readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: NER_ehealth_Spanish_mBERT_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. -->
  
  # NER_ehealth_Spanish_mBERT_fine_tuned
  
  This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6563
  - Precision: 0.8094
  - Recall: 0.8330
  - F1: 0.8210
  - Accuracy: 0.9051
  
  ## 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: 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: 12
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 100  | 0.5335          | 0.8018    | 0.8307 | 0.8160 | 0.9047   |
  | No log        | 2.0   | 200  | 0.5034          | 0.8110    | 0.8253 | 0.8181 | 0.9067   |
  | No log        | 3.0   | 300  | 0.5632          | 0.7932    | 0.8230 | 0.8078 | 0.9038   |
  | No log        | 4.0   | 400  | 0.5904          | 0.8004    | 0.8299 | 0.8149 | 0.9027   |
  | 0.017         | 5.0   | 500  | 0.5958          | 0.7993    | 0.8330 | 0.8158 | 0.9071   |
  | 0.017         | 6.0   | 600  | 0.6168          | 0.7980    | 0.8352 | 0.8162 | 0.9022   |
  | 0.017         | 7.0   | 700  | 0.6219          | 0.8079    | 0.8314 | 0.8195 | 0.9062   |
  | 0.017         | 8.0   | 800  | 0.6441          | 0.8046    | 0.8299 | 0.8171 | 0.9038   |
  | 0.017         | 9.0   | 900  | 0.6338          | 0.8086    | 0.8253 | 0.8168 | 0.9051   |
  | 0.0066        | 10.0  | 1000 | 0.6482          | 0.8021    | 0.8261 | 0.8139 | 0.9029   |
  | 0.0066        | 11.0  | 1100 | 0.6578          | 0.8039    | 0.8291 | 0.8163 | 0.9038   |
  | 0.0066        | 12.0  | 1200 | 0.6563          | 0.8094    | 0.8330 | 0.8210 | 0.9051   |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  