Zero-shot cross-lingual performance comparison of English-only versus multilingual intermediate task training in XTREME-R
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 the zero-shot cross-lingual performance of models trained on a combination of English and multilingual intermediate tasks compare to models trained only on English intermediate tasks across different language families in XTREME-R tasks?
Autonomous synthesis report generated by Assignee Research. Tribunal consensus score: 9.3/10.
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