# Bert and SVM classification

I'm trying to understand the concepts in the title and how they fit into the task of binary classification. According to my understanding so far, you can encode text using various feature-extraction methods such a bag of words. You can then use something like liblinear to obtain a SVM LibLinear model that is able to classify your data. On the other hand, you can build a model by concatenating Bert with a Dense layer. You can then fine tune this model and again, you obtain a classifier. Where would you use either one of them and why?