I’m trying to create an NLP Emotion Classification Model for a research project but kind of confused on where and how to start. I have this huge dataset of Reddit posts and want to classify each post into like 12 different emotion categories.

Is there a way to do this using existing models eg. BERT or can I also do this using unsupervised learning?

I have at least 12000 different posts and so want to avoid supervised learning because its going to take so long to label a set for training data also I might lose a lot of time doing that.

Whats the most efficient and accurate way to do this? Any help would be amazing!