A Failure of Aspect Sentiment Classifiers and an Adaptive Re-weighting Solution
Table 5: Number of incorrectly predicted training examples (# incorrect examples from contra. sent.) from contrastive sentences in one run of training: the training of the model is early stopped by validation set.
['[EMPTY]', '[BOLD] Laptop', '[BOLD] Restaurant']
We notice that the normal training of deep learning model (BERT-DK) naturally leaves more examples from contrastive sentences unresolved, justifying the reason why BERT-DK has poor performance on contrastive test set. BERT-DK + ARW w/o Contra(⋅) obviously takes care of more examples from contrastive sentences before validation set finds the best model.