当我训练自动驾驶汽车模型时,在第一个时期给了我错误。虽然当我减少batch_size
时,它工作正常。但这并没有给我我想要的准确性。
我正在Google Collab中训练我的模型。
tensorflow版本2.3.1
错误:
WARNING:tensorflow:Your input ran out of data; interrupting training. Make sure that your dataset or generator can generate at least `steps_per_epoch * epochs` batches (in this case, 20000 batches). You may need to use the repeat() function when building your dataset.
我的代码:
def modified_model():
model = Sequential()
model.add(Conv2D(60, (5, 5), input_shape=(32, 32, 1), activation='relu'))
model.add(Conv2D(60, (5, 5), activation='relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Conv2D(30, (3, 3), activation='relu'))
model.add(Conv2D(30, (3, 3), activation='relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Flatten())
model.add(Dense(500, activation='relu'))
model.add(Dropout(0.5))
model.add(Dense(43, activation='softmax'))
model.compile(Adam(lr = 0.001), loss='categorical_crossentropy', metrics=['accuracy'])
return model
model = modified_model()
print(model.summary())
history = model.fit_generator(datagen.flow(X_train, y_train, batch_size=50),
steps_per_epoch=2000,
epochs=10,
validation_data=(X_val, y_val), shuffle = 1)
答案 0 :(得分:1)
在使用生成器时,让模型找出实际上要涵盖一个纪元的步骤数,否则必须计算steps_per_epoch=(data_samples/batch_size)
。尝试在没有step_per_epoch
参数的情况下运行