Tag: computer-vision

This article explores the process of fine-tuning Vision Language Models (VLMs) for improved document understanding and data extraction. It covers the motivation, advantages of VLMs over traditional OCR, dataset preparation, annotation strategies, and technical details of supervised fine-tuning (SFT). The guide emphasizes the importance of data quality, meticulous parameter tuning, and presents results demonstrating the effectiveness of fine-tuning for tasks like handwriting recognition and text extraction from images.