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bert-finetuned-ner

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

  • Loss: 0.0660
  • Precision: 0.9126
  • Recall: 0.9347
  • F1: 0.9235
  • Accuracy: 0.9823

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
0.0756 1.0 1756 0.0660 0.9126 0.9347 0.9235 0.9823

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0
  • Datasets 2.16.1
  • Tokenizers 0.15.0
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Dataset used to train monkeyerKong/bert-finetuned-ner

Evaluation results