Clasificacion-vit-model-manuel-chaves Open-source Image Classification Model - Bean Classification Accuracy Reaches Up to 97.74%

Clasificacion Vit Model Manuel Chaves

Developed by machves

An image classification model fine-tuned from google/vit-base-patch16-224-in21k, achieving 97.74% accuracy on the bean dataset

Image Classification

Transformers

Open Source License:Apache-2.0 #High-precision image classification #Bean recognition #ViT architecture

Downloads 15

Release Time : 4/12/2023

Model Overview

This model is an image classification model based on the Vision Transformer architecture, specifically designed for bean image classification tasks.

Model Features

High accuracy

Achieves 97.74% classification accuracy on the bean dataset

Based on ViT architecture

Utilizes Vision Transformer architecture, suitable for image classification tasks

Fine-tuned optimization

Fine-tuned from google/vit-base-patch16-224-in21k

Model Capabilities

Image classification

Bean recognition

Use Cases

Agriculture

Bean variety identification

Used to identify different varieties of bean crops

97.74% recognition accuracy

Food processing

Food ingredient classification

Classifying bean ingredients on food processing lines

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1442	3.85	500	0.0701	0.9774

Property	Details
Model Type	Fine - tuned version of google/vit-base-patch16-224-in21k
Training Data	glue and mrpc datasets
Metrics	accuracy

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Clasificacion Vit Model Manuel Chaves

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