| --- |
| base_model: dmis-lab/biobert-base-cased-v1.2 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| - f1 |
| model-index: |
| - name: NHS-dmis-binary |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # NHS-dmis-binary |
|
|
| This model is a fine-tuned version of [dmis-lab/biobert-base-cased-v1.2](https://huggingface.co/dmis-lab/biobert-base-cased-v1.2) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4752 |
| - Accuracy: 0.8158 |
| - Precision: 0.8102 |
| - Recall: 0.8064 |
| - F1: 0.8081 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 3e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 6 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | 0.0543 | 1.0 | 397 | 0.3985 | 0.8240 | 0.8232 | 0.8089 | 0.8141 | |
| | 0.1033 | 2.0 | 794 | 0.4902 | 0.7817 | 0.7913 | 0.7996 | 0.7811 | |
| | 2.162 | 3.0 | 1191 | 0.4752 | 0.8158 | 0.8102 | 0.8064 | 0.8081 | |
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| ### Framework versions |
|
|
| - Transformers 4.38.2 |
| - Pytorch 2.2.1+cu121 |
| - Datasets 2.18.0 |
| - Tokenizers 0.15.2 |
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|
