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Vit Base Food101

Developed by eslamxm
An image classification model fine-tuned on the Food101 dataset based on Google's ViT model, achieving an accuracy of 85.39%
Image Classification
Transformers
Open Source License:Apache-2.0#Food Image Classification#High Accuracy#ViT Fine-tuning
Downloads 445
Release Time : 5/19/2022

Model Overview

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the food101 dataset, specifically designed for food image classification tasks.

Model Features

High Accuracy
Achieves 85.39% classification accuracy on the Food101 test set
Based on ViT Architecture
Utilizes the Vision Transformer architecture with powerful image feature extraction capabilities
Lightweight Fine-tuning
Only 4 epochs of fine-tuning on the pre-trained model, ensuring high training efficiency

Model Capabilities

Food Image Classification
Image Feature Extraction

Use Cases

Catering Industry
Smart Menu Recognition
Automatically identifies and classifies restaurant dish photos
85.39% accuracy
Food Content Moderation
Automatically identifies and classifies user-uploaded food images
Health Management
Diet Record Analysis
Automatically identifies and records food types in user diet photos
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