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Platzi Vit Model Julenalvaro
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Platzi Vit Model Julenalvaro

Developed by julenalvaro
A bean leaf disease classification model based on ViT architecture, fine-tuned on the beans dataset with an accuracy of 99.25%
Image Classification
Transformers
Open Source License:Apache-2.0#Bean Disease Classification#High-Precision ViT Model#Agricultural Image Recognition
Downloads 20
Release Time : 1/4/2023

Model Overview

This model is an image classification model fine-tuned on the beans dataset using Google's ViT-base-patch16-224-in21k, specifically designed to identify the health status and disease types of bean leaves.

Model Features

High-Precision Classification
Achieves 99.25% accuracy on the beans test set, reliably distinguishing between healthy and diseased leaves.
ViT-Based Architecture
Uses the Vision Transformer base model with powerful image feature extraction capabilities.
Lightweight Fine-Tuning
Requires only 4 training epochs to achieve excellent performance, with high training efficiency.

Model Capabilities

Bean Leaf Health Status Classification
Plant Disease Recognition
Agricultural Image Analysis

Use Cases

Smart Agriculture
Automatic Bean Disease Detection
Automatically identifies the health status of field bean crops, detecting diseases such as rust in a timely manner.
99.25% accuracy
Crop Health Monitoring System
Integrated into agricultural monitoring systems to provide real-time plant health analysis.
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