lr: 0.0001
sub_1:Test (Best Model) - Loss: 0.6542 - Accuracy: 0.7188 - F1: 0.6946
sub_1:Test (Best Model) - Loss: 0.7645 - Accuracy: 0.6250 - F1: 0.5844
sub_1:Test (Best Model) - Loss: 0.6986 - Accuracy: 0.6875 - F1: 0.6761
sub_1:Test (Best Model) - Loss: 0.6126 - Accuracy: 0.7812 - F1: 0.7519
sub_1:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.7500 - F1: 0.7333
sub_1:Test (Best Model) - Loss: 0.6492 - Accuracy: 0.7273 - F1: 0.6997
sub_1:Test (Best Model) - Loss: 0.4859 - Accuracy: 0.8182 - F1: 0.8036
sub_1:Test (Best Model) - Loss: 0.6435 - Accuracy: 0.7273 - F1: 0.7179
sub_1:Test (Best Model) - Loss: 0.9475 - Accuracy: 0.7273 - F1: 0.6857
sub_1:Test (Best Model) - Loss: 0.8014 - Accuracy: 0.7273 - F1: 0.6857
sub_1:Test (Best Model) - Loss: 0.4769 - Accuracy: 0.8438 - F1: 0.8359
sub_1:Test (Best Model) - Loss: 0.4391 - Accuracy: 0.7188 - F1: 0.6946
sub_1:Test (Best Model) - Loss: 0.2771 - Accuracy: 0.9062 - F1: 0.9039
sub_1:Test (Best Model) - Loss: 0.5650 - Accuracy: 0.7500 - F1: 0.7091
sub_1:Test (Best Model) - Loss: 0.5412 - Accuracy: 0.8125 - F1: 0.8057
sub_2:Test (Best Model) - Loss: 0.8427 - Accuracy: 0.6667 - F1: 0.6553
sub_2:Test (Best Model) - Loss: 0.9470 - Accuracy: 0.7273 - F1: 0.6997
sub_2:Test (Best Model) - Loss: 1.1340 - Accuracy: 0.6970 - F1: 0.6827
sub_2:Test (Best Model) - Loss: 0.9723 - Accuracy: 0.7273 - F1: 0.7102
sub_2:Test (Best Model) - Loss: 0.9842 - Accuracy: 0.7576 - F1: 0.7462
sub_2:Test (Best Model) - Loss: 0.9384 - Accuracy: 0.6250 - F1: 0.5636
sub_2:Test (Best Model) - Loss: 0.8677 - Accuracy: 0.5938 - F1: 0.5135
sub_2:Test (Best Model) - Loss: 0.7704 - Accuracy: 0.6562 - F1: 0.6390
sub_2:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.6562 - F1: 0.5883
sub_2:Test (Best Model) - Loss: 0.7418 - Accuracy: 0.5938 - F1: 0.5393
sub_2:Test (Best Model) - Loss: 0.7200 - Accuracy: 0.6970 - F1: 0.6898
sub_2:Test (Best Model) - Loss: 0.9404 - Accuracy: 0.6061 - F1: 0.6002
sub_2:Test (Best Model) - Loss: 0.6233 - Accuracy: 0.7576 - F1: 0.7574
sub_2:Test (Best Model) - Loss: 0.7567 - Accuracy: 0.6667 - F1: 0.6553
sub_2:Test (Best Model) - Loss: 0.7401 - Accuracy: 0.6970 - F1: 0.6898
sub_3:Test (Best Model) - Loss: 1.2276 - Accuracy: 0.5625 - F1: 0.5625
sub_3:Test (Best Model) - Loss: 1.2288 - Accuracy: 0.5938 - F1: 0.5836
sub_3:Test (Best Model) - Loss: 1.1644 - Accuracy: 0.6250 - F1: 0.6190
sub_3:Test (Best Model) - Loss: 1.2807 - Accuracy: 0.5938 - F1: 0.5589
sub_3:Test (Best Model) - Loss: 1.1656 - Accuracy: 0.4688 - F1: 0.4555
sub_3:Test (Best Model) - Loss: 0.9450 - Accuracy: 0.6061 - F1: 0.5815
sub_3:Test (Best Model) - Loss: 1.2934 - Accuracy: 0.3939 - F1: 0.3934
sub_3:Test (Best Model) - Loss: 0.9974 - Accuracy: 0.5758 - F1: 0.5658
sub_3:Test (Best Model) - Loss: 1.2820 - Accuracy: 0.5152 - F1: 0.4545
sub_3:Test (Best Model) - Loss: 1.3159 - Accuracy: 0.4242 - F1: 0.4157
sub_3:Test (Best Model) - Loss: 1.7421 - Accuracy: 0.5152 - F1: 0.5038
sub_3:Test (Best Model) - Loss: 1.1760 - Accuracy: 0.4545 - F1: 0.4288
sub_3:Test (Best Model) - Loss: 1.3486 - Accuracy: 0.4545 - F1: 0.3864
sub_3:Test (Best Model) - Loss: 1.4613 - Accuracy: 0.4242 - F1: 0.3660
sub_3:Test (Best Model) - Loss: 1.6336 - Accuracy: 0.3333 - F1: 0.3019
sub_4:Test (Best Model) - Loss: 0.9722 - Accuracy: 0.6061 - F1: 0.5460
sub_4:Test (Best Model) - Loss: 0.5972 - Accuracy: 0.7273 - F1: 0.6857
sub_4:Test (Best Model) - Loss: 0.8724 - Accuracy: 0.6364 - F1: 0.5909
sub_4:Test (Best Model) - Loss: 0.7348 - Accuracy: 0.6970 - F1: 0.6591
sub_4:Test (Best Model) - Loss: 1.1729 - Accuracy: 0.6061 - F1: 0.5196
sub_4:Test (Best Model) - Loss: 0.8406 - Accuracy: 0.6970 - F1: 0.6413
sub_4:Test (Best Model) - Loss: 0.9129 - Accuracy: 0.6061 - F1: 0.5662
sub_4:Test (Best Model) - Loss: 0.7710 - Accuracy: 0.6364 - F1: 0.6071
sub_4:Test (Best Model) - Loss: 1.3513 - Accuracy: 0.6061 - F1: 0.5662
sub_4:Test (Best Model) - Loss: 1.6480 - Accuracy: 0.6364 - F1: 0.5909
sub_4:Test (Best Model) - Loss: 0.6452 - Accuracy: 0.6667 - F1: 0.6667
sub_4:Test (Best Model) - Loss: 0.8334 - Accuracy: 0.6667 - F1: 0.6553
sub_4:Test (Best Model) - Loss: 0.4756 - Accuracy: 0.7879 - F1: 0.7806
sub_4:Test (Best Model) - Loss: 0.5418 - Accuracy: 0.7273 - F1: 0.7263
sub_4:Test (Best Model) - Loss: 0.4592 - Accuracy: 0.6970 - F1: 0.6944
sub_5:Test (Best Model) - Loss: 1.6874 - Accuracy: 0.3438 - F1: 0.3431
sub_5:Test (Best Model) - Loss: 1.4409 - Accuracy: 0.4688 - F1: 0.4640
sub_5:Test (Best Model) - Loss: 2.0835 - Accuracy: 0.4688 - F1: 0.4640
sub_5:Test (Best Model) - Loss: 1.4097 - Accuracy: 0.5312 - F1: 0.5308
sub_5:Test (Best Model) - Loss: 1.2240 - Accuracy: 0.4688 - F1: 0.4682
sub_5:Test (Best Model) - Loss: 0.9109 - Accuracy: 0.5000 - F1: 0.4667
sub_5:Test (Best Model) - Loss: 0.7794 - Accuracy: 0.4688 - F1: 0.4231
sub_5:Test (Best Model) - Loss: 0.6522 - Accuracy: 0.6250 - F1: 0.6250
sub_5:Test (Best Model) - Loss: 0.7617 - Accuracy: 0.5625 - F1: 0.5608
sub_5:Test (Best Model) - Loss: 0.7161 - Accuracy: 0.6250 - F1: 0.6235
sub_5:Test (Best Model) - Loss: 1.0199 - Accuracy: 0.5312 - F1: 0.5195
sub_5:Test (Best Model) - Loss: 1.1286 - Accuracy: 0.5000 - F1: 0.4921
sub_5:Test (Best Model) - Loss: 1.1509 - Accuracy: 0.5625 - F1: 0.5556
sub_5:Test (Best Model) - Loss: 0.7775 - Accuracy: 0.6250 - F1: 0.6235
sub_5:Test (Best Model) - Loss: 0.9942 - Accuracy: 0.5625 - F1: 0.5608
sub_6:Test (Best Model) - Loss: 0.9870 - Accuracy: 0.6875 - F1: 0.6537
sub_6:Test (Best Model) - Loss: 1.0147 - Accuracy: 0.7500 - F1: 0.7333
sub_6:Test (Best Model) - Loss: 1.0648 - Accuracy: 0.5938 - F1: 0.5589
sub_6:Test (Best Model) - Loss: 0.9509 - Accuracy: 0.6562 - F1: 0.6390
sub_6:Test (Best Model) - Loss: 0.7978 - Accuracy: 0.7500 - F1: 0.7229
sub_6:Test (Best Model) - Loss: 1.9105 - Accuracy: 0.4545 - F1: 0.3125
sub_6:Test (Best Model) - Loss: 2.2621 - Accuracy: 0.4545 - F1: 0.3125
sub_6:Test (Best Model) - Loss: 2.4031 - Accuracy: 0.4848 - F1: 0.3265
sub_6:Test (Best Model) - Loss: 1.9672 - Accuracy: 0.5152 - F1: 0.3400
sub_6:Test (Best Model) - Loss: 2.1555 - Accuracy: 0.5152 - F1: 0.3889
sub_6:Test (Best Model) - Loss: 1.1222 - Accuracy: 0.5758 - F1: 0.4978
sub_6:Test (Best Model) - Loss: 0.8653 - Accuracy: 0.6364 - F1: 0.5909
sub_6:Test (Best Model) - Loss: 0.8596 - Accuracy: 0.5758 - F1: 0.4978
sub_6:Test (Best Model) - Loss: 0.9683 - Accuracy: 0.7273 - F1: 0.6857
sub_6:Test (Best Model) - Loss: 1.0422 - Accuracy: 0.6364 - F1: 0.5696
sub_7:Test (Best Model) - Loss: 0.8088 - Accuracy: 0.5625 - F1: 0.5152
sub_7:Test (Best Model) - Loss: 1.0252 - Accuracy: 0.5625 - F1: 0.5152
sub_7:Test (Best Model) - Loss: 1.2195 - Accuracy: 0.5000 - F1: 0.4818
sub_7:Test (Best Model) - Loss: 0.9278 - Accuracy: 0.6250 - F1: 0.6190
sub_7:Test (Best Model) - Loss: 1.1716 - Accuracy: 0.5000 - F1: 0.4818
sub_7:Test (Best Model) - Loss: 1.5817 - Accuracy: 0.3750 - F1: 0.3750
sub_7:Test (Best Model) - Loss: 1.2399 - Accuracy: 0.4375 - F1: 0.4170
sub_7:Test (Best Model) - Loss: 1.2862 - Accuracy: 0.4062 - F1: 0.4010
sub_7:Test (Best Model) - Loss: 1.6318 - Accuracy: 0.4688 - F1: 0.4640
sub_7:Test (Best Model) - Loss: 1.1882 - Accuracy: 0.3750 - F1: 0.3725
sub_7:Test (Best Model) - Loss: 0.9220 - Accuracy: 0.6250 - F1: 0.6250
sub_7:Test (Best Model) - Loss: 1.2850 - Accuracy: 0.5000 - F1: 0.5000
sub_7:Test (Best Model) - Loss: 1.4240 - Accuracy: 0.5625 - F1: 0.5556
sub_7:Test (Best Model) - Loss: 0.8304 - Accuracy: 0.6250 - F1: 0.6235
sub_7:Test (Best Model) - Loss: 0.8296 - Accuracy: 0.6562 - F1: 0.6559
sub_8:Test (Best Model) - Loss: 1.1127 - Accuracy: 0.5625 - F1: 0.5333
sub_8:Test (Best Model) - Loss: 1.6957 - Accuracy: 0.6562 - F1: 0.5883
sub_8:Test (Best Model) - Loss: 1.0032 - Accuracy: 0.6562 - F1: 0.6532
sub_8:Test (Best Model) - Loss: 0.9138 - Accuracy: 0.7188 - F1: 0.6632
sub_8:Test (Best Model) - Loss: 1.2773 - Accuracy: 0.6562 - F1: 0.6102
sub_8:Test (Best Model) - Loss: 0.7951 - Accuracy: 0.7812 - F1: 0.7625
sub_8:Test (Best Model) - Loss: 1.3558 - Accuracy: 0.6875 - F1: 0.6537
sub_8:Test (Best Model) - Loss: 0.9330 - Accuracy: 0.5938 - F1: 0.5589
sub_8:Test (Best Model) - Loss: 1.8936 - Accuracy: 0.5625 - F1: 0.5333
sub_8:Test (Best Model) - Loss: 1.0068 - Accuracy: 0.7188 - F1: 0.6632
sub_8:Test (Best Model) - Loss: 1.2238 - Accuracy: 0.4375 - F1: 0.4286
sub_8:Test (Best Model) - Loss: 1.0896 - Accuracy: 0.5312 - F1: 0.5195
sub_8:Test (Best Model) - Loss: 0.7913 - Accuracy: 0.5938 - F1: 0.5733
sub_8:Test (Best Model) - Loss: 0.8744 - Accuracy: 0.6562 - F1: 0.6267
sub_8:Test (Best Model) - Loss: 0.7082 - Accuracy: 0.6250 - F1: 0.6113
sub_9:Test (Best Model) - Loss: 0.6479 - Accuracy: 0.7812 - F1: 0.7519
sub_9:Test (Best Model) - Loss: 0.8626 - Accuracy: 0.7188 - F1: 0.6946
sub_9:Test (Best Model) - Loss: 0.5095 - Accuracy: 0.7500 - F1: 0.7409
sub_9:Test (Best Model) - Loss: 0.7019 - Accuracy: 0.6875 - F1: 0.6537
sub_9:Test (Best Model) - Loss: 0.6463 - Accuracy: 0.8125 - F1: 0.7922
sub_9:Test (Best Model) - Loss: 0.6526 - Accuracy: 0.7188 - F1: 0.7117
sub_9:Test (Best Model) - Loss: 0.6717 - Accuracy: 0.6562 - F1: 0.6476
sub_9:Test (Best Model) - Loss: 1.0723 - Accuracy: 0.6562 - F1: 0.6390
sub_9:Test (Best Model) - Loss: 0.7731 - Accuracy: 0.7188 - F1: 0.7117
sub_9:Test (Best Model) - Loss: 0.8484 - Accuracy: 0.6250 - F1: 0.6000
sub_9:Test (Best Model) - Loss: 1.3021 - Accuracy: 0.5938 - F1: 0.5589
sub_9:Test (Best Model) - Loss: 0.8924 - Accuracy: 0.7188 - F1: 0.7163
sub_9:Test (Best Model) - Loss: 1.4255 - Accuracy: 0.5312 - F1: 0.5271
sub_9:Test (Best Model) - Loss: 1.0689 - Accuracy: 0.7188 - F1: 0.7117
sub_9:Test (Best Model) - Loss: 0.7961 - Accuracy: 0.6875 - F1: 0.6825
sub_10:Test (Best Model) - Loss: 0.9627 - Accuracy: 0.5312 - F1: 0.4910
sub_10:Test (Best Model) - Loss: 0.8984 - Accuracy: 0.5625 - F1: 0.5556
sub_10:Test (Best Model) - Loss: 0.9778 - Accuracy: 0.4062 - F1: 0.3914
sub_10:Test (Best Model) - Loss: 1.0684 - Accuracy: 0.5625 - F1: 0.4909
sub_10:Test (Best Model) - Loss: 1.3550 - Accuracy: 0.5312 - F1: 0.5308
sub_10:Test (Best Model) - Loss: 1.2287 - Accuracy: 0.4688 - F1: 0.4640
sub_10:Test (Best Model) - Loss: 1.3466 - Accuracy: 0.5625 - F1: 0.5466
sub_10:Test (Best Model) - Loss: 1.2472 - Accuracy: 0.4375 - F1: 0.4353
sub_10:Test (Best Model) - Loss: 1.1608 - Accuracy: 0.5000 - F1: 0.4921
sub_10:Test (Best Model) - Loss: 1.4931 - Accuracy: 0.3438 - F1: 0.3431
sub_10:Test (Best Model) - Loss: 1.1808 - Accuracy: 0.4848 - F1: 0.4772
sub_10:Test (Best Model) - Loss: 1.2528 - Accuracy: 0.4848 - F1: 0.4848
sub_10:Test (Best Model) - Loss: 1.0215 - Accuracy: 0.6061 - F1: 0.6046
sub_10:Test (Best Model) - Loss: 1.0835 - Accuracy: 0.5152 - F1: 0.5111
sub_10:Test (Best Model) - Loss: 1.2514 - Accuracy: 0.5758 - F1: 0.5658
sub_11:Test (Best Model) - Loss: 1.9548 - Accuracy: 0.4848 - F1: 0.4527
sub_11:Test (Best Model) - Loss: 1.4277 - Accuracy: 0.4848 - F1: 0.4527
sub_11:Test (Best Model) - Loss: 1.4771 - Accuracy: 0.4545 - F1: 0.4417
sub_11:Test (Best Model) - Loss: 1.0989 - Accuracy: 0.5455 - F1: 0.5171
sub_11:Test (Best Model) - Loss: 1.5627 - Accuracy: 0.4848 - F1: 0.4527
sub_11:Test (Best Model) - Loss: 1.3175 - Accuracy: 0.5455 - F1: 0.4058
sub_11:Test (Best Model) - Loss: 1.2485 - Accuracy: 0.5758 - F1: 0.4225
sub_11:Test (Best Model) - Loss: 0.9547 - Accuracy: 0.5758 - F1: 0.4978
sub_11:Test (Best Model) - Loss: 1.5926 - Accuracy: 0.4848 - F1: 0.4328
sub_11:Test (Best Model) - Loss: 1.2245 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 1.0299 - Accuracy: 0.4848 - F1: 0.3718
sub_11:Test (Best Model) - Loss: 0.8002 - Accuracy: 0.6061 - F1: 0.5662
sub_11:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.5455 - F1: 0.4457
sub_11:Test (Best Model) - Loss: 1.1933 - Accuracy: 0.5758 - F1: 0.4653
sub_11:Test (Best Model) - Loss: 1.3385 - Accuracy: 0.6061 - F1: 0.4850
sub_12:Test (Best Model) - Loss: 0.7886 - Accuracy: 0.7188 - F1: 0.6946
sub_12:Test (Best Model) - Loss: 0.8580 - Accuracy: 0.6250 - F1: 0.5636
sub_12:Test (Best Model) - Loss: 0.9990 - Accuracy: 0.7188 - F1: 0.6811
sub_12:Test (Best Model) - Loss: 0.8465 - Accuracy: 0.7188 - F1: 0.6946
sub_12:Test (Best Model) - Loss: 1.2274 - Accuracy: 0.6562 - F1: 0.5883
sub_12:Test (Best Model) - Loss: 0.7501 - Accuracy: 0.6667 - F1: 0.6330
sub_12:Test (Best Model) - Loss: 0.9423 - Accuracy: 0.6364 - F1: 0.5909
sub_12:Test (Best Model) - Loss: 0.9119 - Accuracy: 0.6061 - F1: 0.4850
sub_12:Test (Best Model) - Loss: 1.0434 - Accuracy: 0.6061 - F1: 0.5196
sub_12:Test (Best Model) - Loss: 0.5697 - Accuracy: 0.7273 - F1: 0.6997
sub_12:Test (Best Model) - Loss: 1.0771 - Accuracy: 0.5938 - F1: 0.5393
sub_12:Test (Best Model) - Loss: 1.1450 - Accuracy: 0.5625 - F1: 0.5556
sub_12:Test (Best Model) - Loss: 1.0721 - Accuracy: 0.5625 - F1: 0.5466
sub_12:Test (Best Model) - Loss: 1.0694 - Accuracy: 0.6250 - F1: 0.6000
sub_12:Test (Best Model) - Loss: 1.1390 - Accuracy: 0.5938 - F1: 0.5589
sub_13:Test (Best Model) - Loss: 0.5663 - Accuracy: 0.7812 - F1: 0.7758
sub_13:Test (Best Model) - Loss: 0.6382 - Accuracy: 0.7812 - F1: 0.7758
sub_13:Test (Best Model) - Loss: 0.4305 - Accuracy: 0.8750 - F1: 0.8730
sub_13:Test (Best Model) - Loss: 0.7611 - Accuracy: 0.6875 - F1: 0.6875
sub_13:Test (Best Model) - Loss: 0.4355 - Accuracy: 0.8438 - F1: 0.8303
sub_13:Test (Best Model) - Loss: 0.8262 - Accuracy: 0.6364 - F1: 0.6192
sub_13:Test (Best Model) - Loss: 0.5470 - Accuracy: 0.8182 - F1: 0.8180
sub_13:Test (Best Model) - Loss: 0.8328 - Accuracy: 0.5455 - F1: 0.5438
sub_13:Test (Best Model) - Loss: 0.8685 - Accuracy: 0.5152 - F1: 0.5147
sub_13:Test (Best Model) - Loss: 0.8228 - Accuracy: 0.5758 - F1: 0.5754
sub_13:Test (Best Model) - Loss: 0.5374 - Accuracy: 0.6875 - F1: 0.6875
sub_13:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.7188 - F1: 0.7117
sub_13:Test (Best Model) - Loss: 0.4842 - Accuracy: 0.7500 - F1: 0.7460
sub_13:Test (Best Model) - Loss: 0.5402 - Accuracy: 0.8125 - F1: 0.8095
sub_13:Test (Best Model) - Loss: 0.6259 - Accuracy: 0.7188 - F1: 0.7163
sub_14:Test (Best Model) - Loss: 0.8977 - Accuracy: 0.6250 - F1: 0.6250
sub_14:Test (Best Model) - Loss: 0.6141 - Accuracy: 0.7188 - F1: 0.7117
sub_14:Test (Best Model) - Loss: 1.1030 - Accuracy: 0.5625 - F1: 0.5556
sub_14:Test (Best Model) - Loss: 0.7811 - Accuracy: 0.5938 - F1: 0.5934
sub_14:Test (Best Model) - Loss: 0.5901 - Accuracy: 0.7188 - F1: 0.7185
sub_14:Test (Best Model) - Loss: 0.6389 - Accuracy: 0.6250 - F1: 0.6113
sub_14:Test (Best Model) - Loss: 0.7334 - Accuracy: 0.5938 - F1: 0.5589
sub_14:Test (Best Model) - Loss: 0.8227 - Accuracy: 0.5000 - F1: 0.4921
sub_14:Test (Best Model) - Loss: 0.8817 - Accuracy: 0.5938 - F1: 0.5589
sub_14:Test (Best Model) - Loss: 0.9183 - Accuracy: 0.5625 - F1: 0.5152
sub_14:Test (Best Model) - Loss: 0.6404 - Accuracy: 0.7188 - F1: 0.6811
sub_14:Test (Best Model) - Loss: 0.8495 - Accuracy: 0.5625 - F1: 0.5466
sub_14:Test (Best Model) - Loss: 0.9827 - Accuracy: 0.6250 - F1: 0.6113
sub_14:Test (Best Model) - Loss: 1.3732 - Accuracy: 0.4688 - F1: 0.4555
sub_14:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5625 - F1: 0.5466
sub_15:Test (Best Model) - Loss: 1.2734 - Accuracy: 0.7500 - F1: 0.7333
sub_15:Test (Best Model) - Loss: 1.0682 - Accuracy: 0.5312 - F1: 0.5308
sub_15:Test (Best Model) - Loss: 1.0161 - Accuracy: 0.6562 - F1: 0.6532
sub_15:Test (Best Model) - Loss: 1.3159 - Accuracy: 0.5938 - F1: 0.5934
sub_15:Test (Best Model) - Loss: 1.0060 - Accuracy: 0.6875 - F1: 0.6761
sub_15:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.6562 - F1: 0.6559
sub_15:Test (Best Model) - Loss: 1.5347 - Accuracy: 0.5625 - F1: 0.5556
sub_15:Test (Best Model) - Loss: 1.0686 - Accuracy: 0.6250 - F1: 0.6235
sub_15:Test (Best Model) - Loss: 1.3609 - Accuracy: 0.5938 - F1: 0.5733
sub_15:Test (Best Model) - Loss: 1.8675 - Accuracy: 0.5312 - F1: 0.5271
sub_15:Test (Best Model) - Loss: 0.7965 - Accuracy: 0.6562 - F1: 0.6532
sub_15:Test (Best Model) - Loss: 0.8708 - Accuracy: 0.6250 - F1: 0.6000
sub_15:Test (Best Model) - Loss: 1.1328 - Accuracy: 0.5000 - F1: 0.4921
sub_15:Test (Best Model) - Loss: 1.1166 - Accuracy: 0.6250 - F1: 0.6113
sub_15:Test (Best Model) - Loss: 0.8846 - Accuracy: 0.5938 - F1: 0.5836
sub_16:Test (Best Model) - Loss: 0.9294 - Accuracy: 0.5625 - F1: 0.5608
sub_16:Test (Best Model) - Loss: 0.8282 - Accuracy: 0.5625 - F1: 0.5608
sub_16:Test (Best Model) - Loss: 0.9340 - Accuracy: 0.5312 - F1: 0.5271
sub_16:Test (Best Model) - Loss: 0.8214 - Accuracy: 0.5625 - F1: 0.5556
sub_16:Test (Best Model) - Loss: 0.9208 - Accuracy: 0.5938 - F1: 0.5901
sub_16:Test (Best Model) - Loss: 1.2347 - Accuracy: 0.7188 - F1: 0.7163
sub_16:Test (Best Model) - Loss: 1.0528 - Accuracy: 0.7500 - F1: 0.7409
sub_16:Test (Best Model) - Loss: 1.0559 - Accuracy: 0.7500 - F1: 0.7460
sub_16:Test (Best Model) - Loss: 0.9364 - Accuracy: 0.6875 - F1: 0.6761
sub_16:Test (Best Model) - Loss: 1.4415 - Accuracy: 0.6875 - F1: 0.6825
sub_16:Test (Best Model) - Loss: 1.5525 - Accuracy: 0.5312 - F1: 0.5077
sub_16:Test (Best Model) - Loss: 1.3497 - Accuracy: 0.5000 - F1: 0.4182
sub_16:Test (Best Model) - Loss: 1.3910 - Accuracy: 0.5938 - F1: 0.5589
sub_16:Test (Best Model) - Loss: 1.2319 - Accuracy: 0.5625 - F1: 0.5333
sub_16:Test (Best Model) - Loss: 1.4068 - Accuracy: 0.5312 - F1: 0.4684
sub_17:Test (Best Model) - Loss: 0.8838 - Accuracy: 0.6667 - F1: 0.6459
sub_17:Test (Best Model) - Loss: 0.7955 - Accuracy: 0.6364 - F1: 0.6278
sub_17:Test (Best Model) - Loss: 0.8814 - Accuracy: 0.4848 - F1: 0.4772
sub_17:Test (Best Model) - Loss: 1.0754 - Accuracy: 0.6061 - F1: 0.5662
sub_17:Test (Best Model) - Loss: 0.7837 - Accuracy: 0.5758 - F1: 0.5227
sub_17:Test (Best Model) - Loss: 1.1978 - Accuracy: 0.4242 - F1: 0.4157
sub_17:Test (Best Model) - Loss: 1.0016 - Accuracy: 0.5455 - F1: 0.5299
sub_17:Test (Best Model) - Loss: 1.2529 - Accuracy: 0.5455 - F1: 0.5438
sub_17:Test (Best Model) - Loss: 0.9457 - Accuracy: 0.5758 - F1: 0.5417
sub_17:Test (Best Model) - Loss: 0.9116 - Accuracy: 0.5152 - F1: 0.4762
sub_17:Test (Best Model) - Loss: 0.8230 - Accuracy: 0.5000 - F1: 0.4980
sub_17:Test (Best Model) - Loss: 0.9749 - Accuracy: 0.5625 - F1: 0.5466
sub_17:Test (Best Model) - Loss: 1.2505 - Accuracy: 0.5312 - F1: 0.4910
sub_17:Test (Best Model) - Loss: 1.0735 - Accuracy: 0.6562 - F1: 0.6476
sub_17:Test (Best Model) - Loss: 1.1088 - Accuracy: 0.5625 - F1: 0.5466
sub_18:Test (Best Model) - Loss: 0.6193 - Accuracy: 0.6970 - F1: 0.6967
sub_18:Test (Best Model) - Loss: 0.6333 - Accuracy: 0.7273 - F1: 0.7263
sub_18:Test (Best Model) - Loss: 0.6498 - Accuracy: 0.6970 - F1: 0.6944
sub_18:Test (Best Model) - Loss: 0.6041 - Accuracy: 0.7576 - F1: 0.7462
sub_18:Test (Best Model) - Loss: 0.4298 - Accuracy: 0.7273 - F1: 0.7232
sub_18:Test (Best Model) - Loss: 0.7531 - Accuracy: 0.6562 - F1: 0.6532
sub_18:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.6875 - F1: 0.6825
sub_18:Test (Best Model) - Loss: 0.8649 - Accuracy: 0.6250 - F1: 0.6235
sub_18:Test (Best Model) - Loss: 0.7833 - Accuracy: 0.7812 - F1: 0.7758
sub_18:Test (Best Model) - Loss: 0.7224 - Accuracy: 0.7188 - F1: 0.7046
sub_18:Test (Best Model) - Loss: 0.5100 - Accuracy: 0.7500 - F1: 0.7409
sub_18:Test (Best Model) - Loss: 0.7140 - Accuracy: 0.7188 - F1: 0.7046
sub_18:Test (Best Model) - Loss: 0.5252 - Accuracy: 0.8125 - F1: 0.8000
sub_18:Test (Best Model) - Loss: 0.7256 - Accuracy: 0.7500 - F1: 0.7460
sub_18:Test (Best Model) - Loss: 0.6266 - Accuracy: 0.6875 - F1: 0.6537
sub_19:Test (Best Model) - Loss: 1.3805 - Accuracy: 0.5000 - F1: 0.3333
sub_19:Test (Best Model) - Loss: 1.0143 - Accuracy: 0.5938 - F1: 0.4340
sub_19:Test (Best Model) - Loss: 1.0440 - Accuracy: 0.4688 - F1: 0.3637
sub_19:Test (Best Model) - Loss: 1.6849 - Accuracy: 0.4688 - F1: 0.3637
sub_19:Test (Best Model) - Loss: 1.1853 - Accuracy: 0.5625 - F1: 0.4167
sub_19:Test (Best Model) - Loss: 1.2440 - Accuracy: 0.5000 - F1: 0.4182
sub_19:Test (Best Model) - Loss: 1.1239 - Accuracy: 0.5312 - F1: 0.4386
sub_19:Test (Best Model) - Loss: 1.1510 - Accuracy: 0.5000 - F1: 0.4459
sub_19:Test (Best Model) - Loss: 1.2594 - Accuracy: 0.5000 - F1: 0.4182
sub_19:Test (Best Model) - Loss: 1.4064 - Accuracy: 0.4688 - F1: 0.4421
sub_19:Test (Best Model) - Loss: 1.0611 - Accuracy: 0.5000 - F1: 0.4921
sub_19:Test (Best Model) - Loss: 0.9558 - Accuracy: 0.5938 - F1: 0.5901
sub_19:Test (Best Model) - Loss: 0.8857 - Accuracy: 0.5625 - F1: 0.5608
sub_19:Test (Best Model) - Loss: 0.7159 - Accuracy: 0.6562 - F1: 0.6532
sub_19:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.6250 - F1: 0.6250
sub_20:Test (Best Model) - Loss: 1.2186 - Accuracy: 0.6562 - F1: 0.5883
sub_20:Test (Best Model) - Loss: 1.0261 - Accuracy: 0.6250 - F1: 0.5636
sub_20:Test (Best Model) - Loss: 1.4414 - Accuracy: 0.6250 - F1: 0.5844
sub_20:Test (Best Model) - Loss: 1.1756 - Accuracy: 0.5938 - F1: 0.5135
sub_20:Test (Best Model) - Loss: 1.7047 - Accuracy: 0.5312 - F1: 0.4386
sub_20:Test (Best Model) - Loss: 1.1863 - Accuracy: 0.7188 - F1: 0.7117
sub_20:Test (Best Model) - Loss: 1.1509 - Accuracy: 0.6250 - F1: 0.6000
sub_20:Test (Best Model) - Loss: 1.5214 - Accuracy: 0.5625 - F1: 0.5152
sub_20:Test (Best Model) - Loss: 1.2989 - Accuracy: 0.6562 - F1: 0.6390
sub_20:Test (Best Model) - Loss: 1.1411 - Accuracy: 0.6875 - F1: 0.6667
sub_20:Test (Best Model) - Loss: 1.6404 - Accuracy: 0.4848 - F1: 0.4672
sub_20:Test (Best Model) - Loss: 1.8902 - Accuracy: 0.5758 - F1: 0.5558
sub_20:Test (Best Model) - Loss: 1.5342 - Accuracy: 0.6364 - F1: 0.6278
sub_20:Test (Best Model) - Loss: 2.3227 - Accuracy: 0.5455 - F1: 0.5171
sub_20:Test (Best Model) - Loss: 1.3819 - Accuracy: 0.6970 - F1: 0.6726
sub_21:Test (Best Model) - Loss: 1.4872 - Accuracy: 0.4375 - F1: 0.4170
sub_21:Test (Best Model) - Loss: 1.5022 - Accuracy: 0.3438 - F1: 0.3431
sub_21:Test (Best Model) - Loss: 1.4856 - Accuracy: 0.3750 - F1: 0.3333
sub_21:Test (Best Model) - Loss: 1.3798 - Accuracy: 0.4062 - F1: 0.3552
sub_21:Test (Best Model) - Loss: 1.4564 - Accuracy: 0.5312 - F1: 0.5077
sub_21:Test (Best Model) - Loss: 1.1162 - Accuracy: 0.5000 - F1: 0.4182
sub_21:Test (Best Model) - Loss: 1.1587 - Accuracy: 0.4062 - F1: 0.3914
sub_21:Test (Best Model) - Loss: 1.3118 - Accuracy: 0.3125 - F1: 0.3016
sub_21:Test (Best Model) - Loss: 1.3095 - Accuracy: 0.5312 - F1: 0.4910
sub_21:Test (Best Model) - Loss: 1.1166 - Accuracy: 0.6250 - F1: 0.6190
sub_21:Test (Best Model) - Loss: 1.4579 - Accuracy: 0.3438 - F1: 0.3273
sub_21:Test (Best Model) - Loss: 1.3410 - Accuracy: 0.4062 - F1: 0.3914
sub_21:Test (Best Model) - Loss: 1.7213 - Accuracy: 0.3750 - F1: 0.3333
sub_21:Test (Best Model) - Loss: 1.6032 - Accuracy: 0.2812 - F1: 0.2451
sub_21:Test (Best Model) - Loss: 1.5295 - Accuracy: 0.3750 - F1: 0.3333
sub_22:Test (Best Model) - Loss: 0.7511 - Accuracy: 0.6875 - F1: 0.6537
sub_22:Test (Best Model) - Loss: 0.6583 - Accuracy: 0.7188 - F1: 0.6946
sub_22:Test (Best Model) - Loss: 0.6464 - Accuracy: 0.6875 - F1: 0.6761
sub_22:Test (Best Model) - Loss: 0.6657 - Accuracy: 0.5938 - F1: 0.4793
sub_22:Test (Best Model) - Loss: 0.8610 - Accuracy: 0.6250 - F1: 0.5636
sub_22:Test (Best Model) - Loss: 1.0304 - Accuracy: 0.5758 - F1: 0.4978
sub_22:Test (Best Model) - Loss: 0.8060 - Accuracy: 0.6667 - F1: 0.5935
sub_22:Test (Best Model) - Loss: 1.1628 - Accuracy: 0.6970 - F1: 0.6413
sub_22:Test (Best Model) - Loss: 1.2210 - Accuracy: 0.6061 - F1: 0.4850
sub_22:Test (Best Model) - Loss: 0.9155 - Accuracy: 0.6667 - F1: 0.6330
sub_22:Test (Best Model) - Loss: 0.8879 - Accuracy: 0.7188 - F1: 0.7046
sub_22:Test (Best Model) - Loss: 0.8356 - Accuracy: 0.6250 - F1: 0.6190
sub_22:Test (Best Model) - Loss: 0.8882 - Accuracy: 0.6562 - F1: 0.6102
sub_22:Test (Best Model) - Loss: 0.7149 - Accuracy: 0.6875 - F1: 0.6364
sub_22:Test (Best Model) - Loss: 0.7624 - Accuracy: 0.6875 - F1: 0.6761
sub_23:Test (Best Model) - Loss: 0.9311 - Accuracy: 0.6970 - F1: 0.6726
sub_23:Test (Best Model) - Loss: 0.9681 - Accuracy: 0.6970 - F1: 0.6413
sub_23:Test (Best Model) - Loss: 1.1094 - Accuracy: 0.6667 - F1: 0.5935
sub_23:Test (Best Model) - Loss: 0.9070 - Accuracy: 0.6061 - F1: 0.4850
sub_23:Test (Best Model) - Loss: 0.7865 - Accuracy: 0.6970 - F1: 0.6591
sub_23:Test (Best Model) - Loss: 1.0743 - Accuracy: 0.4688 - F1: 0.4682
sub_23:Test (Best Model) - Loss: 0.8577 - Accuracy: 0.6250 - F1: 0.6235
sub_23:Test (Best Model) - Loss: 0.6738 - Accuracy: 0.6562 - F1: 0.6476
sub_23:Test (Best Model) - Loss: 0.5778 - Accuracy: 0.6875 - F1: 0.6875
sub_23:Test (Best Model) - Loss: 0.8254 - Accuracy: 0.5938 - F1: 0.5934
sub_23:Test (Best Model) - Loss: 1.2399 - Accuracy: 0.6061 - F1: 0.5196
sub_23:Test (Best Model) - Loss: 0.7717 - Accuracy: 0.6667 - F1: 0.6330
sub_23:Test (Best Model) - Loss: 0.7399 - Accuracy: 0.6970 - F1: 0.6591
sub_23:Test (Best Model) - Loss: 1.1674 - Accuracy: 0.6061 - F1: 0.5196
sub_23:Test (Best Model) - Loss: 1.1251 - Accuracy: 0.6364 - F1: 0.5696
sub_24:Test (Best Model) - Loss: 1.1483 - Accuracy: 0.5938 - F1: 0.5836
sub_24:Test (Best Model) - Loss: 1.1294 - Accuracy: 0.4375 - F1: 0.4353
sub_24:Test (Best Model) - Loss: 1.0404 - Accuracy: 0.4688 - F1: 0.4640
sub_24:Test (Best Model) - Loss: 1.0380 - Accuracy: 0.5938 - F1: 0.5836
sub_24:Test (Best Model) - Loss: 0.9058 - Accuracy: 0.5625 - F1: 0.5466
sub_24:Test (Best Model) - Loss: 1.0149 - Accuracy: 0.5938 - F1: 0.5901
sub_24:Test (Best Model) - Loss: 0.8739 - Accuracy: 0.5938 - F1: 0.5934
sub_24:Test (Best Model) - Loss: 0.9501 - Accuracy: 0.5625 - F1: 0.5608
sub_24:Test (Best Model) - Loss: 0.7705 - Accuracy: 0.5938 - F1: 0.5733
sub_24:Test (Best Model) - Loss: 0.6848 - Accuracy: 0.6875 - F1: 0.6875
sub_24:Test (Best Model) - Loss: 1.5357 - Accuracy: 0.5312 - F1: 0.5195
sub_24:Test (Best Model) - Loss: 1.3800 - Accuracy: 0.4375 - F1: 0.4353
sub_24:Test (Best Model) - Loss: 1.3131 - Accuracy: 0.4375 - F1: 0.4375
sub_24:Test (Best Model) - Loss: 1.3619 - Accuracy: 0.5000 - F1: 0.4818
sub_24:Test (Best Model) - Loss: 1.2141 - Accuracy: 0.5312 - F1: 0.4910
sub_25:Test (Best Model) - Loss: 1.4471 - Accuracy: 0.4242 - F1: 0.2979
sub_25:Test (Best Model) - Loss: 1.2987 - Accuracy: 0.4545 - F1: 0.4288
sub_25:Test (Best Model) - Loss: 1.3074 - Accuracy: 0.5152 - F1: 0.4762
sub_25:Test (Best Model) - Loss: 1.5447 - Accuracy: 0.4242 - F1: 0.2979
sub_25:Test (Best Model) - Loss: 1.4216 - Accuracy: 0.4242 - F1: 0.3365
sub_25:Test (Best Model) - Loss: 0.9220 - Accuracy: 0.5938 - F1: 0.5589
sub_25:Test (Best Model) - Loss: 0.6357 - Accuracy: 0.6875 - F1: 0.6537
sub_25:Test (Best Model) - Loss: 0.9586 - Accuracy: 0.5938 - F1: 0.5901
sub_25:Test (Best Model) - Loss: 1.0973 - Accuracy: 0.6250 - F1: 0.5362
sub_25:Test (Best Model) - Loss: 0.8014 - Accuracy: 0.6875 - F1: 0.6364
sub_25:Test (Best Model) - Loss: 0.7950 - Accuracy: 0.6875 - F1: 0.6364
sub_25:Test (Best Model) - Loss: 1.0399 - Accuracy: 0.6875 - F1: 0.6667
sub_25:Test (Best Model) - Loss: 0.9404 - Accuracy: 0.6875 - F1: 0.6364
sub_25:Test (Best Model) - Loss: 1.1609 - Accuracy: 0.5625 - F1: 0.4589
sub_25:Test (Best Model) - Loss: 1.1686 - Accuracy: 0.6562 - F1: 0.6102
sub_26:Test (Best Model) - Loss: 1.0731 - Accuracy: 0.6061 - F1: 0.5815
sub_26:Test (Best Model) - Loss: 1.2236 - Accuracy: 0.6061 - F1: 0.5662
sub_26:Test (Best Model) - Loss: 0.8309 - Accuracy: 0.7576 - F1: 0.7381
sub_26:Test (Best Model) - Loss: 0.6181 - Accuracy: 0.7273 - F1: 0.6997
sub_26:Test (Best Model) - Loss: 0.7047 - Accuracy: 0.6667 - F1: 0.5935
sub_26:Test (Best Model) - Loss: 0.8369 - Accuracy: 0.6250 - F1: 0.6235
sub_26:Test (Best Model) - Loss: 0.7563 - Accuracy: 0.6562 - F1: 0.6532
sub_26:Test (Best Model) - Loss: 1.0592 - Accuracy: 0.6562 - F1: 0.6559
sub_26:Test (Best Model) - Loss: 0.7618 - Accuracy: 0.7188 - F1: 0.7046
sub_26:Test (Best Model) - Loss: 0.7119 - Accuracy: 0.6875 - F1: 0.6761
sub_26:Test (Best Model) - Loss: 0.3196 - Accuracy: 0.8125 - F1: 0.7922
sub_26:Test (Best Model) - Loss: 0.5644 - Accuracy: 0.7812 - F1: 0.7519
sub_26:Test (Best Model) - Loss: 0.7493 - Accuracy: 0.6875 - F1: 0.6761
sub_26:Test (Best Model) - Loss: 0.4808 - Accuracy: 0.8438 - F1: 0.8303
sub_26:Test (Best Model) - Loss: 0.4272 - Accuracy: 0.8125 - F1: 0.7922
sub_27:Test (Best Model) - Loss: 0.8838 - Accuracy: 0.6667 - F1: 0.6459
sub_27:Test (Best Model) - Loss: 0.7955 - Accuracy: 0.6364 - F1: 0.6278
sub_27:Test (Best Model) - Loss: 0.8814 - Accuracy: 0.4848 - F1: 0.4772
sub_27:Test (Best Model) - Loss: 1.0754 - Accuracy: 0.6061 - F1: 0.5662
sub_27:Test (Best Model) - Loss: 0.7837 - Accuracy: 0.5758 - F1: 0.5227
sub_27:Test (Best Model) - Loss: 1.1978 - Accuracy: 0.4242 - F1: 0.4157
sub_27:Test (Best Model) - Loss: 1.0016 - Accuracy: 0.5455 - F1: 0.5299
sub_27:Test (Best Model) - Loss: 1.2529 - Accuracy: 0.5455 - F1: 0.5438
sub_27:Test (Best Model) - Loss: 0.9457 - Accuracy: 0.5758 - F1: 0.5417
sub_27:Test (Best Model) - Loss: 0.9116 - Accuracy: 0.5152 - F1: 0.4762
sub_27:Test (Best Model) - Loss: 0.8230 - Accuracy: 0.5000 - F1: 0.4980
sub_27:Test (Best Model) - Loss: 0.9749 - Accuracy: 0.5625 - F1: 0.5466
sub_27:Test (Best Model) - Loss: 1.2505 - Accuracy: 0.5312 - F1: 0.4910
sub_27:Test (Best Model) - Loss: 1.0735 - Accuracy: 0.6562 - F1: 0.6476
sub_27:Test (Best Model) - Loss: 1.1088 - Accuracy: 0.5625 - F1: 0.5466
sub_28:Test (Best Model) - Loss: 0.5055 - Accuracy: 0.6562 - F1: 0.6390
sub_28:Test (Best Model) - Loss: 0.8499 - Accuracy: 0.5625 - F1: 0.5608
sub_28:Test (Best Model) - Loss: 0.9691 - Accuracy: 0.3750 - F1: 0.3750
sub_28:Test (Best Model) - Loss: 1.2874 - Accuracy: 0.5000 - F1: 0.4182
sub_28:Test (Best Model) - Loss: 1.0364 - Accuracy: 0.4375 - F1: 0.4286
sub_28:Test (Best Model) - Loss: 1.5084 - Accuracy: 0.5625 - F1: 0.4909
sub_28:Test (Best Model) - Loss: 1.5493 - Accuracy: 0.5000 - F1: 0.4818
sub_28:Test (Best Model) - Loss: 1.6961 - Accuracy: 0.4688 - F1: 0.4421
sub_28:Test (Best Model) - Loss: 1.2920 - Accuracy: 0.5312 - F1: 0.4386
sub_28:Test (Best Model) - Loss: 2.4124 - Accuracy: 0.5938 - F1: 0.5836
sub_28:Test (Best Model) - Loss: 1.2161 - Accuracy: 0.5625 - F1: 0.5466
sub_28:Test (Best Model) - Loss: 1.1085 - Accuracy: 0.4375 - F1: 0.4286
sub_28:Test (Best Model) - Loss: 1.0324 - Accuracy: 0.5312 - F1: 0.5195
sub_28:Test (Best Model) - Loss: 0.9502 - Accuracy: 0.6562 - F1: 0.6559
sub_28:Test (Best Model) - Loss: 1.1024 - Accuracy: 0.5000 - F1: 0.4921
sub_29:Test (Best Model) - Loss: 0.7928 - Accuracy: 0.7812 - F1: 0.7519
sub_29:Test (Best Model) - Loss: 0.9010 - Accuracy: 0.6875 - F1: 0.6537
sub_29:Test (Best Model) - Loss: 0.8261 - Accuracy: 0.7812 - F1: 0.7519
sub_29:Test (Best Model) - Loss: 0.8999 - Accuracy: 0.7500 - F1: 0.7091
sub_29:Test (Best Model) - Loss: 0.8881 - Accuracy: 0.7500 - F1: 0.7091
sub_29:Test (Best Model) - Loss: 0.4902 - Accuracy: 0.7812 - F1: 0.7703
sub_29:Test (Best Model) - Loss: 0.2730 - Accuracy: 0.8750 - F1: 0.8704
sub_29:Test (Best Model) - Loss: 0.1891 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.3211 - Accuracy: 0.8750 - F1: 0.8667
sub_29:Test (Best Model) - Loss: 0.4312 - Accuracy: 0.7500 - F1: 0.7091
sub_29:Test (Best Model) - Loss: 0.5723 - Accuracy: 0.8182 - F1: 0.8167
sub_29:Test (Best Model) - Loss: 0.6998 - Accuracy: 0.7273 - F1: 0.7179
sub_29:Test (Best Model) - Loss: 0.3868 - Accuracy: 0.9394 - F1: 0.9380
sub_29:Test (Best Model) - Loss: 0.5186 - Accuracy: 0.9091 - F1: 0.9060
sub_29:Test (Best Model) - Loss: 0.4684 - Accuracy: 0.9394 - F1: 0.9380

=== Summary Results ===

acc: 60.91 ± 8.76
F1: 57.99 ± 9.33
acc-in: 68.23 ± 7.11
F1-in: 65.41 ± 7.90
