为了评估FLAN在未见过任务上的zero-shot能力,我们将NLP数据集按类型划分为cluster,评估每一个cluster时则将模型在其它cluster数据集上做微调。 评估显示,FLAN大幅提升了137B基础模型的zero-shot能力,在评估的25个数据集中有20个超越了GPT-3,且在一部分数据集中甚至超越了GPT-3的few-shot设定。在消融实验中,我们发现...
Zero COT:通过非常简单的话,让模型自己去构造思维链路 Least to Most prompting,从最少到最多的Prompting,将一个问题分解为若干个子问题,子问题中再用COT的方法来做,最后将答案汇总,实验证明这种方法比COT的方法要更好
对每个数据集的十个模板进行测试，求出平均值和标准差，代表自然语言指令预期性能的典型结果。比较LaMDA-PT的zero-shot和few-shot结果，FLAN在25个数据集中的20个任务上超越了GPT-3。同时，FLAN在10个数据集上优于few-shot GPT-3，在GLaM上也有类似效果。核心实验研究instruction tuning如何提升模型对unse...
论文解读:Finetuned Language Models Are Zero-shot Learners 简要信息: 一、概念: Instruction-tuning——finetuning language models on a collection of tasks (more than 60 NLP tasks) described via instructions 本文提出一种基于instruction-tuning的方法叫做FLAN(Finetuned LAnguage Net) 评估方法:对所...
This paper explores a simple method for improving the zero-shot learning abilities of language models. We show that instruction tuning -- finetuning language models on a collection of tasks described via instructions -- substantially improves zero-shot performance on unseen tasks. We take a 137B ...
GPT1采用了pre-train + fine-tuning训练方式,也就是说为了适应不同的训练任务,模型还是需要在特定任务的数据集上微调,仍然存在较多人工干预的成本。GPT-2 想彻底解决这个问题,通过 zero-shot,在迁移到其他任务上的时候不需要额外的标注数据,也不需要额外的模型训练。
Finetuned Language Models Are Zero-Shot LearnersJason WeiMaarten BosmaVincent Y. ZhaoKelvin GuuAdams Wei YuBrian LesterNan DuAndrew M. DaiQuoc V. Le
Broadly, for most tasks we find relatively smooth scaling with model capacity in all three settings; one notable pattern is that the gap between zero-, one-, and few-shot performance often grows with model capacity, perhaps suggesting that larger models are more proficient meta-learners. Finally...
GPT-3《Language Models are Few-Shot Learners》解读 GPT-3 和 GPT-2差别 1. 效果上,超出 GPT-2 非常多,能生成人类难以区分的新闻文章; 2. 主推 few-shot,相比于 GPT-2 的 zero-shot,具有很强的创新性; 3. 模型结构略微变化,采用 sparse attention 模块;...
language models. The assessment was that language models may not be worth investing significant resources in because there has been no convincing demonstration that current language models are significantly better than current methods for generating text, and because methods for “targeting” or “...