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

WESSA at SemEval-2020 Task 9: Code-Mixed Sentiment Analysis using Transformers