新闻
Mix, Don't Tune: Bilingual Pre-Training Outperforms Hyperparameter Search in Data-Constrained Settings
Apple Machine Learning Research · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- Apple researchers found that mixing high-resource language data during pre-training outperforms hyperparameter tuning for low-resource language models across multiple scales.
- 为何重要
- Engineers building language models for under-resourced languages should consider this when choosing between tuning hyperparameters or augmenting training data with auxiliary languages.
- 注意
- The study used Arabic and English; results may not generalize equally to all language pairs or domains with different resource disparities.
- language model
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