The adapter-based approach may face potential limitations when handling languages with significantly different writing systems or morphological complexity compared to the modern languages used in pre-training. One limitation is the reliance on subword tokenization, which may not adequately capture the unique morphological features of languages with complex morphological structures. Subword tokenization may struggle to represent intricate morphological phenomena present in languages with rich inflectional or agglutinative systems. Additionally, languages with non-alphabetic scripts or logographic writing systems may pose challenges for the model in terms of tokenization and representation of characters. The model may struggle to capture the semantic and syntactic nuances encoded in the characters of such languages, leading to suboptimal performance in tasks requiring understanding of complex writing systems.