model = Sequential()
model.add(Conv1D(32, 12, activation='relu', input_shape=(1500, 1)))
model.add(MaxPooling1D(3))
model.add(Dropout(0.5))
model.add(Conv1D(64, 12, activation='relu'))
model.add(MaxPooling1D(3))
model.add(Dropout(0.5))
model.add(Conv1D(128, 12, activation='relu'))
model.add(GlobalAveragePooling1D())
model.add(Dropout(0.5))
model.add(Dense(1, activation='sigmoid'))

model.compile(loss='binary_crossentropy',
          optimizer='rmsprop',
          metrics=['accuracy'])