| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: DISO_bsc_test |
| 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. --> |
|
|
| # DISO_bsc_test |
|
|
| This model is a fine-tuned version of [PlanTL-GOB-ES/bsc-bio-ehr-es](https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0959 |
| - Diso Precision: 0.7766 |
| - Diso Recall: 0.7803 |
| - Diso F1: 0.7784 |
| - Diso Number: 4552 |
| - Overall Precision: 0.7766 |
| - Overall Recall: 0.7803 |
| - Overall F1: 0.7784 |
| - Overall Accuracy: 0.9744 |
|
|
| ## Model description |
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| More information needed |
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|
| ## Intended uses & limitations |
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| More information needed |
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|
| ## Training and evaluation data |
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| More information needed |
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|
| ## Training procedure |
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| ### Training hyperparameters |
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| The following hyperparameters were used during training: |
| - learning_rate: 2e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 4 |
|
|
| ### Training results |
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|
| | Training Loss | Epoch | Step | Validation Loss | Diso Precision | Diso Recall | Diso F1 | Diso Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------------:|:-----------:|:-------:|:-----------:|:-----------------:|:--------------:|:----------:|:----------------:| |
| | 0.0849 | 1.0 | 2799 | 0.0734 | 0.7360 | 0.7676 | 0.7515 | 4552 | 0.7360 | 0.7676 | 0.7515 | 0.9726 | |
| | 0.0572 | 2.0 | 5598 | 0.0736 | 0.7674 | 0.7768 | 0.7721 | 4552 | 0.7674 | 0.7768 | 0.7721 | 0.9743 | |
| | 0.0462 | 3.0 | 8397 | 0.0836 | 0.7737 | 0.7707 | 0.7722 | 4552 | 0.7737 | 0.7707 | 0.7722 | 0.9736 | |
| | 0.0318 | 4.0 | 11196 | 0.0959 | 0.7766 | 0.7803 | 0.7784 | 4552 | 0.7766 | 0.7803 | 0.7784 | 0.9744 | |
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| ### Framework versions |
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|
| - Transformers 4.25.1 |
| - Pytorch 1.13.0+cu116 |
| - Datasets 2.8.0 |
| - Tokenizers 0.13.2 |
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|
