CoolFace
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JoshGriffithsDev/mutation_BERT

sourceHugging Faceapache-2.0updated 5mo agoView on Hugging Face
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Model Card

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mutation_BERT

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

  • Loss: 0.0335
  • Precision: 0.9672
  • Recall: 0.9690
  • F1: 0.9681
  • Accuracy: 0.9961

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: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lrschedulertype: linear
  • num_epochs: 10

Training results

Training LossEpochStepValidation LossPrecisionRecallF1Accuracy
0.03151.024260.02320.95210.93600.94400.9930
0.01582.048520.02040.95460.95590.95520.9944
0.01043.072780.01850.96140.95960.96050.9951
0.00664.097040.02500.96300.96190.96240.9954
0.00425.0121300.02540.96290.96580.96430.9955
0.00236.0145560.03010.95580.96690.96130.9951
0.00157.0169820.02810.96320.96670.96500.9956
0.00118.0194080.03060.96520.96650.96580.9957
0.00109.0218340.03180.96850.96760.96800.9961
0.000310.0242600.03350.96720.96900.96810.9961

Framework versions

  • Transformers 5.0.0
  • Pytorch 2.10.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.22.2