My task involves Greek text used by a branch of the Greek State Administration. To accomplish my set objectives I will use the large Greek Spacy model, for a starter.
However, since the text is specialized, I would like to fine-tune the Spacy Greek model using the particular Corpus. I refer to unsupervised learning. My hope is that following the fine-tuning, the performance of the existing Greek SPACY model will improve when it comes to NER tasks with documents originating from the aforementioned Corpus.
Could you please advise how such fine-tuning can be accomplished? Please be generous in suggesting possible answers, tutorials and pertinent links if you happen to know of.
In general we can only provide limited support for spaCy-only questions that don't involve Prodigy directly here, as we need to make sure the forum stays more or less on-topic. Fortunately spaCy has quite an active community, so you should be able to find a lot of information from other users, and if you need more direct help there are several consultants who know the software well.