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FareehaAly/fator-fallacy-detector

sourceHugging Faceapache-2.0updated 5mo agoView on Hugging Face
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fator-fallacy-detector

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

  • —Loss: 0.7968
  • —Accuracy: 0.8598
  • —F1 Macro: 0.6798
  • —F1 Weighted: 0.7825

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: 3e-05
  • —trainbatchsize: 32
  • —evalbatchsize: 64
  • —seed: 42
  • —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 0.1
  • —num_epochs: 4
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossAccuracyF1 MacroF1 Weighted
2.03531.0692.24170.40410.30830.4288
1.10182.01381.82710.56190.53190.5691
1.01663.02071.06060.78080.61070.6679
0.79684.02760.92680.85980.67980.7825

Framework versions

  • —Transformers 5.0.0
  • —Pytorch 2.10.0+cu128
  • —Datasets 4.0.0
  • —Tokenizers 0.22.2