Open-source vit-base-beans Image Classification Model - Accurately identify beans with an accuracy rate of up to 97.74%

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Vit Base Beans

Developed by socokal

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

Image Classification

Transformers

Open Source License:Apache-2.0 #Bean Image Classification #High Accuracy #ViT Fine-tuning

Downloads 30

Release Time : 12/18/2022

Model Overview

This model is a fine-tuned version of Google's ViT-base-patch16-224-in21k model on a bean dataset, primarily used for bean image classification tasks.

Model Features

High Accuracy

Achieves a classification accuracy of 97.74% on the bean dataset

Based on ViT Architecture

Utilizes the Vision Transformer architecture with powerful image feature extraction capabilities

Few-shot Fine-tuning

Requires only a small number of training samples to achieve good performance

Model Capabilities

Image Classification

Bean Identification

Plant Image Analysis

Use Cases

Agriculture

Bean Variety Identification

Automatically identifies different varieties of beans

97.74% accuracy

Agricultural Product Quality Inspection

Used for agricultural product classification and quality control

Education

Botany Teaching Aid

Helps students identify different bean varieties

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1111	1.54	100	0.0720	0.9774
0.0249	3.08	200	0.1081	0.9774

Property	Details
Model Type	Fine - tuned Vision Transformer
Training Data	Beans dataset
Metrics	Accuracy

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Vit Base Beans

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