Order Matters in the Presence of Dataset Imbalance for Multilingual Learning

• URL: http://arxiv.org/abs/2312.06134v1
• Date: Mon, 11 Dec 2023 05:46:57 GMT
• Title: Order Matters in the Presence of Dataset Imbalance for Multilingual Learning
• Authors: Dami Choi, Derrick Xin, Hamid Dadkhahi, Justin Gilmer, Ankush Garg, Orhan Firat, Chih-Kuan Yeh, Andrew M. Dai, Behrooz Ghorbani
• Abstract summary: We present a simple yet effective method of pre-training on high-resource tasks, followed by fine-tuning on a mixture of high/low-resource tasks. We show its improvements in neural machine translation (NMT) and multi-lingual language modeling.
• Score: 53.74649778447903
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this paper, we empirically study the optimization dynamics of multi-task learning, particularly focusing on those that govern a collection of tasks with significant data imbalance. We present a simple yet effective method of pre-training on high-resource tasks, followed by fine-tuning on a mixture of high/low-resource tasks. We provide a thorough empirical study and analysis of this method's benefits showing that it achieves consistent improvements relative to the performance trade-off profile of standard static weighting. We analyze under what data regimes this method is applicable and show its improvements empirically in neural machine translation (NMT) and multi-lingual language modeling.

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