  This paper presents our work for the Violence Inciting Text Detection shared
task in the First Workshop on Bangla Language Processing. Social media has
accelerated the propagation of hate and violence-inciting speech in society. It
is essential to develop efficient mechanisms to detect and curb the propagation
of such texts. The problem of detecting violence-inciting texts is further
exacerbated in low-resource settings due to sparse research and less data. The
data provided in the shared task consists of texts in the Bangla language,
where each example is classified into one of the three categories defined based
on the types of violence-inciting texts. We try and evaluate several BERT-based
models, and then use an ensemble of the models as our final submission. Our
submission is ranked 10th in the final leaderboard of the shared task with a
macro F1 score of 0.737.
