QuizMe

* השאלה נוספה בתאריך: 20-03-2024

		Because it increases the computational efficiency during the forward pass
		Because it prevents bias in the model by removing unnecessary tokens
		Because it ensures all training examples have identical lengths
		Because it may lead to loss of data and computational inefficiency

Why is padding and truncation considered wasteful in traditional data preparation methods?