  This paper describes the system submitted to Dravidian-Codemix-HASOC2020:
Hate Speech and Offensive Content Identification in Dravidian languages
(Tamil-English and Malayalam-English). The task aims to identify offensive
language in code-mixed dataset of comments/posts in Dravidian languages
collected from social media. We participated in both Sub-task A, which aims to
identify offensive content in mixed-script (mixture of Native and Roman script)
and Sub-task B, which aims to identify offensive content in Roman script, for
Dravidian languages. In order to address these tasks, we proposed pre-training
ULMFiT on synthetically generated code-mixed data, generated by modelling
code-mixed data generation as a Markov process using Markov chains. Our model
achieved 0.88 weighted F1-score for code-mixed Tamil-English language in
Sub-task B and got 2nd rank on the leader-board. Additionally, our model
achieved 0.91 weighted F1-score (4th Rank) for mixed-script Malayalam-English
in Sub-task A and 0.74 weighted F1-score (5th Rank) for code-mixed
Malayalam-English language in Sub-task B.
