If you don't mind me asking, what sentence embeddings model (bert/roberta/etc) did you have the best luck with for your classifier? I like the quick retrain that can be done with an approach like this, though I have found that if you throw too many different SPAM profiles at a classifier it starts to degrade, and you might have to build multiple and ensemble them. The embedding backend can help a lot with that.