| --- |
| license: apache-2.0 |
| base_model: bert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: task-t1 |
| 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-t1 |
|
|
| This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4146 |
| - F1: 0.7293 |
| - Chronic Disease F1: 0.7306 |
| - Chronic Disease Num: 2537 |
| - Cancer F1: 0.7151 |
| - Cancer Num: 880 |
| - Allergy F1: 0.6551 |
| - Allergy Num: 219 |
| - Treatment F1: 0.7365 |
| - Treatment Num: 3197 |
| - 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 | |
| |:-------------:|:------:|:----:|:---------------:|:------:|:------------------:|:-------------------:|:---------:|:----------:|:----------:|:-----------:|:------------:|:-------------:|:--------:|:---------:| |
| | 1.0109 | 0.2717 | 100 | 0.6744 | 0.4452 | 0.4017 | 2537 | 0.0448 | 880 | 0.0 | 219 | 0.5504 | 3197 | 0 | 0 | |
| | 0.5833 | 0.5435 | 200 | 0.4954 | 0.6268 | 0.6392 | 2537 | 0.5937 | 880 | 0.0 | 219 | 0.6459 | 3197 | 0 | 0 | |
| | 0.4668 | 0.8152 | 300 | 0.4519 | 0.6782 | 0.6951 | 2537 | 0.6396 | 880 | 0.0359 | 219 | 0.6962 | 3197 | 0 | 0 | |
| | 0.4275 | 1.0870 | 400 | 0.4314 | 0.7046 | 0.7102 | 2537 | 0.6883 | 880 | 0.5127 | 219 | 0.7138 | 3197 | 0 | 0 | |
| | 0.3483 | 1.3587 | 500 | 0.4282 | 0.7181 | 0.7212 | 2537 | 0.7078 | 880 | 0.6469 | 219 | 0.7226 | 3197 | 0 | 0 | |
| | 0.3334 | 1.6304 | 600 | 0.4126 | 0.7293 | 0.7313 | 2537 | 0.7170 | 880 | 0.6683 | 219 | 0.7349 | 3197 | 0 | 0 | |
| | 0.3249 | 1.9022 | 700 | 0.4146 | 0.7293 | 0.7306 | 2537 | 0.7151 | 880 | 0.6551 | 219 | 0.7365 | 3197 | 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 |
|
|
