evaluations/evaluate_models.py

from sklearn.metrics import accuracy_score, f1_scoredef evaluate_model(model, X_test, y_test):    """    Evaluate the model's performance on the test set.    """    predictions = model.predict(X_test)    accuracy = accuracy_score(y_test, predictions)    f1 = f1_score(y_test, predictions, average='weighted')    return {'accuracy': accuracy, 'f1_score': f1}