tensorflow / tensorflow/recommenders
[Question] Batch metrics and Top K Factorized do not correlate.
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- Python
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Description
Hi!
I have a retrieval model which is showing the following behaviour:
- loss is reducing
- top k factorized is falling (degrading)
- top k batch metric is improving
- AUC (batch) is improving
Tweaking the model, I have seen this also swap around, but there have been a few configurations in which these metrics seem to not correlate.
I would really like to understand and learn under which conditions this is possible.
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First steps
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Research direction
The issue names Top K Factorized, the batch top-k metric, batch AUC, and loss, but no files, tests, or entry points. Start by locating the definitions of those metrics and comparing their evaluation conditions; done means documenting when their values can diverge and why.
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Assessment
- Tech stack
- python, tensorflow
- Domain
- machine-learning
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 15/100