**************__flight_delay_**************
**************__bert_**************
------------union-----------------
Accuracy in F1: 0.71660777385159, 	 Precision: 0.5868055555555556, 	 Recall: 0.9201451905626135
------------intersection-----------------
Accuracy in F1: 0.8442081057775221, 	 Precision: 0.9471138342470171, 	 Recall: 0.7614726471350791
**************__roberta_**************
------------union-----------------
Accuracy in F1: 0.8324479858344399, 	 Precision: 0.72620196949218, 	 Recall: 0.9751101892662691
------------intersection-----------------
Accuracy in F1: 0.723665107275367, 	 Precision: 0.9577284372331341, 	 Recall: 0.5815400570391496
**************__xlnet_**************
------------union-----------------
Accuracy in F1: 0.5532664471164893, 	 Precision: 0.39260869565217393, 	 Recall: 0.9364791288566243
------------intersection-----------------
Accuracy in F1: 0.3985594237695078, 	 Precision: 0.8729184925503944, 	 Recall: 0.25823178636245786
**************__albert_**************
------------union-----------------
Accuracy in F1: 0.7976255908541278, 	 Precision: 0.6923664122137405, 	 Recall: 0.9406274306455795
------------intersection-----------------
Accuracy in F1: 0.8700914470145239, 	 Precision: 0.9038837664151997, 	 Recall: 0.8387347679543686
**************__student_perf_**************
**************__bert_**************
------------union-----------------
Accuracy in F1: 0.4785276073619632, 	 Precision: 0.4103385178408051, 	 Recall: 0.5738963531669866
------------intersection-----------------
Accuracy in F1: 0.48509123275478416, 	 Precision: 0.7967836257309941, 	 Recall: 0.3486884197056942
**************__roberta_**************
------------union-----------------
Accuracy in F1: 0.4625850340136054, 	 Precision: 0.4152671755725191, 	 Recall: 0.5220729366602687
------------intersection-----------------
Accuracy in F1: 0.3250920568122041, 	 Precision: 0.9142011834319527, 	 Recall: 0.19769673704414586
**************__xlnet_**************
------------union-----------------
Accuracy in F1: 0.3259013282732448, 	 Precision: 0.25895212966453074, 	 Recall: 0.43953934740882916
------------intersection-----------------
Accuracy in F1: 0.07234825260576334, 	 Precision: 0.8676470588235294, 	 Recall: 0.037747920665387076
**************__albert_**************
------------union-----------------
Accuracy in F1: 0.4860557768924303, 	 Precision: 0.41553133514986373, 	 Recall: 0.5854126679462572
------------intersection-----------------
Accuracy in F1: 0.48034107058266223, 	 Precision: 0.9251824817518248, 	 Recall: 0.32437619961612285
**************__online_delivary_**************
**************__bert_**************
------------union-----------------
Accuracy in F1: 0.6295556665002496, 	 Precision: 0.5223695111847556, 	 Recall: 0.7920854271356784
------------intersection-----------------
Accuracy in F1: 0.6172195303764443, 	 Precision: 0.7589367552703942, 	 Recall: 0.5201005025125628
**************__roberta_**************
------------union-----------------
Accuracy in F1: 0.628615702479339, 	 Precision: 0.5337719298245615, 	 Recall: 0.7644472361809045
------------intersection-----------------
Accuracy in F1: 0.5400619743249225, 	 Precision: 0.9214501510574018, 	 Recall: 0.38196618659987475
**************__xlnet_**************
------------union-----------------
Accuracy in F1: 0.4417922948073702, 	 Precision: 0.33134422110552764, 	 Recall: 0.6626884422110553
------------intersection-----------------
Accuracy in F1: 0.11458885941644562, 	 Precision: 0.3737024221453287, 	 Recall: 0.06766917293233082
**************__albert_**************
------------union-----------------
Accuracy in F1: 0.6061479346781941, 	 Precision: 0.4906687402799378, 	 Recall: 0.792713567839196
------------intersection-----------------
Accuracy in F1: 0.6316939890710384, 	 Precision: 0.7545691906005222, 	 Recall: 0.543233082706767
