readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - cantemist-ner
  metrics:
  - f1
  model-index:
  - name: biomedical-roberta-finetuned-cantemist-test
    results:
    - task:
        name: Token Classification
        type: token-classification
      dataset:
        name: cantemist-ner
        type: cantemist-ner
        config: CantemistNer
        split: train
        args: CantemistNer
      metrics:
      - name: F1
        type: f1
        value: 0.8379235519946587
  ---
  
  <!-- 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. -->
  
  # biomedical-roberta-finetuned-cantemist-test
  
  This model is a fine-tuned version of [PlanTL-GOB-ES/bsc-bio-ehr-es-cantemist](https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es-cantemist) on the cantemist-ner dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0597
  - F1: 0.8379
  
  ## 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: 5e-05
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 1
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.0015        | 1.0   | 607  | 0.0597          | 0.8379 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  