input: 
  def binary_classification_model(data: List[List[float]], labels: List[int]) -> float:
      """Implement a basic machine learning model that performs binary classification on the given data.
      The model uses logistic regression from the sklearn library to predict the labels.
      Return the accuracy of the model on the given data.
      >>> binary_classification_model([[0.3, 0.2, 0.6], [0.3, 0.1, 0.4], [0.2, 0.3, 0.4], [0.7, 0.4, 0.2], [0.5, 0.2, 0.1]], [1, 0, 0, 1, 0])
      1.0
      """
  
output:     
      from sklearn.linear_model import LogisticRegression
      from sklearn.metrics import accuracy_score
  
      model = LogisticRegression()
      model.fit(data, labels)
      predictions = model.predict(data)
      return accuracy_score(labels, predictions)
  