Issue with new models
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- Dominant language
- Python
- Stars
- 1k
- Forks
- 131
- PR merge metrics
- No merged PRs in 30d
Description
I'm not sure if this is the correct place to raise this issue and tbh I'm pretty sure alotta people have raised it.
But why are the results of the new models still consistently worse than 2.3?
It seems that quality has peaked around that point and both 3.1 3.8 and 3.9 performed worse than 2.3 quality wise, although being much better speed wise.
Is it an issue with training or a change in code?
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Compare the reported quality and speed of models 2.3, 3.1, 3.8, and 3.9 using the project's model entry points and evaluation process. Determine whether the regression comes from training or a code change; done means identifying a reproducible cause and documenting the comparison.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- computer-vision, machine-learning
- Issue type
- Bug
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 15/100