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Intermediate-task training---fine-tuning a pretrained model on anintermediate task before fine-tuning again on the target task---often improvesmodel performance substantially on language understanding tasks in monolingualEnglish settings. We investigate whether English intermediate-task training isstill helpful on non-English target tasks. Using nine intermediatelanguage-understanding tasks, we evaluate intermediate-task transfer in azero-shot cross-lingual setting on the XTREME benchmark. We see largeimprovements from intermediate training on the BUCC and Tatoeba sentenceretrieval tasks and moderate improvements on question-answering target tasks.MNLI, SQuAD and HellaSwag achieve the best overall results as intermediatetasks, while multi-task intermediate offers small additional improvements.Using our best intermediate-task models for each target task, we obtain a 5.4point improvement over XLM-R Large on the XTREME benchmark, setting the stateof the art as of June 2020. We also investigate continuing multilingual MLMduring intermediate-task training and using machine-translatedintermediate-task data, but neither consistently outperforms simply performingEnglish intermediate-task training.

English Intermediate-Task Training Improves Zero-Shot Cross-Lingual Transfer Too