Practical Guide to Fine-Tuning Vision-Language Models Based on LLaMA-Factory: Document Understanding and Chart Parsing

Introduction / Main Post: Practical Guide to Fine-Tuning Vision-Language Models Based on LLaMA-Factory: Document Understanding and Chart Parsing

This article introduces a fine-tuning project for Vision-Language Models (VLM) based on the LLaMA-Factory framework, focusing on document understanding, chart parsing, and visual question answering tasks. The project demonstrates how to use LoRA and full fine-tuning techniques to enhance the performance of VLMs in specific domains, and provides complete architecture design, training workflow, and performance evaluation results.