input: from typing import Tuple
  from sklearn.svm import SVC
  from sklearn.metrics import accuracy_score
  
  def evaluate_model_accuracy(model, X_train, y_train, X_test, y_test) -> Tuple[str, float]:
      """ Evaluate the accuracy of a given machine-learning model using provided datasets.
      >>> clf = SVC(kernel='poly', degree=2, gamma=0.05)
      >>> evaluate_model_accuracy(clf, X_train, y_train, X_test, y_test)
      ('Accuracy:', 0.85)
      """
      model.fit(X_train, y_train)
      y_pred = model.predict(X_test)
      accuracy = accuracy_score(y_test, y_pred)
      return "Accuracy:", accuracy
output:     model.fit(X_train, y_train)
      y_pred = model.predict(X_test)
      accuracy = accuracy_score(y_test, y_pred)
      return "Accuracy:", accuracy