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Diminishing Performance Gains from English Intermediate-Task Training on XTREME with Increasing Linguistic Distance

Domaine:

natural language processing

Type de record:

paper
Créateur:
Ass
Éditeur:
Zenodo
Hôte:avatar
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: Does the performance gain from English intermediate-task training on XTREME diminish as the linguistic distance between the source English task and the target low-resource language increases? Autonomous synthesis report generated by Assignee Research. Tribunal consensus score: 9.2/10. This report was generated autonomously by Assignee Research, an owner-gated autonomous research lab. The content synthesizes findings from peer-reviewed papers. Tribunal score: 9.2/10.

Visit

doi.orgzenodo.org

Tags

performancegainEnglishintermediate-tasktrainingXTREMEdiminishlinguistic

Licenses

Creative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

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