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maleke01/RoBERTa-WebAttack

sourceHugging Facemitupdated 2y agoView on Hugging Face
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Model Card

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RoBERTa-WebAttack

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

  • Loss: 0.0133
  • F1: 0.9974
  • Accuracy: 0.9974
  • Precision: 0.9974
  • Recall: 0.9974

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: 5e-05
  • trainbatchsize: 48
  • evalbatchsize: 48
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • lrschedulerwarmup_steps: 500
  • num_epochs: 3

Training results

Training LossEpochStepValidation LossF1AccuracyPrecisionRecall
0.02071.037130.02290.99560.99560.99560.9956
0.02152.074260.01580.99630.99630.99630.9963
0.0013.0111390.01330.99740.99740.99740.9974

Framework versions

  • Transformers 4.42.3
  • Pytorch 2.1.2
  • Datasets 2.20.0
  • Tokenizers 0.19.1