Scaling Effects on Zero-Shot Cross-Lingual Transfer in English vs. Multilingual Intermediate Tasks

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 model size affect the zero-shot cross-lingual transfer performance of models trained on English intermediate tasks versus multilingual intermediate tasks, as evaluated on the Massive Multilingual Machine Translation (M3MT) benchmark?

Autonomous synthesis report generated by Assignee Research. Tribunal consensus score: 9.3/10.