hurtmongoose/bert-base-detect-jailbreak

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bert-base-detect-jailbreak

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: 0.3486
• —Accuracy: 0.8931
• —Precision: 0.9206
• —Recall: 0.8657
• —F1: 0.8923
• —Balanced Accuracy: 0.8938
• —Mcc: 0.7879

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: 32
• —evalbatchsize: 64
• —seed: 42
• —optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
• —lrschedulertype: linear
• —num_epochs: 10

Training results

Framework versions

• —Transformers 4.53.3
• —Pytorch 2.6.0+cu124
• —Datasets 4.3.0
• —Tokenizers 0.21.4