| --- |
| license: apache-2.0 |
| base_model: KpRT/task-t1 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: task-t2 |
| 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. --> |
|
|
| # task-t2 |
|
|
| This model is a fine-tuned version of [KpRT/task-t1](https://huggingface.co/KpRT/task-t1) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3666 |
| - F1: 0.7591 |
| - Chronic Disease F1: 0.7643 |
| - Chronic Disease Num: 2090 |
| - Cancer F1: 0.6815 |
| - Cancer Num: 896 |
| - Allergy F1: 0.7304 |
| - Allergy Num: 200 |
| - Treatment F1: 0.7803 |
| - Treatment Num: 3185 |
| - Other F1: 0 |
| - Other Num: 0 |
|
|
| ## 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: 2e-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: 2 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | F1 | Chronic Disease F1 | Chronic Disease Num | Cancer F1 | Cancer Num | Allergy F1 | Allergy Num | Treatment F1 | Treatment Num | Other F1 | Other Num | |
| |:-------------:|:------:|:----:|:---------------:|:------:|:------------------:|:-------------------:|:---------:|:----------:|:----------:|:-----------:|:------------:|:-------------:|:--------:|:---------:| |
| | 0.4565 | 0.3049 | 100 | 0.4226 | 0.7177 | 0.7053 | 2090 | 0.6397 | 896 | 0.6633 | 200 | 0.7524 | 3185 | 0 | 0 | |
| | 0.4055 | 0.6098 | 200 | 0.3888 | 0.7396 | 0.7399 | 2090 | 0.6684 | 896 | 0.5989 | 200 | 0.7673 | 3185 | 0 | 0 | |
| | 0.4327 | 0.9146 | 300 | 0.3818 | 0.7441 | 0.7441 | 2090 | 0.6614 | 896 | 0.7506 | 200 | 0.7684 | 3185 | 0 | 0 | |
| | 0.3348 | 1.2195 | 400 | 0.3783 | 0.7518 | 0.7459 | 2090 | 0.6825 | 896 | 0.7032 | 200 | 0.7778 | 3185 | 0 | 0 | |
| | 0.3207 | 1.5244 | 500 | 0.3701 | 0.7597 | 0.7619 | 2090 | 0.6830 | 896 | 0.7457 | 200 | 0.7825 | 3185 | 0 | 0 | |
| | 0.3224 | 1.8293 | 600 | 0.3666 | 0.7591 | 0.7643 | 2090 | 0.6815 | 896 | 0.7304 | 200 | 0.7803 | 3185 | 0 | 0 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.42.4 |
| - Pytorch 2.3.1+cu121 |
| - Datasets 2.20.0 |
| - Tokenizers 0.19.1 |
|
|
