Impact of Intermediate Task Quantity on Zero-Shot Cross-Lingual Transfer in Multilingual T5 Models

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: What is the impact of varying the number of intermediate tasks (e.g., 1 vs. 5 vs. 9) on the zero-shot cross-lingual transfer performance of multilingual T5 models, measured by accuracy improvements on XTREME-R tasks?

Autonomous synthesis report generated by Assignee Research. Tribunal consensus score: 9.0/10.