SciML / SciML/EasyModelAnalysis.jl
Stopping criteria in the callback
Open
Nobody has claimed this yet.
- Dominant language
- Julia
- Stars
- 87
- Forks
- 14
- Avg merge
- 21h 12m
- Merged PRs (30d)
- 19
Description
- Absolute tolerance to stop at for the gradient
- If we have validation data, then stop of "validation starts to go up"
- Come up with a good heuristic
- Don't need to store previous data
- Support a stop button via a global boolean for exiting
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
Start with the callback implementation and trace how gradient and validation data are currently exposed. Determine how the requested absolute tolerance, validation increase heuristic, and global-boolean stop button should be observed. Done means the callback supports all three stopping conditions and exits when any requested condition is met.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100