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Platzi Vit Model Elyager

Developed by platzi
This model is a fine-tuned image classification model based on Google's ViT architecture on the beans dataset, achieving an accuracy of 97.74%.
Image Classification
Transformers
Open Source License:Apache-2.0#High-precision image classification#Plant disease identification#Fine-tuned ViT model
Downloads 18
Release Time : 1/13/2023

Model Overview

This is an image classification model based on the Vision Transformer (ViT) architecture, specifically fine-tuned for the beans dataset, suitable for agricultural applications such as plant disease identification.

Model Features

High Accuracy
Achieves 97.74% classification accuracy on the beans test set
ViT-based Architecture
Utilizes Vision Transformer architecture with powerful image feature extraction capabilities
Lightweight Fine-tuning
Achieves excellent performance with only 4 epochs of fine-tuning on the pre-trained model

Model Capabilities

Image classification
Plant disease identification
Agricultural image analysis

Use Cases

Agricultural Technology
Bean Disease Diagnosis
Identify the health status and disease types of bean plants
97.74% accuracy
Crop Health Monitoring
Automated monitoring of crop growth conditions
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