V

Vit Base Patch16 224 In21k Finetuned Cassava3

Developed by siddharth963
An image classification model based on Google Vision Transformer (ViT) architecture, fine-tuned on an image folder dataset with an accuracy of 88.55%
Downloads 13
Release Time : 10/12/2022

Model Overview

This model is a fine-tuned version of Google's ViT-base-patch16-224-in21k pre-trained model for specific image classification tasks, primarily used for image classification.

Model Features

High accuracy
Achieves 88.55% classification accuracy on the evaluation set
Based on ViT architecture
Uses Vision Transformer architecture, suitable for processing image data
Transfer learning
Fine-tuned based on a pre-trained model to adapt to specific classification tasks

Model Capabilities

Image classification
Visual feature extraction

Use Cases

Agriculture
Cassava disease identification
Inferred from the model name, it may be used for cassava crop disease classification
88.55% classification accuracy
General image classification
General object recognition
Can be used for various image classification tasks
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