My Awesome Food Model: An Open-Source Food Image Classification Model - Accurately Identify Food Categories with Nearly 90% Accuracy

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My Awesome Food Model

Developed by asd0936

Food image classification model based on ViT architecture, fine-tuned on the Food101 dataset with an accuracy of 89.7%

Image Classification

Transformers

Open Source License:Apache-2.0 #Food Image Classification #High-precision Recognition #ViT Fine-tuning

Downloads 38

Release Time : 1/15/2023

Model Overview

This model is a fine-tuned version of Google's ViT-base-patch16-224-in21k on the Food101 dataset, specifically designed for food image classification tasks.

Model Features

High Accuracy

Achieves 89.7% classification accuracy on the Food101 dataset

Based on ViT Architecture

Uses Vision Transformer architecture with excellent image understanding capabilities

Food-Specific

Optimized specifically for food image classification tasks

Model Capabilities

Food Image Classification

Multi-category Image Recognition

Use Cases

Food and Beverage Industry

Dish Recognition

Used in restaurant menu auto-recognition systems

Can automatically recognize 5,000 dishes

Nutritional Analysis

Combined with nutrition databases for dietary analysis

Retail Industry

Smart Shopping

Used for product recognition in supermarket smart carts

Property	Details
Model Type	Fine - tuned version of [google/vit - base - patch16 - 224 - in21k](https://huggingface.co/google/vit - base - patch16 - 224 - in21k)
Training Data	food101
Metrics	Accuracy

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.6742	0.99	62	2.5104	0.821
1.8036	1.99	124	1.7824	0.863
1.591	2.99	186	1.5916	0.897

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My Awesome Food Model

Model Overview

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