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imrazaa/named-entity-recognition-distilbert-B

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face
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named-entity-recognition-distilbert-B

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

  • Loss: 0.0350
  • Precision: 0.9377
  • Recall: 0.9442
  • F1: 0.9409
  • Accuracy: 0.9918

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: 32
  • evalbatchsize: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 3

Training results

Training LossEpochStepValidation LossPrecisionRecallF1Accuracy
0.01641.082050.02560.93470.93850.93660.9913
0.00822.0164100.02880.93810.94130.93970.9917
0.00443.0246150.03500.93770.94420.94090.9918

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.1+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0

Citation

Bibtex

@software{Ali_Raza,
    author = {Raza, Ali},
    license = { BSD-2-Clause license},
    title = {{Named Entity Recognition using Multinerd}},
    url = {https://github.com/raza4729/NER}
}