| --- |
| license: apache-2.0 |
| base_model: KpRT/task-t2 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: task-t3 |
| 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-t3 |
|
|
| This model is a fine-tuned version of [KpRT/task-t2](https://huggingface.co/KpRT/task-t2) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3985 |
| - F1: 0.7669 |
| - Chronic Disease F1: 0.7755 |
| - Chronic Disease Num: 2507 |
| - Cancer F1: 0.7152 |
| - Cancer Num: 753 |
| - Allergy F1: 0.7833 |
| - Allergy Num: 271 |
| - Treatment F1: 0.7715 |
| - Treatment Num: 2963 |
| - 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 | |
| |:-------------:|:------:|:----:|:---------------:|:------:|:------------------:|:-------------------:|:---------:|:----------:|:----------:|:-----------:|:------------:|:-------------:|:--------:|:---------:| |
| | 0.236 | 0.3135 | 100 | 0.4006 | 0.7553 | 0.7577 | 2507 | 0.7027 | 753 | 0.7767 | 271 | 0.7650 | 2963 | 0 | 0 | |
| | 0.2141 | 0.6270 | 200 | 0.4293 | 0.7513 | 0.7662 | 2507 | 0.6703 | 753 | 0.7850 | 271 | 0.7577 | 2963 | 0 | 0 | |
| | 0.2483 | 0.9404 | 300 | 0.4024 | 0.7628 | 0.7710 | 2507 | 0.6994 | 753 | 0.7765 | 271 | 0.7712 | 2963 | 0 | 0 | |
| | 0.19 | 1.2539 | 400 | 0.4005 | 0.7666 | 0.7764 | 2507 | 0.7010 | 753 | 0.8069 | 271 | 0.7720 | 2963 | 0 | 0 | |
| | 0.1997 | 1.5674 | 500 | 0.3986 | 0.7698 | 0.7786 | 2507 | 0.7137 | 753 | 0.7946 | 271 | 0.7750 | 2963 | 0 | 0 | |
| | 0.2297 | 1.8809 | 600 | 0.3985 | 0.7669 | 0.7755 | 2507 | 0.7152 | 753 | 0.7833 | 271 | 0.7715 | 2963 | 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 |
|
|
