thainq107 commited on
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Training complete

Browse files
README.md CHANGED
@@ -18,8 +18,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [d4data/biomedical-ner-all](https://huggingface.co/d4data/biomedical-ner-all) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5565
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- - Accuracy: 0.7909
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  ## Model description
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@@ -42,7 +42,7 @@ The following hyperparameters were used during training:
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
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- - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - num_epochs: 20
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@@ -50,31 +50,31 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 2.641 | 1.0 | 10 | 1.5081 | 0.3577 |
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- | 1.338 | 2.0 | 20 | 0.9042 | 0.6165 |
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- | 0.877 | 3.0 | 30 | 0.6942 | 0.7081 |
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- | 0.6363 | 4.0 | 40 | 0.5950 | 0.7520 |
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- | 0.4868 | 5.0 | 50 | 0.5515 | 0.7573 |
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- | 0.3798 | 6.0 | 60 | 0.5296 | 0.7688 |
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- | 0.3047 | 7.0 | 70 | 0.5217 | 0.7825 |
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- | 0.2521 | 8.0 | 80 | 0.5290 | 0.7788 |
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- | 0.2123 | 9.0 | 90 | 0.5283 | 0.7852 |
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- | 0.1819 | 10.0 | 100 | 0.5309 | 0.7880 |
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- | 0.1585 | 11.0 | 110 | 0.5345 | 0.7835 |
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- | 0.1388 | 12.0 | 120 | 0.5430 | 0.7823 |
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- | 0.1235 | 13.0 | 130 | 0.5350 | 0.7871 |
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- | 0.1128 | 14.0 | 140 | 0.5406 | 0.7882 |
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- | 0.1036 | 15.0 | 150 | 0.5561 | 0.7873 |
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- | 0.0985 | 16.0 | 160 | 0.5603 | 0.7887 |
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- | 0.0924 | 17.0 | 170 | 0.5559 | 0.7894 |
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- | 0.0883 | 18.0 | 180 | 0.5575 | 0.7909 |
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- | 0.0832 | 19.0 | 190 | 0.5545 | 0.7910 |
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- | 0.0843 | 20.0 | 200 | 0.5565 | 0.7909 |
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  ### Framework versions
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  - Transformers 4.47.1
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- - Pytorch 2.5.1+cu124
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  - Datasets 3.2.0
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  - Tokenizers 0.21.0
 
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19
  This model is a fine-tuned version of [d4data/biomedical-ner-all](https://huggingface.co/d4data/biomedical-ner-all) on an unknown dataset.
20
  It achieves the following results on the evaluation set:
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+ - Loss: 0.6342
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+ - Accuracy: 0.7903
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  ## Model description
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42
  - train_batch_size: 16
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  - eval_batch_size: 16
44
  - seed: 42
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+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - num_epochs: 20
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 2.5437 | 1.0 | 10 | 1.6009 | 0.3671 |
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+ | 1.3262 | 2.0 | 20 | 0.9660 | 0.6254 |
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+ | 0.8675 | 3.0 | 30 | 0.7436 | 0.7145 |
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+ | 0.6199 | 4.0 | 40 | 0.6544 | 0.7385 |
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+ | 0.4707 | 5.0 | 50 | 0.6131 | 0.7660 |
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+ | 0.3735 | 6.0 | 60 | 0.6027 | 0.7709 |
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+ | 0.3049 | 7.0 | 70 | 0.6056 | 0.7786 |
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+ | 0.2507 | 8.0 | 80 | 0.5992 | 0.7792 |
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+ | 0.2144 | 9.0 | 90 | 0.6115 | 0.7780 |
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+ | 0.1801 | 10.0 | 100 | 0.6062 | 0.7863 |
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+ | 0.1539 | 11.0 | 110 | 0.6101 | 0.7854 |
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+ | 0.1372 | 12.0 | 120 | 0.6157 | 0.7892 |
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+ | 0.1234 | 13.0 | 130 | 0.6269 | 0.7896 |
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+ | 0.1119 | 14.0 | 140 | 0.6285 | 0.7881 |
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+ | 0.1025 | 15.0 | 150 | 0.6364 | 0.7879 |
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+ | 0.0945 | 16.0 | 160 | 0.6326 | 0.7896 |
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+ | 0.09 | 17.0 | 170 | 0.6297 | 0.7916 |
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+ | 0.0861 | 18.0 | 180 | 0.6318 | 0.7908 |
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+ | 0.083 | 19.0 | 190 | 0.6317 | 0.7901 |
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+ | 0.0817 | 20.0 | 200 | 0.6342 | 0.7903 |
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  ### Framework versions
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  - Transformers 4.47.1
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+ - Pytorch 2.5.1+cu121
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  - Datasets 3.2.0
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  - Tokenizers 0.21.0
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