| 2023-10-17 18:04:35,825 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:04:35,826 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 18:04:35,826 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:04:35,826 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 18:04:35,826 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:04:35,826 Train: 5777 sentences | |
| 2023-10-17 18:04:35,826 (train_with_dev=False, train_with_test=False) | |
| 2023-10-17 18:04:35,826 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:04:35,826 Training Params: | |
| 2023-10-17 18:04:35,826 - learning_rate: "3e-05" | |
| 2023-10-17 18:04:35,826 - mini_batch_size: "8" | |
| 2023-10-17 18:04:35,826 - max_epochs: "10" | |
| 2023-10-17 18:04:35,826 - shuffle: "True" | |
| 2023-10-17 18:04:35,826 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:04:35,826 Plugins: | |
| 2023-10-17 18:04:35,826 - TensorboardLogger | |
| 2023-10-17 18:04:35,826 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-17 18:04:35,827 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:04:35,827 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-17 18:04:35,827 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-17 18:04:35,827 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:04:35,827 Computation: | |
| 2023-10-17 18:04:35,827 - compute on device: cuda:0 | |
| 2023-10-17 18:04:35,827 - embedding storage: none | |
| 2023-10-17 18:04:35,827 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:04:35,827 Model training base path: "hmbench-icdar/nl-hmteams/teams-base-historic-multilingual-discriminator-bs8-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-4" | |
| 2023-10-17 18:04:35,827 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:04:35,827 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:04:35,827 Logging anything other than scalars to TensorBoard is currently not supported. | |
| 2023-10-17 18:04:40,869 epoch 1 - iter 72/723 - loss 3.14780265 - time (sec): 5.04 - samples/sec: 3212.85 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 18:04:46,354 epoch 1 - iter 144/723 - loss 1.91689024 - time (sec): 10.53 - samples/sec: 3248.38 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 18:04:51,606 epoch 1 - iter 216/723 - loss 1.35009273 - time (sec): 15.78 - samples/sec: 3276.04 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 18:04:56,946 epoch 1 - iter 288/723 - loss 1.05729540 - time (sec): 21.12 - samples/sec: 3274.92 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 18:05:02,237 epoch 1 - iter 360/723 - loss 0.87211949 - time (sec): 26.41 - samples/sec: 3299.80 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 18:05:07,703 epoch 1 - iter 432/723 - loss 0.74573597 - time (sec): 31.87 - samples/sec: 3312.62 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 18:05:12,988 epoch 1 - iter 504/723 - loss 0.65737284 - time (sec): 37.16 - samples/sec: 3318.84 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 18:05:18,380 epoch 1 - iter 576/723 - loss 0.59117923 - time (sec): 42.55 - samples/sec: 3318.60 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 18:05:24,033 epoch 1 - iter 648/723 - loss 0.53883556 - time (sec): 48.20 - samples/sec: 3299.42 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 18:05:28,712 epoch 1 - iter 720/723 - loss 0.49808664 - time (sec): 52.88 - samples/sec: 3321.46 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-17 18:05:28,893 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:05:28,894 EPOCH 1 done: loss 0.4968 - lr: 0.000030 | |
| 2023-10-17 18:05:32,615 DEV : loss 0.10252858698368073 - f1-score (micro avg) 0.6435 | |
| 2023-10-17 18:05:32,634 saving best model | |
| 2023-10-17 18:05:33,009 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:05:38,412 epoch 2 - iter 72/723 - loss 0.08824932 - time (sec): 5.40 - samples/sec: 3445.98 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-17 18:05:43,268 epoch 2 - iter 144/723 - loss 0.09284165 - time (sec): 10.26 - samples/sec: 3459.67 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 18:05:49,301 epoch 2 - iter 216/723 - loss 0.09672994 - time (sec): 16.29 - samples/sec: 3286.52 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 18:05:54,557 epoch 2 - iter 288/723 - loss 0.09200487 - time (sec): 21.55 - samples/sec: 3302.04 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 18:05:59,668 epoch 2 - iter 360/723 - loss 0.09466436 - time (sec): 26.66 - samples/sec: 3295.03 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 18:06:04,651 epoch 2 - iter 432/723 - loss 0.09512636 - time (sec): 31.64 - samples/sec: 3301.25 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 18:06:10,475 epoch 2 - iter 504/723 - loss 0.09272504 - time (sec): 37.47 - samples/sec: 3290.58 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 18:06:15,387 epoch 2 - iter 576/723 - loss 0.09030789 - time (sec): 42.38 - samples/sec: 3293.41 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 18:06:20,677 epoch 2 - iter 648/723 - loss 0.08892716 - time (sec): 47.67 - samples/sec: 3294.64 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 18:06:26,199 epoch 2 - iter 720/723 - loss 0.08670549 - time (sec): 53.19 - samples/sec: 3305.28 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 18:06:26,360 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:06:26,360 EPOCH 2 done: loss 0.0868 - lr: 0.000027 | |
| 2023-10-17 18:06:29,657 DEV : loss 0.07472483813762665 - f1-score (micro avg) 0.8086 | |
| 2023-10-17 18:06:29,676 saving best model | |
| 2023-10-17 18:06:30,161 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:06:35,368 epoch 3 - iter 72/723 - loss 0.05396348 - time (sec): 5.21 - samples/sec: 3359.73 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 18:06:40,571 epoch 3 - iter 144/723 - loss 0.05386152 - time (sec): 10.41 - samples/sec: 3348.20 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 18:06:45,548 epoch 3 - iter 216/723 - loss 0.05763223 - time (sec): 15.39 - samples/sec: 3351.57 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 18:06:50,644 epoch 3 - iter 288/723 - loss 0.05871276 - time (sec): 20.48 - samples/sec: 3338.22 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 18:06:56,207 epoch 3 - iter 360/723 - loss 0.05735120 - time (sec): 26.05 - samples/sec: 3312.70 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 18:07:02,101 epoch 3 - iter 432/723 - loss 0.05744013 - time (sec): 31.94 - samples/sec: 3320.41 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 18:07:07,544 epoch 3 - iter 504/723 - loss 0.05703734 - time (sec): 37.38 - samples/sec: 3329.27 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 18:07:12,605 epoch 3 - iter 576/723 - loss 0.05670689 - time (sec): 42.44 - samples/sec: 3338.18 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 18:07:17,846 epoch 3 - iter 648/723 - loss 0.05681013 - time (sec): 47.68 - samples/sec: 3330.06 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 18:07:23,059 epoch 3 - iter 720/723 - loss 0.05774106 - time (sec): 52.90 - samples/sec: 3317.61 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 18:07:23,314 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:07:23,314 EPOCH 3 done: loss 0.0578 - lr: 0.000023 | |
| 2023-10-17 18:07:27,112 DEV : loss 0.05712844431400299 - f1-score (micro avg) 0.8812 | |
| 2023-10-17 18:07:27,129 saving best model | |
| 2023-10-17 18:07:27,652 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:07:32,710 epoch 4 - iter 72/723 - loss 0.03483535 - time (sec): 5.06 - samples/sec: 3414.70 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 18:07:37,907 epoch 4 - iter 144/723 - loss 0.03934497 - time (sec): 10.25 - samples/sec: 3374.65 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 18:07:43,328 epoch 4 - iter 216/723 - loss 0.03886039 - time (sec): 15.67 - samples/sec: 3339.03 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 18:07:48,534 epoch 4 - iter 288/723 - loss 0.03985048 - time (sec): 20.88 - samples/sec: 3333.40 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 18:07:53,639 epoch 4 - iter 360/723 - loss 0.03887291 - time (sec): 25.98 - samples/sec: 3306.91 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 18:07:59,171 epoch 4 - iter 432/723 - loss 0.04024768 - time (sec): 31.52 - samples/sec: 3306.96 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 18:08:04,658 epoch 4 - iter 504/723 - loss 0.04285831 - time (sec): 37.00 - samples/sec: 3311.61 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 18:08:09,714 epoch 4 - iter 576/723 - loss 0.04317139 - time (sec): 42.06 - samples/sec: 3314.94 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 18:08:14,986 epoch 4 - iter 648/723 - loss 0.04227368 - time (sec): 47.33 - samples/sec: 3321.28 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 18:08:20,439 epoch 4 - iter 720/723 - loss 0.04245703 - time (sec): 52.78 - samples/sec: 3326.15 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 18:08:20,628 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:08:20,628 EPOCH 4 done: loss 0.0424 - lr: 0.000020 | |
| 2023-10-17 18:08:23,988 DEV : loss 0.06662245094776154 - f1-score (micro avg) 0.8791 | |
| 2023-10-17 18:08:24,007 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:08:29,324 epoch 5 - iter 72/723 - loss 0.01990662 - time (sec): 5.32 - samples/sec: 3344.69 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 18:08:35,095 epoch 5 - iter 144/723 - loss 0.02279437 - time (sec): 11.09 - samples/sec: 3189.92 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 18:08:40,075 epoch 5 - iter 216/723 - loss 0.02479149 - time (sec): 16.07 - samples/sec: 3231.66 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 18:08:45,591 epoch 5 - iter 288/723 - loss 0.02719107 - time (sec): 21.58 - samples/sec: 3262.26 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 18:08:50,464 epoch 5 - iter 360/723 - loss 0.02575671 - time (sec): 26.46 - samples/sec: 3295.06 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 18:08:55,631 epoch 5 - iter 432/723 - loss 0.02771082 - time (sec): 31.62 - samples/sec: 3302.82 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 18:09:00,979 epoch 5 - iter 504/723 - loss 0.02956349 - time (sec): 36.97 - samples/sec: 3277.40 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 18:09:06,490 epoch 5 - iter 576/723 - loss 0.03084776 - time (sec): 42.48 - samples/sec: 3270.69 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 18:09:11,875 epoch 5 - iter 648/723 - loss 0.03111872 - time (sec): 47.87 - samples/sec: 3273.52 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 18:09:17,582 epoch 5 - iter 720/723 - loss 0.03213599 - time (sec): 53.57 - samples/sec: 3278.68 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 18:09:17,791 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:09:17,791 EPOCH 5 done: loss 0.0322 - lr: 0.000017 | |
| 2023-10-17 18:09:21,121 DEV : loss 0.10735854506492615 - f1-score (micro avg) 0.852 | |
| 2023-10-17 18:09:21,139 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:09:26,445 epoch 6 - iter 72/723 - loss 0.01459516 - time (sec): 5.30 - samples/sec: 3243.72 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 18:09:31,377 epoch 6 - iter 144/723 - loss 0.01916253 - time (sec): 10.24 - samples/sec: 3349.32 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 18:09:36,924 epoch 6 - iter 216/723 - loss 0.02024065 - time (sec): 15.78 - samples/sec: 3321.70 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 18:09:41,719 epoch 6 - iter 288/723 - loss 0.01952469 - time (sec): 20.58 - samples/sec: 3309.42 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 18:09:47,484 epoch 6 - iter 360/723 - loss 0.02084252 - time (sec): 26.34 - samples/sec: 3323.30 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 18:09:52,279 epoch 6 - iter 432/723 - loss 0.02140543 - time (sec): 31.14 - samples/sec: 3382.54 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 18:09:57,342 epoch 6 - iter 504/723 - loss 0.02072648 - time (sec): 36.20 - samples/sec: 3382.64 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 18:10:02,892 epoch 6 - iter 576/723 - loss 0.02209234 - time (sec): 41.75 - samples/sec: 3391.15 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 18:10:07,864 epoch 6 - iter 648/723 - loss 0.02271147 - time (sec): 46.72 - samples/sec: 3387.47 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 18:10:13,045 epoch 6 - iter 720/723 - loss 0.02324330 - time (sec): 51.91 - samples/sec: 3386.73 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 18:10:13,187 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:10:13,187 EPOCH 6 done: loss 0.0233 - lr: 0.000013 | |
| 2023-10-17 18:10:16,951 DEV : loss 0.09898053109645844 - f1-score (micro avg) 0.8787 | |
| 2023-10-17 18:10:16,973 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:10:22,091 epoch 7 - iter 72/723 - loss 0.01179340 - time (sec): 5.12 - samples/sec: 3273.92 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 18:10:27,430 epoch 7 - iter 144/723 - loss 0.01110712 - time (sec): 10.46 - samples/sec: 3283.64 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 18:10:32,925 epoch 7 - iter 216/723 - loss 0.01314864 - time (sec): 15.95 - samples/sec: 3319.64 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 18:10:38,240 epoch 7 - iter 288/723 - loss 0.01571089 - time (sec): 21.27 - samples/sec: 3304.77 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 18:10:43,718 epoch 7 - iter 360/723 - loss 0.01630848 - time (sec): 26.74 - samples/sec: 3311.36 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 18:10:49,005 epoch 7 - iter 432/723 - loss 0.01910391 - time (sec): 32.03 - samples/sec: 3309.95 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 18:10:54,705 epoch 7 - iter 504/723 - loss 0.01877318 - time (sec): 37.73 - samples/sec: 3310.78 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 18:10:59,635 epoch 7 - iter 576/723 - loss 0.01811978 - time (sec): 42.66 - samples/sec: 3315.06 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 18:11:04,812 epoch 7 - iter 648/723 - loss 0.01804125 - time (sec): 47.84 - samples/sec: 3320.49 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 18:11:10,018 epoch 7 - iter 720/723 - loss 0.01810548 - time (sec): 53.04 - samples/sec: 3312.43 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 18:11:10,198 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:11:10,199 EPOCH 7 done: loss 0.0181 - lr: 0.000010 | |
| 2023-10-17 18:11:13,489 DEV : loss 0.112530916929245 - f1-score (micro avg) 0.8757 | |
| 2023-10-17 18:11:13,508 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:11:18,960 epoch 8 - iter 72/723 - loss 0.00982102 - time (sec): 5.45 - samples/sec: 3354.45 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 18:11:24,206 epoch 8 - iter 144/723 - loss 0.01111392 - time (sec): 10.70 - samples/sec: 3381.94 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 18:11:29,275 epoch 8 - iter 216/723 - loss 0.01252694 - time (sec): 15.77 - samples/sec: 3393.20 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 18:11:34,521 epoch 8 - iter 288/723 - loss 0.01206236 - time (sec): 21.01 - samples/sec: 3334.63 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 18:11:40,082 epoch 8 - iter 360/723 - loss 0.01224851 - time (sec): 26.57 - samples/sec: 3331.83 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 18:11:45,118 epoch 8 - iter 432/723 - loss 0.01187705 - time (sec): 31.61 - samples/sec: 3354.56 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 18:11:50,453 epoch 8 - iter 504/723 - loss 0.01236789 - time (sec): 36.94 - samples/sec: 3310.07 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 18:11:55,804 epoch 8 - iter 576/723 - loss 0.01200156 - time (sec): 42.30 - samples/sec: 3306.51 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 18:12:01,328 epoch 8 - iter 648/723 - loss 0.01252768 - time (sec): 47.82 - samples/sec: 3309.92 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 18:12:06,499 epoch 8 - iter 720/723 - loss 0.01258916 - time (sec): 52.99 - samples/sec: 3318.22 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 18:12:06,648 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:12:06,648 EPOCH 8 done: loss 0.0126 - lr: 0.000007 | |
| 2023-10-17 18:12:10,019 DEV : loss 0.13107195496559143 - f1-score (micro avg) 0.8717 | |
| 2023-10-17 18:12:10,042 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:12:15,640 epoch 9 - iter 72/723 - loss 0.00761981 - time (sec): 5.60 - samples/sec: 3132.39 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 18:12:20,962 epoch 9 - iter 144/723 - loss 0.00858213 - time (sec): 10.92 - samples/sec: 3216.86 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 18:12:26,242 epoch 9 - iter 216/723 - loss 0.00853157 - time (sec): 16.20 - samples/sec: 3295.29 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 18:12:31,518 epoch 9 - iter 288/723 - loss 0.00876791 - time (sec): 21.47 - samples/sec: 3321.23 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 18:12:36,672 epoch 9 - iter 360/723 - loss 0.00859438 - time (sec): 26.63 - samples/sec: 3294.91 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 18:12:41,859 epoch 9 - iter 432/723 - loss 0.00864313 - time (sec): 31.82 - samples/sec: 3318.31 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 18:12:47,352 epoch 9 - iter 504/723 - loss 0.00850276 - time (sec): 37.31 - samples/sec: 3303.20 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 18:12:52,892 epoch 9 - iter 576/723 - loss 0.00950137 - time (sec): 42.85 - samples/sec: 3299.80 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 18:12:57,736 epoch 9 - iter 648/723 - loss 0.00908151 - time (sec): 47.69 - samples/sec: 3312.61 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 18:13:03,216 epoch 9 - iter 720/723 - loss 0.01015906 - time (sec): 53.17 - samples/sec: 3303.07 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 18:13:03,433 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:13:03,433 EPOCH 9 done: loss 0.0101 - lr: 0.000003 | |
| 2023-10-17 18:13:07,279 DEV : loss 0.13919697701931 - f1-score (micro avg) 0.877 | |
| 2023-10-17 18:13:07,296 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:13:12,754 epoch 10 - iter 72/723 - loss 0.01328488 - time (sec): 5.46 - samples/sec: 3397.73 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 18:13:18,228 epoch 10 - iter 144/723 - loss 0.00911430 - time (sec): 10.93 - samples/sec: 3247.20 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 18:13:23,492 epoch 10 - iter 216/723 - loss 0.00839632 - time (sec): 16.19 - samples/sec: 3258.25 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 18:13:28,454 epoch 10 - iter 288/723 - loss 0.00791484 - time (sec): 21.16 - samples/sec: 3301.29 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 18:13:34,083 epoch 10 - iter 360/723 - loss 0.00921151 - time (sec): 26.79 - samples/sec: 3299.18 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 18:13:39,827 epoch 10 - iter 432/723 - loss 0.00866624 - time (sec): 32.53 - samples/sec: 3286.87 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 18:13:44,998 epoch 10 - iter 504/723 - loss 0.00879169 - time (sec): 37.70 - samples/sec: 3293.71 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 18:13:49,760 epoch 10 - iter 576/723 - loss 0.00813104 - time (sec): 42.46 - samples/sec: 3326.77 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 18:13:55,140 epoch 10 - iter 648/723 - loss 0.00845184 - time (sec): 47.84 - samples/sec: 3334.43 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-17 18:14:00,144 epoch 10 - iter 720/723 - loss 0.00785129 - time (sec): 52.85 - samples/sec: 3320.66 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-17 18:14:00,361 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:14:00,361 EPOCH 10 done: loss 0.0078 - lr: 0.000000 | |
| 2023-10-17 18:14:03,744 DEV : loss 0.13295623660087585 - f1-score (micro avg) 0.8843 | |
| 2023-10-17 18:14:03,761 saving best model | |
| 2023-10-17 18:14:04,705 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 18:14:04,706 Loading model from best epoch ... | |
| 2023-10-17 18:14:06,078 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 18:14:09,142 | |
| Results: | |
| - F-score (micro) 0.8753 | |
| - F-score (macro) 0.7737 | |
| - Accuracy 0.7867 | |
| By class: | |
| precision recall f1-score support | |
| PER 0.8809 0.8589 0.8697 482 | |
| LOC 0.9342 0.9301 0.9322 458 | |
| ORG 0.5484 0.4928 0.5191 69 | |
| micro avg 0.8846 0.8662 0.8753 1009 | |
| macro avg 0.7878 0.7606 0.7737 1009 | |
| weighted avg 0.8823 0.8662 0.8741 1009 | |
| 2023-10-17 18:14:09,142 ---------------------------------------------------------------------------------------------------- | |