Problems involving code-mixed language are often plagued by a lack of\nresources and an absence of materials to perform sophisticated transfer\nlearning with. In this paper we describe our submission to the Sentimix\nHindi-English task involving sentiment classification of code-mixed texts, and\nwith an F1 score of 67.1%, we demonstrate that simple convolution and attention\nmay well produce reasonable results.\n