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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
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
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