Table 13.

Overview of the results (number of wins, rank sum, and rank position, respectively) achieved by evaluating each Transformer-based model on the 22 datasets, for each classification algorithm

Model	LR	SVM	MLP	RF	XGB	Total
Accuracy
BERT	2/45.0/2.0	0/65.0/3.0	3/47.0/2.0	4/46.5/2.0	3/43.5/2.0	12/247.0/11.0
RoBERTa	2/60.0/3.0	3/42.0/2.0	2/57.0/3.0	5/52.5/3.0	0/63.0/3.0	12/274.5/14.0
BERTweet	18/27.0/1.0	19/25.0/1.0	17/28.0/1.0	15/33.0/1.0	20/   25.5/1.0	89/138.5/5.0
$F_1$-macro
BERT	2/45.0/2.0	0/65.0/3.0	3/47.0/2.0	3/48.0/2.0	3/44.0/2.0	11/249.0/11.0
RoBERTa	2/60.0/3.0	3/42.0/2.0	2/57.0/3.0	5/52.5/3.0	0/61.0/3.0	12/272.5/14.0
BERTweet	18/27.0/1.0	19/25.0/1.0	17/28.0/1.0	15/31.5/1.0	19/   27.0/1.0	88/138.5/5.0

Bold values indicate the best results