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我正在使用卷积神经网络，在使用顺序神经网络时，我在训练数据时遇到了问题。使用顺序是不可能获得最好的分数吗？

from numpy import array
from numpy import reshape
import numpy as np
def model_CNN(X_train,Y_train,X_test,Y_test):

    model = Sequential()

    model.add(Conv1D(filters=512, kernel_size=32, padding='same', kernel_initializer='normal', activation='relu', input_shape=(256, 1)))
    model.add(Conv1D(filters=512, kernel_size=32, padding='same', kernel_initializer='normal', activation='relu'))
    model.add(Dropout(0.2)) # This is the dropout layer. It's main function is to inactivate 20% of neurons in order to prevent overfitting
    model.add(Conv1D(filters=256, kernel_size=32, padding='same', kernel_initializer='normal', activation='relu'))
    model.add(Dropout(0.2))
    model.add(Conv1D(filters=256, kernel_size=32, padding='same', kernel_initializer='normal', activation='relu'))

    model.add(Flatten())

    optimizer = keras.optimizers.SGD(lr=0.01, momentum=0.5)
    model.compile(loss='binary_crossentropy', optimizer=optimizer, metrics=['accuracy'])
    convolutional_model = model.fit(X_train, Y_train, epochs=5,batch_size=64,verbose=1, validation_data=(X_test, Y_test))
    print(convolutional_model.score(X_train,Y_train))
    model.summary()
    return …