| 2023-10-25 11:54:59,919 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 11:54:59,920 Model: "SequenceTagger( | |
| (embeddings): TransformerWordEmbeddings( | |
| (model): BertModel( | |
| (embeddings): BertEmbeddings( | |
| (word_embeddings): Embedding(64001, 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() | |
| )" | |
| 2023-10-25 11:54:59,920 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 11:54:59,920 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 | |
| 2023-10-25 11:54:59,920 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 11:54:59,920 Train: 6183 sentences | |
| 2023-10-25 11:54:59,920 (train_with_dev=False, train_with_test=False) | |
| 2023-10-25 11:54:59,920 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 11:54:59,920 Training Params: | |
| 2023-10-25 11:54:59,920 - learning_rate: "5e-05" | |
| 2023-10-25 11:54:59,920 - mini_batch_size: "4" | |
| 2023-10-25 11:54:59,920 - max_epochs: "10" | |
| 2023-10-25 11:54:59,920 - shuffle: "True" | |
| 2023-10-25 11:54:59,920 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 11:54:59,921 Plugins: | |
| 2023-10-25 11:54:59,921 - TensorboardLogger | |
| 2023-10-25 11:54:59,921 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-25 11:54:59,921 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 11:54:59,921 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-25 11:54:59,921 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-25 11:54:59,921 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 11:54:59,921 Computation: | |
| 2023-10-25 11:54:59,921 - compute on device: cuda:0 | |
| 2023-10-25 11:54:59,921 - embedding storage: none | |
| 2023-10-25 11:54:59,921 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 11:54:59,921 Model training base path: "hmbench-topres19th/en-dbmdz/bert-base-historic-multilingual-64k-td-cased-bs4-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-3" | |
| 2023-10-25 11:54:59,921 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 11:54:59,921 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 11:54:59,921 Logging anything other than scalars to TensorBoard is currently not supported. | |
| 2023-10-25 11:55:07,914 epoch 1 - iter 154/1546 - loss 1.25390389 - time (sec): 7.99 - samples/sec: 1781.21 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-25 11:55:15,333 epoch 1 - iter 308/1546 - loss 0.76642917 - time (sec): 15.41 - samples/sec: 1690.78 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-25 11:55:23,717 epoch 1 - iter 462/1546 - loss 0.56225091 - time (sec): 23.80 - samples/sec: 1626.05 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-25 11:55:31,627 epoch 1 - iter 616/1546 - loss 0.45626833 - time (sec): 31.70 - samples/sec: 1603.14 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-25 11:55:39,613 epoch 1 - iter 770/1546 - loss 0.39138368 - time (sec): 39.69 - samples/sec: 1593.46 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-25 11:55:47,776 epoch 1 - iter 924/1546 - loss 0.35571490 - time (sec): 47.85 - samples/sec: 1556.21 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-25 11:55:55,520 epoch 1 - iter 1078/1546 - loss 0.32332623 - time (sec): 55.60 - samples/sec: 1557.39 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-25 11:56:03,305 epoch 1 - iter 1232/1546 - loss 0.29722994 - time (sec): 63.38 - samples/sec: 1563.96 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-25 11:56:11,421 epoch 1 - iter 1386/1546 - loss 0.27559241 - time (sec): 71.50 - samples/sec: 1558.87 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-25 11:56:19,164 epoch 1 - iter 1540/1546 - loss 0.25930733 - time (sec): 79.24 - samples/sec: 1561.70 - lr: 0.000050 - momentum: 0.000000 | |
| 2023-10-25 11:56:19,464 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 11:56:19,464 EPOCH 1 done: loss 0.2589 - lr: 0.000050 | |
| 2023-10-25 11:56:22,011 DEV : loss 0.0908343568444252 - f1-score (micro avg) 0.7229 | |
| 2023-10-25 11:56:22,033 saving best model | |
| 2023-10-25 11:56:22,639 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 11:56:30,630 epoch 2 - iter 154/1546 - loss 0.09739237 - time (sec): 7.99 - samples/sec: 1474.65 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-25 11:56:38,495 epoch 2 - iter 308/1546 - loss 0.09761310 - time (sec): 15.85 - samples/sec: 1552.78 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-25 11:56:46,873 epoch 2 - iter 462/1546 - loss 0.09917743 - time (sec): 24.23 - samples/sec: 1568.90 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-25 11:56:54,625 epoch 2 - iter 616/1546 - loss 0.09370713 - time (sec): 31.98 - samples/sec: 1598.84 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-25 11:57:02,309 epoch 2 - iter 770/1546 - loss 0.09462855 - time (sec): 39.67 - samples/sec: 1600.11 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-25 11:57:10,081 epoch 2 - iter 924/1546 - loss 0.09486483 - time (sec): 47.44 - samples/sec: 1579.18 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-25 11:57:17,853 epoch 2 - iter 1078/1546 - loss 0.09618995 - time (sec): 55.21 - samples/sec: 1574.82 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-25 11:57:25,684 epoch 2 - iter 1232/1546 - loss 0.09626906 - time (sec): 63.04 - samples/sec: 1578.83 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-25 11:57:33,458 epoch 2 - iter 1386/1546 - loss 0.10061257 - time (sec): 70.82 - samples/sec: 1570.84 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-25 11:57:41,280 epoch 2 - iter 1540/1546 - loss 0.09989085 - time (sec): 78.64 - samples/sec: 1573.54 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-25 11:57:41,600 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 11:57:41,600 EPOCH 2 done: loss 0.0997 - lr: 0.000044 | |
| 2023-10-25 11:57:44,817 DEV : loss 0.056556034833192825 - f1-score (micro avg) 0.7042 | |
| 2023-10-25 11:57:44,836 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 11:57:52,516 epoch 3 - iter 154/1546 - loss 0.05181413 - time (sec): 7.68 - samples/sec: 1614.43 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-25 11:58:00,324 epoch 3 - iter 308/1546 - loss 0.05067804 - time (sec): 15.49 - samples/sec: 1602.32 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-25 11:58:08,395 epoch 3 - iter 462/1546 - loss 0.05926773 - time (sec): 23.56 - samples/sec: 1633.22 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-25 11:58:15,574 epoch 3 - iter 616/1546 - loss 0.06021083 - time (sec): 30.74 - samples/sec: 1650.50 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-25 11:58:22,888 epoch 3 - iter 770/1546 - loss 0.06372716 - time (sec): 38.05 - samples/sec: 1638.48 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-25 11:58:30,255 epoch 3 - iter 924/1546 - loss 0.06361460 - time (sec): 45.42 - samples/sec: 1616.96 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-25 11:58:37,724 epoch 3 - iter 1078/1546 - loss 0.06346591 - time (sec): 52.89 - samples/sec: 1633.90 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-25 11:58:45,214 epoch 3 - iter 1232/1546 - loss 0.06338422 - time (sec): 60.38 - samples/sec: 1635.44 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-25 11:58:52,791 epoch 3 - iter 1386/1546 - loss 0.06363303 - time (sec): 67.95 - samples/sec: 1638.00 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-25 11:59:00,043 epoch 3 - iter 1540/1546 - loss 0.06408898 - time (sec): 75.21 - samples/sec: 1648.35 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-25 11:59:00,317 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 11:59:00,318 EPOCH 3 done: loss 0.0642 - lr: 0.000039 | |
| 2023-10-25 11:59:03,151 DEV : loss 0.10106009989976883 - f1-score (micro avg) 0.7469 | |
| 2023-10-25 11:59:03,168 saving best model | |
| 2023-10-25 11:59:03,853 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 11:59:11,915 epoch 4 - iter 154/1546 - loss 0.04283787 - time (sec): 8.06 - samples/sec: 1594.31 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-25 11:59:19,911 epoch 4 - iter 308/1546 - loss 0.05126655 - time (sec): 16.05 - samples/sec: 1603.31 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-25 11:59:27,978 epoch 4 - iter 462/1546 - loss 0.04992581 - time (sec): 24.12 - samples/sec: 1593.74 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-25 11:59:35,538 epoch 4 - iter 616/1546 - loss 0.05045699 - time (sec): 31.68 - samples/sec: 1602.73 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-25 11:59:43,185 epoch 4 - iter 770/1546 - loss 0.04799193 - time (sec): 39.33 - samples/sec: 1610.64 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-25 11:59:51,099 epoch 4 - iter 924/1546 - loss 0.04985205 - time (sec): 47.24 - samples/sec: 1605.35 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-25 11:59:58,609 epoch 4 - iter 1078/1546 - loss 0.05016705 - time (sec): 54.75 - samples/sec: 1598.42 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-25 12:00:06,623 epoch 4 - iter 1232/1546 - loss 0.05063862 - time (sec): 62.77 - samples/sec: 1579.46 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-25 12:00:14,517 epoch 4 - iter 1386/1546 - loss 0.05249377 - time (sec): 70.66 - samples/sec: 1565.67 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-25 12:00:22,462 epoch 4 - iter 1540/1546 - loss 0.05219490 - time (sec): 78.61 - samples/sec: 1573.98 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-25 12:00:22,782 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 12:00:22,782 EPOCH 4 done: loss 0.0521 - lr: 0.000033 | |
| 2023-10-25 12:00:25,339 DEV : loss 0.10263549536466599 - f1-score (micro avg) 0.7336 | |
| 2023-10-25 12:00:25,356 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 12:00:33,332 epoch 5 - iter 154/1546 - loss 0.04033890 - time (sec): 7.97 - samples/sec: 1471.01 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-25 12:00:40,954 epoch 5 - iter 308/1546 - loss 0.03417886 - time (sec): 15.60 - samples/sec: 1537.25 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-25 12:00:48,579 epoch 5 - iter 462/1546 - loss 0.03520716 - time (sec): 23.22 - samples/sec: 1580.31 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-25 12:00:55,977 epoch 5 - iter 616/1546 - loss 0.03469198 - time (sec): 30.62 - samples/sec: 1604.23 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-25 12:01:03,419 epoch 5 - iter 770/1546 - loss 0.03632234 - time (sec): 38.06 - samples/sec: 1592.53 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-25 12:01:10,602 epoch 5 - iter 924/1546 - loss 0.03675886 - time (sec): 45.24 - samples/sec: 1622.62 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-25 12:01:18,263 epoch 5 - iter 1078/1546 - loss 0.03717145 - time (sec): 52.91 - samples/sec: 1620.29 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-25 12:01:25,824 epoch 5 - iter 1232/1546 - loss 0.03733963 - time (sec): 60.47 - samples/sec: 1623.60 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-25 12:01:33,254 epoch 5 - iter 1386/1546 - loss 0.03739261 - time (sec): 67.90 - samples/sec: 1626.40 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-25 12:01:40,791 epoch 5 - iter 1540/1546 - loss 0.03609247 - time (sec): 75.43 - samples/sec: 1643.28 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-25 12:01:41,081 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 12:01:41,081 EPOCH 5 done: loss 0.0361 - lr: 0.000028 | |
| 2023-10-25 12:01:43,649 DEV : loss 0.10063710063695908 - f1-score (micro avg) 0.7578 | |
| 2023-10-25 12:01:43,670 saving best model | |
| 2023-10-25 12:01:44,401 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 12:01:52,516 epoch 6 - iter 154/1546 - loss 0.02144957 - time (sec): 8.11 - samples/sec: 1503.38 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-25 12:02:00,367 epoch 6 - iter 308/1546 - loss 0.01944377 - time (sec): 15.96 - samples/sec: 1548.06 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-25 12:02:07,813 epoch 6 - iter 462/1546 - loss 0.02131841 - time (sec): 23.41 - samples/sec: 1594.82 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-25 12:02:15,050 epoch 6 - iter 616/1546 - loss 0.02451594 - time (sec): 30.65 - samples/sec: 1608.35 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-25 12:02:22,532 epoch 6 - iter 770/1546 - loss 0.02711661 - time (sec): 38.13 - samples/sec: 1659.82 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-25 12:02:29,884 epoch 6 - iter 924/1546 - loss 0.02668924 - time (sec): 45.48 - samples/sec: 1666.07 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-25 12:02:37,236 epoch 6 - iter 1078/1546 - loss 0.02684771 - time (sec): 52.83 - samples/sec: 1654.02 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-25 12:02:44,824 epoch 6 - iter 1232/1546 - loss 0.02616481 - time (sec): 60.42 - samples/sec: 1648.23 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-25 12:02:52,412 epoch 6 - iter 1386/1546 - loss 0.02831231 - time (sec): 68.01 - samples/sec: 1640.42 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-25 12:02:59,852 epoch 6 - iter 1540/1546 - loss 0.02698839 - time (sec): 75.45 - samples/sec: 1641.36 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-25 12:03:00,129 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 12:03:00,129 EPOCH 6 done: loss 0.0269 - lr: 0.000022 | |
| 2023-10-25 12:03:02,808 DEV : loss 0.11260586231946945 - f1-score (micro avg) 0.7391 | |
| 2023-10-25 12:03:02,825 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 12:03:10,873 epoch 7 - iter 154/1546 - loss 0.02745142 - time (sec): 8.05 - samples/sec: 1514.77 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-25 12:03:19,090 epoch 7 - iter 308/1546 - loss 0.02694082 - time (sec): 16.26 - samples/sec: 1527.22 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-25 12:03:27,221 epoch 7 - iter 462/1546 - loss 0.02268879 - time (sec): 24.39 - samples/sec: 1535.08 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-25 12:03:35,458 epoch 7 - iter 616/1546 - loss 0.01949071 - time (sec): 32.63 - samples/sec: 1521.69 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-25 12:03:43,242 epoch 7 - iter 770/1546 - loss 0.02044806 - time (sec): 40.42 - samples/sec: 1518.87 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-25 12:03:50,661 epoch 7 - iter 924/1546 - loss 0.02138991 - time (sec): 47.83 - samples/sec: 1556.48 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-25 12:03:58,015 epoch 7 - iter 1078/1546 - loss 0.02319470 - time (sec): 55.19 - samples/sec: 1566.13 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-25 12:04:06,082 epoch 7 - iter 1232/1546 - loss 0.02195662 - time (sec): 63.25 - samples/sec: 1552.82 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-25 12:04:13,523 epoch 7 - iter 1386/1546 - loss 0.02149172 - time (sec): 70.70 - samples/sec: 1571.28 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-25 12:04:20,843 epoch 7 - iter 1540/1546 - loss 0.02143786 - time (sec): 78.02 - samples/sec: 1587.63 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-25 12:04:21,121 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 12:04:21,121 EPOCH 7 done: loss 0.0214 - lr: 0.000017 | |
| 2023-10-25 12:04:24,404 DEV : loss 0.12575747072696686 - f1-score (micro avg) 0.7455 | |
| 2023-10-25 12:04:24,421 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 12:04:32,398 epoch 8 - iter 154/1546 - loss 0.01166650 - time (sec): 7.98 - samples/sec: 1498.85 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-25 12:04:40,449 epoch 8 - iter 308/1546 - loss 0.01080450 - time (sec): 16.03 - samples/sec: 1560.63 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-25 12:04:47,717 epoch 8 - iter 462/1546 - loss 0.00876722 - time (sec): 23.30 - samples/sec: 1617.64 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-25 12:04:54,944 epoch 8 - iter 616/1546 - loss 0.01013665 - time (sec): 30.52 - samples/sec: 1646.31 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-25 12:05:02,132 epoch 8 - iter 770/1546 - loss 0.01169730 - time (sec): 37.71 - samples/sec: 1660.62 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-25 12:05:09,312 epoch 8 - iter 924/1546 - loss 0.01259154 - time (sec): 44.89 - samples/sec: 1651.26 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-25 12:05:17,209 epoch 8 - iter 1078/1546 - loss 0.01208262 - time (sec): 52.79 - samples/sec: 1642.63 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-25 12:05:25,133 epoch 8 - iter 1232/1546 - loss 0.01242729 - time (sec): 60.71 - samples/sec: 1629.92 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-25 12:05:33,093 epoch 8 - iter 1386/1546 - loss 0.01220123 - time (sec): 68.67 - samples/sec: 1618.55 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-25 12:05:40,793 epoch 8 - iter 1540/1546 - loss 0.01251829 - time (sec): 76.37 - samples/sec: 1618.93 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-25 12:05:41,103 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 12:05:41,104 EPOCH 8 done: loss 0.0126 - lr: 0.000011 | |
| 2023-10-25 12:05:44,000 DEV : loss 0.13706336915493011 - f1-score (micro avg) 0.7418 | |
| 2023-10-25 12:05:44,018 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 12:05:52,150 epoch 9 - iter 154/1546 - loss 0.00423093 - time (sec): 8.13 - samples/sec: 1508.70 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-25 12:05:59,918 epoch 9 - iter 308/1546 - loss 0.00796578 - time (sec): 15.90 - samples/sec: 1535.43 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-25 12:06:07,701 epoch 9 - iter 462/1546 - loss 0.00742909 - time (sec): 23.68 - samples/sec: 1543.35 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-25 12:06:15,465 epoch 9 - iter 616/1546 - loss 0.00683659 - time (sec): 31.44 - samples/sec: 1554.84 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-25 12:06:23,449 epoch 9 - iter 770/1546 - loss 0.00668404 - time (sec): 39.43 - samples/sec: 1580.63 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-25 12:06:30,775 epoch 9 - iter 924/1546 - loss 0.00669052 - time (sec): 46.75 - samples/sec: 1594.92 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-25 12:06:38,008 epoch 9 - iter 1078/1546 - loss 0.00778673 - time (sec): 53.99 - samples/sec: 1608.11 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-25 12:06:45,365 epoch 9 - iter 1232/1546 - loss 0.00738229 - time (sec): 61.34 - samples/sec: 1626.26 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-25 12:06:52,500 epoch 9 - iter 1386/1546 - loss 0.00725643 - time (sec): 68.48 - samples/sec: 1641.64 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-25 12:06:59,907 epoch 9 - iter 1540/1546 - loss 0.00755278 - time (sec): 75.89 - samples/sec: 1632.10 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-25 12:07:00,187 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 12:07:00,187 EPOCH 9 done: loss 0.0076 - lr: 0.000006 | |
| 2023-10-25 12:07:02,823 DEV : loss 0.13333649933338165 - f1-score (micro avg) 0.7536 | |
| 2023-10-25 12:07:02,840 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 12:07:10,967 epoch 10 - iter 154/1546 - loss 0.00165995 - time (sec): 8.13 - samples/sec: 1685.09 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-25 12:07:18,856 epoch 10 - iter 308/1546 - loss 0.00222406 - time (sec): 16.02 - samples/sec: 1592.31 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-25 12:07:26,838 epoch 10 - iter 462/1546 - loss 0.00205192 - time (sec): 24.00 - samples/sec: 1595.86 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-25 12:07:34,915 epoch 10 - iter 616/1546 - loss 0.00309192 - time (sec): 32.07 - samples/sec: 1579.51 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-25 12:07:42,987 epoch 10 - iter 770/1546 - loss 0.00355935 - time (sec): 40.15 - samples/sec: 1584.03 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-25 12:07:51,142 epoch 10 - iter 924/1546 - loss 0.00377660 - time (sec): 48.30 - samples/sec: 1572.64 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-25 12:07:59,104 epoch 10 - iter 1078/1546 - loss 0.00389532 - time (sec): 56.26 - samples/sec: 1560.53 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-25 12:08:07,198 epoch 10 - iter 1232/1546 - loss 0.00374600 - time (sec): 64.36 - samples/sec: 1549.34 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-25 12:08:15,337 epoch 10 - iter 1386/1546 - loss 0.00399484 - time (sec): 72.50 - samples/sec: 1544.18 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-25 12:08:23,099 epoch 10 - iter 1540/1546 - loss 0.00406636 - time (sec): 80.26 - samples/sec: 1543.72 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-25 12:08:23,376 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 12:08:23,377 EPOCH 10 done: loss 0.0042 - lr: 0.000000 | |
| 2023-10-25 12:08:26,002 DEV : loss 0.14262209832668304 - f1-score (micro avg) 0.7546 | |
| 2023-10-25 12:08:26,470 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 12:08:26,472 Loading model from best epoch ... | |
| 2023-10-25 12:08:28,407 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 | |
| 2023-10-25 12:08:37,488 | |
| Results: | |
| - F-score (micro) 0.7585 | |
| - F-score (macro) 0.5929 | |
| - Accuracy 0.6256 | |
| By class: | |
| precision recall f1-score support | |
| LOC 0.7988 0.8436 0.8206 946 | |
| BUILDING 0.5938 0.3081 0.4057 185 | |
| STREET 0.5918 0.5179 0.5524 56 | |
| micro avg 0.7727 0.7447 0.7585 1187 | |
| macro avg 0.6615 0.5565 0.5929 1187 | |
| weighted avg 0.7571 0.7447 0.7433 1187 | |
| 2023-10-25 12:08:37,488 ---------------------------------------------------------------------------------------------------- | |