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.
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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. 
 Question: What hyperparameters have been tuned?

Answer: number of coattention blocks, the batch size, and the number of epochs trained and ensembled our three best networks


Question: We consider QA PGNet and Multi-decoder QA PGNet with lookup table embedding as baseline models and improve on the baselines with other variations described below. 
 Question: What is the baseline?

Answer: QA PGNet Multi-decoder QA PGNet with lookup table embedding


Question: We compare our best F1 score with other state-of-the-art approaches in table TABREF39 , which shows our model has competitive advantage in dealing with drug-drug interaction extraction. 
 Question: What is the performance of their model?

Answer:
Answer with content missing: (Table II) Proposed model has F1 score of  0.7220.