Swin-Tiny-Patch4-Window7-224-Finetuned-EuroSAT open-source image classification model with over 97% image classification accuracy

Swin Tiny Patch4 Window7 224 Finetuned Eurosat

Developed by nielsr

A fine-tuned image classification model based on the Swin Transformer architecture, achieving 97.44% accuracy on the image folder dataset

Downloads 51

Release Time : 4/12/2022

Model Overview

This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 for image classification tasks, excelling in image classification tasks

High accuracy

Achieves 97.44% classification accuracy on the evaluation set

Based on Swin Transformer

Utilizes the advanced Swin Transformer architecture with excellent visual feature extraction capabilities

Lightweight model

Designed with tiny variant, suitable for deployment in resource-constrained environments

Image classification

Visual feature extraction

Remote sensing image analysis

Land cover classification

Classify different land types in satellite images

97.44% accuracy

General image classification

Object recognition

Identify main object categories in images

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.2621	1.0	190	0.1083	0.9630
0.1769	2.0	380	0.1425	0.95
0.1343	3.0	570	0.0664	0.9744

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