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w2v
w2v
Commits
dbb4648f
Commit
dbb4648f
authored
Aug 4, 2021
by
Silas Dohm
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added missing character
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Dokumentation/silas/w2vCNN.tex
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Dokumentation/silas/w2vCNN.tex
Dokumentation/w2v.pdf
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Dokumentation/silas/w2vCNN.tex
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@@ -114,7 +114,6 @@ Fehlerfunktion \lstinline{sparse_categorical_crossentropy} sowie die Metrik
...
@@ -114,7 +114,6 @@ Fehlerfunktion \lstinline{sparse_categorical_crossentropy} sowie die Metrik
Die Zusammenfassung des Modells, die durch Zeile
Die Zusammenfassung des Modells, die durch Zeile
19 erzeugt wurde, befindet sich im Listing
\ref
{
list:modelCNNSummary
}
.
19 erzeugt wurde, befindet sich im Listing
\ref
{
list:modelCNNSummary
}
.
\wip
{
eval acc=0.8144
}
\begin{lstlisting}
[caption=
{
CNN - Summary
}
,label=
{
list:modelCNNSummary
}
,numbers=none, basicstyle=
\normalsize
]
\begin{lstlisting}
[caption=
{
CNN - Summary
}
,label=
{
list:modelCNNSummary
}
,numbers=none, basicstyle=
\normalsize
]
Model: "sequential"
Model: "sequential"
______________________________________________________________
______________________________________________________________
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@@ -161,7 +160,7 @@ cW = {0:4.18,1:9.51,2:1.52}
...
@@ -161,7 +160,7 @@ cW = {0:4.18,1:9.51,2:1.52}
hist = modelNN.fit(trainData, validation
_
data=valData, epochs=50,class
_
weight=cW, steps
_
per
_
epoch=steps, validation
_
steps=int(steps/3),callbacks=cbList
hist = modelNN.fit(trainData, validation
_
data=valData, epochs=50,class
_
weight=cW, steps
_
per
_
epoch=steps, validation
_
steps=int(steps/3),callbacks=cbList
testData = hdf5Generator(path + "w2vCNN.hdf5", batchSize, "Test",loop=False)
testData = hdf5Generator(path + "w2vCNN.hdf5", batchSize, "Test",loop=False)
modelNN.evaluate(testData
modelNN.evaluate(testData
)
\end{lstlisting}
\end{lstlisting}
Hierfür wird die Größe der Trainingsmenge durch die BatchSize geteilt (Zeile 24).
Hierfür wird die Größe der Trainingsmenge durch die BatchSize geteilt (Zeile 24).
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