  We explore the task of sentiment analysis on Hinglish (code-mixed
Hindi-English) tweets as participants of Task 9 of the SemEval-2020
competition, 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. During
the evaluation phase of the competition, we obtained an F-score of 71.3% with
our best model, which placed $4^{th}$ out of 62 entries in the official system
rankings.
