Comments (2)
sfalkner
commented on August 11, 2024
This behavior is totally expected. You can find an explanation here in the best practices.
The TLDR is, more workers make only sense if you run enough iterations.
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JarnoRFB
commented on August 11, 2024
Thanks for your answer. I could swear I read this passage several times... Anyway, after reading the section about parallelization in the paper again things became a lot clearer. I wrote a little function to understand how BOBH will behave given its hyperparameters in #43. Maybe that is useful for others as well.
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Related Issues (20)
- A bunch of errors when using categoricals
- Interferance between two BOHB instances when they have the same networking parameters? HOT 2
- Why get_incumbent_id selects the incumbent only from runs with max_budget? HOT 1
- How to stop a worker
- How to plot pictures like your work
- Support scipy 1.3+ HOT 1
- Download code button for keras example is not working
- Missing Optimizer
- Minor documentation fixes
- Machine precision problem in determening s_max
- Fit reinforcement learning model with hyperparameter optimization method
- Hyperband bracket generation is inconsistent with the original Hyperband paper HOT 1
- Continuing from running halfway
- Warm start: results.json and configs.json (from live json_result_logger) do not contain results from previous runs HOT 3
- "Ideally, the optimizer would adjust the budgets online" -- when will it be implemented and using what method?
- Issue in case of warmstarting case
- Saving optimization process HOT 1
- conda package? HOT 2
- License file for conda package
- some problem HOT 1
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