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Ak Vit Base Patch16 224 In21k Image Classification

Developed by amitkayal
An image classification model based on Google's Vision Transformer (ViT) architecture, fine-tuned on a custom image dataset with an evaluation accuracy of 100%
Downloads 19
Release Time : 4/23/2022

Model Overview

This model is a fine-tuned Vision Transformer based on google/vit-base-patch16-224-in21k, specifically designed for image classification tasks. It performs exceptionally well on the evaluation set, achieving an accuracy of 1.0.

Model Features

High Accuracy
Achieved 100% classification accuracy on the evaluation set
Based on ViT Architecture
Utilizes the Vision Transformer architecture, effectively capturing global image features
Transfer Learning
Fine-tuned from a pre-trained ViT model, suitable for domain-specific image classification tasks

Model Capabilities

Image classification
Visual feature extraction

Use Cases

Computer Vision
Domain-specific Image Classification
Can be used for professional image classification tasks in fields such as healthcare and industrial applications
Evaluation accuracy of 100%
Visual Quality Inspection
Suitable for visual quality inspection on production lines
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