**************__flight_delay_**************
**************__bert_**************
------------union-----------------
Accuracy in F1: 0.8084779266417746, 	 Precision: 0.7012764336064012, 	 Recall: 0.9543686803214934
------------intersection-----------------
Accuracy in F1: 0.8257640674093116, 	 Precision: 0.9192368839427663, 	 Recall: 0.7495462794918331
**************__roberta_**************
------------union-----------------
Accuracy in F1: 0.6758226037195996, 	 Precision: 0.5345503922751962, 	 Recall: 0.9185895773917553
------------intersection-----------------
Accuracy in F1: 0.6390614216701174, 	 Precision: 0.9551315110881898, 	 Recall: 0.4801659320715582
**************__xlnet_**************
------------union-----------------
Accuracy in F1: 0.6491723100075245, 	 Precision: 0.5093726937269373, 	 Recall: 0.8947368421052632
------------intersection-----------------
Accuracy in F1: 0.6185167232186136, 	 Precision: 0.8207547169811321, 	 Recall: 0.49624060150375937
**************__albert_**************
------------union-----------------
Accuracy in F1: 0.7735613010842368, 	 Precision: 0.6469049694856146, 	 Recall: 0.9618874773139746
------------intersection-----------------
Accuracy in F1: 0.8187150837988826, 	 Precision: 0.8873751135331517, 	 Recall: 0.759917033964221
**************__student_perf_**************
**************__bert_**************
------------union-----------------
Accuracy in F1: 0.46738315421144716, 	 Precision: 0.3835110746513536, 	 Recall: 0.5982085732565579
------------intersection-----------------
Accuracy in F1: 0.49979550102249487, 	 Precision: 0.6927437641723356, 	 Recall: 0.3909149072296865
**************__roberta_**************
------------union-----------------
Accuracy in F1: 0.481410079867805, 	 Precision: 0.42263056092843326, 	 Recall: 0.5591810620601407
------------intersection-----------------
Accuracy in F1: 0.35502342529932324, 	 Precision: 0.952513966480447, 	 Recall: 0.218170185540627
**************__xlnet_**************
------------union-----------------
Accuracy in F1: 0.30613041780554473, 	 Precision: 0.22028659735880865, 	 Recall: 0.5015994881637876
------------intersection-----------------
Accuracy in F1: 0.05476042314872434, 	 Precision: 1.0, 	 Recall: 0.02815099168266155
**************__albert_**************
------------union-----------------
Accuracy in F1: 0.5091206098557038, 	 Precision: 0.4431279620853081, 	 Recall: 0.5982085732565579
------------intersection-----------------
Accuracy in F1: 0.5130174989329919, 	 Precision: 0.7705128205128206, 	 Recall: 0.38451695457453616
**************__online_delivary_**************
**************__bert_**************
------------union-----------------
Accuracy in F1: 0.6354117087101381, 	 Precision: 0.5114942528735632, 	 Recall: 0.8385678391959799
------------intersection-----------------
Accuracy in F1: 0.6823687752355316, 	 Precision: 0.7347826086956522, 	 Recall: 0.6369346733668342
**************__roberta_**************
------------union-----------------
Accuracy in F1: 0.6542150429076224, 	 Precision: 0.5468354430379747, 	 Recall: 0.8140703517587939
------------intersection-----------------
Accuracy in F1: 0.5650899958141482, 	 Precision: 0.8511979823455234, 	 Recall: 0.42293233082706766
**************__xlnet_**************
------------union-----------------
Accuracy in F1: 0.4293847566574839, 	 Precision: 0.3033999480923955, 	 Recall: 0.7342964824120602
------------intersection-----------------
Accuracy in F1: 0.4955826672275977, 	 Precision: 0.7503184713375797, 	 Recall: 0.3699748743718593
**************__albert_**************
------------union-----------------
Accuracy in F1: 0.6425073457394711, 	 Precision: 0.5264847512038523, 	 Recall: 0.8241206030150754
------------intersection-----------------
Accuracy in F1: 0.6453827669069686, 	 Precision: 0.7126611068991661, 	 Recall: 0.589711417816813
