CoolFace
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iexploreaiml/Email-Phising-Detection

sourceHugging Faceapache-2.0updated 1y agoView on Hugging Face
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Model Card

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results

This model is a fine-tuned version of bert-base-uncased on the zefang-liu/phishing-email-dataset dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0992
  • Accuracy: 0.9775

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: 8
  • evalbatchsize: 8
  • 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 LossAccuracy
0.06341.018630.09500.9713
0.03362.037260.08420.9785
0.02693.055890.08350.9785
0.04524.074520.10830.9777
0.02335.093150.09920.9775

Framework versions

  • Transformers 4.56.2
  • Pytorch 2.8.0+cu126
  • Datasets 4.0.0
  • Tokenizers 0.22.1