 17:51:36,271 epoch 2 - iter 42/146 - loss 0.24056504 - time (sec): 4.10 - samples/sec: 2973.51 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-17 17:51:37,400 epoch 2 - iter 56/146 - loss 0.24098347 - time (sec): 5.23 - samples/sec: 3023.55 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-17 17:51:39,011 epoch 2 - iter 70/146 - loss 0.23990925 - time (sec): 6.84 - samples/sec: 3004.42 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-17 17:51:40,625 epoch 2 - iter 84/146 - loss 0.22035000 - time (sec): 8.46 - samples/sec: 2931.59 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-17 17:51:42,021 epoch 2 - iter 98/146 - loss 0.20717226 - time (sec): 9.85 - samples/sec: 2902.48 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-17 17:51:43,290 epoch 2 - iter 112/146 - loss 0.20187917 - time (sec): 11.12 - samples/sec: 2913.22 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-17 17:51:44,685 epoch 2 - iter 126/146 - loss 0.19646511 - time (sec): 12.52 - samples/sec: 2935.37 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-17 17:51:46,635 epoch 2 - iter 140/146 - loss 0.18970816 - time (sec): 14.46 - samples/sec: 2944.06 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-17 17:51:47,195 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:51:47,195 EPOCH 2 done: loss 0.1871 - lr: 0.000045 | |
| 2023-10-17 17:51:48,684 DEV : loss 0.12840227782726288 - f1-score (micro avg) 0.6597 | |
| 2023-10-17 17:51:48,690 saving best model | |
| 2023-10-17 17:51:49,150 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:51:50,352 epoch 3 - iter 14/146 - loss 0.12172571 - time (sec): 1.20 - samples/sec: 2897.39 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-17 17:51:52,174 epoch 3 - iter 28/146 - loss 0.09513845 - time (sec): 3.02 - samples/sec: 2796.32 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-17 17:51:53,613 epoch 3 - iter 42/146 - loss 0.09306659 - time (sec): 4.46 - samples/sec: 2847.48 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-17 17:51:55,371 epoch 3 - iter 56/146 - loss 0.08892443 - time (sec): 6.22 - samples/sec: 2801.67 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-17 17:51:56,653 epoch 3 - iter 70/146 - loss 0.09802952 - time (sec): 7.50 - samples/sec: 2817.17 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-17 17:51:58,035 epoch 3 - iter 84/146 - loss 0.09938552 - time (sec): 8.88 - samples/sec: 2849.02 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-17 17:51:59,244 epoch 3 - iter 98/146 - loss 0.09932542 - time (sec): 10.09 - samples/sec: 2830.08 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-17 17:52:00,940 epoch 3 - iter 112/146 - loss 0.09988457 - time (sec): 11.79 - samples/sec: 2851.55 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-17 17:52:02,529 epoch 3 - iter 126/146 - loss 0.09937404 - time (sec): 13.38 - samples/sec: 2840.97 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-17 17:52:04,197 epoch 3 - iter 140/146 - loss 0.10083464 - time (sec): 15.04 - samples/sec: 2855.29 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-17 17:52:04,661 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:52:04,661 EPOCH 3 done: loss 0.0986 - lr: 0.000039 | |
| 2023-10-17 17:52:05,924 DEV : loss 0.11469055712223053 - f1-score (micro avg) 0.7558 | |
| 2023-10-17 17:52:05,929 saving best model | |
| 2023-10-17 17:52:06,381 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:52:07,886 epoch 4 - iter 14/146 - loss 0.08001683 - time (sec): 1.50 - samples/sec: 3162.98 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-17 17:52:09,311 epoch 4 - iter 28/146 - loss 0.08313806 - time (sec): 2.92 - samples/sec: 3113.44 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-17 17:52:10,918 epoch 4 - iter 42/146 - loss 0.08932962 - time (sec): 4.53 - samples/sec: 2955.43 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-17 17:52:12,208 epoch 4 - iter 56/146 - loss 0.08311168 - time (sec): 5.82 - samples/sec: 2896.03 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-17 17:52:13,719 epoch 4 - iter 70/146 - loss 0.07749470 - time (sec): 7.33 - samples/sec: 2885.81 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-17 17:52:15,338 epoch 4 - iter 84/146 - loss 0.07439762 - time (sec): 8.95 - samples/sec: 2898.06 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-17 17:52:16,556 epoch 4 - iter 98/146 - loss 0.07128648 - time (sec): 10.17 - samples/sec: 2885.30 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-17 17:52:17,985 epoch 4 - iter 112/146 - loss 0.07040154 - time (sec): 11.60 - samples/sec: 2874.41 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-17 17:52:19,504 epoch 4 - iter 126/146 - loss 0.06725890 - time (sec): 13.12 - samples/sec: 2895.24 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-17 17:52:21,050 epoch 4 - iter 140/146 - loss 0.06467563 - time (sec): 14.66 - samples/sec: 2904.48 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-17 17:52:21,683 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:52:21,684 EPOCH 4 done: loss 0.0643 - lr: 0.000034 | |
| 2023-10-17 17:52:22,973 DEV : loss 0.12082179635763168 - f1-score (micro avg) 0.7424 | |
| 2023-10-17 17:52:22,978 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:52:24,381 epoch 5 - iter 14/146 - loss 0.06422344 - time (sec): 1.40 - samples/sec: 2739.89 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-17 17:52:25,958 epoch 5 - iter 28/146 - loss 0.05442231 - time (sec): 2.98 - samples/sec: 2842.57 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-17 17:52:27,408 epoch 5 - iter 42/146 - loss 0.04507790 - time (sec): 4.43 - samples/sec: 2940.79 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-17 17:52:29,131 epoch 5 - iter 56/146 - loss 0.05002005 - time (sec): 6.15 - samples/sec: 2884.12 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-17 17:52:30,452 epoch 5 - iter 70/146 - loss 0.04635323 - time (sec): 7.47 - samples/sec: 2896.08 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-17 17:52:31,711 epoch 5 - iter 84/146 - loss 0.04594857 - time (sec): 8.73 - samples/sec: 2876.47 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-17 17:52:33,300 epoch 5 - iter 98/146 - loss 0.04185253 - time (sec): 10.32 - samples/sec: 2899.36 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-17 17:52:34,569 epoch 5 - iter 112/146 - loss 0.04051975 - time (sec): 11.59 - samples/sec: 2904.58 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 17:52:36,442 epoch 5 - iter 126/146 - loss 0.04226250 - time (sec): 13.46 - samples/sec: 2874.79 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 17:52:37,925 epoch 5 - iter 140/146 - loss 0.04401633 - time (sec): 14.95 - samples/sec: 2857.55 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 17:52:38,457 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:52:38,458 EPOCH 5 done: loss 0.0431 - lr: 0.000028 | |
| 2023-10-17 17:52:39,713 DEV : loss 0.12378506362438202 - f1-score (micro avg) 0.7638 | |
| 2023-10-17 17:52:39,718 saving best model | |
| 2023-10-17 17:52:40,156 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:52:41,483 epoch 6 - iter 14/146 - loss 0.02821174 - time (sec): 1.32 - samples/sec: 2970.80 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 17:52:43,424 epoch 6 - iter 28/146 - loss 0.02719467 - time (sec): 3.27 - samples/sec: 2716.97 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 17:52:44,685 epoch 6 - iter 42/146 - loss 0.02593663 - time (sec): 4.53 - samples/sec: 2689.02 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 17:52:46,264 epoch 6 - iter 56/146 - loss 0.02530266 - time (sec): 6.11 - samples/sec: 2759.35 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 17:52:48,033 epoch 6 - iter 70/146 - loss 0.02607955 - time (sec): 7.87 - samples/sec: 2739.94 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 17:52:49,466 epoch 6 - iter 84/146 - loss 0.02856308 - time (sec): 9.31 - samples/sec: 2799.68 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 17:52:50,941 epoch 6 - iter 98/146 - loss 0.03007988 - time (sec): 10.78 - samples/sec: 2810.94 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 17:52:52,315 epoch 6 - iter 112/146 - loss 0.02972773 - time (sec): 12.16 - samples/sec: 2807.81 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 17:52:53,786 epoch 6 - iter 126/146 - loss 0.02975220 - time (sec): 13.63 - samples/sec: 2816.61 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 17:52:55,150 epoch 6 - iter 140/146 - loss 0.03021626 - time (sec): 14.99 - samples/sec: 2858.97 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 17:52:55,649 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:52:55,649 EPOCH 6 done: loss 0.0306 - lr: 0.000023 | |
| 2023-10-17 17:52:56,904 DEV : loss 0.1446683704853058 - f1-score (micro avg) 0.7591 | |
| 2023-10-17 17:52:56,909 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:52:58,252 epoch 7 - iter 14/146 - loss 0.01067881 - time (sec): 1.34 - samples/sec: 2768.15 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 17:52:59,748 epoch 7 - iter 28/146 - loss 0.01553625 - time (sec): 2.84 - samples/sec: 2972.30 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 17:53:01,210 epoch 7 - iter 42/146 - loss 0.02338274 - time (sec): 4.30 - samples/sec: 3013.27 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 17:53:02,788 epoch 7 - iter 56/146 - loss 0.02276518 - time (sec): 5.88 - samples/sec: 2958.23 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 17:53:04,135 epoch 7 - iter 70/146 - loss 0.02040107 - time (sec): 7.22 - samples/sec: 2979.45 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 17:53:05,707 epoch 7 - iter 84/146 - loss 0.01887587 - time (sec): 8.80 - samples/sec: 2899.23 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 17:53:07,090 epoch 7 - iter 98/146 - loss 0.02062489 - time (sec): 10.18 - samples/sec: 2927.81 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 17:53:08,404 epoch 7 - iter 112/146 - loss 0.02270664 - time (sec): 11.49 - samples/sec: 2967.68 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 17:53:10,026 epoch 7 - iter 126/146 - loss 0.02108995 - time (sec): 13.12 - samples/sec: 2940.26 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 17:53:11,723 epoch 7 - iter 140/146 - loss 0.02146590 - time (sec): 14.81 - samples/sec: 2904.13 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 17:53:12,214 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:53:12,214 EPOCH 7 done: loss 0.0221 - lr: 0.000017 | |
| 2023-10-17 17:53:13,493 DEV : loss 0.13926248252391815 - f1-score (micro avg) 0.7588 | |
| 2023-10-17 17:53:13,498 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:53:14,805 epoch 8 - iter 14/146 - loss 0.04199538 - time (sec): 1.31 - samples/sec: 2869.25 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 17:53:16,360 epoch 8 - iter 28/146 - loss 0.03623353 - time (sec): 2.86 - samples/sec: 2858.33 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 17:53:17,765 epoch 8 - iter 42/146 - loss 0.02909497 - time (sec): 4.27 - samples/sec: 2789.70 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 17:53:19,130 epoch 8 - iter 56/146 - loss 0.02582501 - time (sec): 5.63 - samples/sec: 2822.08 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 17:53:20,472 epoch 8 - iter 70/146 - loss 0.02248507 - time (sec): 6.97 - samples/sec: 2905.70 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 17:53:21,992 epoch 8 - iter 84/146 - loss 0.02039668 - time (sec): 8.49 - samples/sec: 2948.75 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 17:53:23,243 epoch 8 - iter 98/146 - loss 0.02065091 - time (sec): 9.74 - samples/sec: 2953.56 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 17:53:24,793 epoch 8 - iter 112/146 - loss 0.01976567 - time (sec): 11.29 - samples/sec: 2967.93 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 17:53:26,152 epoch 8 - iter 126/146 - loss 0.01878112 - time (sec): 12.65 - samples/sec: 2964.08 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 17:53:27,832 epoch 8 - iter 140/146 - loss 0.01820202 - time (sec): 14.33 - samples/sec: 2977.10 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 17:53:28,544 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:53:28,544 EPOCH 8 done: loss 0.0180 - lr: 0.000012 | |
| 2023-10-17 17:53:29,816 DEV : loss 0.1338219791650772 - f1-score (micro avg) 0.8125 | |
| 2023-10-17 17:53:29,821 saving best model | |
| 2023-10-17 17:53:30,265 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:53:31,690 epoch 9 - iter 14/146 - loss 0.00900173 - time (sec): 1.42 - samples/sec: 3146.38 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 17:53:33,172 epoch 9 - iter 28/146 - loss 0.01353775 - time (sec): 2.91 - samples/sec: 2969.76 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 17:53:34,800 epoch 9 - iter 42/146 - loss 0.01411638 - time (sec): 4.53 - samples/sec: 2925.56 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 17:53:36,570 epoch 9 - iter 56/146 - loss 0.01717406 - time (sec): 6.30 - samples/sec: 2832.55 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 17:53:38,322 epoch 9 - iter 70/146 - loss 0.01651724 - time (sec): 8.06 - samples/sec: 2779.14 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 17:53:39,653 epoch 9 - iter 84/146 - loss 0.01447022 - time (sec): 9.39 - samples/sec: 2809.42 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 17:53:41,289 epoch 9 - iter 98/146 - loss 0.01305284 - time (sec): 11.02 - samples/sec: 2793.58 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 17:53:42,484 epoch 9 - iter 112/146 - loss 0.01276152 - time (sec): 12.22 - samples/sec: 2817.73 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 17:53:43,877 epoch 9 - iter 126/146 - loss 0.01240197 - time (sec): 13.61 - samples/sec: 2825.26 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 17:53:45,221 epoch 9 - iter 140/146 - loss 0.01247661 - time (sec): 14.95 - samples/sec: 2864.35 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 17:53:45,888 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:53:45,888 EPOCH 9 done: loss 0.0125 - lr: 0.000006 | |
| 2023-10-17 17:53:47,153 DEV : loss 0.1447986215353012 - f1-score (micro avg) 0.7973 | |
| 2023-10-17 17:53:47,157 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:53:48,470 epoch 10 - iter 14/146 - loss 0.01128755 - time (sec): 1.31 - samples/sec: 3088.10 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 17:53:49,879 epoch 10 - iter 28/146 - loss 0.01029360 - time (sec): 2.72 - samples/sec: 2992.37 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 17:53:51,519 epoch 10 - iter 42/146 - loss 0.01240356 - time (sec): 4.36 - samples/sec: 2861.25 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 17:53:52,894 epoch 10 - iter 56/146 - loss 0.01088444 - time (sec): 5.74 - samples/sec: 2944.20 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 17:53:54,438 epoch 10 - iter 70/146 - loss 0.01024052 - time (sec): 7.28 - samples/sec: 2969.04 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 17:53:56,006 epoch 10 - iter 84/146 - loss 0.00903528 - time (sec): 8.85 - samples/sec: 2930.05 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 17:53:57,751 epoch 10 - iter 98/146 - loss 0.01043615 - time (sec): 10.59 - samples/sec: 2857.32 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 17:53:59,290 epoch 10 - iter 112/146 - loss 0.01019047 - time (sec): 12.13 - samples/sec: 2865.50 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 17:54:00,771 epoch 10 - iter 126/146 - loss 0.00966469 - time (sec): 13.61 - samples/sec: 2864.12 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 17:54:02,058 epoch 10 - iter 140/146 - loss 0.01137448 - time (sec): 14.90 - samples/sec: 2865.91 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-17 17:54:02,617 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:54:02,617 EPOCH 10 done: loss 0.0111 - lr: 0.000000 | |
| 2023-10-17 17:54:03,903 DEV : loss 0.14230762422084808 - f1-score (micro avg) 0.8044 | |
| 2023-10-17 17:54:04,247 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 17:54:04,249 Loading model from best epoch ... | |
| 2023-10-17 17:54:05,633 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 17:54:08,070 | |
| Results: | |
| - F-score (micro) 0.7704 | |
| - F-score (macro) 0.7203 | |
| - Accuracy 0.6484 | |
| By class: | |
| precision recall f1-score support | |
| PER 0.8179 0.8649 0.8408 348 | |
| LOC 0.6503 0.8123 0.7223 261 | |
| ORG 0.5745 0.5192 0.5455 52 | |
| HumanProd 0.7727 0.7727 0.7727 22 | |
| micro avg 0.7300 0.8155 0.7704 683 | |
| macro avg 0.7039 0.7423 0.7203 683 | |
| weighted avg 0.7339 0.8155 0.7708 683 | |
| 2023-10-17 17:54:08,070 ---------------------------------------------------------------------------------------------------- | |