# Text wrangling before classification

**URL:** </static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Ftext-wrangling-before-classification%2F6069%3E%5C
**Category:** 🤗Transformers\
**Created:** [May 7, 2021, 5:45pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Ftext-wrangling-before-classification%2F6069 "2021-05-07T17:45:31Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![DanDanDan](https://avatars.discourse-cdn.com/v4/letter/d/eada6e/32.png) [@DanDanDan](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2FDanDanDan)%5C
**Post date:** [May 7, 2021, 5:45pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Ftext-wrangling-before-classification%2F6069%2F1 "2021-05-07T17:45:32Z")

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Hi!  
I’m performing sentiment classification on some sentences.  
What I do is I fine-tune RoBERTa on a subset of my data.  
My question is what text wrangling I should perform?  
Should I lowercase, stem, remove punctuation?  
With a simpler model (logistic regression, tree, etc.), I would definitely do all of these things, but I’m not sure what to do when I use a transformer.