Spoofing_ViT_16_224 Open-source Image Anti-counterfeiting Detection Model - Accuracy Exceeds 70% on Unknown Datasets after Fine-tuning

Spoofing Vit 16 224

Developed by venuv62

An image anti-counterfeiting detection model based on ViT architecture, achieving 70.88% accuracy after fine-tuning on an unknown dataset

Image Classification

Transformers

Open Source License:Apache-2.0 #Anti-counterfeiting detection #ViT fine-tuning #Image authentication

Downloads 59

Release Time : 12/18/2022

Model Overview

This model is a fine-tuned image classification model based on Google's ViT-base-patch16-224 architecture, primarily used for anti-counterfeiting detection tasks.

Model Features

High accuracy

Achieves 70.88% accuracy on the evaluation set

ViT-based architecture

Utilizes Vision Transformer architecture with excellent feature extraction capabilities

Efficient fine-tuning

Requires only a few epochs of fine-tuning on the base model to achieve good results

Model Capabilities

Image classification

Anti-counterfeiting detection

Image feature extraction

Use Cases

Security verification

Document anti-counterfeiting detection

Detect authenticity of ID cards, passports and other documents

Accurately identifies over 70% of counterfeit samples

Product anti-counterfeiting verification

Verify authenticity of product packaging and labels

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.7746	0.99	54	0.6401	0.6405
0.339	1.99	108	0.9389	0.6042
0.0437	2.99	162	1.0560	0.7088

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Spoofing Vit 16 224

Model Overview

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