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Skullly/DeepFake-image-detection-ViT-384

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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Model Card

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DeepFake-image-detection-ViT-384

This model is a fine-tuned version of google/vit-base-patch16-384 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0272
  • Accuracy: 0.9911

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: 32
  • seed: 42
  • gradientaccumulationsteps: 8
  • totaltrainbatch_size: 256
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: cosine
  • lrschedulerwarmup_ratio: 0.1
  • num_epochs: 2.5
  • mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossAccuracy
0.00370.99845460.02720.9911
0.00061.998610930.11210.9644
0.00022.49613650.13570.9582

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.1.2
  • Datasets 2.19.2
  • Tokenizers 0.19.1