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Platzi Vit Model Cristian Rubio
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Platzi Vit Model Cristian Rubio

Developed by platzi
This model is a fine-tuned image classification model based on Google's ViT-base-patch16-224-in21k on the beans dataset, achieving 98.5% accuracy on the validation set.
Image Classification
Transformers
Open Source License:Apache-2.0#High-precision image classification#Plant disease identification#Fine-tuned ViT model
Downloads 18
Release Time : 2/14/2023

Model Overview

A Vision Transformer model optimized for the beans dataset, designed for plant leaf disease image classification tasks.

Model Features

High-precision classification
Achieves 98.5% classification accuracy on the beans validation set
ViT-based architecture
Utilizes the foundational Vision Transformer architecture with powerful feature extraction capabilities
Lightweight fine-tuning
Requires only 4 training epochs to achieve excellent performance

Model Capabilities

Plant leaf image classification
Disease identification
Agricultural image analysis

Use Cases

Agricultural technology
Crop disease diagnosis
Automatically identifies common diseases in legume crops
Validation accuracy of 98.5%
Farm monitoring system
Integrated into farm surveillance systems for real-time disease detection
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