mlcommons / mlcommons/algorithmic-efficiency
schedule-free adamw: Analyze why jax performed better than pytorch on finewebedu workload
Open
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 425
- Forks
- 78
- PR merge metrics
- No merged PRs in 30d
Description
schedule free adamw:
adamw:
Contributor guide
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
No files, tests, or entry points are mentioned. Start by reproducing the FineWebEdu workload comparison for schedule-free AdamW and AdamW, then investigate the JAX and PyTorch benchmark configurations; done means documenting the cause of the performance difference and supporting evidence.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning, performance
- Issue type
- Bug
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100