# ViT Fine-tuning

A Vision Transformer model fine-tuned on the beans dataset based on google/vit-base-patch16-224-in21k for image classification tasks

An image classification solution implemented using Hugging Face's pre-trained Vision Transformer (ViT) model, capable of classifying images into six types of garbage

This model is a logo recognition model fine-tuned based on Google's Vision Transformer (ViT), specifically designed for classifying UAE company logos.

A visual classification model fine-tuned on the Stanford Cars dataset based on the CLIP Vision Transformer architecture

A Bhutanese textile image classification model fine-tuned based on Google's ViT model

A celebrity classification model based on Google Vision Transformer (ViT) architecture, designed to recognize 1000 top celebrities

A Vision Transformer model fine-tuned on a flower image dataset based on Google's ViT-Base-Patch16-224 model

An image classification model fine-tuned on a legume dataset based on Google's ViT model, achieving 97.74% accuracy

An image classification model fine-tuned based on google/vit-base-patch16-224, suitable for histology image analysis tasks.

A vision model fine-tuned based on google/vit-base-patch16-224, suitable for image classification tasks

An image classification model fine-tuned on a letter recognition dataset based on Google's ViT base model, achieving 98.81% accuracy

A Vision Transformer model fine-tuned on a flower image dataset, based on Google's ViT model

This model is a fine-tuned image classification model based on Google's ViT-base model on the beans dataset, achieving an accuracy of 98.5%.

A visual classification model fine-tuned on flower image datasets based on Google's Vision Transformer (ViT)

A vision Transformer model fine-tuned on flower image datasets based on Google's ViT model

A Vision Transformer model fine-tuned on flower image datasets based on Google's ViT model, suitable for image classification tasks

A Vision Transformer model fine-tuned on a flower image dataset based on Google's ViT model, suitable for image classification tasks

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%

This is an image classification model fine-tuned based on Google's ViT model, trained on the fl_image_category_ds dataset with an accuracy of 66.22%.

This is a food classification model fine-tuned on the food101 dataset based on Google's ViT model, achieving an accuracy of 89.5%.

This model is a vision classification model fine-tuned on an algae dataset based on Google's ViT model, primarily used for algae image classification tasks.

This model is a fine-tuned image classification model based on Google's ViT-base-patch16-224-in21k on the beans dataset, achieving an accuracy of 98.5%.

This model is an image classification model fine-tuned on a bean dataset based on Google's ViT architecture, achieving 100% accuracy on the validation set.

Vision Transformer model based on ViT architecture for gender and age classification tasks

A cartoon face recognition model fine-tuned based on the Google Vision Transformer (ViT) architecture, excelling in image classification tasks

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

This model is an image classification model fine-tuned on the beans dataset based on Google's ViT architecture, achieving an accuracy of 97.74%.

A gastrointestinal image classification model based on ViT architecture for diagnosing various conditions from colonoscopy images

A Vision Transformer model fine-tuned on a flower image dataset based on Google's ViT model

An image classification model fine-tuned on a bean dataset based on Google's ViT model, achieving an accuracy of 97.74%

An image classification model based on ViT architecture, fine-tuned on an image folder dataset

This model is an image classification model fine-tuned on the beans dataset based on Google's ViT architecture, designed to identify the health status of legume plants.

An image classification model fine-tuned on a bean dataset based on Google's ViT model, achieving 99.25% accuracy

This model is a fine-tuned image classification model based on google/vit-base-patch16-224-in21k on a bean dataset, achieving 100% accuracy on the evaluation set.

A vision classification model fine-tuned on flower image datasets based on Google's ViT model

A vision Transformer model fine-tuned on flower image datasets based on Google's ViT model

Fine-tuned based on Google's ViT model for handwriting recognition tasks

This model is based on Google's ViT architecture, fine-tuned on the beans dataset, achieving an accuracy of 98.5%.

This model is a fine-tuned version of google/vit-base-patch16-224 on the imagefolder dataset, suitable for vision tasks.