README.md

metadata

license: apache-2.0
tags:
  - token-classification
datasets:
  - wikiann-conll2003
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: distilroberta-base-ner-wikiann-conll2003-3-class
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: wikiann-conll2003
          type: wikiann-conll2003
        metrics:
          - name: Precision
            type: precision
            value: 0.9624757386241104
          - name: Recall
            type: recall
            value: 0.9667497021553124
          - name: F1
            type: f1
            value: 0.964607986167396
          - name: Accuracy
            type: accuracy
            value: 0.9913626461292995

distilroberta-base-ner-wikiann-conll2003-3-class

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

• Loss: 0.0520
• Precision: 0.9625
• Recall: 0.9667
• F1: 0.9646
• Accuracy: 0.9914

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: 4.9086903597787154e-05
• train_batch_size: 32
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5.0
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.6.1
• Pytorch 1.8.1+cu101
• Datasets 1.6.2
• Tokenizers 0.10.3