In this paper we describe our submission to GramEval2020 competition on morphological tagging, lemmatization and dependency parsing. Our model uses biaffine attention over the BERT representations. The main feature of our work is the extensive usage of language model, tagger and parser fine-tuning on several distinct genres and the implementation of genre classifier. To deal with dataset idiosyncrasies we also extensively apply handwritten rules. Our model took second place in the overall model performance scoring 90.8 aggregate measure over all 4 tasks