Impact of Intermediate-Task Training Sequence Length on Zero-Shot Cross-Lingual Transfer Inference Latency in XTREME-R

Abstract

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 intermediate-task training sequence length (i.e., number of intermediate tasks) on inference latency during zero-shot cross-lingual transfer on XTREME-R while maintaining performance? Autonomous synthesis report generated by Assignee Research. Tribunal consensus score: 9.0/10.