How to use loss instead of accuray in HPO

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Describe the issue: I just started using nni and followed the /hpo_quickstart_pytorch/ example to inplement. But, instead of accuracy, I need to thave the main monitor and optimize for the loss, and the lower loss, the better, obviously.

I used nni.report_intermediate_result(valLossSingle) to report the loss. I think I need to let the tuner know that this is actually loss, rather than accuracy. How to do that?

Environment:

• NNI version: 2.7
• Training service (local|remote|pai|aml|etc): local
• Client OS: ubuntu
• Server OS (for remote mode only):
• Python version: 3.10
• PyTorch/TensorFlow version: 2
• Is conda/virtualenv/venv used?: conda
• Is running in Docker?: no

Configuration:

• Experiment config (remember to remove secrets!):
• Search space:

Log message:

• nnimanager.log:
• dispatcher.log:
• nnictl stdout and stderr:

How to reproduce it?: