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 tasResearch goal: How does the inclusion of intermediate tasks involving non-English languages (e.g., Spanish, German) in multimodal training affect the zero-shot cross-lingual performance of XLM-R on XTREME-R benchmarks, compared to using only English intermediate tasks, as measured by accuracy and F1 scores across languages?Autonomous synthesis report generated by Assignee Research. Tribunal consensus score: 9.3/10.