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usamahfirdaa/mlops-fraud-detection

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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Model Card

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mlops-fraud-detection

This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0021

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

Training results

Training LossEpochStepValidation Loss
No log1.040.0155
No log2.080.0088
0.0213.0120.0055
0.0214.0160.0041
0.00625.0200.0034
0.00626.0240.0028
0.00627.0280.0024
0.00388.0320.0022
0.00389.0360.0021
0.00310.0400.0021

Framework versions

  • Transformers 4.47.1
  • Pytorch 2.5.1+cu121
  • Datasets 3.2.0
  • Tokenizers 0.21.0