Hi @Kwiebes1995,
You don’t need to put a SEP token between each sentence.   The SEP token is intended particularly for tasks like Next Sentence Prediction, where you are predicting whether a second sentence logically follows a first sentence.
In some cases, you will want to use only one text, that can be made up of lots of sentences.  If so, you would have a SEP token at the very end of the text only.   In which case, I think the segment_ids would all be 0, and I think you wouldn’t need to define it because it is an optional parameter.
Since you have only used one MASK token in the whole text, I assume you are treating the whole text as one input. Is that correct?    If so, then I don’t think you should separate the text into sentences.
You can still make a tensor out of a single input text (if the model is expecting a tensor): it will just have a dimension of 1 in that direction.
[I might have misunderstood what you are doing.  I’ve only used BertForSequenceClassification.]