Deepfake Image Detector (Real and Fake Faces Fine-Tuned)

Model Performance

  • Test Accuracy: 93.02%
  • Best Validation Accuracy: 94.12%
  • Best Epoch: 1
  • Planned Epochs: 12
  • Actual Epochs Trained: 5 (early stopping applied)

Dataset

  • Training: 1,367 images
  • Validation: 170 images
  • Test: 172 images

Training Details

Training was stopped early at epoch 5 due to early stopping criteria being met. The best model was achieved at epoch 1 with validation accuracy of 94.12%.

Usage

from transformers import ViTForImageClassification, ViTFeatureExtractor

model = ViTForImageClassification.from_pretrained('shivani1511/deepfake-image-detector-new-latest-v2')
feature_extractor = ViTFeatureExtractor.from_pretrained('shivani1511/deepfake-image-detector-new-latest-v2')

Notes

  • Fine-tuned on Real and Fake Faces dataset to address AI-generated fake detection.
  • Base model: shivani1511/deepfake-image-detector-new-latest (Vision Transformer).
  • Improvements: Enhanced data augmentation, class-weighted loss, Mixup, more unfrozen layers.
Downloads last month
54
Safetensors
Model size
85.8M params
Tensor type
F32
·
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support