D To evaluate each model, we had it summarize posts from the validation set and asked humans to compare their summaries to the human-written TL;DR. The results are shown in Figure 1. We found that RL fine-t
本文是OpenAI在2020年NIPS上发布的在摘要任务中使用RLHF的Paper, 后续的Instruction等等内容, 都是以这篇文章为基础进行研究的. 1. Abstract 摘要模型经常被训练来预测人类进行摘要任务, 但用来评估的ROUGE分数只是最终目标-摘要质量的平替. 因此研究人员通过根据人类偏好训练一个模型去提升摘要的质量. 首先,他们收集了...
Learning to summarize from human feedbackarxiv.org/abs/2009.01325 这篇工作是OpenAI早于ChatGPT两年发表在NeurIPS 2020,在这篇文章中ChatGPT的框架雏形已经显现。文章专注于英文摘要任务,所用的方法和ChatGPT基本一致,包括了ChatGPT的核心方法,RLHF(Reinforcement Learning from Human Feedback)。 问题 随着语言...
(1)生成摘要等模型,虽然有评估方法,但是人类总结的质量依旧难以相比 总结: (1)在各种NLP任务中,大规模语言模型的预训练以及取得了很高的性能 (2) 当把大模型用于下游任务的时候,通常需要监督数据进行微调,数据一般来源于人类总结的证据,来最大化似然函数 (3)这些方法提高了性能,但是呢存在无法对其的问题,微调最大...
📚 在本章中,我们将一同探索强化学习从人类反馈中学习(Reinforcement Learning from Human Feedback, RLHF)这一引人入胜且日益重要的领域。我们将从宏观视角出发,理解RLHF为何在当前人工智能(Artificial Intelligence, AI)的发展浪潮中扮演着关键角色,它试图解决什么核心问题,以及它的起源和发展历程。无论您是初学者...
Learning to Summarize from Human Feedback This repository contains code to run our models, including the supervised baseline, the trained reward model, and the RL fine-tuned policy. Supported platform: Python 3.7 64-bit on Ubuntu 18.04
OpenAI 推出的 ChatGPT 对话模型掀起了新的 AI 热潮,它面对多种多样的问题对答如流,似乎已经打破了机器和人的边界。这一工作的背后是大型语言模型 (Large Language Model,LLM) 生成领域的新训练范式:RLHF (Reinforcement Learning from Human Feedback) ,即以强化学习方式依据人类反馈优化语言模型。
To summarize our experimental results, we found that human subjects adopted feature-based learning in dynamic environments even when this approach did not reduce dimensionality. Subjects switched to object-based learning when the combination of features’ values could not accurately predict all objects’...
We then summarize the various approaches taken to solve four main questions: when, what, who and when to imitate. We emphasize the importance of choosing well the interface and the channels used to convey the demonstrations, with an eye on interfaces providing force control and force feedback....
We hope the evidence from our paper motivates machine learning researchers to pay closer attention to how their training loss affects the model behavior they actually want. ChatGPT 翻译:随着语言模型变得越来越强大,训练和评估越来越受到特定任务所使用的数据和指标的限制。例如,摘要模型通常会被训练以预测...