# Average Loss in optimization output

**URL:** <https://discourse.pymc.io/t/average-loss-in-optimization-output/372>\
**Category:** Questions\
**Created:** [September 27, 2017, 4:51pm UTC](https://discourse.pymc.io/t/average-loss-in-optimization-output/372 "2017-09-27T16:51:21Z")\
**Posts on this page:** 1\
**Page:** 2

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**Author:** ![mkesin](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/mkesin/32/992_2.png) [@mkesin](https://discourse.pymc.io/u/mkesin)\
**Post date:** [July 20, 2018, 6:39pm UTC](https://discourse.pymc.io/t/average-loss-in-optimization-output/372/22 "2018-07-20T18:39:48Z")

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So I’ve run into a situation where the loss first decreases with number of samples then increases. Should I assume that the model deteriorated based on this? (something in me says “no” but I can’t justify the intuition)

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