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intermezzo672/NHS-bert-binary-random

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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NHS-bert-binary-random

This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5693
  • Accuracy: 0.8050
  • Precision: 0.7984
  • Recall: 0.8048
  • F1: 0.8006

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: 3e-05
  • trainbatchsize: 16
  • evalbatchsize: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 6

Training results

Training LossEpochStepValidation LossAccuracyPrecisionRecallF1
0.05541.03970.43930.81200.80500.80820.8064
0.0872.07940.48100.77290.78040.78900.7721
2.19693.011910.56930.80500.79840.80480.8006

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2