  This paper describes the system of the LowResource Team for Task 2 of
BLP-2023, which involves conducting sentiment analysis on a dataset composed of
public posts and comments from diverse social media platforms. Our primary aim
is to utilize BanglaBert, a BERT model pre-trained on a large Bangla corpus,
using various strategies including fine-tuning, dropping random tokens, and
using several external datasets. Our final model is an ensemble of the three
best BanglaBert variations. Our system has achieved overall 3rd in the Test Set
among 30 participating teams with a score of 0.718. Additionally, we discuss
the promising systems that didn't perform well namely task-adaptive pertaining
and paraphrasing using BanglaT5. Training codes and external datasets which are
used for our system are publicly available at
https://github.com/Aunabil4602/bnlp-workshop-task2-2023
