instruction:
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.
question:
The best baseline model is NO-MOVE, reaching an accuracy of 30.3% on single sentences and 0.3 on complete paragraphs.
answer:
How well did the baseline perform?


question:
Finally, we combine our CNN and RNN models using a voting process. For each sentence in the test set, we apply several CNN and RNN models presented in Tables TABREF12 and TABREF14 and predict the class with the most votes. In case of a tie, we pick one of the most frequent classes randomly.
answer:
How does their simple voting scheme work?


question:
 We modeled the relationship between word count and the two metrics of user engagement (overall rating, mean number of turns) in separate linear regressions.
answer:

What are all the metrics to measure user engagement?