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--- |
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license: apache-2.0 |
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base_model: PlanTL-GOB-ES/bsc-bio-ehr-es |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: vih_explainability3 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# vih_explainability3 |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3951 |
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- Roc Auc: 0.8213 |
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- Ap Score: 0.7049 |
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- Precision: 0.9836 |
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- Recall: 0.6452 |
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- F1: 0.7792 |
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## 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: |
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- learning_rate: 1e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Roc Auc | Ap Score | Precision | Recall | F1 | |
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|:-------------:|:------:|:----:|:---------------:|:-------:|:--------:|:---------:|:------:|:------:| |
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| 0.4261 | 0.8475 | 100 | 0.3832 | 0.6129 | 0.3793 | 1.0 | 0.2258 | 0.3684 | |
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| 0.2405 | 1.6949 | 200 | 0.4736 | 0.6344 | 0.4138 | 1.0 | 0.2688 | 0.4237 | |
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| 0.2088 | 2.5424 | 300 | 0.3452 | 0.7729 | 0.6274 | 0.9808 | 0.5484 | 0.7034 | |
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| 0.2196 | 3.3898 | 400 | 0.3644 | 0.7151 | 0.5431 | 1.0 | 0.4301 | 0.6015 | |
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| 0.2068 | 4.2373 | 500 | 0.5156 | 0.6344 | 0.4138 | 1.0 | 0.2688 | 0.4237 | |
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| 0.1374 | 5.0847 | 600 | 0.3988 | 0.7944 | 0.6619 | 0.9821 | 0.5914 | 0.7383 | |
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| 0.1098 | 5.9322 | 700 | 0.3629 | 0.8051 | 0.6791 | 0.9828 | 0.6129 | 0.7550 | |
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| 0.0914 | 6.7797 | 800 | 0.3394 | 0.8240 | 0.6934 | 0.9531 | 0.6559 | 0.7771 | |
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| 0.088 | 7.6271 | 900 | 0.3612 | 0.8334 | 0.7009 | 0.9403 | 0.6774 | 0.7875 | |
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| 0.0787 | 8.4746 | 1000 | 0.3801 | 0.8213 | 0.7049 | 0.9836 | 0.6452 | 0.7792 | |
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| 0.0588 | 9.3220 | 1100 | 0.3951 | 0.8213 | 0.7049 | 0.9836 | 0.6452 | 0.7792 | |
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### Framework versions |
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- Transformers 4.41.0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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