V

Virtus

Developed by agasta
A Vision Transformer-based binary classification model specifically designed for detecting deepfake images, with an accuracy rate of 99.2%
Downloads 970
Release Time : 4/14/2025

Model Overview

Virtus is a fine-tuned Vision Transformer model specifically designed to distinguish between real and deepfake images. The model was trained on a balanced dataset containing 190,000 images and achieves extremely high detection accuracy.

Model Features

High Accuracy
Achieves 99.2% accuracy on test sets, effectively identifying deepfake images
Balanced Dataset
Trained on a balanced dataset of 190,000 images to ensure model fairness
Data Augmentation
Utilizes various data augmentation techniques such as random rotation and sharpness adjustment to enhance generalization
Distilled Architecture
Based on the distilled version of Vision Transformer (DeiT) architecture, combining efficiency with high performance

Model Capabilities

Image Classification
Deepfake Detection
Facial Authenticity Analysis

Use Cases

Security Detection
Social Media Content Moderation
Automatically identifies deepfake images on social media
99.2% accuracy
Identity Verification Systems
Serves as an additional verification layer for biometric systems
Education & Research
Digital Media Literacy Tool
Helps students identify synthetic media
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