Прогон нейронки по выборкам

def neiroKars():
  model = Sequential() # пустая сеть
  model.add(Dense(1200, input_dim = 8, activation = 'relu', use_bias=True))
  #model.add(Dropout(0.2))
  
  model.add(Dense(820, activation = 'sigmoid'))
  #model.add(BatchNormalization())
  #model.add(Dropout(0.2089))
  #model.add(Dense(100, activation = 'relu'))
  #model.add(Dropout(0.2))
  model.add(BatchNormalization()) #normalizatciia
  model.add(Dense(1, activation = 'sigmoid'))
 
  # компиляция
  model.compile(loss = 'mae', optimizer = 'adam', metrics = ['accuracy'])
 
  # обучаем
  
  return model
model = neiroKars()
 
from sklearn.model_selection import train_test_split as tts
 
x_train_new, x_val, y_train_new, y_val =  tts(x_train, y_train, test_size = 0.2)
# obuchaem set'
otvet = model.fit(x_train_new,         
          y_train_new,         
          batch_size=81,
          
          epochs=20,
          validation_data = (x_val, y_val), # Ukazy`vaem 20% sluchai`ny`kh primerov dlia proverochnoi` vy`borki
          verbose=1)
scores = model.evaluate(x_test, y_test, verbose=1)

  return model
Epoch 1/20
540/540 [==============================] - 11s 20ms/step - loss: 0.7893 - accuracy: 0.0000e+00 - val_loss: 0.7574 - val_accuracy: 0.0000e+00
......
Epoch 7/20
540/540 [==============================] - 10s 19ms/step - loss: 0.6070 - accuracy: 0.0000e+00 - val_loss: 0.6291 - val_accuracy: 0.0000e+00
Epoch 8/20
540/540 [==============================] - 10s 19ms/step - loss: 0.6073 - accuracy: 0.0000e+00 - val_loss: 0.6780 - val_accuracy: 0.0000e+00

  model.compile(optimizer = 'adam', loss = 'mae', metrics = ['accuracy'])

  Epoch 1/20
540/540 [==============================] - 11s 19ms/step - loss: 0.7948 - accuracy: 0.0000e+00 - val_loss: 0.7563 - val_accuracy: 0.0000e+00
Epoch 2/20
540/540 [==============================] - 10s 19ms/step - loss: 0.7174 - accuracy: 0.0000e+00 - val_loss: 0.7496 - val_accuracy: 0.0000e+00
Epoch 3/20
540/540 [==============================] - 11s 21ms/step - loss: 0.6471 - accuracy: 0.0000e+00 - val_loss: 0.6358 - val_accuracy: 0.0000e+00
Epoch 4/20
540/540 [==============================] - 11s 20ms/step - loss: 0.6308 - accuracy: 0.0000e+00 - val_loss: 0.6111 - val_accuracy: 0.0000e+00