Impact of Intermediate English Task Training on XTREME-R Low-Resource Language Robustness

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

To what extent does English intermediate-task training degrade robustness on low-resource language subsets of XTREME-R compared to direct target-language fine-tuning?

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