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код работал, но я получал значение точности равным нулю в каждую эпоху, перепробовал много идей и предложений от Google и stackoverflow, но ничего не помогло

 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=0.001, momentum=0.5 )
    model.compile(loss='mean_squared_error', optimizer=optimizer,metrics=['accuracy'])
    convolutional_model = model.fit(X_train, Y_train, epochs=5,batch_size=256,verbose = 1, validation_data=(X_test, Y_test))
  

это форма моих значений :

 (426, 29, 1) (426, 1)
(143, 29, 1) (143, 1)
  

и я получил свой результат следующим образом:

 Epoch 1/5
WARNING:tensorflow:Model was constructed with shape (None, 256, 1) for input Tensor("conv1d_48_input:0", shape=(None, 256, 1), dtype=float32), but it was called on an input with incompatible shape (None, 29, 1).
WARNING:tensorflow:Model was constructed with shape (None, 256, 1) for input Tensor("conv1d_48_input:0", shape=(None, 256, 1), dtype=float32), but it was called on an input with incompatible shape (None, 29, 1).
2/2 [==============================] - ETA: 0s - loss: 66.5119 - accuracy: 0.0000e 00WARNING:tensorflow:Callbacks method `on_train_batch_end` is slow compared to the batch time (batch time: 0.0449s vs `on_train_batch_end` time: 0.0872s). Check your callbacks.
WARNING:tensorflow:Model was constructed with shape (None, 256, 1) for input Tensor("conv1d_48_input:0", shape=(None, 256, 1), dtype=float32), but it was called on an input with incompatible shape (None, 29, 1).
2/2 [==============================] - 0s 216ms/step - loss: 66.5119 - accuracy: 0.0000e 00 - val_loss: 11.4075 - val_accuracy: 0.0000e 00
Epoch 2/5
2/2 [==============================] - 0s 142ms/step - loss: 20.7915 - accuracy: 0.0000e 00 - val_loss: 5.1864 - val_accuracy: 0.0000e 00
Epoch 3/5
2/2 [==============================] - 0s 140ms/step - loss: 11.4995 - accuracy: 0.0000e 00 - val_loss: 3.5993 - val_accuracy: 0.0000e 00
Epoch 4/5
2/2 [==============================] - 0s 145ms/step - loss: 8.5100 - accuracy: 0.0000e 00 - val_loss: 2.9013 - val_accuracy: 0.0000e 00
Epoch 5/5
2/2 [==============================] - 0s 139ms/step - loss: 7.1619 - accuracy: 0.0000e 00 - val_loss: 2.4821 - val_accuracy: 0.0000e 00
  

любые возможные методы повышения точности для решения вышеуказанной проблемы, пожалуйста, помогите мне