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leomaurodesenv/bert-base-uncased-trustairlab-jailbreak

sourceHugging Faceapache-2.0updated 12d agoView on Hugging Face
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Model Card

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bert-base-uncased-trustairlab-jailbreak

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: 0.1904
  • —Accuracy: 0.9388

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
0.28791.06050.21150.9363
0.12282.012100.19010.9396
0.15723.018150.22560.9400
0.15614.024200.23020.9396
0.06005.030250.32270.9342

Framework versions

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