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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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@ -9,6 +9,14 @@
|
||||
\usepackage{placeins}
|
||||
\usepackage{caption}
|
||||
\usepackage{subcaption}
|
||||
\usepackage{tikz}
|
||||
\usetikzlibrary{shapes, arrows}
|
||||
|
||||
\tikzstyle{terminator} = [rectangle, draw, text centered, rounded corners, minimum height=2em]
|
||||
\tikzstyle{process} = [rectangle, draw, text centered, minimum height=2em]
|
||||
\tikzstyle{decision} = [diamond, draw, text centered, minimum height=2em]
|
||||
\tikzstyle{data}=[trapezium, draw, text centered, trapezium left angle=60, trapezium right angle=120, minimum height=2em]
|
||||
\tikzstyle{connector} = [draw, -latex']
|
||||
|
||||
\title{Generacja tekstów piosenek}
|
||||
\author{Maciej Krzyżanowski, Sebastian Kutny, Tomasz Lewandowski}
|
||||
@ -338,4 +346,264 @@ Jeśli dać mu fragmet obrazu to wytworzy spójny stylistycznie ciąg dalszy i t
|
||||
\caption{Obrazek przedstawia schemat działania gpt-2 na obrazach.}
|
||||
\label{fig:mesh1}
|
||||
\end{figure}
|
||||
\pagebreak
|
||||
\section{Realizacja praktyczna z wykorzystaniem RNN}
|
||||
\subsection{Użyte narzędzia}
|
||||
\begin{itemize}
|
||||
\item Python3
|
||||
\item Tensorflow
|
||||
\item Keras i Keras\_NLP
|
||||
\item Embedding GloVe (6B.100d)
|
||||
\item Gotowy model GPT-2 (za pomocą pakietu gpt\_2\_simple)
|
||||
\item Teksty piosenek AC/DC, Metalliki i Jimiego Hendrixa
|
||||
\end{itemize}
|
||||
\subsection{Struktura kodu}
|
||||
\begin{itemize}
|
||||
\item main.py - plik obsługujący pobieranie danych od użytkownika i wykorzystujący inne moduły do ładowania i trenowania lub generacji tekstów z modeli.
|
||||
\item models.py - zawiera definicje poniżej opisanych modeli.
|
||||
\item data\_processor.py - impementacja klasy służącej do obróbki danych m.in. przygotowania danych treningowych i testowych
|
||||
\item song\_generator.py - generator piosenek, który wykorzystuje przekazany model i instancję klasy DataProcessor
|
||||
\item edit\_distances.py - kod obliczający metryki edit distance
|
||||
\item plots.py - kod rysujący wykresy metryk
|
||||
\item transformer.py - kod trenujący i generujący piosenki za pomocą GPT-2
|
||||
\end{itemize}
|
||||
\subsection{Dane uczące}
|
||||
Zbiory danych wykorzystane do treningu i oceny rekurencyjnych sieci neuronowych to łącznie kilkaset tekstów utworów:
|
||||
\begin{itemize}
|
||||
\item Tekty piosenek AC/DC do treningu sieci opartych o LSTM lub GRU (ac\_dc.csv)
|
||||
\item Połączenie tekstów Metalliki i Hendrixa do dotrenowania modelu GPT-2 (metallica\_hendrix.txt)
|
||||
\end{itemize}
|
||||
\newpage
|
||||
\subsection{Modele RNN}
|
||||
Opisując metrykę Edit Distance wartości rozdzielone średnikami oznaczają generacje odpowiednio dla 4 wersów po 6 słów, 2 wersów po 6 słów, 1 wersu składajacego się z 6 słów i 1 wersu składającego się z 2 słów.
|
||||
\subsubsection{default\_lstm}
|
||||
\textbf{Warstwy modelu} \\ \\
|
||||
\begin{tikzpicture}[node distance = 2.2cm]
|
||||
\node [process, fill=blue!20] (we) {\textbf{We}};
|
||||
\node [process, fill=green!20, right of=we] (lstm1) {LSTM(256)};
|
||||
\node [process, fill=green!20, right of=lstm1] (dropout1) {Dropout(0.2)};
|
||||
\node [process, fill=green!20, right of=dropout1] (lstm2) {LSTM(256)};
|
||||
\node [process, fill=green!20, right of=lstm2] (dropout2) {Dropout(0.2)};
|
||||
\node [process, fill=blue!20, right of=dropout2] (wy) {\textbf{Wy}};
|
||||
\path [connector] (we) -- (lstm1);
|
||||
\path [connector] (lstm1) -- (dropout1);
|
||||
\path [connector] (dropout1) -- (lstm2);
|
||||
\path [connector] (lstm2) -- (dropout2);
|
||||
\path [connector] (dropout2) -- (wy);
|
||||
\end{tikzpicture} \\ \\
|
||||
\textbf{Ocena modelu}
|
||||
\begin{figure}[h]
|
||||
\makebox[\textwidth][c]{\includegraphics[width=1.1\textwidth]{default_lstm}}%
|
||||
\caption{Metryki modelu default\_lstm}
|
||||
\label{fig:default_lstm}
|
||||
\end{figure}
|
||||
\FloatBarrier
|
||||
Wynik edit distance (po normalizacji) dla w pełni wytrenowanego modelu: \\
|
||||
Średni ED: 0.98 ; 0.97 ; 0.95 ; 0.8125 \\
|
||||
Minimalny ED: 0.88 ; 0.83 ; 0.67 ; 0.0 \\
|
||||
Maksymalny ED: 1.0 ; 1.0 ; 1.0 ; 1.0 \\
|
||||
\paragraph{Przykład generacji}
|
||||
\leavevmode\\
|
||||
\textsl{
|
||||
Of broad for the way she’s \\
|
||||
Love out the gotta rock all \\
|
||||
Reputation up all yeah on down \\
|
||||
Finally oh a man you gotta}
|
||||
\leavevmode\\\leavevmode\\
|
||||
\leavevmode\\
|
||||
\newpage
|
||||
\subsubsection{beta\_lstm}
|
||||
\textbf{Warstwy modelu} \\ \\
|
||||
\begin{tikzpicture}[node distance = 2.4cm]
|
||||
\node [process, fill=blue!20] (we) {\textbf{We}};
|
||||
\node [process, fill=green!20, right of=we] (lstm1) {LSTM(256)};
|
||||
\node [process, fill=green!20, right of=lstm1] (dropout1) {Dropout(0.36)};
|
||||
\node [process, fill=green!20, right of=dropout1] (lstm2) {LSTM(256)};
|
||||
\node [process, fill=green!20, right of=lstm2] (dropout2) {Dropout(0.2)};
|
||||
\node [process, fill=blue!20, right of=dropout2] (wy) {\textbf{Wy}};
|
||||
\path [connector] (we) -- (lstm1);
|
||||
\path [connector] (lstm1) -- (dropout1);
|
||||
\path [connector] (dropout1) -- (lstm2);
|
||||
\path [connector] (lstm2) -- (dropout2);
|
||||
\path [connector] (dropout2) -- (wy);
|
||||
\end{tikzpicture} \\ \\
|
||||
\textbf{Ocena modelu}
|
||||
\begin{figure}[h]
|
||||
\makebox[\textwidth][c]{\includegraphics[width=1.1\textwidth]{beta_lstm}}%
|
||||
\caption{Metryki modelu beta\_lstm}
|
||||
\label{fig:beta_lstm}
|
||||
\end{figure}
|
||||
\FloatBarrier
|
||||
Wynik edit distance (po normalizacji) dla w pełni wytrenowanego modelu: \\
|
||||
Średni ED: 0.98 ; 0.98 ; 0.99 ; 0.97 \\
|
||||
Minimalny ED: 0.91 ; 0.92 ; 0.83 ; 0.5 \\
|
||||
Maksymalny ED: 1.0 ; 1.0 ; 1.0 ; 1.0 \\
|
||||
\paragraph{Przykład generacji}
|
||||
\leavevmode\\
|
||||
\textsl{
|
||||
Blood sideway up a right I'm \\
|
||||
Up love and fight got the \\
|
||||
Dark oh rock a with feel \\
|
||||
What go come your a can}
|
||||
\leavevmode\\\leavevmode\\
|
||||
\leavevmode\\
|
||||
\newpage
|
||||
\subsubsection{gamma\_lstm}
|
||||
\textbf{Warstwy modelu} \\ \\
|
||||
\begin{tikzpicture}[node distance = 2.4cm]
|
||||
\node [process, fill=blue!20] (we) {\textbf{We}};
|
||||
\node [process, fill=green!20, right of=we] (lstm1) {LSTM(512)};
|
||||
\node [process, fill=green!20, right of=lstm1] (dropout1) {Dropout(0.2)};
|
||||
\node [process, fill=green!20, right of=dropout1] (lstm2) {LSTM(512)};
|
||||
\node [process, fill=green!20, right of=lstm2] (dropout2) {Dropout(0.2)};
|
||||
\node [process, fill=blue!20, right of=dropout2] (wy) {\textbf{Wy}};
|
||||
\path [connector] (we) -- (lstm1);
|
||||
\path [connector] (lstm1) -- (dropout1);
|
||||
\path [connector] (dropout1) -- (lstm2);
|
||||
\path [connector] (lstm2) -- (dropout2);
|
||||
\path [connector] (dropout2) -- (wy);
|
||||
\end{tikzpicture} \\ \\
|
||||
\textbf{Ocena modelu}
|
||||
\begin{figure}[h]
|
||||
\makebox[\textwidth][c]{\includegraphics[width=1.1\textwidth]{gamma_lstm}}%
|
||||
\caption{Metryki modelu gamma\_lstm}
|
||||
\label{fig:gamma_lstm}
|
||||
\end{figure}
|
||||
\FloatBarrier
|
||||
Wynik edit distance (po normalizacji) dla w pełni wytrenowanego modelu: \\
|
||||
Średni ED: 0.98 ; 0.97 ; 0.99 ; 1.0 \\
|
||||
Minimalny ED: 0.83 ; 0.83 ; 0.83 ; 1.0 \\
|
||||
Maksymalny ED: 1.0 ; 1.0 ; 1.0 ; 1.0 \\
|
||||
\paragraph{Przykład generacji}
|
||||
\leavevmode\\
|
||||
\textsl{
|
||||
You got her this it the \\
|
||||
Fire what we're like chorus me \\
|
||||
All come she yeah the way \\
|
||||
She’s commin’ all the way prowler}
|
||||
\leavevmode\\\leavevmode\\
|
||||
\leavevmode\\
|
||||
\newpage
|
||||
\subsubsection{omicron\_lstm}
|
||||
\textbf{Warstwy modelu} \\ \\
|
||||
\begin{tikzpicture}[node distance = 0.75cm]
|
||||
\node [process, fill=blue!20] (we) {\textbf{We}};
|
||||
\node [process, fill=yellow!20, below of=we] (glove) {GloVe.6B.100d};
|
||||
\node [process, fill=green!20, below of=glove] (lstm1) {LSTM(512)};
|
||||
\node [process, fill=green!20, below of=lstm1] (dropout1) {Dropout(0.2)};
|
||||
\node [process, fill=green!20, below of=dropout1] (lstm2) {LSTM(512)};
|
||||
\node [process, fill=green!20, below of=lstm2] (dropout2) {Dropout(0.2)};
|
||||
\node [process, fill=blue!20, below of=dropout2] (wy) {\textbf{Wy}};
|
||||
\path [connector] (we) -- (glove);
|
||||
\path [connector] (glove) -- (lstm1);
|
||||
\path [connector] (lstm1) -- (dropout1);
|
||||
\path [connector] (dropout1) -- (lstm2);
|
||||
\path [connector] (lstm2) -- (dropout2);
|
||||
\path [connector] (dropout2) -- (wy);
|
||||
\end{tikzpicture} \\ \\
|
||||
\textbf{Ocena modelu}
|
||||
\begin{figure}[h]
|
||||
\makebox[\textwidth][c]{\includegraphics[width=1.1\textwidth]{omicron_lstm}}%
|
||||
\caption{Metryki modelu omicron\_lstm}
|
||||
\label{fig:omicron_lstm}
|
||||
\end{figure}
|
||||
\FloatBarrier
|
||||
\paragraph{Przykład generacji}
|
||||
\leavevmode\\
|
||||
\textsl{
|
||||
Twilight sting time who crown pain \\
|
||||
In a legless need no tears \\
|
||||
Yours a take yours lovin' million \\
|
||||
Woods lovin' trip a hearts that}
|
||||
\leavevmode\\\leavevmode\\
|
||||
\leavevmode\\
|
||||
\newpage
|
||||
\subsubsection{default\_gru}
|
||||
\textbf{Warstwy modelu} \\ \\
|
||||
\begin{tikzpicture}[node distance = 2.2cm]
|
||||
\node [process, fill=blue!20] (we) {\textbf{We}};
|
||||
\node [process, fill=green!20, right of=we] (lstm1) {GRU(256)};
|
||||
\node [process, fill=green!20, right of=lstm1] (dropout1) {Dropout(0.2)};
|
||||
\node [process, fill=green!20, right of=dropout1] (lstm2) {GRU(256)};
|
||||
\node [process, fill=green!20, right of=lstm2] (dropout2) {Dropout(0.2)};
|
||||
\node [process, fill=blue!20, right of=dropout2] (wy) {\textbf{Wy}};
|
||||
\path [connector] (we) -- (lstm1);
|
||||
\path [connector] (lstm1) -- (dropout1);
|
||||
\path [connector] (dropout1) -- (lstm2);
|
||||
\path [connector] (lstm2) -- (dropout2);
|
||||
\path [connector] (dropout2) -- (wy);
|
||||
\end{tikzpicture} \\ \\
|
||||
\textbf{Ocena modelu}
|
||||
\begin{figure}[h]
|
||||
\makebox[\textwidth][c]{\includegraphics[width=1.1\textwidth]{default_gru}}%
|
||||
\caption{Metryki modelu default\_gru}
|
||||
\label{fig:default_gru}
|
||||
\end{figure}
|
||||
\FloatBarrier
|
||||
Wynik edit distance (po normalizacji) dla w pełni wytrenowanego modelu: \\
|
||||
Średni ED: 0.99 ; 0.99 ; 0.99 ; 1.0 \\
|
||||
Minimalny ED: 0.96 ; 0.92 ; 0.83 ; 1.0 \\
|
||||
Maksymalny ED: 1.0 ; 1.0 ; 1.0 ; 1.0
|
||||
\paragraph{Przykład generacji}
|
||||
\leavevmode\\
|
||||
\textsl{
|
||||
Sunset but got on have call \\
|
||||
I pull shook oh a can \\
|
||||
Of conduct known back satisfy out \\
|
||||
You bustin' himself the handful run}
|
||||
\leavevmode\\\leavevmode\\
|
||||
\leavevmode\\
|
||||
\newpage
|
||||
\subsubsection{beta\_gru}
|
||||
\textbf{Warstwy modelu} \\ \\
|
||||
\begin{tikzpicture}[node distance = 2.2cm]
|
||||
\node [process, fill=blue!20] (we) {\textbf{We}};
|
||||
\node [process, fill=green!20, right of=we] (lstm1) {GRU(128)};
|
||||
\node [process, fill=green!20, right of=lstm1] (dropout1) {Dropout(0.2)};
|
||||
\node [process, fill=green!20, right of=dropout1] (lstm2) {GRU(128)};
|
||||
\node [process, fill=green!20, right of=lstm2] (dropout2) {Dropout(0.2)};
|
||||
\node [process, fill=blue!20, right of=dropout2] (wy) {\textbf{Wy}};
|
||||
\path [connector] (we) -- (lstm1);
|
||||
\path [connector] (lstm1) -- (dropout1);
|
||||
\path [connector] (dropout1) -- (lstm2);
|
||||
\path [connector] (lstm2) -- (dropout2);
|
||||
\path [connector] (dropout2) -- (wy);
|
||||
\end{tikzpicture} \\ \\
|
||||
\textbf{Ocena modelu}
|
||||
\begin{figure}[h]
|
||||
\makebox[\textwidth][c]{\includegraphics[width=1.1\textwidth]{beta_gru}}%
|
||||
\caption{Metryki modelu beta\_gru}
|
||||
\label{fig:beta_gru}
|
||||
\end{figure}
|
||||
\FloatBarrier
|
||||
Wynik edit distance (po normalizacji) dla w pełni wytrenowanego modelu: \\
|
||||
Średni ED: 0.98 ; 0.96 ; 0.99 ; 1.0 \\
|
||||
Minimalny ED: 0.92 ; 0.83 ; 0.83 ; 1.0 \\
|
||||
Maksymalny ED: 1.0 ; 1.0 ; 1.0 ; 1.0 \\
|
||||
\paragraph{Przykład generacji}
|
||||
\leavevmode\\
|
||||
\textsl{
|
||||
Into from rock way down the \\
|
||||
Way the go jack which train \\
|
||||
Play when down just I'm the \\
|
||||
Way restless makin' and like damnation}
|
||||
\leavevmode\\\leavevmode\\
|
||||
\leavevmode\\
|
||||
\newpage
|
||||
\subsubsection{Dotrenowany model GPT-2}
|
||||
Do generacji określonego rodzaju tekstów można też wykorzystać już gotowe modele. Jednym z nich jest wcześniej opisany GPT-2.
|
||||
Wykorzystując pakiet gpt-2-simple dotrenowaliśmy model wykorzystując połączenie zbioru piosenek Metalliki i Jimiego Hendrixa.
|
||||
Poniżej znajduje się przykład generacji tekstu przez takie rozwiązanie: \\
|
||||
\leavevmode\\
|
||||
\textsl{
|
||||
Got to stay up through tonight \\
|
||||
Nobody's fool around tonight \\
|
||||
Yeah, yeah, ya better get over yourself \\
|
||||
Yeah, ya better get over yourself \\
|
||||
Everybody's gotta live together \\
|
||||
Under the same bed \\
|
||||
Every night \\
|
||||
Night falls over o'er the Sun}
|
||||
\leavevmode\\\leavevmode\\
|
||||
\leavevmode\\
|
||||
\end{document}
|
||||
|
||||
40
report/report.toc
Normal file
40
report/report.toc
Normal file
@ -0,0 +1,40 @@
|
||||
\babel@toc {polish}{}\relax
|
||||
\contentsline {section}{\numberline {1}Wstęp}{3}{section.1}%
|
||||
\contentsline {section}{\numberline {2}Łańcuchy Markova}{4}{section.2}%
|
||||
\contentsline {subsection}{\numberline {2.1}Wstęp}{4}{subsection.2.1}%
|
||||
\contentsline {subsection}{\numberline {2.2}Prawo Zipfa}{6}{subsection.2.2}%
|
||||
\contentsline {subsection}{\numberline {2.3}Prawo Heapsa}{9}{subsection.2.3}%
|
||||
\contentsline {subsection}{\numberline {2.4}Entropia Krzyżowa}{11}{subsection.2.4}%
|
||||
\contentsline {subsection}{\numberline {2.5}Perpleksja}{12}{subsection.2.5}%
|
||||
\contentsline {subsection}{\numberline {2.6}Self-BLEU}{13}{subsection.2.6}%
|
||||
\contentsline {subsection}{\numberline {2.7}Przykładowe wyniki}{14}{subsection.2.7}%
|
||||
\contentsline {section}{\numberline {3}Rekurencyjne Sieci Neuronowe}{16}{section.3}%
|
||||
\contentsline {subsection}{\numberline {3.1}Wstęp o rekurencyjnych sieciach neuronowych}{16}{subsection.3.1}%
|
||||
\contentsline {subsection}{\numberline {3.2}LSTM}{17}{subsection.3.2}%
|
||||
\contentsline {subsection}{\numberline {3.3}GRU}{18}{subsection.3.3}%
|
||||
\contentsline {subsection}{\numberline {3.4}Różnice między LSTM, a GRU}{19}{subsection.3.4}%
|
||||
\contentsline {subsection}{\numberline {3.5}Problem znikającego gradientu}{19}{subsection.3.5}%
|
||||
\contentsline {subsection}{\numberline {3.6}Embedding}{19}{subsection.3.6}%
|
||||
\contentsline {section}{\numberline {4}Sieci neuronowe na transformatorach}{21}{section.4}%
|
||||
\contentsline {subsection}{\numberline {4.1}Przykładowe wykorzystanie sieci neuronowych na transformatoarach:}{21}{subsection.4.1}%
|
||||
\contentsline {subsection}{\numberline {4.2}Analiza działania transformera:}{21}{subsection.4.2}%
|
||||
\contentsline {subsection}{\numberline {4.3}Wady i zalety:}{23}{subsection.4.3}%
|
||||
\contentsline {section}{\numberline {5}GPT-2}{25}{section.5}%
|
||||
\contentsline {section}{\numberline {6}Realizacja praktyczna z wykorzystaniem RNN}{27}{section.6}%
|
||||
\contentsline {subsection}{\numberline {6.1}Użyte narzędzia}{27}{subsection.6.1}%
|
||||
\contentsline {subsection}{\numberline {6.2}Struktura kodu}{27}{subsection.6.2}%
|
||||
\contentsline {subsection}{\numberline {6.3}Dane uczące}{27}{subsection.6.3}%
|
||||
\contentsline {subsection}{\numberline {6.4}Modele RNN}{28}{subsection.6.4}%
|
||||
\contentsline {subsubsection}{\numberline {6.4.1}default\_lstm}{28}{subsubsection.6.4.1}%
|
||||
\contentsline {paragraph}{Przykład generacji}{28}{section*.18}%
|
||||
\contentsline {subsubsection}{\numberline {6.4.2}beta\_lstm}{29}{subsubsection.6.4.2}%
|
||||
\contentsline {paragraph}{Przykład generacji}{29}{section*.20}%
|
||||
\contentsline {subsubsection}{\numberline {6.4.3}gamma\_lstm}{30}{subsubsection.6.4.3}%
|
||||
\contentsline {paragraph}{Przykład generacji}{30}{section*.22}%
|
||||
\contentsline {subsubsection}{\numberline {6.4.4}omicron\_lstm}{31}{subsubsection.6.4.4}%
|
||||
\contentsline {paragraph}{Przykład generacji}{31}{section*.24}%
|
||||
\contentsline {subsubsection}{\numberline {6.4.5}default\_gru}{32}{subsubsection.6.4.5}%
|
||||
\contentsline {paragraph}{Przykład generacji}{32}{section*.26}%
|
||||
\contentsline {subsubsection}{\numberline {6.4.6}beta\_gru}{33}{subsubsection.6.4.6}%
|
||||
\contentsline {paragraph}{Przykład generacji}{33}{section*.28}%
|
||||
\contentsline {subsubsection}{\numberline {6.4.7}Dotrenowany model GPT-2}{34}{subsubsection.6.4.7}%
|
||||
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Reference in New Issue
Block a user