  Code-mixing is a frequent communication style among multilingual speakers
where they mix words and phrases from two different languages in the same
utterance of text or speech. Identifying and filtering code-mixed text is a
challenging task due to its co-existence with monolingual and noisy text. Over
the years, several code-mixing metrics have been extensively used to identify
and validate code-mixed text quality. This paper demonstrates several inherent
limitations of code-mixing metrics with examples from the already existing
datasets that are popularly used across various experiments.
