google-colaboratory - Google Colab 没有实现模型训练
问题描述
我多次尝试在 Google Colab 上训练以下模型,但它永久断开连接(在 5 或 6 时期),并且永远不会完成训练。我还尝试了在单击按钮连接但不起作用时维护会话的 JavaScript 函数。请问我该如何解决这个问题?
classifier = Sequential()
classifier.add(Conv2D(6, (3, 3), input_shape = (30, 30, 3), data_format="channels_last", activation = 'relu'))
classifier.add(MaxPooling2D(pool_size = (2, 2)))
classifier.add(Conv2D(6, (3, 3), activation = 'relu'))
classifier.add(MaxPooling2D(pool_size = (2, 2)))
classifier.add(Flatten())
classifier.add(Dense(units = 128, activation = 'relu'))
classifier.add(Dense(units = 64, activation = 'relu'))
classifier.add(Dense(units = 1, activation = 'sigmoid'))
opt = Adam(learning_rate = 0.001, beta_1 = 0.9, beta_2 = 0.999, epsilon = 1e-08, decay = 0.0)
classifier.compile(optimizer = opt, loss = 'binary_crossentropy', metrics = ['accuracy', precision, recall, fmeasure])
from keras.preprocessing.image import ImageDataGenerator
train_datagen = ImageDataGenerator(rescale = 1./255,
horizontal_flip = True,
vertical_flip = True,
rotation_range = 180)
validation_datagen = ImageDataGenerator(rescale = 1./255)
training_set = train_datagen.flow_from_directory('/home/dataset/training_set',
target_size = (30, 30),
batch_size = 32,
class_mode = 'binary')
validation_set = validation_datagen.flow_from_directory('/home/dataset/validation_set',
target_size = (30, 30),
batch_size = 32,
class_mode = 'binary')
history = classifier.fit_generator(training_set,
steps_per_epoch = 208170,
epochs = 25,
validation_data = validation_set,
validation_steps = 89140)
解决方案
Colab 将在 8-9 小时后自动关闭您的笔记本,因此您应该在每个 epoch 后检查模型到谷歌驱动器
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