| Property | Value |
|---|---|
| Parameter Count | 125M |
| Model Type | Token Classification |
| Base Model | microsoft/layoutlmv3-base |
| Performance Metrics | F1: 90.78%, Accuracy: 83.30% |
What is layoutlmv3-finetuned-funsd?
This is a specialized document understanding model based on Microsoft's LayoutLMv3 architecture, fine-tuned on the FUNSD dataset. It represents a significant advancement in document AI, combining visual and textual information processing capabilities to understand document layouts and extract structured information.
Implementation Details
The model was trained using the Adam optimizer with a learning rate of 1e-05 and linear scheduling across 1000 training steps. It employs both F32 and I64 tensor types and was trained with a batch size of 16.
- Training duration: 100 epochs
- Precision: 90.26%
- Recall: 91.30%
- F1 Score: 90.78%
- Accuracy: 83.30%
Core Capabilities
- Document layout analysis
- Token classification for form understanding
- Visual-linguistic document processing
- Structured information extraction
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its high-performance metrics in document understanding tasks, achieving over 90% F1 score. It's particularly effective at combining visual and textual information for form understanding tasks.
Q: What are the recommended use cases?
The model is ideal for processing structured documents, forms, and receipts where understanding both the text content and its spatial layout is crucial. It's particularly well-suited for automated document processing systems and information extraction from forms.