readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - wl
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: spanish-clinical-ner
    results:
    - task:
        name: Token Classification
        type: token-classification
      dataset:
        name: wl
        type: wl
        config: WL
        split: train
        args: WL
      metrics:
      - name: Precision
        type: precision
        value: 0.6868542362104594
      - name: Recall
        type: recall
        value: 0.7348639455782313
      - name: F1
        type: f1
        value: 0.7100484758853013
      - name: Accuracy
        type: accuracy
        value: 0.8262735659847573
  ---
  
  <!-- 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. -->
  
  # spanish-clinical-ner
  
  This model is a fine-tuned version of [plncmm/roberta-clinical-wl-es](https://huggingface.co/plncmm/roberta-clinical-wl-es) on the wl dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6181
  - Precision: 0.6869
  - Recall: 0.7349
  - F1: 0.7100
  - Accuracy: 0.8263
  
  ## 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: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 1.0283        | 1.0   | 500  | 0.6862          | 0.6690    | 0.6959 | 0.6822 | 0.8091   |
  | 0.599         | 2.0   | 1000 | 0.6198          | 0.6856    | 0.7276 | 0.7059 | 0.8252   |
  | 0.4973        | 3.0   | 1500 | 0.6181          | 0.6869    | 0.7349 | 0.7100 | 0.8263   |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.2
  