Platzi - vit - model - javi - javiai open-source image classification model, fine-tuned based on the dataset, with an accuracy rate approaching 98%

Platzi Vit Model Javi Javiai

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 #Plant Disease Identification #High-precision Classification #Agricultural Image Analysis

Downloads 40

Release Time : 1/19/2023

Model Overview

An image classification model based on the Vision Transformer (ViT) architecture, specifically fine-tuned for the beans dataset, designed for plant disease identification.

Model Features

High Accuracy

Achieves 97.74% classification accuracy on the beans test set.

ViT-based Architecture

Utilizes the Vision Transformer architecture with powerful image feature extraction capabilities.

Lightweight Fine-tuning

Fine-tuned based on a pre-trained model, ensuring high training efficiency.

Model Capabilities

Image Classification

Plant Disease Identification

Agricultural Image Analysis

Use Cases

Agriculture

Bean Disease Diagnosis

Identifies the health status and disease types of bean plants.

Accuracy: 97.74%

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0532	3.85	500	0.0623	0.9774

Property	Details
Tags	generated_from_trainer
Datasets	beans
Metrics	accuracy
Model Name	platzi-vit-model-javi-javiai
Task	Image Classification
Dataset Name	beans
Dataset Split	train
Accuracy	0.9774436090225563

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Platzi Vit Model Javi Javiai

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