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Layoutlmv3 Finetuned Sroie

Developed by Theivaprakasham
A document understanding model fine-tuned on the SROIE dataset based on Microsoft's LayoutLMv3-base model, excelling in extracting structured information from scanned documents
Downloads 409
Release Time : 6/7/2022

Model Overview

This model is specifically designed for document information extraction tasks, capable of identifying and classifying key fields in documents such as receipts (e.g., date, amount, merchant information)

Model Features

High-precision Document Understanding
Achieves 94% F1 score on the SROIE dataset, accurately identifying key information in receipts
Multimodal Processing Capability
Simultaneously processes text content and visual layout information to enhance document understanding
End-to-end Training
Supports direct information extraction from raw document images without complex preprocessing

Model Capabilities

Receipt Information Extraction
Document Entity Recognition
Structured Data Generation
Visual Text Understanding

Use Cases

Financial Automation
Receipt Information Digitization
Automatically extracts merchant, amount, date, and other information from scanned receipts
Accuracy exceeds 99%, with an F1 score of 94%
Document Processing
Invoice Information Extraction
Identifies key fields in invoices and generates structured data
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