Open source platzi-vit-model-nelson-silvera image classification model - High-precision recognition of bean images

Platzi Vit Model Nelson Silvera

Developed by platzi

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

Downloads 16

Release Time : 4/7/2023

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.

High Accuracy

Achieved 98.5% accuracy on the validation set of the beans dataset.

Based on ViT Architecture

Uses the Vision Transformer (ViT) architecture, which has powerful image feature extraction capabilities.

Lightweight Fine-tuning

Only 4 epochs of fine-tuning were performed on the pre-trained model, ensuring high training efficiency.

Image Classification

Plant Disease Recognition

Agriculture

Bean Disease Identification

Identify the health status and disease types of bean plants

Achieved 98.5% accuracy on the beans dataset

Property	Details
Model Type	Fine - tuned version of google/vit-base-patch16-224-in21k
Training Data	beans dataset
Metrics	accuracy
License	apache - 2.0

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1404	3.85	500	0.0522	0.9850

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