readme: ---
  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
  
  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: 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
  
  | 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           |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  