open-compass / open-compass/VLMEvalKit
Finetuned LLaVA Model output
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- Python
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Description
Hi, I finetuned the LLaVA-v1.5-13B model and managed to benchmark it on a custom dataset.
I noticed, however, that when benchmarking the finetuned version on that dataset, I didn't get the QA pairs of each image, like I did during the standard model evaluation on that same dataset.
Is there a way to activate those?
Thank you.
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First steps
- Read the whole issue, then the project's contributing guide.
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Research direction
The issue does not name a file, test, or entry point. Start by comparing the standard-model and finetuned LLaVA evaluation paths, then determine where generated QA pairs are handled; the work is done when finetuned evaluation can expose the QA pairs for each image on the custom dataset.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- computer-vision, machine-learning, testing-qa
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100