Multilingual Intermediate-Task Training and Zero-Shot Transfer Accuracy on XTREME-R Subsets

Abstract

Abstract: 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 Question

How does multilingual intermediate-task training affect zero-shot transfer accuracy on XTREME-R subsets compared to English-only intermediate training?

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