CoolFace
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sandesh2233/Deepfakes_detection

sourceHugging Faceapache-2.0updated 5mo agoView on Hugging Face
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Model Card

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Deepfakes_detection

This model is a fine-tuned version of google/vit-base-patch16-224 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3242
  • Accuracy: 0.9222
  • Auc: 0.9998
  • F1 Fake: 0.9278

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: 0.0002
  • trainbatchsize: 256
  • evalbatchsize: 512
  • 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: 5
  • num_epochs: 5
  • mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossAccuracyAucF1 Fake
No log1.0110.36300.85790.95270.8454
No log2.0220.26800.91140.98630.9166
No log3.0330.30720.91230.98790.9178
No log4.0440.29170.9140.9880.9193
0.05685.0550.28400.91320.9880.9182

Framework versions

  • Transformers 5.5.4
  • Pytorch 2.11.0+cu130
  • Datasets 4.8.4
  • Tokenizers 0.22.2