Open-source vit-base-beans model - Accurately classify bean leaf diseases with an accuracy rate of up to 98.5%

Vit Base Beans

Developed by nickmuchi

A fine-tuned bean leaf disease classification model based on Google Vision Transformer (ViT) architecture, achieving 98.5% accuracy on the beans dataset

Image Classification

Transformers

Open Source License:Apache-2.0 #High-precision plant disease identification #Agricultural image classification #ViT fine-tuned model

Downloads 25

Release Time : 3/2/2022

Model Overview

This model is specifically designed to identify the health status of bean crop leaves, capable of classifying healthy leaves, angular leaf spot, and bean rust leaves. Suitable for agricultural disease monitoring scenarios

Model Features

High-precision classification

Achieves 96.88% accuracy on the beans test set and 98.5% accuracy on the validation set

Efficient fine-tuning

Based on pre-trained ViT model for transfer learning, requiring only 8 training epochs to achieve excellent performance

Agricultural disease recognition

Specifically optimized for common bean crop diseases (angular leaf spot and rust)

Model Capabilities

Bean leaf image classification

Plant disease identification

Agricultural health monitoring

Use Cases

Smart agriculture

Early disease detection

Automatically identify early disease symptoms through leaf photos

Accurately distinguish between healthy leaves and two common diseases

Field monitoring system

Integrated into mobile devices or drones for large-scale crop health scanning

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1166	1.54	100	0.0764	0.9850
0.1607	3.08	200	0.2114	0.9398
0.0067	4.62	300	0.0692	0.9774
0.005	6.15	400	0.0944	0.9624
0.0043	7.69	500	0.0505	0.9850

Property	Details
Model Type	Image Classification
Training Data	beans
Base Model	google/vit - base - patch16 - 224 - in21k
Metrics	Accuracy, Precision, Recall, F1, Loss

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Vit Base Beans

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