# Overwritting the default metric parameter

**URL:** <https://discuss.ray.io/t/overwritting-the-default-metric-parameter/6067>\
**Category:** Ray Tune\
**Created:** [May 8, 2022, 10:02pm UTC](https://discuss.ray.io/t/overwritting-the-default-metric-parameter/6067 "2022-05-08T22:02:17Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![RIPUVENDRA\_SINGH](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/ripuvendra_singh/32/2497_2.png) [@RIPUVENDRA\_SINGH](https://discuss.ray.io/u/RIPUVENDRA_SINGH)\
**Post date:** [May 8, 2022, 10:02pm UTC](https://discuss.ray.io/t/overwritting-the-default-metric-parameter/6067/1 "2022-05-08T22:02:17Z")

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Hi i am new to raytune , and while trying some example i got stuck at a point

I know that we have to pass a “metric” and “mode” for comparing the results of various trials while hyperparameter tuning process.

I want to compare various trials based on AUROC metric based on “max” mode ,  
can you please help me to overwrite the “\_metric/val\_loss” with AUROC, (i don’t know what modification i have to make for that). Thank you !!

Here i am attaching the colab notebook for your reference

[Google colab notebook link](https://colab.research.google.com/drive/1z2Dcw-n2s4qSghvyYXH9xPxL844lnOPK?usp=sharing)

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**Author:** ![matthewdeng](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/matthewdeng/32/1446_2.png) [@matthewdeng](https://discuss.ray.io/u/matthewdeng)\
**Post date:** [May 10, 2022, 3:53am UTC](https://discuss.ray.io/t/overwritting-the-default-metric-parameter/6067/2 "2022-05-10T03:53:31Z")

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Hey @RIPUVENDRA_SINGH, thanks for the question. I’m not familiar with `pytorch_widedeep`, but I took a look at [their example](https://github.com/jrzaurin/pytorch-widedeep/blob/master/examples/notebooks/10_hyperParameter_tuning_w_raytune_n_wnb.ipynb) and it looks like in their call to `analysis.results` all their metrics are being tracked, but in your notebook it looks like it’s missing auroc is missing from `_metrics`.

1. Perhaps as a first step you can look into seeing why auro isn’t being calculated/returned in the metrics.
2. After this, you should be able to change `metric="_metric/val_loss"` to `metric="_metric/val_auroc"` (or whatever the produced metric name is).