JuliaAI / JuliaAI/MLJIteration.jl
Feedback from a serious user
Nobody has claimed this yet.
- Dominant language
- Julia
- Stars
- 12
- Forks
- 3
- PR merge metrics
- No merged PRs in 30d
Description
I received some feedback from a valued user which I thought might be useful to post here for the record:
I don't remember having many problems with IteratedModel, so I was able to do all I wanted with little effort. It provides a lot of options off-the-shelf in an intuitive way. I only needed to spend some time thinking about two things:
- How to do learning-rate (LR) scheduling through this feature. A complication is that the
Adamtype is immutable, so whenever I wanted to update the LR, I had to get its value, alter it, and create a new Adam instance with it. - The difference between "control cycles" and
Step(n)and how they relate to training batches and epochs when using NNs. Understanding all these "progress measures" is needed to define how often the LR will be updated. When using decay, if updates are too frequent, the LR vanishes too fast and training halts
Contributor guide
No contributing guide indexed for this repository
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
Review the IteratedModel and Adam usage described in the issue, focusing on learning-rate scheduling and the relationship between control cycles, Step(n), batches, and epochs. Done should make these concepts and scheduling choices understandable to users without requiring the original investigation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- machine-learning
- Issue type
- Documentation
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100