text: Title: How to use loss instead of accuray in HPO
  Body: **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: 
   
  <!--
  Where can you find the log files:
  LOG: https://github.com/microsoft/nni/blob/master/docs/en_US/Tutorial/HowToDebug.md#experiment-root-director
  STDOUT/STDERR: https://nni.readthedocs.io/en/stable/reference/nnictl.html#nnictl-log-stdout
  -->
  
  
  **How to reproduce it?**: 