How does the scaling of intermediate-task training data size impact the zero-shot cross-lingual transfer accuracy of mT5 versus

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 scaling of intermediate-task training data size impact the zero-shot cross-lingual transfer accuracy of mT5 versus monolingual T5 on high-resource languages in the XTREME-L benchmark, and does the performance gap between low- and high-resource languages narrow with increased intermediate-task data?

Autonomous synthesis report generated by Assignee Research. Tribunal consensus score: 8.8/10.