readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: Negation_Scope_Detection_SFU_Spanish_NLP-CIC-WFU_DisTEMIST_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. -->
  
  # Negation_Scope_Detection_SFU_Spanish_NLP-CIC-WFU_DisTEMIST_fine_tuned
  
  This model is a fine-tuned version of [ajtamayoh/NER_EHR_Spanish_model_Mulitlingual_BERT](https://huggingface.co/ajtamayoh/NER_EHR_Spanish_model_Mulitlingual_BERT) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3219
  - Precision: 0.7403
  - Recall: 0.7571
  - F1: 0.7486
  - Accuracy: 0.9518
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 72   | 0.2142          | 0.5227    | 0.6497 | 0.5793 | 0.9267   |
  | No log        | 2.0   | 144  | 0.2019          | 0.625     | 0.7062 | 0.6631 | 0.9420   |
  | No log        | 3.0   | 216  | 0.3089          | 0.6444    | 0.6554 | 0.6499 | 0.9432   |
  | No log        | 4.0   | 288  | 0.2376          | 0.6952    | 0.7345 | 0.7143 | 0.9478   |
  | No log        | 5.0   | 360  | 0.2876          | 0.7037    | 0.7514 | 0.7268 | 0.9538   |
  | No log        | 6.0   | 432  | 0.3077          | 0.7278    | 0.7401 | 0.7339 | 0.9534   |
  | 0.091         | 7.0   | 504  | 0.3219          | 0.7403    | 0.7571 | 0.7486 | 0.9518   |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  