Swin-Tiny Open-Source Vision Model - Free Deployment to Boost Image Classification, Good Results after 10 Rounds of Fine-Tuning

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Swin Tiny Patch4 Window7 224 Finetuned Og Dataset 10e

Developed by Gokulapriyan

Vision model based on Swin Transformer Tiny architecture, fine-tuned for 10 epochs on image classification tasks

Image Classification

Transformers

Open Source License:Apache-2.0 #Image Classification Fine-tuning #High-precision Classification #Swin-Transformer

Downloads 19

Release Time : 2/16/2023

Model Overview

This is a computer vision model based on the Swin Transformer Tiny architecture, fine-tuned for 10 epochs on the original dataset, suitable for image classification tasks.

Model Features

Efficient Transformer Architecture

Adopts Swin Transformer architecture, reducing computational complexity while maintaining high performance

High Accuracy

Achieves 98.15% accuracy on the evaluation set

Fast Inference

Can process 71.796 samples per second, suitable for real-time applications

Model Capabilities

Image Classification

Feature Extraction

Visual Representation Learning

Use Cases

Computer Vision

General Image Classification

Classify and recognize input images

Evaluation accuracy 98.15%

Visual Feature Extraction

Extract high-level feature representations of images

Property	Details
Model Type	swin-tiny-patch4-window7-224-finetuned-og_dataset_10e
Training Data	imagefolder

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Swin Tiny Patch4 Window7 224 Finetuned Og Dataset 10e

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 swin-tiny-patch4-window7-224-finetuned-og_dataset_10e

🚀 Quick Start

📚 Documentation

Training and evaluation data

Training procedure

Training hyperparameters

Framework versions

📄 License