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cleandata/bert-finetuned-ner

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

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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: 0.0643
  • Precision: 0.9293
  • Recall: 0.9467
  • F1: 0.9379
  • Accuracy: 0.9855

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: 8
  • evalbatchsize: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 3

Training results

Training LossEpochStepValidation LossPrecisionRecallF1Accuracy
0.08661.017560.07220.91160.92900.92020.9816
0.0342.035120.06760.92730.94610.93660.9852
0.01893.052680.06430.92930.94670.93790.9855

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.13.0+cu116
  • Datasets 2.8.0
  • Tokenizers 0.13.2