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Swin Tiny Patch4 Window7 224 Finetuned Eurosat
An image classification model based on the Swin Transformer Tiny architecture, fine-tuned on the CIFAR10 dataset with an accuracy of 97.24%
Downloads 16
Release Time : 3/8/2023
Model Overview
This model is a vision Transformer based on Microsoft's Swin Transformer Tiny architecture, specifically fine-tuned for the CIFAR10 image classification task.
Model Features
High Accuracy
Achieves 97.24% accuracy on the CIFAR10 test set
Efficient Architecture
Utilizes Swin Transformer's hierarchical window attention mechanism to balance computational efficiency and performance
Fine-tuning Optimization
Optimized for specific tasks on the base model to enhance performance in target domains
Model Capabilities
Image Classification
Visual Feature Extraction
Use Cases
Computer Vision
CIFAR10 Image Classification
Classifies images of 10 categories in the CIFAR10 dataset
Accuracy: 97.24%
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