the loss suddenly increases
Nobody has claimed this yet.
Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 25/100
- Issue type
- Bug
- Clarity
- Needs clarification
- Activity status
- Stale
- Tech stack
- python
- Domain
- machine-learning
Research direction
Start by locating the model-training loop that calls net.update() with net = DMC(), then inspect how the loss changes around iterations 300–400. Determine whether the update is expected once per iteration and identify the cause of the sudden loss increase. Done means the training behavior and update frequency are explained from the existing code.
Written by the indexing model from the issue text.
Description
Why does the loss suddenly increase by several times after three to four hundred iterations during model training? Another question is, during each iteration of training, does the function net.update() need to run once (with net = DMC())?
- Dominant language
- Python
- Stars
- 829
- Forks
- 138
- PR merge metrics
- No merged PRs in 30d
Getting set up
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.
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