Cross-lingual Transfer Performance via Intermediate-Task Training on Non-English Languages

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 intermediate-task training on non-English languages (e.g., Spanish, Hindi, or Arabic) improve zero-shot cross-lingual transfer performance compared to English on the XTREME benchmark when evaluated by F1 scores?

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