🛡️ InvoiceGuard LayoutLMv3 Invoice Extractor

Fine-tuned microsoft/layoutlmv3-base model for multimodal token classification and Key Information Extraction (KIE) on commercial invoices.

Model Details

• Base Architecture: microsoft/layoutlmv3-base
• Task: Multimodal Document Token Classification
• Dataset: Kwash67/layoutlmv3-invoice-dataset (~2,043 train / 70 val / 125 test)
• Training Epochs: 12 (lr=3e-5, warmup=10%, batch=4, grad_acc=2)
• Mixed Precision: fp16

Test Set Metrics (Seqeval Entity-Level)

Metric	Score
Overall F1	0.7244
Overall Precision	0.7167
Overall Recall	0.7324

InvoiceGuard Schema Mapping

Maps dataset entities to 21 canonical InvoiceGuard fields: invoice_number, invoice_date, due_date, seller, client, seller_tax_id, client_tax_id, iban, item_desc, item_qty, item_net_price, item_net_worth, item_vat, item_gross_worth, subtotal, total_vat, total_gross_worth, currency, discount, shipping, payment_terms.

Limitations

• Optimized for invoices with bounding boxes normalized to [0..1000].
• Highly dependent on OCR word-level segmentation accuracy.