In this task, you will be presented with a context from an academic paper and a question separated with a 
. You have to answer the question based on the context.

[EX Q]: 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. 
 Question: What hyperparameters have been tuned?
[EX A]: number of coattention blocks, the batch size, and the number of epochs trained and ensembled our three best networks

[EX Q]: The ensembles were formed by simply averaging the predictions from the constituent single models. 
 Question: How does their ensemble method work?
[EX A]: simply averaging the predictions from the constituent single models

[EX Q]: Let all word vectors be normalized and $W$ be the word matrix. Inspired by BIBREF21 , where vector space models are used for evaluating topic coherence, we suggest to estimate the interpretability of $k$ th component as $ \operatorname{interp}_k W = \sum _{i,j=1}^N W_{i,k} W_{j,k} \left(W_i \cdot W_j \right). $  
 Question: How do they evaluate interpretability in this paper?
[EX A]:
we suggest to estimate the interpretability of $k$ th component as $ \operatorname{interp}_k W = \sum _{i,j=1}^N W_{i,k} W_{j,k} \left(W_i \cdot W_j \right). $