For text classification, how are these 2 different?

Hi,

I read somewhere about these 2 approaches for text classification

1. BERT + a new head layer: freeze the BERT, train the new head layer
2. SBERT + logistic regression: use SBERT to generate the embedding, and train the logistic layer as a traditional classifier

How are these 2 different? I believe in approach #1, the head layer is just a regular feed forward, which is not much different from a logistic regression. Both are using LLM to convert …

bert classification classifier embedding generate head languagetechnology layer logistic regression regression sbert text text classification train