“Why is ‘Chicago’ deceptive?”Towards Building Model-Driven Tutorials for Humans
Table 1: Accuracy of machine learning models on the test set.
['Model', 'Accuracy (%)']
Models. We consider a linear SVM classifier with unigram bag-of-words as features, which represents a simple model, and BERT (devlin2018bert), which represents a deep learning model with state-of-the-art performance in many NLP tasks. The hyperparameter for linear SVM was selected via 5-fold cross validation with the training set; BERT was fine-tuned on 70% of the reviews and the other 10% of the reviews in the training set were used as the development set for selecting hyperparameters.