How does intermediate-task training on high-resource non-English languages affect zero-shot transfer accuracy on the XCOPA and
Description
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: How does intermediate-task training on high-resource non-English languages affect zero-shot transfer accuracy on the XCOPA and XNLI subsets of the XTREME benchmark compared to English-only fine-tuning?
Autonomous synthesis report generated by Assignee Research. Tribunal consensus score: 8.7/10.
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