Deepfake Image Detection Using Fine-Tuned Vision Transformer (ViT)
This project focuses on detecting deepfake images using a fine-tuned version of the pre-trained model google/vit-base-patch16-224-in21k
. The approach leverages the power of Vision Transformers (ViT) to classify images as real or fake.
Model Overview
- Base Model: google/vit-base-patch16-224-in21k
- Dataset: DFDC.
- Classes: Deepfake and Real
- Performance:
- Validation Accuracy: 95%
- Test Accuracy: 91%
Figure : Confusion matrix for test data
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Base model
google/vit-base-patch16-224-in21k