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JoshGriffithsDev/Mutation_distillBERT

sourceHugging Faceapache-2.0updated 5mo agoView on Hugging Face
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mutation_distillBERT

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

  • Loss: 0.0338
  • Precision: 0.9496
  • Recall: 0.9500
  • F1: 0.9498
  • Accuracy: 0.9932

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: 5

Training results

Training LossEpochStepValidation LossPrecisionRecallF1Accuracy
0.13521.09710.03880.91360.92170.91760.9881
0.03032.019420.03050.93690.93160.93420.9909
0.01573.029130.03180.94730.94050.94390.9923
0.00794.038840.03170.95580.94720.95150.9934
0.00555.048550.03380.94960.95000.94980.9932

Framework versions

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