I want to use spacy
's pretrained BERT model for text classification but I'm a little confused about cased/uncased
models. I read somewhere that cased
models should only be used when there is a chance that letter casing will be helpful for the task. In my specific case: I am working with German texts. And in German all nouns start with the capital letter. So, I think, (correct me if I'm wrong) that this is the exact situation where cased
model must be used. (There is also no uncased
model available for German in spacy
).
But what must be done with data in this situation?
Should I (while preprocessing train data) leave it as it is (by that I mean not using the .lower()
function) or it doesn't make any difference?