How long does it typically take to train a MNIST data on a Mac Pro?
0
$begingroup$
My code is below:
# define a simple CNN model
def baseline_model():
# create model
model = Sequential()
model.add(Conv2D(30, (5, 5), input_shape=(1, 28, 28), activation='relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Conv2D(15, (3, 3), activation='relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.2))
model.add(Flatten())
model.add(Dense(128, activation='relu'))
model.add(Dense(50, activation='relu'))
model.add(Dense(num_classes, activation='softmax'))
# Compile model
model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])
return model
# build the model
model = baseline_model()
# Fit the model
model.fit(X_train, y_train, validation_data=(X_test, y_test), epochs=500, batch_size=200)
# Final evaluation of the model
scores = model.evaluate(X_test, y_test, verbose=0)
My Mac's capacity:
Grphics Radeon Pro 555 2048 MB
Intel HD Graphics 630 1536 MB
Memeory 16 GB 2133 MHz LPDDR3
Processor 2.8 GHz Intel Core i7
It is taking several hours to train this the MNIST image classification dataset on my computer. Is this normal?
cnn mnist
asked 14 mins ago
user697911user697911
101
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user697911 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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$endgroup$
add a comment |
0
$begingroup$
My code is below:
# define a simple CNN model
def baseline_model():
# create model
model = Sequential()
model.add(Conv2D(30, (5, 5), input_shape=(1, 28, 28), activation='relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Conv2D(15, (3, 3), activation='relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.2))
model.add(Flatten())
model.add(Dense(128, activation='relu'))
model.add(Dense(50, activation='relu'))
model.add(Dense(num_classes, activation='softmax'))
# Compile model
model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])
return model
# build the model
model = baseline_model()
# Fit the model
model.fit(X_train, y_train, validation_data=(X_test, y_test), epochs=500, batch_size=200)
# Final evaluation of the model
scores = model.evaluate(X_test, y_test, verbose=0)
My Mac's capacity:
Grphics Radeon Pro 555 2048 MB
Intel HD Graphics 630 1536 MB
Memeory 16 GB 2133 MHz LPDDR3
Processor 2.8 GHz Intel Core i7
It is taking several hours to train this the MNIST image classification dataset on my computer. Is this normal?
cnn mnist
asked 14 mins ago
user697911user697911
101
New contributor
user697911 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
0
0
0
$begingroup$
My code is below:
# define a simple CNN model
def baseline_model():
# create model
model = Sequential()
model.add(Conv2D(30, (5, 5), input_shape=(1, 28, 28), activation='relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Conv2D(15, (3, 3), activation='relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.2))
model.add(Flatten())
model.add(Dense(128, activation='relu'))
model.add(Dense(50, activation='relu'))
model.add(Dense(num_classes, activation='softmax'))
# Compile model
model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])
return model
# build the model
model = baseline_model()
# Fit the model
model.fit(X_train, y_train, validation_data=(X_test, y_test), epochs=500, batch_size=200)
# Final evaluation of the model
scores = model.evaluate(X_test, y_test, verbose=0)
My Mac's capacity:
Grphics Radeon Pro 555 2048 MB
Intel HD Graphics 630 1536 MB
Memeory 16 GB 2133 MHz LPDDR3
Processor 2.8 GHz Intel Core i7
It is taking several hours to train this the MNIST image classification dataset on my computer. Is this normal?
cnn mnist
asked 14 mins ago
user697911user697911
101
New contributor
user697911 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
My code is below:
# define a simple CNN model
def baseline_model():
# create model
model = Sequential()
model.add(Conv2D(30, (5, 5), input_shape=(1, 28, 28), activation='relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Conv2D(15, (3, 3), activation='relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.2))
model.add(Flatten())
model.add(Dense(128, activation='relu'))
model.add(Dense(50, activation='relu'))
model.add(Dense(num_classes, activation='softmax'))
# Compile model
model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])
return model
# build the model
model = baseline_model()
# Fit the model
model.fit(X_train, y_train, validation_data=(X_test, y_test), epochs=500, batch_size=200)
# Final evaluation of the model
scores = model.evaluate(X_test, y_test, verbose=0)
My Mac's capacity:
Grphics Radeon Pro 555 2048 MB
Intel HD Graphics 630 1536 MB
Memeory 16 GB 2133 MHz LPDDR3
Processor 2.8 GHz Intel Core i7
It is taking several hours to train this the MNIST image classification dataset on my computer. Is this normal?
cnn mnist
cnn mnist
asked 14 mins ago
user697911user697911
101
New contributor
user697911 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 14 mins ago
user697911user697911
101
New contributor
user697911 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 14 mins ago
user697911user697911
101
New contributor
user697911 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 14 mins ago
user697911user697911
101
asked 14 mins ago
user697911user697911
101
101
New contributor
user697911 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
user697911 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
user697911 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
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