CoolFace
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autoevaluate/entity-extraction

sourceHugging Faceapache-2.0updated 4y agoView on Hugging Face
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Model Card

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entity-extraction

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: 0.0808
  • Precision: 0.8863
  • Recall: 0.9085
  • F1: 0.8972
  • Accuracy: 0.9775

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
  • trainbatchsize: 16
  • evalbatchsize: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 1

Training results

Training LossEpochStepValidation LossPrecisionRecallF1Accuracy
0.25521.08780.08080.88630.90850.89720.9775

Framework versions

  • Transformers 4.19.2
  • Pytorch 1.11.0+cu113
  • Datasets 2.2.2
  • Tokenizers 0.12.1