Fine‑Tuning Qwen‑Video‑8B with LLaMA‑Factory for Domain‑Specific Video Understanding

Multimodal Learning Overview

Multimodal learning leverages data from different senses (text, image, audio, video) to train models that can perceive and reason across modalities.

Challenges in Domain‑Specific Video Understanding

Domain knowledge gap : models struggle with industry‑specific terminology and context.

Weak temporal modeling : insufficient capture of dynamic relationships between frames.

Insufficient multimodal fusion : limited joint reasoning among visual, audio, and subtitle streams.

Project Overview: Qwen‑Video‑8B + LLaMA‑Factory

The project fine‑tunes the Qwen3‑VL‑8B‑Instruct model using the LLaMA‑Factory framework to inject domain knowledge, strengthen temporal modeling, and improve multimodal reasoning for long‑video understanding.

Key Steps

Data preparation : Selected 408 city‑scenery clips from the MiraData dataset, converted them to the LLaMA‑Factory format, and split into train/validation/test sets.

Baseline model testing : Ran the original Qwen‑Video model on random clips to obtain reference outputs.

English‑corpus LoRA fine‑tuning : Loaded an English LoRA adapter, trained on the English subtitles, and adjusted hyper‑parameters as needed.

Chinese‑corpus LoRA fine‑tuning : Repeated the process with Chinese subtitles, ensuring data format matches Chinese requirements and tuning learning rates.

Result inspection : Compared baseline, English‑fine‑tuned, and Chinese‑fine‑tuned outputs, observing improvements in conciseness, accuracy, and fluency.

Result Highlights

Baseline outputs provide the most detailed scene description. The English fine‑tuned model yields concise and precise captions, while the Chinese fine‑tuned model delivers vivid, context‑aware descriptions that align with human expectations.

Sample output quality meets the standard “scene‑correct + detail‑rich + semantic‑consistent”.

Potential Applications

Tourism: automatic generation of promotional video narrations.

Security: precise detection of abnormal behaviors in surveillance footage.

Online education: extraction of key points from experimental or procedural videos.

Industrial quality inspection: understanding production‑line videos to spot non‑standard steps.

Platform Support

The Lab4AI platform supplies the compute power and data infrastructure needed for the entire workflow, from model reproduction to inference.