Vit-model-beimer Open-source Image Classification Model - Free Deployment to Achieve Accurate Classification of Bean Images with 98.5% Accuracy

Vit Model Beimer

Developed by tadeous

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%.

Image Classification

Transformers

Open Source License:Apache-2.0 #Plant Disease Identification #High-precision Classification #Agricultural Image Analysis

Downloads 39

Release Time : 1/28/2023

Model Overview

This is a Vision Transformer model for image classification, specifically optimized for the beans dataset, capable of accurately identifying disease types in legume plants.

Model Features

High Accuracy

Achieves 98.5% classification accuracy on the beans validation set.

Based on ViT Architecture

Uses the Vision Transformer base architecture with powerful image feature extraction capabilities.

Lightweight Fine-tuning

Only requires a few epochs of fine-tuning on the beans dataset.

Model Capabilities

Image Classification

Plant Disease Identification

Use Cases

Agricultural Technology

Legume Disease Diagnosis

Automatically identifies disease types in legume plants.

98.5% accuracy

Botanical Research

Plant Pathology Analysis

Assists researchers in quickly classifying plant disease samples.

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1394	3.85	500	0.0637	0.9850

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Vit Model Beimer

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