readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - conll2002
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: bert-base-spanish-wwm-cased-finetuned-ner-false
    results:
    - task:
        name: Token Classification
        type: token-classification
      dataset:
        name: conll2002
        type: conll2002
        args: es
      metrics:
      - name: Precision
        type: precision
        value: 0.8527941844616084
      - name: Recall
        type: recall
        value: 0.8625919117647058
      - name: F1
        type: f1
        value: 0.8576650673977612
      - name: Accuracy
        type: accuracy
        value: 0.9780246773614496
  ---
  
  <!-- 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. -->
  
  # bert-base-spanish-wwm-cased-finetuned-ner-false
  
  This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-cased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased) on the conll2002 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1154
  - Precision: 0.8528
  - Recall: 0.8626
  - F1: 0.8577
  - Accuracy: 0.9780
  
  ## 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: 10
  - eval_batch_size: 10
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.1072        | 1.0   | 833  | 0.0905          | 0.8432    | 0.8451 | 0.8442 | 0.9779   |
  | 0.0347        | 2.0   | 1666 | 0.0934          | 0.8592    | 0.8612 | 0.8602 | 0.9782   |
  | 0.0218        | 3.0   | 2499 | 0.1078          | 0.8537    | 0.8568 | 0.8553 | 0.9776   |
  | 0.0106        | 4.0   | 3332 | 0.1154          | 0.8528    | 0.8626 | 0.8577 | 0.9780   |
  
  
  ### Framework versions
  
  - Transformers 4.12.5
  - Pytorch 1.10.0+cu111
  - Datasets 1.15.1
  - Tokenizers 0.10.3
  