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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: bert-finetuned-ner |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# bert-finetuned-ner |
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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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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 100 |
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### Training results |
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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 |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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