In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
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Question: Finally, we performed hyperparameter tuning by adjusting the number of coattention blocks, the batch size, and the number of epochs trained and ensembled our three best networks.

Answer: What hyperparameters have been tuned?


Question: We used the relation classification dataset of the SemEval 2010 task 8 BIBREF8 . It consists of sentences which have been manually labeled with 19 relations (9 directed relations and one artificial class Other). 8,000 sentences have been distributed as training set and 2,717 sentences served as test set.

Answer: Which dataset do they train their models on?


Question: Recommendation diversity. As defined in BIBREF18 , we calculate recommendation diversity as the average dissimilarity of all pairs of tags in the list of recommended tags.

Answer:
how is diversity measured?