  Sentiment analysis of social media posts and comments for various marketing
and emotional purposes is gaining recognition. With the increasing presence of
code-mixed content in various native languages, there is a need for ardent
research to produce promising results. This research paper bestows a tiny
contribution to this research in the form of sentiment analysis of code-mixed
social media comments in the popular Dravidian languages Kannada, Tamil and
Malayalam. It describes the work for the shared task conducted by
Dravidian-CodeMix at FIRE 2021 by employing pre-trained models like ULMFiT and
multilingual BERT fine-tuned on the code-mixed dataset, transliteration (TRAI)
of the same, English translations (TRAA) of the TRAI data and the combination
of all the three. The results are recorded in this research paper where the
best models stood 4th, 5th and 10th ranks in the Tamil, Kannada and Malayalam
tasks respectively.
