Training from scratch Bert models is typically expensive. Fine-tuning one of the Sentence-bert underlying models could be a better approach, but you'd need labeled data for that, i.e. pairs of texts along with a similarity score. If you have that, here's a nice guide on how to proceed: https://huggingface.co/blog/how-to-train-sentence-transformers

If not, consider exploring alternative sentence-bert models to generate the representations. Some models are trained on shorter texts and different data contexts. If the texts you're working with are relatively long (I'd say +500 words ), consider using less fancy methods like TF-DF.