  Sarcasm is a form of figurative language where the intended meaning of a
sentence differs from its literal meaning. This poses a serious challenge to
several Natural Language Processing (NLP) applications such as Sentiment
Analysis, Opinion Mining, and Author Profiling. In this paper, we present our
participating system to the intended sarcasm detection task in English and
Arabic languages. Our system\footnote{The source code of our system is
available at \url{https://github.com/AbdelkaderMH/iSarcasmEval}} consists of
three deep learning-based models leveraging two existing pre-trained language
models for Arabic and English. We have participated in all sub-tasks. Our
official submissions achieve the best performance on sub-task A for Arabic
language and rank second in sub-task B. For sub-task C, our system is ranked
7th and 11th on Arabic and English datasets, respectively.
