| 2023-10-17 20:12:25,534 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:12:25,535 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 20:12:25,535 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:12:25,535 MultiCorpus: 1085 train + 148 dev + 364 test sentences | |
| - NER_HIPE_2022 Corpus: 1085 train + 148 dev + 364 test sentences - /root/.flair/datasets/ner_hipe_2022/v2.1/newseye/sv/with_doc_seperator | |
| 2023-10-17 20:12:25,535 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:12:25,535 Train: 1085 sentences | |
| 2023-10-17 20:12:25,536 (train_with_dev=False, train_with_test=False) | |
| 2023-10-17 20:12:25,536 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:12:25,536 Training Params: | |
| 2023-10-17 20:12:25,536 - learning_rate: "3e-05" | |
| 2023-10-17 20:12:25,536 - mini_batch_size: "8" | |
| 2023-10-17 20:12:25,536 - max_epochs: "10" | |
| 2023-10-17 20:12:25,536 - shuffle: "True" | |
| 2023-10-17 20:12:25,536 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:12:25,536 Plugins: | |
| 2023-10-17 20:12:25,536 - TensorboardLogger | |
| 2023-10-17 20:12:25,536 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-17 20:12:25,536 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:12:25,536 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-17 20:12:25,536 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-17 20:12:25,536 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:12:25,536 Computation: | |
| 2023-10-17 20:12:25,536 - compute on device: cuda:0 | |
| 2023-10-17 20:12:25,536 - embedding storage: none | |
| 2023-10-17 20:12:25,536 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:12:25,536 Model training base path: "hmbench-newseye/sv-hmteams/teams-base-historic-multilingual-discriminator-bs8-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-3" | |
| 2023-10-17 20:12:25,536 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:12:25,536 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:12:25,536 Logging anything other than scalars to TensorBoard is currently not supported. | |
| 2023-10-17 20:12:26,980 epoch 1 - iter 13/136 - loss 3.56469652 - time (sec): 1.44 - samples/sec: 3585.96 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 20:12:28,536 epoch 1 - iter 26/136 - loss 3.33018314 - time (sec): 3.00 - samples/sec: 3781.08 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 20:12:30,021 epoch 1 - iter 39/136 - loss 2.95543144 - time (sec): 4.48 - samples/sec: 3735.60 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 20:12:31,254 epoch 1 - iter 52/136 - loss 2.55098163 - time (sec): 5.72 - samples/sec: 3716.28 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 20:12:32,731 epoch 1 - iter 65/136 - loss 2.16561603 - time (sec): 7.19 - samples/sec: 3665.22 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 20:12:33,786 epoch 1 - iter 78/136 - loss 1.95630135 - time (sec): 8.25 - samples/sec: 3676.32 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 20:12:35,197 epoch 1 - iter 91/136 - loss 1.74967521 - time (sec): 9.66 - samples/sec: 3616.63 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 20:12:36,561 epoch 1 - iter 104/136 - loss 1.55037843 - time (sec): 11.02 - samples/sec: 3669.59 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 20:12:37,858 epoch 1 - iter 117/136 - loss 1.41500927 - time (sec): 12.32 - samples/sec: 3698.94 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 20:12:39,033 epoch 1 - iter 130/136 - loss 1.31279338 - time (sec): 13.50 - samples/sec: 3697.45 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 20:12:39,636 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:12:39,636 EPOCH 1 done: loss 1.2734 - lr: 0.000028 | |
| 2023-10-17 20:12:40,860 DEV : loss 0.17920981347560883 - f1-score (micro avg) 0.6068 | |
| 2023-10-17 20:12:40,865 saving best model | |
| 2023-10-17 20:12:41,222 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:12:42,459 epoch 2 - iter 13/136 - loss 0.23296681 - time (sec): 1.24 - samples/sec: 3765.35 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-17 20:12:43,820 epoch 2 - iter 26/136 - loss 0.24799180 - time (sec): 2.60 - samples/sec: 3732.19 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 20:12:44,999 epoch 2 - iter 39/136 - loss 0.22292966 - time (sec): 3.78 - samples/sec: 3845.54 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 20:12:46,415 epoch 2 - iter 52/136 - loss 0.21149373 - time (sec): 5.19 - samples/sec: 3724.35 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 20:12:47,777 epoch 2 - iter 65/136 - loss 0.20240517 - time (sec): 6.55 - samples/sec: 3700.29 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 20:12:49,399 epoch 2 - iter 78/136 - loss 0.19342818 - time (sec): 8.18 - samples/sec: 3600.69 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 20:12:50,745 epoch 2 - iter 91/136 - loss 0.18557542 - time (sec): 9.52 - samples/sec: 3600.10 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 20:12:52,371 epoch 2 - iter 104/136 - loss 0.18162443 - time (sec): 11.15 - samples/sec: 3578.27 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 20:12:53,841 epoch 2 - iter 117/136 - loss 0.17641577 - time (sec): 12.62 - samples/sec: 3601.85 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 20:12:55,198 epoch 2 - iter 130/136 - loss 0.16835610 - time (sec): 13.97 - samples/sec: 3576.06 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 20:12:55,859 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:12:55,860 EPOCH 2 done: loss 0.1664 - lr: 0.000027 | |
| 2023-10-17 20:12:57,380 DEV : loss 0.12096702307462692 - f1-score (micro avg) 0.7178 | |
| 2023-10-17 20:12:57,385 saving best model | |
| 2023-10-17 20:12:57,885 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:12:59,565 epoch 3 - iter 13/136 - loss 0.10688261 - time (sec): 1.68 - samples/sec: 2818.79 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 20:13:00,706 epoch 3 - iter 26/136 - loss 0.11348635 - time (sec): 2.82 - samples/sec: 3122.93 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 20:13:02,144 epoch 3 - iter 39/136 - loss 0.10946288 - time (sec): 4.26 - samples/sec: 3337.16 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 20:13:03,448 epoch 3 - iter 52/136 - loss 0.09875128 - time (sec): 5.56 - samples/sec: 3419.92 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 20:13:04,795 epoch 3 - iter 65/136 - loss 0.10238528 - time (sec): 6.91 - samples/sec: 3496.81 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 20:13:06,069 epoch 3 - iter 78/136 - loss 0.09890742 - time (sec): 8.18 - samples/sec: 3529.37 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 20:13:07,400 epoch 3 - iter 91/136 - loss 0.09927605 - time (sec): 9.51 - samples/sec: 3489.99 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 20:13:09,059 epoch 3 - iter 104/136 - loss 0.10213739 - time (sec): 11.17 - samples/sec: 3465.90 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 20:13:10,483 epoch 3 - iter 117/136 - loss 0.10125728 - time (sec): 12.60 - samples/sec: 3489.58 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 20:13:12,174 epoch 3 - iter 130/136 - loss 0.09993701 - time (sec): 14.29 - samples/sec: 3467.14 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 20:13:12,782 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:13:12,782 EPOCH 3 done: loss 0.0986 - lr: 0.000024 | |
| 2023-10-17 20:13:14,255 DEV : loss 0.08591549098491669 - f1-score (micro avg) 0.7942 | |
| 2023-10-17 20:13:14,260 saving best model | |
| 2023-10-17 20:13:14,727 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:13:15,913 epoch 4 - iter 13/136 - loss 0.06018926 - time (sec): 1.18 - samples/sec: 3558.55 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 20:13:17,244 epoch 4 - iter 26/136 - loss 0.06085278 - time (sec): 2.51 - samples/sec: 3578.74 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 20:13:18,689 epoch 4 - iter 39/136 - loss 0.06043327 - time (sec): 3.96 - samples/sec: 3479.26 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 20:13:20,225 epoch 4 - iter 52/136 - loss 0.06185287 - time (sec): 5.49 - samples/sec: 3426.97 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 20:13:21,401 epoch 4 - iter 65/136 - loss 0.05755276 - time (sec): 6.67 - samples/sec: 3537.79 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 20:13:23,133 epoch 4 - iter 78/136 - loss 0.06276857 - time (sec): 8.40 - samples/sec: 3485.61 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 20:13:24,317 epoch 4 - iter 91/136 - loss 0.06484688 - time (sec): 9.59 - samples/sec: 3540.53 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 20:13:25,962 epoch 4 - iter 104/136 - loss 0.06068370 - time (sec): 11.23 - samples/sec: 3532.08 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 20:13:27,379 epoch 4 - iter 117/136 - loss 0.06208566 - time (sec): 12.65 - samples/sec: 3578.80 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 20:13:28,583 epoch 4 - iter 130/136 - loss 0.06298638 - time (sec): 13.85 - samples/sec: 3603.24 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 20:13:29,189 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:13:29,189 EPOCH 4 done: loss 0.0615 - lr: 0.000020 | |
| 2023-10-17 20:13:30,692 DEV : loss 0.10039487481117249 - f1-score (micro avg) 0.7971 | |
| 2023-10-17 20:13:30,697 saving best model | |
| 2023-10-17 20:13:31,165 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:13:32,955 epoch 5 - iter 13/136 - loss 0.03987252 - time (sec): 1.79 - samples/sec: 3074.23 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 20:13:34,130 epoch 5 - iter 26/136 - loss 0.03912310 - time (sec): 2.96 - samples/sec: 3323.99 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 20:13:35,468 epoch 5 - iter 39/136 - loss 0.03863979 - time (sec): 4.30 - samples/sec: 3262.17 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 20:13:36,801 epoch 5 - iter 52/136 - loss 0.03622420 - time (sec): 5.63 - samples/sec: 3478.53 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 20:13:38,388 epoch 5 - iter 65/136 - loss 0.03387900 - time (sec): 7.22 - samples/sec: 3483.48 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 20:13:39,949 epoch 5 - iter 78/136 - loss 0.03469888 - time (sec): 8.78 - samples/sec: 3504.32 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 20:13:41,157 epoch 5 - iter 91/136 - loss 0.03515893 - time (sec): 9.99 - samples/sec: 3502.52 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 20:13:42,657 epoch 5 - iter 104/136 - loss 0.03745754 - time (sec): 11.49 - samples/sec: 3501.30 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 20:13:44,109 epoch 5 - iter 117/136 - loss 0.03876292 - time (sec): 12.94 - samples/sec: 3462.10 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 20:13:45,464 epoch 5 - iter 130/136 - loss 0.03993650 - time (sec): 14.30 - samples/sec: 3492.18 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 20:13:46,046 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:13:46,047 EPOCH 5 done: loss 0.0401 - lr: 0.000017 | |
| 2023-10-17 20:13:47,576 DEV : loss 0.11180326342582703 - f1-score (micro avg) 0.7904 | |
| 2023-10-17 20:13:47,582 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:13:49,187 epoch 6 - iter 13/136 - loss 0.02256178 - time (sec): 1.60 - samples/sec: 3203.98 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 20:13:50,516 epoch 6 - iter 26/136 - loss 0.02483432 - time (sec): 2.93 - samples/sec: 3436.08 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 20:13:51,729 epoch 6 - iter 39/136 - loss 0.02830385 - time (sec): 4.15 - samples/sec: 3482.11 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 20:13:53,135 epoch 6 - iter 52/136 - loss 0.02444290 - time (sec): 5.55 - samples/sec: 3479.67 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 20:13:54,664 epoch 6 - iter 65/136 - loss 0.02307868 - time (sec): 7.08 - samples/sec: 3515.74 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 20:13:55,765 epoch 6 - iter 78/136 - loss 0.02339547 - time (sec): 8.18 - samples/sec: 3541.86 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 20:13:57,053 epoch 6 - iter 91/136 - loss 0.02421288 - time (sec): 9.47 - samples/sec: 3540.14 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 20:13:58,360 epoch 6 - iter 104/136 - loss 0.02596671 - time (sec): 10.78 - samples/sec: 3563.87 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 20:13:59,837 epoch 6 - iter 117/136 - loss 0.02545975 - time (sec): 12.25 - samples/sec: 3577.26 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 20:14:01,410 epoch 6 - iter 130/136 - loss 0.02737841 - time (sec): 13.83 - samples/sec: 3566.42 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 20:14:02,079 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:14:02,080 EPOCH 6 done: loss 0.0269 - lr: 0.000014 | |
| 2023-10-17 20:14:03,594 DEV : loss 0.11931055039167404 - f1-score (micro avg) 0.7906 | |
| 2023-10-17 20:14:03,599 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:14:05,036 epoch 7 - iter 13/136 - loss 0.02728369 - time (sec): 1.44 - samples/sec: 3647.55 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 20:14:06,754 epoch 7 - iter 26/136 - loss 0.02508212 - time (sec): 3.15 - samples/sec: 3243.52 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 20:14:07,977 epoch 7 - iter 39/136 - loss 0.01944223 - time (sec): 4.38 - samples/sec: 3359.95 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 20:14:09,367 epoch 7 - iter 52/136 - loss 0.01891054 - time (sec): 5.77 - samples/sec: 3445.16 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 20:14:10,931 epoch 7 - iter 65/136 - loss 0.01886752 - time (sec): 7.33 - samples/sec: 3414.88 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 20:14:12,273 epoch 7 - iter 78/136 - loss 0.02600379 - time (sec): 8.67 - samples/sec: 3438.12 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 20:14:13,711 epoch 7 - iter 91/136 - loss 0.02405010 - time (sec): 10.11 - samples/sec: 3474.80 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 20:14:15,069 epoch 7 - iter 104/136 - loss 0.02314826 - time (sec): 11.47 - samples/sec: 3458.49 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 20:14:16,353 epoch 7 - iter 117/136 - loss 0.02220090 - time (sec): 12.75 - samples/sec: 3495.04 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 20:14:17,726 epoch 7 - iter 130/136 - loss 0.02185557 - time (sec): 14.13 - samples/sec: 3499.49 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 20:14:18,387 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:14:18,387 EPOCH 7 done: loss 0.0216 - lr: 0.000010 | |
| 2023-10-17 20:14:19,971 DEV : loss 0.1356595754623413 - f1-score (micro avg) 0.7842 | |
| 2023-10-17 20:14:19,978 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:14:21,419 epoch 8 - iter 13/136 - loss 0.01459122 - time (sec): 1.44 - samples/sec: 3223.63 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 20:14:22,884 epoch 8 - iter 26/136 - loss 0.01524438 - time (sec): 2.91 - samples/sec: 3345.87 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 20:14:24,288 epoch 8 - iter 39/136 - loss 0.01681237 - time (sec): 4.31 - samples/sec: 3506.61 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 20:14:25,632 epoch 8 - iter 52/136 - loss 0.01579062 - time (sec): 5.65 - samples/sec: 3488.23 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 20:14:27,289 epoch 8 - iter 65/136 - loss 0.01850053 - time (sec): 7.31 - samples/sec: 3476.24 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 20:14:28,856 epoch 8 - iter 78/136 - loss 0.01750239 - time (sec): 8.88 - samples/sec: 3400.75 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 20:14:30,174 epoch 8 - iter 91/136 - loss 0.01679539 - time (sec): 10.20 - samples/sec: 3458.71 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 20:14:31,621 epoch 8 - iter 104/136 - loss 0.01636561 - time (sec): 11.64 - samples/sec: 3460.03 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 20:14:32,839 epoch 8 - iter 117/136 - loss 0.01625463 - time (sec): 12.86 - samples/sec: 3488.55 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 20:14:34,305 epoch 8 - iter 130/136 - loss 0.01599673 - time (sec): 14.33 - samples/sec: 3475.87 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 20:14:34,871 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:14:34,872 EPOCH 8 done: loss 0.0155 - lr: 0.000007 | |
| 2023-10-17 20:14:36,374 DEV : loss 0.13436543941497803 - f1-score (micro avg) 0.8051 | |
| 2023-10-17 20:14:36,378 saving best model | |
| 2023-10-17 20:14:36,851 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:14:38,467 epoch 9 - iter 13/136 - loss 0.01017808 - time (sec): 1.61 - samples/sec: 3125.28 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 20:14:39,861 epoch 9 - iter 26/136 - loss 0.00781613 - time (sec): 3.01 - samples/sec: 3384.75 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 20:14:41,513 epoch 9 - iter 39/136 - loss 0.00860655 - time (sec): 4.66 - samples/sec: 3275.36 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 20:14:42,651 epoch 9 - iter 52/136 - loss 0.00830057 - time (sec): 5.80 - samples/sec: 3299.77 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 20:14:43,851 epoch 9 - iter 65/136 - loss 0.00782478 - time (sec): 7.00 - samples/sec: 3391.09 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 20:14:45,388 epoch 9 - iter 78/136 - loss 0.00919217 - time (sec): 8.53 - samples/sec: 3393.01 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 20:14:46,901 epoch 9 - iter 91/136 - loss 0.01018609 - time (sec): 10.05 - samples/sec: 3385.34 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 20:14:48,204 epoch 9 - iter 104/136 - loss 0.01072845 - time (sec): 11.35 - samples/sec: 3442.69 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 20:14:49,825 epoch 9 - iter 117/136 - loss 0.01148823 - time (sec): 12.97 - samples/sec: 3450.66 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 20:14:51,005 epoch 9 - iter 130/136 - loss 0.01159600 - time (sec): 14.15 - samples/sec: 3492.50 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 20:14:51,676 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:14:51,676 EPOCH 9 done: loss 0.0114 - lr: 0.000004 | |
| 2023-10-17 20:14:53,187 DEV : loss 0.14552520215511322 - f1-score (micro avg) 0.8183 | |
| 2023-10-17 20:14:53,191 saving best model | |
| 2023-10-17 20:14:53,662 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:14:54,950 epoch 10 - iter 13/136 - loss 0.01469245 - time (sec): 1.29 - samples/sec: 3230.38 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 20:14:56,089 epoch 10 - iter 26/136 - loss 0.02040672 - time (sec): 2.42 - samples/sec: 3368.12 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 20:14:57,468 epoch 10 - iter 39/136 - loss 0.01427909 - time (sec): 3.80 - samples/sec: 3452.11 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 20:14:58,855 epoch 10 - iter 52/136 - loss 0.01331876 - time (sec): 5.19 - samples/sec: 3514.99 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 20:15:00,113 epoch 10 - iter 65/136 - loss 0.01438903 - time (sec): 6.45 - samples/sec: 3491.61 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 20:15:01,548 epoch 10 - iter 78/136 - loss 0.01258656 - time (sec): 7.88 - samples/sec: 3591.51 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 20:15:03,037 epoch 10 - iter 91/136 - loss 0.01300637 - time (sec): 9.37 - samples/sec: 3576.70 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 20:15:04,424 epoch 10 - iter 104/136 - loss 0.01261802 - time (sec): 10.76 - samples/sec: 3624.70 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 20:15:05,828 epoch 10 - iter 117/136 - loss 0.01157527 - time (sec): 12.16 - samples/sec: 3630.39 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 20:15:07,223 epoch 10 - iter 130/136 - loss 0.01084597 - time (sec): 13.56 - samples/sec: 3632.39 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-17 20:15:08,084 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:15:08,084 EPOCH 10 done: loss 0.0107 - lr: 0.000000 | |
| 2023-10-17 20:15:09,555 DEV : loss 0.15006117522716522 - f1-score (micro avg) 0.8132 | |
| 2023-10-17 20:15:09,926 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:15:09,928 Loading model from best epoch ... | |
| 2023-10-17 20:15:11,517 SequenceTagger predicts: Dictionary with 17 tags: O, S-LOC, B-LOC, E-LOC, I-LOC, S-PER, B-PER, E-PER, I-PER, S-HumanProd, B-HumanProd, E-HumanProd, I-HumanProd, S-ORG, B-ORG, E-ORG, I-ORG | |
| 2023-10-17 20:15:13,740 | |
| Results: | |
| - F-score (micro) 0.7926 | |
| - F-score (macro) 0.7586 | |
| - Accuracy 0.6716 | |
| By class: | |
| precision recall f1-score support | |
| LOC 0.8479 0.8397 0.8438 312 | |
| PER 0.7121 0.8798 0.7871 208 | |
| ORG 0.4667 0.5091 0.4870 55 | |
| HumanProd 0.8462 1.0000 0.9167 22 | |
| micro avg 0.7592 0.8291 0.7926 597 | |
| macro avg 0.7182 0.8072 0.7586 597 | |
| weighted avg 0.7654 0.8291 0.7939 597 | |
| 2023-10-17 20:15:13,740 ---------------------------------------------------------------------------------------------------- | |