layoutlmv3-finetuned-invoice
| Property | Value |
|---|---|
| Framework | PyTorch 1.11.0 |
| Training Steps | 2000 |
| Final Accuracy | 100% |
| Author | Theivaprakasham |
What is layoutlmv3-finetuned-invoice?
This is a specialized version of Microsoft's LayoutLMv3-base model, fine-tuned specifically for invoice processing. The model demonstrates exceptional performance in extracting key information from invoice documents, achieving perfect scores across precision, recall, F1, and accuracy metrics.
Implementation Details
The model was trained using a carefully optimized process with Adam optimizer, utilizing a learning rate of 1e-05 and linear scheduler. Training was conducted over 40 epochs with 2000 steps, using batch sizes of 2 for both training and evaluation.
- Trained on invoice dataset for specific field extraction
- Optimized for identifying Biller Name, Address, Post Code, Dates, GST, Invoice Numbers, and Amounts
- Achieves 100% accuracy in final evaluation
Core Capabilities
- Precise extraction of invoice information
- Perfect recognition of key invoice fields
- Robust performance across different invoice layouts
- Integration-ready for automated invoice processing systems
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its perfect accuracy scores across all metrics (precision, recall, F1, accuracy) in invoice processing, achieved through careful fine-tuning of the LayoutLMv3 architecture.
Q: What are the recommended use cases?
The model is ideal for automated invoice processing systems, accounts payable automation, and any application requiring precise extraction of structured information from invoice documents.
