title: Neural Network train and val accuracy score is 0.00000
body: <p>Developing a neural network for the Spaceship Titanic comp binary classification problem.  However, I keep getting a score of 0.0000 for train and val data, and can't figure out why.  Models have worked for knn, lightxgb and random forest, so I don't think it's a data issue.</p>
  <p>Code as below</p>
  <pre><code>print(X_train_scaled.shape)
  print(y_train2.shape)
  
  (6085, 23)
  (6085, 1)
  
  # Create model
  model1 = Sequential()
  
  model1.add(Dense(18, activation = 'relu', kernel_initializer='he_uniform', input_dim = X_train_scaled.shape[1]))
  model1.add(Dense(9, activation='relu', kernel_initializer='he_uniform'))
  model1.add(Dense(1, activation = 'sigmoid'))
  
  optimizer = Adam(learning_rate=0.001)
  model1.compile(loss='binary_crossentropy',
                optimizer=optimizer,
                metrics=[tf.keras.metrics.Accuracy()])
  
  history = model1.fit(X_train_scaled, y_train2, batch_size=100, epochs=30, validation_split = 0.3)
  
  Epoch 1/30
  43/43 [==============================] - 1s 7ms/step - loss: 0.7348 - accuracy: 0.0000e+00 - val_loss: 0.6989 - val_accuracy: 0.0000e+00
  Epoch 2/30
  43/43 [==============================] - 0s 4ms/step - loss: 0.6603 - accuracy: 0.0000e+00 - val_loss: 0.6324 - val_accuracy: 0.0000e+00
  Epoch 3/30
  43/43 [==============================] - 0s 3ms/step - loss: 0.5994 - accuracy: 0.0000e+00 - val_loss: 0.5784 - val_accuracy: 0.0000e+00
  Epoch 4/30
  43/43 [==============================] - 0s 3ms/step - loss: 0.5539 - accuracy: 0.0000e+00 - val_loss: 0.5401 - val_accuracy: 0.0000e+00
  
  </code></pre>