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We explore the task of sentiment analysis on Hinglish (code-mixedHindi-English) tweets as participants of Task 9 of the SemEval-2020competition, known as the SentiMix task. We had two main approaches: 1)applying transfer learning by fine-tuning pre-trained BERT models and 2)training feedforward neural networks on bag-of-words representations. Duringthe evaluation phase of the competition, we obtained an F-score of 71.3% withour best model, which placed $4^{th}$ out of 62 entries in the official systemrankings.

Reed at SemEval-2020 Task 9: Fine-Tuning and Bag-of-Words Approaches to Code-Mixed Sentiment Analysis