Language is constantly changing and evolving, leaving language models to quickly become outdated, both factually and linguistically. Recent research proposes we continuously update our models using new data. Continuous training allows us to teach language models about new events and facts and changing norms. However, continuous training also means continuous costs. We show there is currently limited evidence for the benefits of continuous training, be it for the actual downstream performance or the environmental cost. Our results show continuous training does not significantly improve performance. While it is clear that, sooner or later, our language models need to be updated, it is unclear when this effort is worth the cost. We call for a critical reflection about when and how to use continuous training and for more benchmarks to support this research direction.
翻译:语言在不断变化和演变,使得语言模式在事实和语言方面迅速过时。最近的研究表明,我们不断更新我们的模型,使用新的数据。持续的培训使我们得以教授语言模型有关新的事件和事实以及不断变化的规范。然而,持续的培训也意味着持续的费用。我们表明,目前关于持续培训的好处的证据有限,无论是对于实际下游绩效还是环境成本而言。我们的结果显示,持续培训并没有显著改善绩效。虽然我们的语言模型迟早需要更新,但不清楚这一努力何时值得花费。我们呼吁对何时以及如何使用持续培训进行批判性反思,并要求制定更多的基准来支持这一研究方向。