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leomaurodesenv/bert-base-uncased-disaster-tweet-jailbreaking-augmented

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

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bert-base-uncased-disaster-tweet-jailbreaking-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: 0.1527
  • —Accuracy: 0.9798

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 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
0.46771.016800.50910.7702
0.48602.033600.34870.9039
0.37003.050400.30000.9411
0.03044.067200.19370.9610
0.07135.084000.19890.9670
0.00026.0100800.20610.9685
0.00017.0117600.16810.9729
0.00018.0134400.18180.975
0.00009.0151200.15280.9798
0.000010.0168000.15810.9795

Framework versions

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