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I Want To Clone An Experiment And Then Try With A Different Hyperparameter Value . I Was Wondering If There Is A Way To Explicitly Specify A Hyperparameter. Right Now, I Guess Its Picking It Up From Tensorboard And I Don'T See The Hyperparameters That Are

I want to clone an experiment and then try with a different hyperparameter value . I was wondering if there is a way to explicitly specify a hyperparameter. Right now, I guess its picking it up from tensorboard and I don't see the hyperparameters that are of interest. I don't even see the learning rate . (I am using tf keras)

  
  
Posted 4 years ago
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Answers 5


I only see these tensorflow flags and not any of the actual hyperparameters

  
  
Posted 4 years ago

I think I figured it out. I need to use argparse to set the hyperparameters. Then it logs it automatically

  
  
Posted 4 years ago

Hi FriendlyKoala70 , sorry for replying only now...
You are correct - you can use argparse to define hyper parameters that will be automatically logged and visible in the WebApp. You can check out the https://github.com/allegroai/trains/blob/master/examples/hyper_parameters_example.py to see this and other ways you can report and connect hyper-parameters to your experiment.

  
  
Posted 4 years ago

Or you can do:
param={'key': 123}
task.connect(param)

  
  
Posted 4 years ago

Thanks .. I tried both the approaches.

  
  
Posted 4 years ago
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