How to choose a base model while fine tuning
Hello. I am new to NLP. I am researching how huggingface can best be utilized for a use case in my organization. Use case is - support ticket categorization. This seems like atext-classificationtask. I am planning to fine tune a base model based on the organization’s dataset.My question is - How to choose the best base model that suits my purpose. I have seen in thedocumentationthat, although the task istext-classification, butfill-maskmodel is used. Here the task in text-classification butdistilbert-base-uncasedmodel is used which isfill-masktype.So, is it okay if any NLP base model is used for training? How does that work?