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update model card README.md
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metadata
tags:
  - generated_from_trainer
datasets:
  - conll2002
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: bert-base-spanish-wwm-cased-t1
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: conll2002
          type: conll2002
          config: es
          split: validation
          args: es
        metrics:
          - name: Precision
            type: precision
            value: 0.7979376919701624
          - name: Recall
            type: recall
            value: 0.8357077205882353
          - name: F1
            type: f1
            value: 0.8163860830527497
          - name: Accuracy
            type: accuracy
            value: 0.9686647656831143

bert-base-spanish-wwm-cased-t1

This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on the conll2002 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1173
  • Precision: 0.7979
  • Recall: 0.8357
  • F1: 0.8164
  • Accuracy: 0.9687

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: 1

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.0773 1.0 1041 0.1173 0.7979 0.8357 0.8164 0.9687

Framework versions

  • Transformers 4.26.1
  • Pytorch 1.13.1+cu116
  • Datasets 2.10.1
  • Tokenizers 0.13.2