input: Write a python function to train a RandomForestRegressor model to predict movie popularity based on the given features and target variable.
  assert len(X_train) > 0
  assert len(X_test) > 0
  assert len(y_train) > 0
  assert len(y_test) > 0
output: def train_random_forest_regressor(X_train, X_test, y_train, y_test):
      from sklearn.ensemble import RandomForestRegressor
      from sklearn.metrics import mean_squared_error
  
      # Initialize the model
      model = RandomForestRegressor()
  
      # Train the model
      model.fit(X_train, y_train)
  
      # Make predictions
      y_pred = model.predict(X_test)
  
      # Calculate mean squared error
      mse = mean_squared_error(y_test, y_pred)
      
      return model, mse