大体上,在NLP任务中,GPT-3在zero-shot和one-shot设置中取得了令人满意的结果,在few-shot设置中,有时与最先进的技术相竞争,甚至有时超过最先进的技术(尽管微调模型保持着最先进的技术)。例如,GPT-3在zero-shot设置下的CoQA上达到81.5 F1,在one-shot设置下的CoQA上达到84.0 F1,在few-shot设置下达到85.0 F1。...
Language Models are Few-Shot LearnersRecent work has demonstrated substantial gains on many NLP tasks and benchmarks by pre-training on a large corpus of text followed by fine-tuning on a specific tas, 视频播放量 2766、弹幕量 0、点赞数 82、投硬币枚数 24
对于每一个任务,作者都测试了模型“few-shotlearning”,“one-shot learning”和“zero-shot learning”三种条件的性能。虽然GPT-3也支持fine-tune过程,但本文并未测试。关于GPT-3的研究结果: 整体上,GPT-3在zero-shot或one-shot设置下能取得尚可的成绩,在few-shot设置下有可能超越基于fine-tune的SOTA模型。
Language Models are Few-Shot Learners 郑重声明:原文参见标题,如有侵权,请联系作者,将会撤销发布! NeurIPS2020 Abstract 我们证明,扩展语言模型大大提高了任务不可知小样本的性能,有时甚至与最先进的微调方法相比具有竞争力。具体来说,我们训练GPT-3,这是一个具有1750亿个参数的自回归语言模型,比以前的任何非稀疏语...
humans can generally perform a new language task from only a few examples or from simple instructions - something which current NLP systems still largely struggle to do. Here we show that scaling up language models greatly improves task-agnostic, few-shot performance, sometimes even reaching competi...
OpenAI最新论文《Language Models are Few-Shot Learners》的发表,标志着暴力出奇迹的GPT家族又添新成员:GPT-3! 一.论文的基本介绍 OpenAI提出的GPT-3在社交网络上掀起了新一阵风潮。它的参数量要比2月份刚刚推出的、全球最大深度学习模型Turing NLP大上十倍,而且不仅可以更好地答题、翻译、写文章,还带有一些...
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. ...
A. Radford et al., “Language models are unsupervised multitask learners,” OpenAI blog, vol. 1, no. 8, p. 9, 2019. 1.1 背景 OpenAI在18、19与20年接连发布了GPT三部曲,其模型分别被称为GPT-1 、GPT-2 和GPT-3。其中GPT-1借鉴CV领域的预训练思路,基于Transformer模型的解码器,实现了利用无标...
《GPT-3: Language Models are Few-Shot Learners》的翻译与解读 作者 OpenAI Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Hen...
*《Language Models are Few-Shot Learners》T B. Brown, B Mann, N Ryder, M Subbiah... [OpenAI] (2020) http://t.cn/A626tCj6 view:http://t.cn/A62aPMIM