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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と、他の（実際に起こる）事象の予測確率が下がります。結果として、実際に起こる事象の予
測確率が下がることで、それらの事象に対する-
p ( x )
log
q ( x )
の値が大きくなり、全体の損
失は増加します。
q(x)
-p(x)log q(x)
p(x)
図2.2.1
-p ( x ) log q ( x )
交差エントロピーの例
例として、言語モデルが「私が好きな果物はリンゴです。」という学習データに対して、「私
が好きな果物は」の次のトークンの予測を行う場合を考えます。正解は「リンゴ」であるため、
実際の確率分布は
p ( x
=リンゴ
)
=1と考えます。ここで、モデルによる予測が
p ( x
=リン
ゴ
)
=0.9、
q ( x
=ミカン
)
=0.1、という確率分布だったとします。この例では、交差エントロ
ピーの計算は次のようになります。
,
. .
.
.
log
lo
g l
og
log log
log
H p
q p x q x
p q
p q
1 0 9 0 0 1
0 9
0 105
x
リンゴリンゴ ミカ
ンミ
カン
$ $
.
=-
=- -
=- -
=-
]
]
] ]
] ] ]
g g
g
g
g g
g
!
ここで、
p (
ミカン
)
=0ですから、
p (
ミカン) log
q
(ミカン)の項は0になります。一方で、
088
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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.