open-compass / open-compass/VLMEvalKit
How to evaluate my fine-tuned Qwen-VL model on a locally downloaded dataset?
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Description
Hi all,
Thanks very much for your great repo. Now I have the following scenario but I can't figure out what to do by only reading the documentations. I have a fine-tuned Qwen-VL model (locally) which can be loaded by transformers.AutoModelForVision2Seq.from_pretrained, and a HallusionBench dataset (to which I've made some modifications to the images inside) which can be loaded by datasets.load_from_disk. How to evaluate the model and test on my own local modified HallusionBench dataset? Also, is setting CUDA_VISIBLE_DEVICES enough for setting the GPUs to use, and how is batch size determined in the evaluation process?
Appreciations for your help!
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Research direction
The issue names no repository file, test, or evaluation entry point. Start with the documentation around HallusionBench and compare the expected inputs with a model loaded by AutoModelForVision2Seq.from_pretrained and data loaded by datasets.load_from_disk; document the local-dataset procedure, CUDA_VISIBLE_DEVICES behavior, and batch-size handling.
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Assessment
- Tech stack
- python
- Domain
- computer-vision, documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 45/100