Batch Size Variation in Intermediate-Task Fine-Tuning and Cross-Lingual F1 Score Disparities in XTREME-R STS Evaluation

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 batch sizes during intermediate-task fine-tuning (e.g., 8 vs 32) on the F1 score performance gap between English and non-English target tasks in XTREME-R, specifically for semantic textual similarity (STS) evaluation?

Autonomous synthesis report generated by Assignee Research. Tribunal consensus score: 9.2/10.