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metadata
license: mit
tags:
  - generated_from_trainer
datasets:
  - conll2003
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: test-conll2003-ner
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: conll2003
          type: conll2003
          args: conll2003
        metrics:
          - name: Precision
            type: precision
            value: 0.9459188783174762
          - name: Recall
            type: recall
            value: 0.9537192864355436
          - name: F1
            type: f1
            value: 0.94980306712478
          - name: Accuracy
            type: accuracy
            value: 0.9911218410498034

test-conll2003-ner

This model is a fine-tuned version of xlm-roberta-base on the conll2003 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0470
  • Precision: 0.9459
  • Recall: 0.9537
  • F1: 0.9498
  • Accuracy: 0.9911

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: 3.0

Training results

Framework versions

  • Transformers 4.18.0.dev0
  • Pytorch 1.10.0
  • Datasets 1.18.3
  • Tokenizers 0.11.0