Robustness of Intermediate-Task Training on English vs. Multilingual Benchmarks for Zero-Shot Cross-Lingual Performance

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 robustness of intermediate-task training on English language understanding tasks from the SuperGLUE benchmark compare to training on multilingual benchmarks like XGLUE for zero-shot cross-lingual performance on the XTREME benchmark across different model sizes?

Autonomous synthesis report generated by Assignee Research. Tribunal consensus score: 8.5/10.