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Hi Everyone!
Is Anybody Using Log-Scale Parameter Ranges For Hyper-Parameter Optimization? It Seems That There Is A Bug In The Hpbandster Module. I'M Getting Negative Learning Rates..
GreasyLeopard35 from the implementation:
https://github.com/allegroai/clearml/blob/fcad50b6266f445424a1f1fb361f5a4bc5c7f6a3/clearml/automation/parameters.py#L215
Which basically returns the "self.base" (default) 10 to the power of the selected value:10**-3 = 0.001
So how would I get a negative value ?
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