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Vit Base Cats Vs Dogs
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Vit Base Cats Vs Dogs

Developed by ismgar01
A cat and dog image classification model based on ViT architecture, fine-tuned on the cats_vs_dogs dataset with an accuracy of 99.37%
Image Classification
Transformers
Open Source License:Apache-2.0#High-precision image classification#Pet recognition#ViT fine-tuned model
Downloads 22
Release Time : 3/2/2022

Model Overview

This model is an image classification model fine-tuned on the cats_vs_dogs dataset using Google's ViT-base-patch16-224-in21k pre-trained model, specifically designed to distinguish between cat and dog images.

Model Features

High accuracy
Achieves a classification accuracy of 99.37% on the cats_vs_dogs test set
Based on ViT architecture
Uses the Vision Transformer (ViT) architecture, which has powerful image feature extraction capabilities
Lightweight fine-tuning
Fine-tuned based on a pre-trained model, requiring only a small amount of training data to achieve excellent performance

Model Capabilities

Image classification
Cat and dog recognition
Visual feature extraction

Use Cases

Pet recognition
Pet photo classification
Automatically identifies whether the animal in the photo is a cat or a dog
Classification accuracy of 99.37%
Pet app integration
Can be integrated into pet-related applications to provide automatic classification functionality
Educational demonstration
Machine learning teaching
Used as a teaching case for computer vision and transfer learning
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