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bert-finetuned-ner

Token Classification
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bert
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update model card README.md

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@@ -14,7 +14,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.9029
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  ## Model description
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@@ -45,106 +45,106 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | No log | 1.0 | 71 | 8.8951 |
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- | No log | 2.0 | 142 | 8.8532 |
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- | No log | 3.0 | 213 | 8.7305 |
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- | No log | 4.0 | 284 | 8.5186 |
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- | No log | 5.0 | 355 | 8.3212 |
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- | No log | 6.0 | 426 | 8.1309 |
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- | No log | 7.0 | 497 | 7.9420 |
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- | 8.6328 | 8.0 | 568 | 7.7689 |
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- | 8.6328 | 9.0 | 639 | 7.6050 |
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- | 8.6328 | 10.0 | 710 | 7.4483 |
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- | 8.6328 | 11.0 | 781 | 7.2902 |
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- | 8.6328 | 12.0 | 852 | 7.1421 |
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- | 8.6328 | 13.0 | 923 | 6.9918 |
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- | 8.6328 | 14.0 | 994 | 6.8501 |
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- | 7.5715 | 15.0 | 1065 | 6.7115 |
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- | 7.5715 | 16.0 | 1136 | 6.5774 |
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- | 7.5715 | 17.0 | 1207 | 6.4431 |
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- | 7.5715 | 18.0 | 1278 | 6.3216 |
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- | 7.5715 | 19.0 | 1349 | 6.1973 |
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- | 7.5715 | 20.0 | 1420 | 6.0735 |
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- | 7.5715 | 21.0 | 1491 | 5.9483 |
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- | 6.6466 | 22.0 | 1562 | 5.8385 |
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- | 6.6466 | 23.0 | 1633 | 5.7199 |
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- | 6.6466 | 24.0 | 1704 | 5.6047 |
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- | 6.6466 | 25.0 | 1775 | 5.5008 |
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- | 6.6466 | 26.0 | 1846 | 5.3816 |
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- | 6.6466 | 27.0 | 1917 | 5.2802 |
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- | 6.6466 | 28.0 | 1988 | 5.1727 |
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- | 5.8483 | 29.0 | 2059 | 5.0741 |
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- | 5.8483 | 30.0 | 2130 | 4.9724 |
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- | 5.8483 | 31.0 | 2201 | 4.8772 |
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- | 5.8483 | 32.0 | 2272 | 4.7812 |
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- | 5.8483 | 33.0 | 2343 | 4.6847 |
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- | 5.8483 | 34.0 | 2414 | 4.5938 |
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- | 5.8483 | 35.0 | 2485 | 4.5092 |
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- | 5.1726 | 36.0 | 2556 | 4.4214 |
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- | 5.1726 | 37.0 | 2627 | 4.3330 |
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- | 5.1726 | 38.0 | 2698 | 4.2479 |
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- | 5.1726 | 39.0 | 2769 | 4.1682 |
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- | 5.1726 | 40.0 | 2840 | 4.0822 |
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- | 5.1726 | 41.0 | 2911 | 4.0075 |
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- | 5.1726 | 42.0 | 2982 | 3.9296 |
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- | 4.5503 | 43.0 | 3053 | 3.8511 |
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- | 4.5503 | 44.0 | 3124 | 3.7752 |
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- | 4.5503 | 45.0 | 3195 | 3.7009 |
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- | 4.5503 | 46.0 | 3266 | 3.6335 |
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- | 4.5503 | 47.0 | 3337 | 3.5647 |
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- | 4.5503 | 48.0 | 3408 | 3.4937 |
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- | 4.5503 | 49.0 | 3479 | 3.4242 |
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- | 4.009 | 50.0 | 3550 | 3.3637 |
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- | 4.009 | 51.0 | 3621 | 3.3031 |
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- | 4.009 | 52.0 | 3692 | 3.2395 |
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- | 4.009 | 53.0 | 3763 | 3.1766 |
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- | 4.009 | 54.0 | 3834 | 3.1246 |
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- | 4.009 | 55.0 | 3905 | 3.0673 |
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- | 4.009 | 56.0 | 3976 | 3.0090 |
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- | 3.5477 | 57.0 | 4047 | 2.9559 |
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- | 3.5477 | 58.0 | 4118 | 2.9098 |
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- | 3.5477 | 59.0 | 4189 | 2.8603 |
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- | 3.5477 | 60.0 | 4260 | 2.8132 |
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- | 3.5477 | 61.0 | 4331 | 2.7637 |
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- | 3.5477 | 62.0 | 4402 | 2.7219 |
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- | 3.5477 | 63.0 | 4473 | 2.6734 |
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- | 3.1822 | 64.0 | 4544 | 2.6286 |
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- | 3.1822 | 65.0 | 4615 | 2.5867 |
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- | 3.1822 | 66.0 | 4686 | 2.5491 |
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- | 3.1822 | 67.0 | 4757 | 2.5076 |
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- | 3.1822 | 68.0 | 4828 | 2.4720 |
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- | 3.1822 | 69.0 | 4899 | 2.4349 |
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- | 3.1822 | 70.0 | 4970 | 2.4026 |
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- | 2.8647 | 71.0 | 5041 | 2.3661 |
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- | 2.8647 | 72.0 | 5112 | 2.3343 |
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- | 2.8647 | 73.0 | 5183 | 2.3081 |
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- | 2.8647 | 74.0 | 5254 | 2.2751 |
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- | 2.8647 | 75.0 | 5325 | 2.2461 |
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- | 2.8647 | 76.0 | 5396 | 2.2165 |
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- | 2.8647 | 77.0 | 5467 | 2.1938 |
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- | 2.6306 | 78.0 | 5538 | 2.1681 |
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- | 2.6306 | 79.0 | 5609 | 2.1438 |
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- | 2.6306 | 80.0 | 5680 | 2.1232 |
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- | 2.6306 | 81.0 | 5751 | 2.1022 |
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- | 2.6306 | 82.0 | 5822 | 2.0800 |
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- | 2.6306 | 83.0 | 5893 | 2.0605 |
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- | 2.6306 | 84.0 | 5964 | 2.0427 |
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- | 2.4436 | 85.0 | 6035 | 2.0273 |
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- | 2.4436 | 86.0 | 6106 | 2.0109 |
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- | 2.4436 | 87.0 | 6177 | 1.9975 |
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- | 2.4436 | 88.0 | 6248 | 1.9827 |
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- | 2.4436 | 89.0 | 6319 | 1.9700 |
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- | 2.4436 | 90.0 | 6390 | 1.9584 |
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- | 2.4436 | 91.0 | 6461 | 1.9502 |
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- | 2.3168 | 92.0 | 6532 | 1.9394 |
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- | 2.3168 | 93.0 | 6603 | 1.9307 |
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- | 2.3168 | 94.0 | 6674 | 1.9221 |
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- | 2.3168 | 95.0 | 6745 | 1.9167 |
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- | 2.3168 | 96.0 | 6816 | 1.9122 |
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- | 2.3168 | 97.0 | 6887 | 1.9078 |
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- | 2.3168 | 98.0 | 6958 | 1.9055 |
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- | 2.2563 | 99.0 | 7029 | 1.9039 |
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- | 2.2563 | 100.0 | 7100 | 1.9029 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.9992
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | No log | 1.0 | 67 | 8.8964 |
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+ | No log | 2.0 | 134 | 8.8550 |
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+ | No log | 3.0 | 201 | 8.7423 |
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+ | No log | 4.0 | 268 | 8.5343 |
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+ | No log | 5.0 | 335 | 8.3243 |
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+ | No log | 6.0 | 402 | 8.1392 |
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+ | No log | 7.0 | 469 | 7.9616 |
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+ | 8.6114 | 8.0 | 536 | 7.7924 |
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+ | 8.6114 | 9.0 | 603 | 7.6305 |
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+ | 8.6114 | 10.0 | 670 | 7.4707 |
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+ | 8.6114 | 11.0 | 737 | 7.3065 |
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+ | 8.6114 | 12.0 | 804 | 7.1600 |
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+ | 8.6114 | 13.0 | 871 | 7.0228 |
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+ | 8.6114 | 14.0 | 938 | 6.8804 |
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+ | 7.5409 | 15.0 | 1005 | 6.7334 |
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+ | 7.5409 | 16.0 | 1072 | 6.6021 |
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+ | 7.5409 | 17.0 | 1139 | 6.4789 |
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+ | 7.5409 | 18.0 | 1206 | 6.3473 |
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+ | 7.5409 | 19.0 | 1273 | 6.2252 |
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+ | 7.5409 | 20.0 | 1340 | 6.1058 |
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+ | 7.5409 | 21.0 | 1407 | 5.9892 |
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+ | 7.5409 | 22.0 | 1474 | 5.8674 |
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+ | 6.6051 | 23.0 | 1541 | 5.7496 |
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+ | 6.6051 | 24.0 | 1608 | 5.6393 |
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+ | 6.6051 | 25.0 | 1675 | 5.5244 |
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+ | 6.6051 | 26.0 | 1742 | 5.4279 |
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+ | 6.6051 | 27.0 | 1809 | 5.3221 |
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+ | 6.6051 | 28.0 | 1876 | 5.2126 |
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+ | 6.6051 | 29.0 | 1943 | 5.1221 |
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+ | 5.8003 | 30.0 | 2010 | 5.0178 |
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+ | 5.8003 | 31.0 | 2077 | 4.9183 |
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+ | 5.8003 | 32.0 | 2144 | 4.8303 |
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+ | 5.8003 | 33.0 | 2211 | 4.7328 |
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+ | 5.8003 | 34.0 | 2278 | 4.6467 |
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+ | 5.8003 | 35.0 | 2345 | 4.5548 |
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+ | 5.8003 | 36.0 | 2412 | 4.4697 |
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+ | 5.8003 | 37.0 | 2479 | 4.3860 |
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+ | 5.0905 | 38.0 | 2546 | 4.2980 |
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+ | 5.0905 | 39.0 | 2613 | 4.2172 |
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+ | 5.0905 | 40.0 | 2680 | 4.1351 |
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+ | 5.0905 | 41.0 | 2747 | 4.0635 |
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+ | 5.0905 | 42.0 | 2814 | 3.9834 |
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+ | 5.0905 | 43.0 | 2881 | 3.9091 |
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+ | 5.0905 | 44.0 | 2948 | 3.8376 |
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+ | 4.481 | 45.0 | 3015 | 3.7662 |
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+ | 4.481 | 46.0 | 3082 | 3.7011 |
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+ | 4.481 | 47.0 | 3149 | 3.6335 |
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+ | 4.481 | 48.0 | 3216 | 3.5671 |
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+ | 4.481 | 49.0 | 3283 | 3.5011 |
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+ | 4.481 | 50.0 | 3350 | 3.4388 |
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+ | 4.481 | 51.0 | 3417 | 3.3746 |
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+ | 4.481 | 52.0 | 3484 | 3.3151 |
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+ | 3.9521 | 53.0 | 3551 | 3.2551 |
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+ | 3.9521 | 54.0 | 3618 | 3.1943 |
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+ | 3.9521 | 55.0 | 3685 | 3.1410 |
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+ | 3.9521 | 56.0 | 3752 | 3.0885 |
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+ | 3.9521 | 57.0 | 3819 | 3.0384 |
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+ | 3.9521 | 58.0 | 3886 | 2.9890 |
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+ | 3.9521 | 59.0 | 3953 | 2.9376 |
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+ | 3.5177 | 60.0 | 4020 | 2.8906 |
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+ | 3.5177 | 61.0 | 4087 | 2.8406 |
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+ | 3.5177 | 62.0 | 4154 | 2.7951 |
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+ | 3.5177 | 63.0 | 4221 | 2.7590 |
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+ | 3.5177 | 64.0 | 4288 | 2.7136 |
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+ | 3.5177 | 65.0 | 4355 | 2.6725 |
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+ | 3.5177 | 66.0 | 4422 | 2.6343 |
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+ | 3.5177 | 67.0 | 4489 | 2.5941 |
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+ | 3.1601 | 68.0 | 4556 | 2.5563 |
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+ | 3.1601 | 69.0 | 4623 | 2.5241 |
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+ | 3.1601 | 70.0 | 4690 | 2.4894 |
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+ | 3.1601 | 71.0 | 4757 | 2.4552 |
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+ | 3.1601 | 72.0 | 4824 | 2.4227 |
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+ | 3.1601 | 73.0 | 4891 | 2.3942 |
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+ | 3.1601 | 74.0 | 4958 | 2.3678 |
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+ | 2.8815 | 75.0 | 5025 | 2.3362 |
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+ | 2.8815 | 76.0 | 5092 | 2.3100 |
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+ | 2.8815 | 77.0 | 5159 | 2.2851 |
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+ | 2.8815 | 78.0 | 5226 | 2.2570 |
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+ | 2.8815 | 79.0 | 5293 | 2.2346 |
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+ | 2.8815 | 80.0 | 5360 | 2.2155 |
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+ | 2.8815 | 81.0 | 5427 | 2.1933 |
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+ | 2.8815 | 82.0 | 5494 | 2.1714 |
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+ | 2.6556 | 83.0 | 5561 | 2.1551 |
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+ | 2.6556 | 84.0 | 5628 | 2.1381 |
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+ | 2.6556 | 85.0 | 5695 | 2.1203 |
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+ | 2.6556 | 86.0 | 5762 | 2.1049 |
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+ | 2.6556 | 87.0 | 5829 | 2.0899 |
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+ | 2.6556 | 88.0 | 5896 | 2.0796 |
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+ | 2.6556 | 89.0 | 5963 | 2.0649 |
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+ | 2.5131 | 90.0 | 6030 | 2.0534 |
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+ | 2.5131 | 91.0 | 6097 | 2.0443 |
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+ | 2.5131 | 92.0 | 6164 | 2.0360 |
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+ | 2.5131 | 93.0 | 6231 | 2.0258 |
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+ | 2.5131 | 94.0 | 6298 | 2.0190 |
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+ | 2.5131 | 95.0 | 6365 | 2.0111 |
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+ | 2.5131 | 96.0 | 6432 | 2.0100 |
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+ | 2.5131 | 97.0 | 6499 | 2.0040 |
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+ | 2.4077 | 98.0 | 6566 | 2.0005 |
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+ | 2.4077 | 99.0 | 6633 | 1.9997 |
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+ | 2.4077 | 100.0 | 6700 | 1.9992 |
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  ### Framework versions