input: **Task:**
  Write a Python function that takes in a training and a testing dataset and returns the evaluation score of a deep learning model trained using the data.
  
  **Function Header:**
  
  def train_and_evaluate_model(X_train, y_train, X_test, y_test):
      """
      Trains a neural network model using the given training data and evaluates it on the test data. The function returns the evaluation score.
  
      >>> train_and_evaluate_model(pd.Series([1,2,3]), pd.Series([2,4,6]), pd.Series([4,5,6]), pd.Series([8,10,12]))
      50.0
      """
  
output:     import tensorflow as tf
      from tensorflow.keras.models import Sequential
      from tensorflow.keras.layers import Dense
  
      # Define the model
      model = Sequential([
          Dense(10, input_shape=(1,), activation='relu'),
          Dense(1)
      ])
  
      # Compile the model
      model.compile(optimizer='adam', loss='mean_squared_error')
  
      # Train the model
      model.fit(X_train, y_train, epochs=10, verbose=0)
  
      # Evaluate the model
      evaluation_score = model.evaluate(X_test, y_test, verbose=0)
  
      return evaluation_score