Table 2.

The performance of our model and baseline models using the full training data set.

Model	Accuracy	Precision	Recall	Macro F1
BERTa	0.836	0.779	0.802	0.788
XLNet	0.844	0.790	0.811	0.795
ERNIEb	0.836	0.786	0.795	0.783
RoBERTac	0.840	0.791	0.800	0.792
Ensemble (Voting)	0.846	0.800	0.812	0.802
Our model	0.846	0.803	0.817	0.808

^aBERT: Bidirectional Encoder Representations from Transformers.

^bERNIE: Enhanced Representation through Knowledge Integration.

^cRoBERTa: A Robustly Optimized BERT Pretraining Approach.