Task: Question Answering
Input (English): To reduce variance and boost accuracy, we ensemble 10 CNNs and 10 LSTMs together through soft voting. The models ensembled have different random weight initializations, different number of epochs (from 4 to 20 in total), different set of filter sizes (either INLINEFORM0 , INLINEFORM1 or INLINEFORM2 ) and different embedding pre-training algorithms (either Word2vec or FastText). 
 Question: How many CNNs and LSTMs were ensembled?
Output (English): 10 CNNs and 10 LSTMs