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Beit Base Patch16 224 Pt22k Ft22k Finetuned Mnist
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Beit Base Patch16 224 Pt22k Ft22k Finetuned Mnist

Developed by Karelito00
Vision Transformer model based on BEiT architecture, fine-tuned on MNIST handwritten digit dataset, achieving 99.35% accuracy
Image Classification
Transformers
Open Source License:Apache-2.0#High-precision handwriting recognition#Lightweight image classification#Transfer learning optimization
Downloads 19
Release Time : 10/26/2022

Model Overview

This model is a fine-tuned version of Microsoft's BEiT base model for MNIST handwritten digit recognition, specifically designed for high-precision digit recognition

Model Features

High-precision digit recognition
Achieves 99.35% accuracy on MNIST test set
Based on BEiT architecture
Utilizes advanced Vision Transformer architecture with powerful feature extraction capabilities
Lightweight fine-tuning
Efficient fine-tuning on pre-trained model, saving training resources

Model Capabilities

Handwritten digit recognition
Image classification
Digital image feature extraction

Use Cases

Document processing
Handwritten digit recognition
Recognize handwritten digits in scanned documents
99.35% recognition accuracy
EdTech
Automatic grading system
Recognize digits in students' handwritten answers
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