Keras神经网络值错误

我得用角膜训练神经网络。为此,我使用以下形状的一些测试数据:

 print("     Training data: {}".format(x_Train.shape))
 print("     Training data: {}".format(y_Train.shape))
 print("     Test data: {}".format(x_Test.shape))
 print("     Test data: {}".format(y_Test.shape))

 ....

 Training data: (128, 90, 561)
 Training data: (128,)
 Test data: (43, 90, 561)
 Test data: (43,)

这种网络架构:

class NeuralNetwork:
@staticmethod
def Build(Width, Depth, Classes, Drop = 0.5):
    Model = Sequential()
    Model.add(Conv1D(filters = 32, 
                    kernel_size = 5,
                    input_shape = (Width, Depth)
    ))

    Model.add(Activation("relu"))
    Model.add(MaxPooling1D(pool_size = 2,
                            strides = 2
    ))

    Model.add(Conv1D(filters = 64, 
                    kernel_size = 3
    ))
    Model.add(Activation("relu"))
    Model.add(MaxPooling1D(pool_size = 2,
                            strides = 2
    ))

    Model.add(Flatten())
    Model.add(Dense(1024))
    Model.add(Dropout(Drop))
    Model.add(Dense(Classes))
    Model.add(Activation("softmax"))

    return Model

但当我试图训练我的模型时,我发现了这个错误:

ValueError: Error when checking target: expected activation_3 to have shape (12,) but got array with shape (1,)

我使用此代码进行培训:

print("[INFO] Train model...")
self.__Model = NeuralNetwork.Build(90, 561, 12)
plot_model(self.__Model, show_layer_names = True, show_shapes = True)
self.__Model.compile(loss = "binary_crossentropy", optimizer  = Adam(lr = self.__Learnrate), metrics = ["accuracy"])
self.__Model.fit(x_Train, 
                    y_Train, 
                    validation_data = (x_Test, y_Test), 
                    batch_size = self.__BatchSize,
                    epochs = self.__Epochs, 
                    verbose = 1
)

我不知道这个错误的来源。我用TensorFlow测试了整个代码,它工作得很好。但是我做了一些错误的重新设计与喀拉斯。

谢谢你的提示或其他什么…