Which of the following best describes the purpose of tokenization in transformer models?

What is the role of an attention mask in transformer-based models?

Why is it important to split your dataset into training, validation, and test sets when preparing data for fine-tuning?

When using a tokenizer from a pre-trained transformer model, what is a common output besides input IDs?

Which statement about padding is correct when batching sequences for transformers?

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Quiz: Data Preparation and Tokenization

1. Which of the following best describes the purpose of tokenization in transformer models?

2. What is the role of an attention mask in transformer-based models?

3. Why is it important to split your dataset into training, validation, and test sets when preparing data for fine-tuning?

4. When using a tokenizer from a pre-trained transformer model, what is a common output besides input IDs?

5. Which statement about padding is correct when batching sequences for transformers?