platzi-vit-model-omar-espejel Open Source Image Classification Model - Free Deployment to Achieve 98.5% Accuracy

Platzi Vit Model Omar Espejel

Developed by platzi

This is an image classification model fine-tuned on the beans dataset based on Google's ViT model, achieving an accuracy of 98.5%.

Downloads 23

Release Time : 1/5/2023

Model Overview

This model is a fine-tuned version of Google's ViT-base-patch16-224-in21k model on the beans dataset, primarily used for image classification tasks.

High accuracy

Achieves a classification accuracy of 98.5% on the beans dataset

Based on ViT architecture

Uses the Vision Transformer architecture, suitable for image classification tasks

Lightweight fine-tuning

Requires only 4 training epochs to achieve high performance

Image classification

Plant disease identification

Agriculture

Bean plant disease identification

Identifies the health status and disease types of bean plants

Accuracy reaches 98.5%

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.149	3.85	500	0.0367	0.9850

Property	Details
Model Type	Fine - tuned version of [google/vit - base - patch16 - 224 - in21k](https://huggingface.co/google/vit - base - patch16 - 224 - in21k)
Training Data	beans
Metrics	accuracy

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