Swin Tiny Patch4 Window7 224 Finetuned Main Gpu 20e Final
A fine-tuned image classification model based on the Swin Transformer architecture, achieving 99.17% validation accuracy on the image folder dataset
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Release Time : 3/16/2023
Model Overview
This model is a fine-tuned image classification model based on microsoft/swin-tiny-patch4-window7-224, suitable for general image classification tasks
Model Features
High accuracy
Achieves 99.17% classification accuracy on the validation set
Swin Transformer architecture
Utilizes the advanced Swin Transformer architecture with hierarchical feature representation capabilities
Efficient fine-tuning
Fine-tuned for 20 epochs based on a pre-trained model for rapid convergence
Model Capabilities
Image classification
Feature extraction
Transfer learning
Use Cases
General image classification
Object recognition
Identify the main object categories in images
Achieves 99.17% accuracy on the validation set
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