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Vit Base Roman Numeral
V
Vit Base Roman Numeral
Developed by farleyknight
A ViT-based image classification model for Roman numerals, fine-tuned on the farleyknight/roman_numerals dataset with an accuracy of 83.09%
Downloads 13
Release Time : 8/24/2022
Model Overview
This model is a Vision Transformer (ViT) fine-tuned on a Roman numeral recognition dataset, based on google/vit-base-patch16-224-in21k, specifically designed to identify Roman numeral symbols in images.
Model Features
High-precision recognition
Achieves 83.09% accuracy on the Roman numeral test set
ViT-based architecture
Utilizes the Vision Transformer base architecture with powerful image feature extraction capabilities
Lightweight fine-tuning
Efficient fine-tuning on a pre-trained model, saving training resources
Model Capabilities
Image classification
Roman numeral recognition
Visual feature extraction
Use Cases
Educational technology
Historical document digitization
Automatically identifies Roman numerals in ancient or historical documents
83.09% recognition accuracy
Educational app development
Used to develop auto-grading features in Roman numeral learning applications
Document processing
Automatic document classification
Automatically classifies documents based on Roman numeral page numbers
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