# Dining Scenarios

This is a Vision Transformer model fine-tuned on the Food-101 dataset for food image classification tasks.

This model is a vision classification model fine-tuned on the THFOOD-50 Thai food dataset based on the Swin Transformer V2 architecture, specifically designed for Thai food image recognition.

Food classification model fine-tuned on the food101 dataset based on Google's ViT model

Food image classification model based on Google Vision Transformer (ViT) architecture, fine-tuned on the Food101 dataset with an accuracy of 90.9%

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

An image classification model fine-tuned on the Food101 dataset based on the Swin Transformer architecture, achieving an accuracy of 92.14%

A food image classification model fine-tuned based on the Swin Transformer architecture, achieving 92.1% accuracy on the Food101 dataset