From a9404fc3f7e70f30fe6a46cfc8fbf2c2c8f619cc Mon Sep 17 00:00:00 2001 From: unknown Date: Wed, 6 Dec 2023 15:17:02 +0400 Subject: [PATCH] tsyppo_anton_lab_7 is ready --- tsyppo_anton_lab_7/README.md | 96 +++++++++++ tsyppo_anton_lab_7/img/eng100.png | Bin 0 -> 14306 bytes tsyppo_anton_lab_7/img/eng20.png | Bin 0 -> 14707 bytes tsyppo_anton_lab_7/img/rus100.png | Bin 0 -> 13705 bytes tsyppo_anton_lab_7/img/rus20.png | Bin 0 -> 16145 bytes tsyppo_anton_lab_7/img/translation.png | Bin 0 -> 37886 bytes tsyppo_anton_lab_7/img/work100.png | Bin 0 -> 28936 bytes tsyppo_anton_lab_7/img/work20.png | Bin 0 -> 48427 bytes tsyppo_anton_lab_7/main.py | 95 +++++++++++ tsyppo_anton_lab_7/text/eng.txt | 103 ++++++++++++ tsyppo_anton_lab_7/text/rus.txt | 217 +++++++++++++++++++++++++ 11 files changed, 511 insertions(+) create mode 100644 tsyppo_anton_lab_7/README.md create mode 100644 tsyppo_anton_lab_7/img/eng100.png create mode 100644 tsyppo_anton_lab_7/img/eng20.png create mode 100644 tsyppo_anton_lab_7/img/rus100.png create mode 100644 tsyppo_anton_lab_7/img/rus20.png create mode 100644 tsyppo_anton_lab_7/img/translation.png create mode 100644 tsyppo_anton_lab_7/img/work100.png create mode 100644 tsyppo_anton_lab_7/img/work20.png create mode 100644 tsyppo_anton_lab_7/main.py create mode 100644 tsyppo_anton_lab_7/text/eng.txt create mode 100644 tsyppo_anton_lab_7/text/rus.txt diff --git a/tsyppo_anton_lab_7/README.md b/tsyppo_anton_lab_7/README.md new file mode 100644 index 0000000..cafb2d6 --- /dev/null +++ b/tsyppo_anton_lab_7/README.md @@ -0,0 +1,96 @@ +# Лабораторная работа №7: Рекуррентная нейронная сеть и задача генерации текста +## Задание. Вариант 28 + +Выбрать художественный текст (четные варианты – русскоязычный, нечетные – англоязычный) и обучить на нем рекуррентную +нейронную сеть для решения задачи генерации. Подобрать архитектуру и параметры так, чтобы приблизиться к максимально +осмысленному результату. Далее разбиться на пары четный-нечетный вариант, обменяться разработанными сетями и проверить, +как архитектура товарища справляется с вашим текстом. В завершении подобрать компромиссную архитектуру, справляющуюся +достаточно хорошо с обоими видами текстов. + +## Описание программы + +Данная программа обучается на двух текстах русскоязычном и англоязычном (2912 слов в англоязычном тесте и 1908 в +русскоязычном). В программе по итогу была реализованна архитектура справляющаяся с обоими видами текстов. + +## Как запустить лабораторную работу + +1. Установите необходимые библиотеки: + + ```bash + pip install tensorflow + pip install keras + ``` + +2. Запустите скрипт: + + ```bash + python main.py + ``` + +## Использованные технологии + +- Python +- tensorflow +- keras + +## Что программа делает + +Программа загружает данные, считывает текста из файлов rus.txt и eng.txt. Далее для обоих текстов происходит следующее: +Происходит токенизация текста на отдельные слова. Создание последовательностей (n-грамм) для обучения модели. +Использование рекуррентной нейронной сети (RNN) с LSTM слоями. Потом происходит обучение модели на подготовленных данных. +Использование обученной модели для предсказания следующего слова на основе введенного текста. В конце программа выводит +сгенерированные текста. + +## Тесты + +Запуск программы с 20-ю эпохами: +![Графики моделей](img/work20.png) + +Вывод русскоязычного текста с 20-ю эпохами: +![Графики моделей](img/rus20.png) + +Текст: +> Начало широким надень дочка старик и откуда вдруг ледяной уж август и пошла так на выручили на дверей и тебе перед +> беседуют старику тут сосульки висели они ни обогнал в лесу присесть стукнул считать ждать на сказала да месяцы неба +> покрытая дочку и тихо опять и под между зеленые вязанкой достает + +Вывод англоязычного текста с 20-ю эпохами: +![Графики моделей](img/eng20.png) + +Текст: +> Start if i back ‘i i’m sure we ’ any worked is has aloud into dinner has three coming surprised to soon about the +> back all he said to have thing mr britnell exactly across when he saw that looked at the picture before — a very +> dark he with the + +Запуск программы с 100-й эпохами: +![Графики моделей](img/work100.png) + +Вывод русскоязычного текста с 100-й эпохами: +![Графики моделей](img/rus100.png) + +Текст: +> Начало ему свою длинную бороду старик и говорит сестра — уже домой вернулась а подснежники где за нею замерзнуть +> ворох подснежников чем корзинкой подснежников не выглянут мартом ворох подснежников какие сладких а май обогнал бы +> апрель месяцы не гаснет он за подарили где пожарче и стала греться замолчали братья месяцы тихо + +Вывод англоязычного текста с 100-й эпохами: +![Графики моделей](img/eng100.png) + +Текст: +> Start a see ’ said nisbet ‘but i must have but what i must do first i must ask garwood exactly what he saw when he +> looked at the picture last night then i must have the picture photographed before it goes any further and thirdly i +> must find out where + +Перевод англоязычных текстов с помощью Google-переводчика: +![Графики моделей](img/translation.png) + +## Вывод + +_Смотря на тесты можно заметить что текст с 20-ю эпохами является по сути несвязным набором слов, в отличие от 100 где +уже прослеживаются вполне связный ряд словосочетаний и местами текст обретает хоть какой-то смысл в случае русскоязычного +можно догадаться что основной темой являются подснежники. С англоязычным текстом разница заметна ещё лучше поскольку +англоязычный текст больше. Подводя итоги можно сделать вывод, что количество эпох, а так же объём текста на котором +обучается рекуррентная нейронная сеть влияет на конечный генерируемый текст._ + +--- + diff --git a/tsyppo_anton_lab_7/img/eng100.png b/tsyppo_anton_lab_7/img/eng100.png new file mode 100644 index 0000000000000000000000000000000000000000..32fe2d88255834a464f57ece6fdf464f541927bb GIT binary patch literal 14306 zcmdtJcT|(@wl69oAYFO~1(9A<1OW+33r!FUO?vND2rVGJgD4#((xij*-a8TL9YPZb zEws=QLT>ohxAxj=-?Q%>=iD*w80WlyK*k6!d7k;sXU<=liF~C2Bqw1expCtLxr(yF z>l-(2f^n})ZxiBv_KXccZ`_b5R8e^G*2`#b(fbX}Y$xFXT2YE#4evFV$-VlCyH1Hu zqk<~kN$)5=2x{kzBh3z){}>hg>t{iPV7A;R?!Zrbapti7ljg;5p@R3pH}OWF1zZ*> zyFCS?kZzgCWGvjXJ2(P&`8!~V{r>Ul85vjscRe(j4+E&Ad_4d2_P+Q12Lws?IHTSg zWDomuOA(Ht3X6&0%{wOgTd!=dVI~ih_AqY0MZ++@d49pSSbS0<>&vS%gJX zP0>X0AY(lexv&a&NA72LS|+ock^pW12oerEIdrEx>yzpWkR}N+Gu`%Wgc}~ zrH)cjNJ8ri!v&VQhx!R}Z{|&uFO8>e?3x!wOR&V!$e(D(jU$Ri2Sm72$V00MXBo35 z1S=_2Yi*(GmYyNGGkqd#!|AvTg$j7fd)CX&M5X9QUHQ2Sc9pp4p7q9b1?ilX6^z^Y 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