README.md

metadata

license: apache-2.0
metrics:
  - accuracy
base_model:
  - google/vit-base-patch16-224-in21k
pipeline_tag: image-classification
language:
  - en
library_name: transformers
tags:
  - Python
  - Deepfake

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