@stefan-it thanks for your reply!
The domain of my docs is indeed very different.
I will train the tokenizer and see what is the overlap to determine the applicability of training from scratch.
Thanks for the link to the parper too.

What are your downstream tasks for evaluation btw. 

Classification, NER and embeddings (similarity search)
@rsk97

Not completely sure, but if you change the tokeniser you’ll have to retrain the model as well, cause the model would have never seen these “new” tokens that you have.

This is true, but my understanding of @chrisdoyleIE 's answer  is that extending the existing vocabulary still goes into the flow for fine-tuning, as the internal representation of already existing tokens will not change, am I right?