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JoshGriffithsDev/mutation_BERT_multilingual

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

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

  • Loss: 0.0388
  • Precision: 0.9433
  • Recall: 0.9488
  • F1: 0.9460
  • Accuracy: 0.9935

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
0.04831.024260.03720.90780.91690.91230.9888
0.02842.048520.02840.94130.93540.93830.9923
0.01473.072780.02960.94280.94200.94240.9929
0.00994.097040.03360.94410.94360.94390.9932
0.00505.0121300.03880.94330.94880.94600.9935

Framework versions

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