Scale of Pretrained Language Models and Cross-Lingual Transfer Benefits

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: To what extent does the scale of the pretrained language model (e.g., 1B vs. 10B parameters) influence the benefits of English intermediate-task training for zero-shot cross-lingual transfer on XTREME?

Autonomous synthesis report generated by Assignee Research. Tribunal consensus score: 8.9/10.