  In this paper, we describe our system submitted for SemEval 2020 Task 9,
Sentiment Analysis for Code-Mixed Social Media Text alongside other
experiments. Our best performing system is a Transfer Learning-based model that
fine-tunes "XLM-RoBERTa", a transformer-based multilingual masked language
model, on monolingual English and Spanish data and Spanish-English code-mixed
data. Our system outperforms the official task baseline by achieving a 70.1%
average F1-Score on the official leaderboard using the test set. For later
submissions, our system manages to achieve a 75.9% average F1-Score on the test
set using CodaLab username "ahmed0sultan".
