readme: ---
  license: cc-by-4.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: NLP-CIC-WFU_Clinical_Cases_NER_Sents_Tokenized_bertin_roberta_base_spanish_fine_tuned
    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. -->
  
  # NLP-CIC-WFU_Clinical_Cases_NER_Sents_Tokenized_bertin_roberta_base_spanish_fine_tuned
  
  This model is a fine-tuned version of [bertin-project/bertin-roberta-base-spanish](https://huggingface.co/bertin-project/bertin-roberta-base-spanish) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0973
  - Precision: 0.9012
  - Recall: 0.6942
  - F1: 0.7842
  - Accuracy: 0.9857
  
  ## 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: 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: 7
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.0605        | 1.0   | 2568  | 0.0625          | 0.9400    | 0.6322 | 0.7560 | 0.9836   |
  | 0.0475        | 2.0   | 5136  | 0.0622          | 0.9533    | 0.6572 | 0.7781 | 0.9849   |
  | 0.0374        | 3.0   | 7704  | 0.0552          | 0.9261    | 0.6784 | 0.7831 | 0.9855   |
  | 0.0246        | 4.0   | 10272 | 0.0693          | 0.9381    | 0.6658 | 0.7788 | 0.9849   |
  | 0.0126        | 5.0   | 12840 | 0.0974          | 0.8918    | 0.6830 | 0.7735 | 0.9849   |
  | 0.0061        | 6.0   | 15408 | 0.0886          | 0.8771    | 0.7099 | 0.7847 | 0.9850   |
  | 0.0031        | 7.0   | 17976 | 0.0973          | 0.9012    | 0.6942 | 0.7842 | 0.9857   |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  