Does incorporating intermediate tasks from high-resource non-English languages (e.g., Spanish, German) into multilingual model

Intermediate-task training---fine-tuning a pretrained model on an intermediate task before fine-tuning again on the target task---often improves model performance substantially on language understanding tasks in monolingual English settings. We investigate whether English intermediate-task training is still helpful on non-English target tasks. Using nine intermediate language-understanding tasks, we evaluate intermediate-task transfer in a zero-shot cross-lingual setting on the XTREME benchmark. We see large improvements from intermediate training on the BUCC and Tatoeba sentence retrieval tas

Research goal: Does incorporating intermediate tasks from high-resource non-English languages (e.g., Spanish, German) into multilingual model training improve zero-shot XTREME performance more than English-only intermediate tasks when measured by average accuracy across languages?

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