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Swin Base Finetuned Cifar100
This model is an image classification model fine-tuned on the CIFAR-100 dataset based on the Swin Transformer architecture, achieving an accuracy of 92.01%.
Downloads 119
Release Time : 12/23/2022
Model Overview
This is a vision model based on the Swin Transformer architecture, specifically fine-tuned for the CIFAR-100 image classification task.
Model Features
High Accuracy
Achieves 92.01% accuracy on the CIFAR-100 test set.
Based on Swin Transformer
Utilizes the advanced Swin Transformer architecture with powerful feature extraction capabilities.
Lightweight Fine-tuning
Efficient fine-tuning on pre-trained models, saving training resources.
Model Capabilities
Image Classification
Multi-class Recognition
Use Cases
Computer Vision
Object Recognition
Recognizes 100 common objects in the CIFAR-100 dataset.
92.01% accuracy
Educational Applications
Can be used for computer vision teaching and experiments.
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