platzi-vit-model-orlando-murcia Open-source Image Classification Model - High-precision Identification of Bean Images

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Platzi Vit Model Orlando Murcia

Developed by platzi

High-precision image classification model fine-tuned on the beans dataset based on Google's ViT model

Image Classification

Transformers

Open Source License:Apache-2.0 #High-precision Image Classification #Plant Disease Recognition #Fine-tuned ViT Model

Downloads 37

Release Time : 1/30/2023

Model Overview

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the beans dataset, primarily used for image classification tasks, achieving 98.5% accuracy on the validation set.

Model Features

High Accuracy

Achieves 98.5% classification accuracy on the beans dataset validation set

Based on ViT Architecture

Utilizes Vision Transformer architecture with powerful image feature extraction capabilities

Lightweight Fine-tuning

Requires only 4 training epochs to achieve excellent performance

Model Capabilities

Image Classification

Plant Disease Recognition

Crop Health Detection

Use Cases

Agriculture

Bean Disease Diagnosis

Identifies the health status and disease types of bean plants

Achieves 98.5% accuracy on the beans dataset

Botanical Research

Plant Pathology Analysis

Assists researchers in quickly identifying and classifying plant diseases

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0776	3.85	500	0.0532	0.9850

Property	Details
Model Type	Generated from trainer
Training Data	beans
Metrics	accuracy

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Platzi Vit Model Orlando Murcia

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