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distilbert-base-uncased-finetuned-ner

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

  • Loss: 0.0626
  • Precision: 0.9193
  • Recall: 0.9311
  • F1: 0.9251
  • Accuracy: 0.9824

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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.2393 1.0 878 0.0732 0.9052 0.9207 0.9129 0.9801
0.0569 2.0 1756 0.0626 0.9193 0.9311 0.9251 0.9824

Framework versions

  • Transformers 4.15.0
  • Pytorch 1.10.0+cu111
  • Datasets 1.18.0
  • Tokenizers 0.10.3
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Dataset used to train Vibharkchauhan/distilbert-base-uncased-finetuned-ner

Evaluation results