End-of-chapter quiz

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Test what you learned in this chapter!

1. The <code> emotion </code> dataset contains Twitter messages labeled with emotions. Search for it in the Hub , and read the dataset card. Which of these is not one of its basic emotions?

2. Search for the <code> ar_sarcasm </code> dataset in the Hub . Which task does it support?

3. How does the BERT model expect a pair of sentences to be processed?

4. What are the benefits of the <code> Dataset.map() </code> method?

5. What does dynamic padding mean?

6. What is the purpose of a collate function?

7. What happens when you instantiate one of the <code> AutoModelForXxx </code> classes with a pretrained language model (such as <code> bert-base-uncased </code> ) that corresponds to a different task than the one for which it was trained?

8. What’s the purpose of <code> TrainingArguments </code> ?

9. Why should you use the 🤗 Accelerate library?

10. What is the purpose of the <code> processing_class </code> parameter in the Trainer?

11. Which modern optimization technique can help with memory efficiency during training?

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