February 2025
Intermediate
376 pages
9h 25m
Japanese
Content preview from 仕組みからわかる大規模言語モデル 生成AI時代のソフトウェア開発入門
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2
LLMの事前学習
2.2
事前学習は、はじめに行われるLLM の学習です。この段階では、モデルは大規模なテキス
トデータを用いて、言語の一般的な特徴や構造を学習します。事前学習の主な目的は、モデル
に様々な汎用的な能力を与えることです。例えば、LLMの事前学習では、Webページから収
集された大量のテキストデータで学習させることで、質問応答、翻訳、言語理解、要約のタス
クができるようになるとされています[Radford et al. 2019]。
2.2.1
事前学習用データ
事前学習には、主にインターネット上のWebページ、書籍、論文など、多様的かつ大規模
なコーパスが使用されます。コーパスとは、言語学習のために収集されたテキストデータのこ
とです。表2.2.1 に、いくつかの LLMの事前学習に使用されるコーパスの例を示します。
表2.2.1
モデル名 コーパス
GPT-3 約4,500 億トークン（インターネット上の Webページ、書籍、記事など）[Brown et al. 2020]
GPT-4 約58 兆トークン（インターネット上の Webページ、書籍、記事など）[OpenAI et al. 2024]
BERT 約33 億単語（BookCorpus と英語版Wikipedia）[Devlin et al. 2019]
T5 約7,500 億トークン（Web ページ、書籍、記事、その他のデータセット）[Raffel et al. 2023]
2.2.2
自己教師あり学習
LLM
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.