readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: roberta-base-biomedical-clinical-es-finetuned-ner-Concat_CRAFT_es
    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. -->
  
  # roberta-base-biomedical-clinical-es-finetuned-ner-Concat_CRAFT_es
  
  This model is a fine-tuned version of [PlanTL-GOB-ES/roberta-base-biomedical-clinical-es](https://huggingface.co/PlanTL-GOB-ES/roberta-base-biomedical-clinical-es) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1874
  - Precision: 0.8559
  - Recall: 0.8425
  - F1: 0.8492
  - Accuracy: 0.9696
  
  ## 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: 3e-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 | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.072         | 1.0   | 2719  | 0.1500          | 0.8138    | 0.8224 | 0.8181 | 0.9644   |
  | 0.0305        | 2.0   | 5438  | 0.1555          | 0.8417    | 0.8253 | 0.8334 | 0.9674   |
  | 0.014         | 3.0   | 8157  | 0.1743          | 0.8429    | 0.8412 | 0.8421 | 0.9685   |
  | 0.0076        | 4.0   | 10876 | 0.1874          | 0.8559    | 0.8425 | 0.8492 | 0.9696   |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.0+cu111
  - Datasets 1.18.4
  - Tokenizers 0.11.6
  