# BERT Model always with different results

**URL:** </static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fbert-model-always-with-different-results%2F13805%3E%5C
**Category:** Beginners\
**Created:** [January 17, 2022, 2:53pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fbert-model-always-with-different-results%2F13805 "2022-01-17T14:53:34Z")\
**Posts on this page:** 1\
**Page:** 1

<div class="post-metadata">

**Author:** ![vivalab](https://avatars.discourse-cdn.com/v4/letter/v/8e7dd6/32.png) [@vivalab](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Fvivalab)%5C
**Post date:** [January 17, 2022, 2:53pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fbert-model-always-with-different-results%2F13805%2F1 "2022-01-17T14:53:34Z")

</div>

Hello,

i have trained different BERT models to evaluate which of these models perform best with my dataset.  
At the moment I got the problem that I always get different results when running the model again (e.g. run a new colab session).  
For a reproducible evaluation I want to get always the same results (e.g. F1) but I don’t know how to do this.  
I have ensured that my train/test/validation split is always the same. I have read that it could have something to do with the Dropout of the model, but what do I have to change if I want the output to be every time the same?

Thanks in advance!