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leomaurodesenv/bert-base-uncased-jailbreakv-28k-augmented

sourceHugging Faceapache-2.0updated 9d agoView on Hugging Face
4likes278downloads
Model Card

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bert-base-uncased-jailbreakv-28k-augmented

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

  • Loss: 0.0063
  • Accuracy: 0.9981

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
  • gradientaccumulationsteps: 2
  • totaltrainbatch_size: 16
  • optimizer: Use adamwtorchfused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lrschedulertype: linear
  • lrschedulerwarmup_steps: 50
  • num_epochs: 10

Training results

Training LossEpochStepValidation LossAccuracy
0.00091.078400.01310.9955
0.00032.0156800.01010.9968
0.01693.0235200.00970.9973
0.01154.0313600.00880.9976
0.01955.0392000.01610.9966
0.00166.0470400.01010.9974
0.00387.0548800.00850.9978
0.00008.0627200.00680.9980
0.01389.0705600.00630.9981
0.017010.0784000.00660.9982

Framework versions

  • Transformers 5.2.0
  • Pytorch 2.10.0+cu128
  • Datasets 4.5.0
  • Tokenizers 0.22.2