| 2023-10-16 22:05:02,568 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:05:02,569 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() | |
| )" | |
| 2023-10-16 22:05:02,569 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:05:02,569 MultiCorpus: 6183 train + 680 dev + 2113 test sentences | |
| - NER_HIPE_2022 Corpus: 6183 train + 680 dev + 2113 test sentences - /root/.flair/datasets/ner_hipe_2022/v2.1/topres19th/en/with_doc_seperator | |
| 2023-10-16 22:05:02,569 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:05:02,569 Train: 6183 sentences | |
| 2023-10-16 22:05:02,569 (train_with_dev=False, train_with_test=False) | |
| 2023-10-16 22:05:02,569 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:05:02,569 Training Params: | |
| 2023-10-16 22:05:02,569 - learning_rate: "5e-05" | |
| 2023-10-16 22:05:02,569 - mini_batch_size: "8" | |
| 2023-10-16 22:05:02,569 - max_epochs: "10" | |
| 2023-10-16 22:05:02,569 - shuffle: "True" | |
| 2023-10-16 22:05:02,569 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:05:02,569 Plugins: | |
| 2023-10-16 22:05:02,569 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-16 22:05:02,569 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:05:02,570 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-16 22:05:02,570 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-16 22:05:02,570 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:05:02,570 Computation: | |
| 2023-10-16 22:05:02,570 - compute on device: cuda:0 | |
| 2023-10-16 22:05:02,570 - embedding storage: none | |
| 2023-10-16 22:05:02,570 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:05:02,570 Model training base path: "hmbench-topres19th/en-dbmdz/bert-base-historic-multilingual-cased-bs8-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-2" | |
| 2023-10-16 22:05:02,570 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:05:02,570 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:05:07,108 epoch 1 - iter 77/773 - loss 2.07744315 - time (sec): 4.54 - samples/sec: 2610.32 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-16 22:05:11,553 epoch 1 - iter 154/773 - loss 1.17743079 - time (sec): 8.98 - samples/sec: 2642.75 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-16 22:05:16,195 epoch 1 - iter 231/773 - loss 0.80857450 - time (sec): 13.62 - samples/sec: 2721.79 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-16 22:05:20,634 epoch 1 - iter 308/773 - loss 0.64594888 - time (sec): 18.06 - samples/sec: 2721.06 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-16 22:05:25,021 epoch 1 - iter 385/773 - loss 0.54443571 - time (sec): 22.45 - samples/sec: 2715.07 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-16 22:05:29,309 epoch 1 - iter 462/773 - loss 0.47012773 - time (sec): 26.74 - samples/sec: 2734.10 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-16 22:05:33,752 epoch 1 - iter 539/773 - loss 0.41651204 - time (sec): 31.18 - samples/sec: 2757.19 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-16 22:05:38,386 epoch 1 - iter 616/773 - loss 0.37671127 - time (sec): 35.82 - samples/sec: 2773.34 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-16 22:05:43,095 epoch 1 - iter 693/773 - loss 0.34712982 - time (sec): 40.52 - samples/sec: 2743.12 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-16 22:05:47,514 epoch 1 - iter 770/773 - loss 0.32154236 - time (sec): 44.94 - samples/sec: 2757.20 - lr: 0.000050 - momentum: 0.000000 | |
| 2023-10-16 22:05:47,670 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:05:47,670 EPOCH 1 done: loss 0.3208 - lr: 0.000050 | |
| 2023-10-16 22:05:49,710 DEV : loss 0.0772036612033844 - f1-score (micro avg) 0.6643 | |
| 2023-10-16 22:05:49,722 saving best model | |
| 2023-10-16 22:05:50,064 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:05:54,575 epoch 2 - iter 77/773 - loss 0.07753873 - time (sec): 4.51 - samples/sec: 2686.50 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-16 22:05:58,993 epoch 2 - iter 154/773 - loss 0.08814964 - time (sec): 8.93 - samples/sec: 2682.41 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-16 22:06:03,719 epoch 2 - iter 231/773 - loss 0.08367414 - time (sec): 13.65 - samples/sec: 2695.54 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-16 22:06:08,199 epoch 2 - iter 308/773 - loss 0.08164912 - time (sec): 18.13 - samples/sec: 2694.67 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-16 22:06:12,828 epoch 2 - iter 385/773 - loss 0.08321751 - time (sec): 22.76 - samples/sec: 2705.47 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-16 22:06:17,450 epoch 2 - iter 462/773 - loss 0.08271449 - time (sec): 27.38 - samples/sec: 2672.02 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-16 22:06:22,030 epoch 2 - iter 539/773 - loss 0.08056035 - time (sec): 31.96 - samples/sec: 2676.73 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-16 22:06:26,558 epoch 2 - iter 616/773 - loss 0.08048201 - time (sec): 36.49 - samples/sec: 2680.20 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-16 22:06:31,001 epoch 2 - iter 693/773 - loss 0.07801088 - time (sec): 40.94 - samples/sec: 2693.49 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-16 22:06:35,711 epoch 2 - iter 770/773 - loss 0.07752429 - time (sec): 45.65 - samples/sec: 2713.00 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-16 22:06:35,870 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:06:35,870 EPOCH 2 done: loss 0.0773 - lr: 0.000044 | |
| 2023-10-16 22:06:37,935 DEV : loss 0.06809011846780777 - f1-score (micro avg) 0.7089 | |
| 2023-10-16 22:06:37,947 saving best model | |
| 2023-10-16 22:06:38,714 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:06:43,428 epoch 3 - iter 77/773 - loss 0.05164133 - time (sec): 4.71 - samples/sec: 2719.74 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-16 22:06:47,856 epoch 3 - iter 154/773 - loss 0.05614533 - time (sec): 9.14 - samples/sec: 2744.96 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-16 22:06:52,660 epoch 3 - iter 231/773 - loss 0.05743499 - time (sec): 13.94 - samples/sec: 2704.33 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-16 22:06:57,007 epoch 3 - iter 308/773 - loss 0.05405146 - time (sec): 18.29 - samples/sec: 2728.43 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-16 22:07:01,583 epoch 3 - iter 385/773 - loss 0.05263408 - time (sec): 22.87 - samples/sec: 2735.35 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-16 22:07:06,253 epoch 3 - iter 462/773 - loss 0.05351123 - time (sec): 27.54 - samples/sec: 2719.53 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-16 22:07:10,771 epoch 3 - iter 539/773 - loss 0.05305526 - time (sec): 32.05 - samples/sec: 2720.58 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-16 22:07:15,136 epoch 3 - iter 616/773 - loss 0.05227538 - time (sec): 36.42 - samples/sec: 2714.42 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-16 22:07:19,672 epoch 3 - iter 693/773 - loss 0.05203641 - time (sec): 40.96 - samples/sec: 2731.14 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-16 22:07:24,115 epoch 3 - iter 770/773 - loss 0.05094133 - time (sec): 45.40 - samples/sec: 2730.25 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-16 22:07:24,271 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:07:24,271 EPOCH 3 done: loss 0.0508 - lr: 0.000039 | |
| 2023-10-16 22:07:26,321 DEV : loss 0.08064333349466324 - f1-score (micro avg) 0.784 | |
| 2023-10-16 22:07:26,333 saving best model | |
| 2023-10-16 22:07:26,782 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:07:31,371 epoch 4 - iter 77/773 - loss 0.04532304 - time (sec): 4.59 - samples/sec: 2713.19 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-16 22:07:35,796 epoch 4 - iter 154/773 - loss 0.04515752 - time (sec): 9.01 - samples/sec: 2642.61 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-16 22:07:40,584 epoch 4 - iter 231/773 - loss 0.04011628 - time (sec): 13.80 - samples/sec: 2609.12 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-16 22:07:45,151 epoch 4 - iter 308/773 - loss 0.03827052 - time (sec): 18.37 - samples/sec: 2625.80 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-16 22:07:49,673 epoch 4 - iter 385/773 - loss 0.03710721 - time (sec): 22.89 - samples/sec: 2663.63 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-16 22:07:54,043 epoch 4 - iter 462/773 - loss 0.03902851 - time (sec): 27.26 - samples/sec: 2684.80 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-16 22:07:58,389 epoch 4 - iter 539/773 - loss 0.03842162 - time (sec): 31.60 - samples/sec: 2707.56 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-16 22:08:03,155 epoch 4 - iter 616/773 - loss 0.03858095 - time (sec): 36.37 - samples/sec: 2700.81 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-16 22:08:07,677 epoch 4 - iter 693/773 - loss 0.03732367 - time (sec): 40.89 - samples/sec: 2711.50 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-16 22:08:12,393 epoch 4 - iter 770/773 - loss 0.03734734 - time (sec): 45.61 - samples/sec: 2716.36 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-16 22:08:12,558 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:08:12,558 EPOCH 4 done: loss 0.0373 - lr: 0.000033 | |
| 2023-10-16 22:08:14,643 DEV : loss 0.08836734294891357 - f1-score (micro avg) 0.7582 | |
| 2023-10-16 22:08:14,656 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:08:19,114 epoch 5 - iter 77/773 - loss 0.02324528 - time (sec): 4.46 - samples/sec: 2818.91 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-16 22:08:23,457 epoch 5 - iter 154/773 - loss 0.02467072 - time (sec): 8.80 - samples/sec: 2799.12 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-16 22:08:27,881 epoch 5 - iter 231/773 - loss 0.02448679 - time (sec): 13.22 - samples/sec: 2725.54 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-16 22:08:32,569 epoch 5 - iter 308/773 - loss 0.02574532 - time (sec): 17.91 - samples/sec: 2746.57 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-16 22:08:37,181 epoch 5 - iter 385/773 - loss 0.02467239 - time (sec): 22.52 - samples/sec: 2743.95 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-16 22:08:41,801 epoch 5 - iter 462/773 - loss 0.02435955 - time (sec): 27.14 - samples/sec: 2755.55 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-16 22:08:46,576 epoch 5 - iter 539/773 - loss 0.02374115 - time (sec): 31.92 - samples/sec: 2740.25 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-16 22:08:51,103 epoch 5 - iter 616/773 - loss 0.02505935 - time (sec): 36.45 - samples/sec: 2737.71 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-16 22:08:55,524 epoch 5 - iter 693/773 - loss 0.02470818 - time (sec): 40.87 - samples/sec: 2737.62 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-16 22:08:59,942 epoch 5 - iter 770/773 - loss 0.02388204 - time (sec): 45.29 - samples/sec: 2736.97 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-16 22:09:00,093 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:09:00,094 EPOCH 5 done: loss 0.0239 - lr: 0.000028 | |
| 2023-10-16 22:09:02,150 DEV : loss 0.10162093490362167 - f1-score (micro avg) 0.7743 | |
| 2023-10-16 22:09:02,163 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:09:06,579 epoch 6 - iter 77/773 - loss 0.01159246 - time (sec): 4.42 - samples/sec: 2796.00 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-16 22:09:11,152 epoch 6 - iter 154/773 - loss 0.01350875 - time (sec): 8.99 - samples/sec: 2651.15 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-16 22:09:15,655 epoch 6 - iter 231/773 - loss 0.01496486 - time (sec): 13.49 - samples/sec: 2665.48 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-16 22:09:20,180 epoch 6 - iter 308/773 - loss 0.01695021 - time (sec): 18.02 - samples/sec: 2700.59 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-16 22:09:24,538 epoch 6 - iter 385/773 - loss 0.01737618 - time (sec): 22.37 - samples/sec: 2712.80 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-16 22:09:28,871 epoch 6 - iter 462/773 - loss 0.01752556 - time (sec): 26.71 - samples/sec: 2719.44 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-16 22:09:33,395 epoch 6 - iter 539/773 - loss 0.01769065 - time (sec): 31.23 - samples/sec: 2719.13 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-16 22:09:38,097 epoch 6 - iter 616/773 - loss 0.01836114 - time (sec): 35.93 - samples/sec: 2717.44 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-16 22:09:42,421 epoch 6 - iter 693/773 - loss 0.01786052 - time (sec): 40.26 - samples/sec: 2719.08 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-16 22:09:47,260 epoch 6 - iter 770/773 - loss 0.01820946 - time (sec): 45.10 - samples/sec: 2742.13 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-16 22:09:47,448 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:09:47,448 EPOCH 6 done: loss 0.0182 - lr: 0.000022 | |
| 2023-10-16 22:09:49,464 DEV : loss 0.10438579320907593 - f1-score (micro avg) 0.7863 | |
| 2023-10-16 22:09:49,476 saving best model | |
| 2023-10-16 22:09:49,941 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:09:54,815 epoch 7 - iter 77/773 - loss 0.01326801 - time (sec): 4.87 - samples/sec: 2596.22 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-16 22:09:59,436 epoch 7 - iter 154/773 - loss 0.01133806 - time (sec): 9.49 - samples/sec: 2698.66 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-16 22:10:03,998 epoch 7 - iter 231/773 - loss 0.01166043 - time (sec): 14.05 - samples/sec: 2696.24 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-16 22:10:08,505 epoch 7 - iter 308/773 - loss 0.01086055 - time (sec): 18.56 - samples/sec: 2685.92 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-16 22:10:13,116 epoch 7 - iter 385/773 - loss 0.01053431 - time (sec): 23.17 - samples/sec: 2692.16 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-16 22:10:17,458 epoch 7 - iter 462/773 - loss 0.01175421 - time (sec): 27.51 - samples/sec: 2700.81 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-16 22:10:21,786 epoch 7 - iter 539/773 - loss 0.01094026 - time (sec): 31.84 - samples/sec: 2713.28 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-16 22:10:26,348 epoch 7 - iter 616/773 - loss 0.01147580 - time (sec): 36.40 - samples/sec: 2708.94 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-16 22:10:30,934 epoch 7 - iter 693/773 - loss 0.01097587 - time (sec): 40.99 - samples/sec: 2718.33 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-16 22:10:35,494 epoch 7 - iter 770/773 - loss 0.01075542 - time (sec): 45.55 - samples/sec: 2719.57 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-16 22:10:35,663 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:10:35,663 EPOCH 7 done: loss 0.0109 - lr: 0.000017 | |
| 2023-10-16 22:10:37,719 DEV : loss 0.10951930284500122 - f1-score (micro avg) 0.7983 | |
| 2023-10-16 22:10:37,731 saving best model | |
| 2023-10-16 22:10:38,198 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:10:42,724 epoch 8 - iter 77/773 - loss 0.00728149 - time (sec): 4.52 - samples/sec: 2766.74 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-16 22:10:47,351 epoch 8 - iter 154/773 - loss 0.00617068 - time (sec): 9.15 - samples/sec: 2771.20 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-16 22:10:51,639 epoch 8 - iter 231/773 - loss 0.00654267 - time (sec): 13.44 - samples/sec: 2812.34 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-16 22:10:56,231 epoch 8 - iter 308/773 - loss 0.00737351 - time (sec): 18.03 - samples/sec: 2828.58 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-16 22:11:00,609 epoch 8 - iter 385/773 - loss 0.00732684 - time (sec): 22.41 - samples/sec: 2793.63 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-16 22:11:05,075 epoch 8 - iter 462/773 - loss 0.00803301 - time (sec): 26.88 - samples/sec: 2785.65 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-16 22:11:09,435 epoch 8 - iter 539/773 - loss 0.00840404 - time (sec): 31.24 - samples/sec: 2780.54 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-16 22:11:13,860 epoch 8 - iter 616/773 - loss 0.00808847 - time (sec): 35.66 - samples/sec: 2772.46 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-16 22:11:18,291 epoch 8 - iter 693/773 - loss 0.00861262 - time (sec): 40.09 - samples/sec: 2766.77 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-16 22:11:23,147 epoch 8 - iter 770/773 - loss 0.00822302 - time (sec): 44.95 - samples/sec: 2756.21 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-16 22:11:23,327 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:11:23,327 EPOCH 8 done: loss 0.0082 - lr: 0.000011 | |
| 2023-10-16 22:11:25,361 DEV : loss 0.11846552044153214 - f1-score (micro avg) 0.7943 | |
| 2023-10-16 22:11:25,374 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:11:30,050 epoch 9 - iter 77/773 - loss 0.00433896 - time (sec): 4.67 - samples/sec: 2677.26 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-16 22:11:34,429 epoch 9 - iter 154/773 - loss 0.00498112 - time (sec): 9.05 - samples/sec: 2697.81 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-16 22:11:38,833 epoch 9 - iter 231/773 - loss 0.00373937 - time (sec): 13.46 - samples/sec: 2717.39 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-16 22:11:43,181 epoch 9 - iter 308/773 - loss 0.00412343 - time (sec): 17.81 - samples/sec: 2732.31 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-16 22:11:47,729 epoch 9 - iter 385/773 - loss 0.00375047 - time (sec): 22.35 - samples/sec: 2718.05 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-16 22:11:52,475 epoch 9 - iter 462/773 - loss 0.00369782 - time (sec): 27.10 - samples/sec: 2717.22 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-16 22:11:56,947 epoch 9 - iter 539/773 - loss 0.00383622 - time (sec): 31.57 - samples/sec: 2733.87 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-16 22:12:01,471 epoch 9 - iter 616/773 - loss 0.00413650 - time (sec): 36.10 - samples/sec: 2732.35 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-16 22:12:05,987 epoch 9 - iter 693/773 - loss 0.00456700 - time (sec): 40.61 - samples/sec: 2740.68 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-16 22:12:10,465 epoch 9 - iter 770/773 - loss 0.00488437 - time (sec): 45.09 - samples/sec: 2749.39 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-16 22:12:10,633 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:12:10,634 EPOCH 9 done: loss 0.0049 - lr: 0.000006 | |
| 2023-10-16 22:12:12,648 DEV : loss 0.11912991851568222 - f1-score (micro avg) 0.7859 | |
| 2023-10-16 22:12:12,661 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:12:17,152 epoch 10 - iter 77/773 - loss 0.00307045 - time (sec): 4.49 - samples/sec: 2767.84 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-16 22:12:21,594 epoch 10 - iter 154/773 - loss 0.00429958 - time (sec): 8.93 - samples/sec: 2791.36 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-16 22:12:26,080 epoch 10 - iter 231/773 - loss 0.00374969 - time (sec): 13.42 - samples/sec: 2745.64 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-16 22:12:30,759 epoch 10 - iter 308/773 - loss 0.00293141 - time (sec): 18.10 - samples/sec: 2763.47 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-16 22:12:35,215 epoch 10 - iter 385/773 - loss 0.00303829 - time (sec): 22.55 - samples/sec: 2752.65 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-16 22:12:39,757 epoch 10 - iter 462/773 - loss 0.00299411 - time (sec): 27.09 - samples/sec: 2766.56 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-16 22:12:44,528 epoch 10 - iter 539/773 - loss 0.00315115 - time (sec): 31.87 - samples/sec: 2730.07 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-16 22:12:48,932 epoch 10 - iter 616/773 - loss 0.00309341 - time (sec): 36.27 - samples/sec: 2742.38 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-16 22:12:53,383 epoch 10 - iter 693/773 - loss 0.00291500 - time (sec): 40.72 - samples/sec: 2734.97 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-16 22:12:57,938 epoch 10 - iter 770/773 - loss 0.00293636 - time (sec): 45.28 - samples/sec: 2730.69 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-16 22:12:58,116 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:12:58,116 EPOCH 10 done: loss 0.0029 - lr: 0.000000 | |
| 2023-10-16 22:13:00,131 DEV : loss 0.12098120898008347 - f1-score (micro avg) 0.7832 | |
| 2023-10-16 22:13:00,473 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-16 22:13:00,475 Loading model from best epoch ... | |
| 2023-10-16 22:13:01,959 SequenceTagger predicts: Dictionary with 13 tags: O, S-LOC, B-LOC, E-LOC, I-LOC, S-BUILDING, B-BUILDING, E-BUILDING, I-BUILDING, S-STREET, B-STREET, E-STREET, I-STREET | |
| 2023-10-16 22:13:07,934 | |
| Results: | |
| - F-score (micro) 0.8009 | |
| - F-score (macro) 0.6968 | |
| - Accuracy 0.6881 | |
| By class: | |
| precision recall f1-score support | |
| LOC 0.8549 0.8531 0.8540 946 | |
| BUILDING 0.6000 0.4703 0.5273 185 | |
| STREET 0.7222 0.6964 0.7091 56 | |
| micro avg 0.8163 0.7860 0.8009 1187 | |
| macro avg 0.7257 0.6733 0.6968 1187 | |
| weighted avg 0.8089 0.7860 0.7962 1187 | |
| 2023-10-16 22:13:07,935 ---------------------------------------------------------------------------------------------------- | |