| 2023-10-15 13:16:10,272 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:16:10,273 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=17, bias=True) | |
| (loss_function): CrossEntropyLoss() | |
| )" | |
| 2023-10-15 13:16:10,273 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:16:10,273 MultiCorpus: 20847 train + 1123 dev + 3350 test sentences | |
| - NER_HIPE_2022 Corpus: 20847 train + 1123 dev + 3350 test sentences - /root/.flair/datasets/ner_hipe_2022/v2.1/newseye/de/with_doc_seperator | |
| 2023-10-15 13:16:10,273 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:16:10,273 Train: 20847 sentences | |
| 2023-10-15 13:16:10,273 (train_with_dev=False, train_with_test=False) | |
| 2023-10-15 13:16:10,273 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:16:10,273 Training Params: | |
| 2023-10-15 13:16:10,273 - learning_rate: "5e-05" | |
| 2023-10-15 13:16:10,273 - mini_batch_size: "4" | |
| 2023-10-15 13:16:10,273 - max_epochs: "10" | |
| 2023-10-15 13:16:10,273 - shuffle: "True" | |
| 2023-10-15 13:16:10,273 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:16:10,273 Plugins: | |
| 2023-10-15 13:16:10,273 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-15 13:16:10,273 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:16:10,273 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-15 13:16:10,273 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-15 13:16:10,273 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:16:10,273 Computation: | |
| 2023-10-15 13:16:10,273 - compute on device: cuda:0 | |
| 2023-10-15 13:16:10,273 - embedding storage: none | |
| 2023-10-15 13:16:10,273 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:16:10,273 Model training base path: "hmbench-newseye/de-dbmdz/bert-base-historic-multilingual-cased-bs4-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-1" | |
| 2023-10-15 13:16:10,273 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:16:10,273 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:16:35,448 epoch 1 - iter 521/5212 - loss 1.40362758 - time (sec): 25.17 - samples/sec: 1455.51 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-15 13:17:00,458 epoch 1 - iter 1042/5212 - loss 0.89883300 - time (sec): 50.18 - samples/sec: 1460.27 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-15 13:17:25,878 epoch 1 - iter 1563/5212 - loss 0.67555628 - time (sec): 75.60 - samples/sec: 1488.02 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-15 13:17:50,812 epoch 1 - iter 2084/5212 - loss 0.57238927 - time (sec): 100.54 - samples/sec: 1477.04 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-15 13:18:16,704 epoch 1 - iter 2605/5212 - loss 0.49502228 - time (sec): 126.43 - samples/sec: 1492.43 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-15 13:18:42,337 epoch 1 - iter 3126/5212 - loss 0.45192361 - time (sec): 152.06 - samples/sec: 1483.23 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-15 13:19:08,050 epoch 1 - iter 3647/5212 - loss 0.42525465 - time (sec): 177.78 - samples/sec: 1458.09 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-15 13:19:37,108 epoch 1 - iter 4168/5212 - loss 0.40135861 - time (sec): 206.83 - samples/sec: 1438.06 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-15 13:20:03,562 epoch 1 - iter 4689/5212 - loss 0.38395729 - time (sec): 233.29 - samples/sec: 1429.03 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-15 13:20:30,449 epoch 1 - iter 5210/5212 - loss 0.37262070 - time (sec): 260.17 - samples/sec: 1411.90 - lr: 0.000050 - momentum: 0.000000 | |
| 2023-10-15 13:20:30,541 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:20:30,542 EPOCH 1 done: loss 0.3725 - lr: 0.000050 | |
| 2023-10-15 13:20:36,434 DEV : loss 0.11529939621686935 - f1-score (micro avg) 0.2459 | |
| 2023-10-15 13:20:36,460 saving best model | |
| 2023-10-15 13:20:36,927 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:21:02,702 epoch 2 - iter 521/5212 - loss 0.19455856 - time (sec): 25.77 - samples/sec: 1478.33 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-15 13:21:28,495 epoch 2 - iter 1042/5212 - loss 0.20837326 - time (sec): 51.57 - samples/sec: 1394.34 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-15 13:21:56,301 epoch 2 - iter 1563/5212 - loss 0.19711389 - time (sec): 79.37 - samples/sec: 1372.97 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-15 13:22:22,909 epoch 2 - iter 2084/5212 - loss 0.19827196 - time (sec): 105.98 - samples/sec: 1387.68 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-15 13:22:50,780 epoch 2 - iter 2605/5212 - loss 0.19554159 - time (sec): 133.85 - samples/sec: 1376.38 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-15 13:23:16,034 epoch 2 - iter 3126/5212 - loss 0.19262159 - time (sec): 159.10 - samples/sec: 1367.76 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-15 13:23:41,047 epoch 2 - iter 3647/5212 - loss 0.19419779 - time (sec): 184.12 - samples/sec: 1389.83 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-15 13:24:06,335 epoch 2 - iter 4168/5212 - loss 0.19161465 - time (sec): 209.41 - samples/sec: 1401.90 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-15 13:24:34,437 epoch 2 - iter 4689/5212 - loss 0.19121284 - time (sec): 237.51 - samples/sec: 1404.82 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-15 13:25:02,829 epoch 2 - iter 5210/5212 - loss 0.19317263 - time (sec): 265.90 - samples/sec: 1381.36 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-15 13:25:02,932 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:25:02,932 EPOCH 2 done: loss 0.1931 - lr: 0.000044 | |
| 2023-10-15 13:25:12,816 DEV : loss 0.17544493079185486 - f1-score (micro avg) 0.3654 | |
| 2023-10-15 13:25:12,852 saving best model | |
| 2023-10-15 13:25:13,376 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:25:39,265 epoch 3 - iter 521/5212 - loss 0.15145173 - time (sec): 25.88 - samples/sec: 1458.63 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-15 13:26:04,335 epoch 3 - iter 1042/5212 - loss 0.15678187 - time (sec): 50.95 - samples/sec: 1438.61 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-15 13:26:30,991 epoch 3 - iter 1563/5212 - loss 0.15448299 - time (sec): 77.61 - samples/sec: 1389.38 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-15 13:26:56,639 epoch 3 - iter 2084/5212 - loss 0.15527194 - time (sec): 103.26 - samples/sec: 1392.24 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-15 13:27:25,339 epoch 3 - iter 2605/5212 - loss 0.15240117 - time (sec): 131.96 - samples/sec: 1368.28 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-15 13:27:54,043 epoch 3 - iter 3126/5212 - loss 0.14898541 - time (sec): 160.66 - samples/sec: 1356.81 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-15 13:28:19,990 epoch 3 - iter 3647/5212 - loss 0.14601801 - time (sec): 186.61 - samples/sec: 1379.17 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-15 13:28:47,027 epoch 3 - iter 4168/5212 - loss 0.14444689 - time (sec): 213.65 - samples/sec: 1371.63 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-15 13:29:14,124 epoch 3 - iter 4689/5212 - loss 0.14484556 - time (sec): 240.74 - samples/sec: 1374.81 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-15 13:29:40,292 epoch 3 - iter 5210/5212 - loss 0.14315344 - time (sec): 266.91 - samples/sec: 1376.40 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-15 13:29:40,389 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:29:40,389 EPOCH 3 done: loss 0.1431 - lr: 0.000039 | |
| 2023-10-15 13:29:49,797 DEV : loss 0.23793098330497742 - f1-score (micro avg) 0.3084 | |
| 2023-10-15 13:29:49,824 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:30:14,394 epoch 4 - iter 521/5212 - loss 0.11205687 - time (sec): 24.57 - samples/sec: 1434.64 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-15 13:30:39,652 epoch 4 - iter 1042/5212 - loss 0.10513806 - time (sec): 49.83 - samples/sec: 1419.82 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-15 13:31:05,128 epoch 4 - iter 1563/5212 - loss 0.11011535 - time (sec): 75.30 - samples/sec: 1448.52 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-15 13:31:30,130 epoch 4 - iter 2084/5212 - loss 0.11135520 - time (sec): 100.31 - samples/sec: 1455.61 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-15 13:31:54,730 epoch 4 - iter 2605/5212 - loss 0.11031903 - time (sec): 124.91 - samples/sec: 1449.83 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-15 13:32:19,870 epoch 4 - iter 3126/5212 - loss 0.10935951 - time (sec): 150.05 - samples/sec: 1461.11 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-15 13:32:44,907 epoch 4 - iter 3647/5212 - loss 0.10865845 - time (sec): 175.08 - samples/sec: 1459.09 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-15 13:33:10,118 epoch 4 - iter 4168/5212 - loss 0.10703262 - time (sec): 200.29 - samples/sec: 1465.07 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-15 13:33:35,323 epoch 4 - iter 4689/5212 - loss 0.10572271 - time (sec): 225.50 - samples/sec: 1457.14 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-15 13:34:01,141 epoch 4 - iter 5210/5212 - loss 0.10526184 - time (sec): 251.32 - samples/sec: 1461.60 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-15 13:34:01,232 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:34:01,233 EPOCH 4 done: loss 0.1053 - lr: 0.000033 | |
| 2023-10-15 13:34:09,661 DEV : loss 0.23926250636577606 - f1-score (micro avg) 0.2991 | |
| 2023-10-15 13:34:09,704 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:34:36,513 epoch 5 - iter 521/5212 - loss 0.08552624 - time (sec): 26.81 - samples/sec: 1340.65 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-15 13:35:01,593 epoch 5 - iter 1042/5212 - loss 0.07856810 - time (sec): 51.89 - samples/sec: 1363.29 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-15 13:35:26,794 epoch 5 - iter 1563/5212 - loss 0.08133709 - time (sec): 77.09 - samples/sec: 1389.39 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-15 13:35:52,056 epoch 5 - iter 2084/5212 - loss 0.08333790 - time (sec): 102.35 - samples/sec: 1406.19 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-15 13:36:17,357 epoch 5 - iter 2605/5212 - loss 0.08277969 - time (sec): 127.65 - samples/sec: 1409.26 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-15 13:36:43,034 epoch 5 - iter 3126/5212 - loss 0.08273593 - time (sec): 153.33 - samples/sec: 1420.12 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-15 13:37:08,780 epoch 5 - iter 3647/5212 - loss 0.08084529 - time (sec): 179.07 - samples/sec: 1425.88 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-15 13:37:34,843 epoch 5 - iter 4168/5212 - loss 0.08016018 - time (sec): 205.14 - samples/sec: 1436.62 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-15 13:38:00,799 epoch 5 - iter 4689/5212 - loss 0.07996177 - time (sec): 231.09 - samples/sec: 1442.23 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-15 13:38:25,393 epoch 5 - iter 5210/5212 - loss 0.08003152 - time (sec): 255.69 - samples/sec: 1436.83 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-15 13:38:25,484 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:38:25,484 EPOCH 5 done: loss 0.0800 - lr: 0.000028 | |
| 2023-10-15 13:38:33,739 DEV : loss 0.3471781313419342 - f1-score (micro avg) 0.3072 | |
| 2023-10-15 13:38:33,768 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:38:59,130 epoch 6 - iter 521/5212 - loss 0.04893610 - time (sec): 25.36 - samples/sec: 1550.29 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-15 13:39:24,147 epoch 6 - iter 1042/5212 - loss 0.05092956 - time (sec): 50.38 - samples/sec: 1516.20 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-15 13:39:50,524 epoch 6 - iter 1563/5212 - loss 0.05455800 - time (sec): 76.76 - samples/sec: 1509.47 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-15 13:40:16,811 epoch 6 - iter 2084/5212 - loss 0.05559083 - time (sec): 103.04 - samples/sec: 1460.28 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-15 13:40:41,525 epoch 6 - iter 2605/5212 - loss 0.05732132 - time (sec): 127.76 - samples/sec: 1434.33 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-15 13:41:07,304 epoch 6 - iter 3126/5212 - loss 0.05727400 - time (sec): 153.54 - samples/sec: 1440.88 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-15 13:41:32,019 epoch 6 - iter 3647/5212 - loss 0.05654496 - time (sec): 178.25 - samples/sec: 1428.82 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-15 13:41:57,953 epoch 6 - iter 4168/5212 - loss 0.05631661 - time (sec): 204.18 - samples/sec: 1442.93 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-15 13:42:23,594 epoch 6 - iter 4689/5212 - loss 0.05593561 - time (sec): 229.82 - samples/sec: 1445.76 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-15 13:42:48,376 epoch 6 - iter 5210/5212 - loss 0.05663169 - time (sec): 254.61 - samples/sec: 1442.84 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-15 13:42:48,471 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:42:48,471 EPOCH 6 done: loss 0.0566 - lr: 0.000022 | |
| 2023-10-15 13:42:56,767 DEV : loss 0.3654634654521942 - f1-score (micro avg) 0.3514 | |
| 2023-10-15 13:42:56,796 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:43:21,792 epoch 7 - iter 521/5212 - loss 0.03312481 - time (sec): 25.00 - samples/sec: 1410.93 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-15 13:43:47,410 epoch 7 - iter 1042/5212 - loss 0.03774246 - time (sec): 50.61 - samples/sec: 1425.50 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-15 13:44:12,732 epoch 7 - iter 1563/5212 - loss 0.04380652 - time (sec): 75.94 - samples/sec: 1443.44 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-15 13:44:37,716 epoch 7 - iter 2084/5212 - loss 0.04357735 - time (sec): 100.92 - samples/sec: 1453.08 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-15 13:45:02,712 epoch 7 - iter 2605/5212 - loss 0.04260736 - time (sec): 125.92 - samples/sec: 1453.59 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-15 13:45:27,992 epoch 7 - iter 3126/5212 - loss 0.04472481 - time (sec): 151.20 - samples/sec: 1454.29 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-15 13:45:54,498 epoch 7 - iter 3647/5212 - loss 0.04429013 - time (sec): 177.70 - samples/sec: 1454.84 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-15 13:46:19,450 epoch 7 - iter 4168/5212 - loss 0.04403234 - time (sec): 202.65 - samples/sec: 1452.76 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-15 13:46:44,374 epoch 7 - iter 4689/5212 - loss 0.04448230 - time (sec): 227.58 - samples/sec: 1451.83 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-15 13:47:09,346 epoch 7 - iter 5210/5212 - loss 0.04403781 - time (sec): 252.55 - samples/sec: 1453.77 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-15 13:47:09,455 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:47:09,455 EPOCH 7 done: loss 0.0440 - lr: 0.000017 | |
| 2023-10-15 13:47:17,889 DEV : loss 0.34585681557655334 - f1-score (micro avg) 0.3311 | |
| 2023-10-15 13:47:17,919 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:47:43,267 epoch 8 - iter 521/5212 - loss 0.02689241 - time (sec): 25.35 - samples/sec: 1476.10 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-15 13:48:08,186 epoch 8 - iter 1042/5212 - loss 0.02653419 - time (sec): 50.27 - samples/sec: 1445.14 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-15 13:48:33,822 epoch 8 - iter 1563/5212 - loss 0.02637713 - time (sec): 75.90 - samples/sec: 1441.02 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-15 13:48:59,594 epoch 8 - iter 2084/5212 - loss 0.02733328 - time (sec): 101.67 - samples/sec: 1424.32 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-15 13:49:24,714 epoch 8 - iter 2605/5212 - loss 0.02880069 - time (sec): 126.79 - samples/sec: 1426.83 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-15 13:49:51,571 epoch 8 - iter 3126/5212 - loss 0.02954909 - time (sec): 153.65 - samples/sec: 1435.69 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-15 13:50:16,561 epoch 8 - iter 3647/5212 - loss 0.03040527 - time (sec): 178.64 - samples/sec: 1444.08 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-15 13:50:41,614 epoch 8 - iter 4168/5212 - loss 0.03036981 - time (sec): 203.69 - samples/sec: 1438.53 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-15 13:51:06,615 epoch 8 - iter 4689/5212 - loss 0.02995803 - time (sec): 228.69 - samples/sec: 1442.97 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-15 13:51:33,708 epoch 8 - iter 5210/5212 - loss 0.03001161 - time (sec): 255.79 - samples/sec: 1435.88 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-15 13:51:33,815 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:51:33,816 EPOCH 8 done: loss 0.0300 - lr: 0.000011 | |
| 2023-10-15 13:51:42,835 DEV : loss 0.43034762144088745 - f1-score (micro avg) 0.3493 | |
| 2023-10-15 13:51:42,865 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:52:08,590 epoch 9 - iter 521/5212 - loss 0.02763096 - time (sec): 25.72 - samples/sec: 1534.61 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-15 13:52:33,552 epoch 9 - iter 1042/5212 - loss 0.02207242 - time (sec): 50.69 - samples/sec: 1519.59 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-15 13:52:58,597 epoch 9 - iter 1563/5212 - loss 0.02236283 - time (sec): 75.73 - samples/sec: 1460.68 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-15 13:53:23,759 epoch 9 - iter 2084/5212 - loss 0.02177159 - time (sec): 100.89 - samples/sec: 1469.42 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-15 13:53:49,224 epoch 9 - iter 2605/5212 - loss 0.02114199 - time (sec): 126.36 - samples/sec: 1462.95 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-15 13:54:14,015 epoch 9 - iter 3126/5212 - loss 0.02090215 - time (sec): 151.15 - samples/sec: 1458.83 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-15 13:54:39,333 epoch 9 - iter 3647/5212 - loss 0.02100536 - time (sec): 176.47 - samples/sec: 1454.71 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-15 13:55:04,484 epoch 9 - iter 4168/5212 - loss 0.02104071 - time (sec): 201.62 - samples/sec: 1453.99 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-15 13:55:30,243 epoch 9 - iter 4689/5212 - loss 0.02069058 - time (sec): 227.38 - samples/sec: 1439.28 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-15 13:55:56,291 epoch 9 - iter 5210/5212 - loss 0.02049929 - time (sec): 253.42 - samples/sec: 1449.41 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-15 13:55:56,382 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:55:56,383 EPOCH 9 done: loss 0.0205 - lr: 0.000006 | |
| 2023-10-15 13:56:05,381 DEV : loss 0.5122669339179993 - f1-score (micro avg) 0.3381 | |
| 2023-10-15 13:56:05,407 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 13:56:30,432 epoch 10 - iter 521/5212 - loss 0.01178875 - time (sec): 25.02 - samples/sec: 1530.92 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-15 13:56:55,856 epoch 10 - iter 1042/5212 - loss 0.01468480 - time (sec): 50.45 - samples/sec: 1507.44 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-15 13:57:21,319 epoch 10 - iter 1563/5212 - loss 0.01459527 - time (sec): 75.91 - samples/sec: 1516.01 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-15 13:57:46,537 epoch 10 - iter 2084/5212 - loss 0.01485247 - time (sec): 101.13 - samples/sec: 1506.02 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-15 13:58:11,468 epoch 10 - iter 2605/5212 - loss 0.01444242 - time (sec): 126.06 - samples/sec: 1494.49 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-15 13:58:36,105 epoch 10 - iter 3126/5212 - loss 0.01442687 - time (sec): 150.70 - samples/sec: 1471.55 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-15 13:59:01,128 epoch 10 - iter 3647/5212 - loss 0.01393897 - time (sec): 175.72 - samples/sec: 1466.96 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-15 13:59:26,149 epoch 10 - iter 4168/5212 - loss 0.01439542 - time (sec): 200.74 - samples/sec: 1466.86 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-15 13:59:51,374 epoch 10 - iter 4689/5212 - loss 0.01427652 - time (sec): 225.97 - samples/sec: 1470.47 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-15 14:00:15,042 epoch 10 - iter 5210/5212 - loss 0.01384805 - time (sec): 249.63 - samples/sec: 1471.63 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-15 14:00:15,126 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:00:15,126 EPOCH 10 done: loss 0.0138 - lr: 0.000000 | |
| 2023-10-15 14:00:24,139 DEV : loss 0.46498292684555054 - f1-score (micro avg) 0.3499 | |
| 2023-10-15 14:00:24,544 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:00:24,545 Loading model from best epoch ... | |
| 2023-10-15 14:00:26,145 SequenceTagger predicts: Dictionary with 17 tags: O, S-LOC, B-LOC, E-LOC, I-LOC, S-PER, B-PER, E-PER, I-PER, S-ORG, B-ORG, E-ORG, I-ORG, S-HumanProd, B-HumanProd, E-HumanProd, I-HumanProd | |
| 2023-10-15 14:00:42,346 | |
| Results: | |
| - F-score (micro) 0.2834 | |
| - F-score (macro) 0.1787 | |
| - Accuracy 0.166 | |
| By class: | |
| precision recall f1-score support | |
| LOC 0.3432 0.3534 0.3482 1214 | |
| PER 0.3094 0.2030 0.2451 808 | |
| ORG 0.1345 0.1105 0.1213 353 | |
| HumanProd 0.0000 0.0000 0.0000 15 | |
| micro avg 0.3053 0.2644 0.2834 2390 | |
| macro avg 0.1968 0.1667 0.1787 2390 | |
| weighted avg 0.2988 0.2644 0.2777 2390 | |
| 2023-10-15 14:00:42,346 ---------------------------------------------------------------------------------------------------- | |