lr: 0.0001
sub_1:Test (Best Model) - Loss: 0.7292 - Accuracy: 0.6562 - F1: 0.6267
sub_1:Test (Best Model) - Loss: 0.7883 - Accuracy: 0.5938 - F1: 0.5733
sub_1:Test (Best Model) - Loss: 0.8630 - Accuracy: 0.5312 - F1: 0.5195
sub_1:Test (Best Model) - Loss: 0.7410 - Accuracy: 0.5938 - F1: 0.5589
sub_1:Test (Best Model) - Loss: 0.8801 - Accuracy: 0.6562 - F1: 0.6102
sub_1:Test (Best Model) - Loss: 0.6418 - Accuracy: 0.6970 - F1: 0.6827
sub_1:Test (Best Model) - Loss: 0.5386 - Accuracy: 0.7576 - F1: 0.7462
sub_1:Test (Best Model) - Loss: 0.7452 - Accuracy: 0.6667 - F1: 0.6459
sub_1:Test (Best Model) - Loss: 1.0444 - Accuracy: 0.6970 - F1: 0.6413
sub_1:Test (Best Model) - Loss: 0.6772 - Accuracy: 0.6970 - F1: 0.6591
sub_1:Test (Best Model) - Loss: 0.6118 - Accuracy: 0.7500 - F1: 0.7490
sub_1:Test (Best Model) - Loss: 0.4847 - Accuracy: 0.7188 - F1: 0.7163
sub_1:Test (Best Model) - Loss: 0.5484 - Accuracy: 0.6875 - F1: 0.6875
sub_1:Test (Best Model) - Loss: 0.6833 - Accuracy: 0.7500 - F1: 0.7091
sub_1:Test (Best Model) - Loss: 0.6342 - Accuracy: 0.7500 - F1: 0.7409
sub_2:Test (Best Model) - Loss: 0.8143 - Accuracy: 0.6364 - F1: 0.6278
sub_2:Test (Best Model) - Loss: 0.8273 - Accuracy: 0.6667 - F1: 0.6459
sub_2:Test (Best Model) - Loss: 0.8840 - Accuracy: 0.6970 - F1: 0.6827
sub_2:Test (Best Model) - Loss: 0.9178 - Accuracy: 0.6970 - F1: 0.6726
sub_2:Test (Best Model) - Loss: 0.9377 - Accuracy: 0.7273 - F1: 0.7102
sub_2:Test (Best Model) - Loss: 0.9000 - Accuracy: 0.6562 - F1: 0.6102
sub_2:Test (Best Model) - Loss: 0.7993 - Accuracy: 0.5625 - F1: 0.4909
sub_2:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.6250 - F1: 0.6000
sub_2:Test (Best Model) - Loss: 0.7487 - Accuracy: 0.6562 - F1: 0.5883
sub_2:Test (Best Model) - Loss: 0.7196 - Accuracy: 0.5938 - F1: 0.5393
sub_2:Test (Best Model) - Loss: 0.6260 - Accuracy: 0.6667 - F1: 0.6654
sub_2:Test (Best Model) - Loss: 0.7463 - Accuracy: 0.6061 - F1: 0.6002
sub_2:Test (Best Model) - Loss: 0.5581 - Accuracy: 0.6667 - F1: 0.6667
sub_2:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.6364 - F1: 0.6333
sub_2:Test (Best Model) - Loss: 0.7000 - Accuracy: 0.6667 - F1: 0.6667
sub_3:Test (Best Model) - Loss: 0.9303 - Accuracy: 0.5625 - F1: 0.5608
sub_3:Test (Best Model) - Loss: 0.8955 - Accuracy: 0.6562 - F1: 0.6532
sub_3:Test (Best Model) - Loss: 0.9938 - Accuracy: 0.5938 - F1: 0.5901
sub_3:Test (Best Model) - Loss: 0.9690 - Accuracy: 0.5938 - F1: 0.5836
sub_3:Test (Best Model) - Loss: 0.9444 - Accuracy: 0.3750 - F1: 0.3750
sub_3:Test (Best Model) - Loss: 0.8671 - Accuracy: 0.5152 - F1: 0.5038
sub_3:Test (Best Model) - Loss: 1.0192 - Accuracy: 0.3939 - F1: 0.3934
sub_3:Test (Best Model) - Loss: 0.9022 - Accuracy: 0.4848 - F1: 0.4772
sub_3:Test (Best Model) - Loss: 1.0647 - Accuracy: 0.5455 - F1: 0.4995
sub_3:Test (Best Model) - Loss: 1.0328 - Accuracy: 0.3939 - F1: 0.3934
sub_3:Test (Best Model) - Loss: 1.2967 - Accuracy: 0.5152 - F1: 0.5111
sub_3:Test (Best Model) - Loss: 1.0778 - Accuracy: 0.4545 - F1: 0.4288
sub_3:Test (Best Model) - Loss: 1.0800 - Accuracy: 0.4848 - F1: 0.4527
sub_3:Test (Best Model) - Loss: 1.1903 - Accuracy: 0.4848 - F1: 0.4328
sub_3:Test (Best Model) - Loss: 1.3998 - Accuracy: 0.3939 - F1: 0.3797
sub_4:Test (Best Model) - Loss: 1.1178 - Accuracy: 0.5152 - F1: 0.4762
sub_4:Test (Best Model) - Loss: 0.6694 - Accuracy: 0.5758 - F1: 0.5227
sub_4:Test (Best Model) - Loss: 0.8338 - Accuracy: 0.6061 - F1: 0.5460
sub_4:Test (Best Model) - Loss: 0.7267 - Accuracy: 0.6364 - F1: 0.6071
sub_4:Test (Best Model) - Loss: 0.9110 - Accuracy: 0.6364 - F1: 0.5909
sub_4:Test (Best Model) - Loss: 0.8377 - Accuracy: 0.4848 - F1: 0.4527
sub_4:Test (Best Model) - Loss: 0.9136 - Accuracy: 0.5152 - F1: 0.4923
sub_4:Test (Best Model) - Loss: 0.7134 - Accuracy: 0.6061 - F1: 0.5662
sub_4:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.5455 - F1: 0.4762
sub_4:Test (Best Model) - Loss: 1.1184 - Accuracy: 0.6061 - F1: 0.5662
sub_4:Test (Best Model) - Loss: 0.7508 - Accuracy: 0.5758 - F1: 0.5754
sub_4:Test (Best Model) - Loss: 0.9050 - Accuracy: 0.5758 - F1: 0.5722
sub_4:Test (Best Model) - Loss: 0.6443 - Accuracy: 0.6364 - F1: 0.6333
sub_4:Test (Best Model) - Loss: 0.6000 - Accuracy: 0.6061 - F1: 0.6002
sub_4:Test (Best Model) - Loss: 0.6435 - Accuracy: 0.6667 - F1: 0.6654
sub_5:Test (Best Model) - Loss: 1.4713 - Accuracy: 0.3438 - F1: 0.3431
sub_5:Test (Best Model) - Loss: 1.3441 - Accuracy: 0.4062 - F1: 0.4010
sub_5:Test (Best Model) - Loss: 1.6233 - Accuracy: 0.4688 - F1: 0.4640
sub_5:Test (Best Model) - Loss: 1.2649 - Accuracy: 0.5000 - F1: 0.5000
sub_5:Test (Best Model) - Loss: 1.2363 - Accuracy: 0.3750 - F1: 0.3750
sub_5:Test (Best Model) - Loss: 0.9301 - Accuracy: 0.4375 - F1: 0.3766
sub_5:Test (Best Model) - Loss: 0.7781 - Accuracy: 0.5000 - F1: 0.4459
sub_5:Test (Best Model) - Loss: 0.7277 - Accuracy: 0.4375 - F1: 0.4170
sub_5:Test (Best Model) - Loss: 0.7183 - Accuracy: 0.5625 - F1: 0.5556
sub_5:Test (Best Model) - Loss: 0.8237 - Accuracy: 0.3438 - F1: 0.3273
sub_5:Test (Best Model) - Loss: 0.9591 - Accuracy: 0.4688 - F1: 0.4555
sub_5:Test (Best Model) - Loss: 1.1025 - Accuracy: 0.4375 - F1: 0.4170
sub_5:Test (Best Model) - Loss: 1.0352 - Accuracy: 0.3750 - F1: 0.3522
sub_5:Test (Best Model) - Loss: 0.9092 - Accuracy: 0.5625 - F1: 0.5556
sub_5:Test (Best Model) - Loss: 0.9666 - Accuracy: 0.5000 - F1: 0.4818
sub_6:Test (Best Model) - Loss: 0.8835 - Accuracy: 0.6562 - F1: 0.6267
sub_6:Test (Best Model) - Loss: 0.8005 - Accuracy: 0.6562 - F1: 0.6390
sub_6:Test (Best Model) - Loss: 0.9168 - Accuracy: 0.5938 - F1: 0.5589
sub_6:Test (Best Model) - Loss: 0.7859 - Accuracy: 0.6250 - F1: 0.6000
sub_6:Test (Best Model) - Loss: 0.7708 - Accuracy: 0.7500 - F1: 0.7229
sub_6:Test (Best Model) - Loss: 1.5817 - Accuracy: 0.3939 - F1: 0.2826
sub_6:Test (Best Model) - Loss: 1.9634 - Accuracy: 0.4848 - F1: 0.3265
sub_6:Test (Best Model) - Loss: 1.6960 - Accuracy: 0.4848 - F1: 0.3265
sub_6:Test (Best Model) - Loss: 1.6427 - Accuracy: 0.5152 - F1: 0.3400
sub_6:Test (Best Model) - Loss: 1.7845 - Accuracy: 0.4848 - F1: 0.3718
sub_6:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.5758 - F1: 0.4978
sub_6:Test (Best Model) - Loss: 0.8896 - Accuracy: 0.5455 - F1: 0.4762
sub_6:Test (Best Model) - Loss: 0.8184 - Accuracy: 0.5455 - F1: 0.4762
sub_6:Test (Best Model) - Loss: 0.9527 - Accuracy: 0.6061 - F1: 0.4850
sub_6:Test (Best Model) - Loss: 1.1541 - Accuracy: 0.6061 - F1: 0.5196
sub_7:Test (Best Model) - Loss: 0.7944 - Accuracy: 0.5625 - F1: 0.5333
sub_7:Test (Best Model) - Loss: 0.9464 - Accuracy: 0.5000 - F1: 0.4818
sub_7:Test (Best Model) - Loss: 1.0322 - Accuracy: 0.5000 - F1: 0.4921
sub_7:Test (Best Model) - Loss: 0.8559 - Accuracy: 0.5938 - F1: 0.5836
sub_7:Test (Best Model) - Loss: 0.9476 - Accuracy: 0.5000 - F1: 0.4921
sub_7:Test (Best Model) - Loss: 1.3475 - Accuracy: 0.3750 - F1: 0.3750
sub_7:Test (Best Model) - Loss: 1.1190 - Accuracy: 0.4375 - F1: 0.4353
sub_7:Test (Best Model) - Loss: 1.0762 - Accuracy: 0.4062 - F1: 0.4010
sub_7:Test (Best Model) - Loss: 1.3977 - Accuracy: 0.3750 - F1: 0.3651
sub_7:Test (Best Model) - Loss: 1.4968 - Accuracy: 0.3438 - F1: 0.3431
sub_7:Test (Best Model) - Loss: 1.0474 - Accuracy: 0.5938 - F1: 0.5934
sub_7:Test (Best Model) - Loss: 1.0082 - Accuracy: 0.5312 - F1: 0.5308
sub_7:Test (Best Model) - Loss: 1.2365 - Accuracy: 0.5000 - F1: 0.4818
sub_7:Test (Best Model) - Loss: 0.9027 - Accuracy: 0.5938 - F1: 0.5934
sub_7:Test (Best Model) - Loss: 0.9160 - Accuracy: 0.5938 - F1: 0.5901
sub_8:Test (Best Model) - Loss: 0.9901 - Accuracy: 0.5625 - F1: 0.5333
sub_8:Test (Best Model) - Loss: 1.4482 - Accuracy: 0.4688 - F1: 0.4421
sub_8:Test (Best Model) - Loss: 0.9606 - Accuracy: 0.4688 - F1: 0.4682
sub_8:Test (Best Model) - Loss: 0.9405 - Accuracy: 0.6875 - F1: 0.6364
sub_8:Test (Best Model) - Loss: 1.0495 - Accuracy: 0.4688 - F1: 0.4421
sub_8:Test (Best Model) - Loss: 0.7525 - Accuracy: 0.6875 - F1: 0.6667
sub_8:Test (Best Model) - Loss: 1.1722 - Accuracy: 0.6562 - F1: 0.6267
sub_8:Test (Best Model) - Loss: 0.9553 - Accuracy: 0.5000 - F1: 0.4667
sub_8:Test (Best Model) - Loss: 1.3524 - Accuracy: 0.5625 - F1: 0.5333
sub_8:Test (Best Model) - Loss: 0.9187 - Accuracy: 0.5938 - F1: 0.5589
sub_8:Test (Best Model) - Loss: 1.5024 - Accuracy: 0.2812 - F1: 0.2633
sub_8:Test (Best Model) - Loss: 1.1840 - Accuracy: 0.3750 - F1: 0.3750
sub_8:Test (Best Model) - Loss: 0.9050 - Accuracy: 0.5312 - F1: 0.5195
sub_8:Test (Best Model) - Loss: 0.9583 - Accuracy: 0.5312 - F1: 0.5077
sub_8:Test (Best Model) - Loss: 0.8872 - Accuracy: 0.4688 - F1: 0.4682
sub_9:Test (Best Model) - Loss: 0.8302 - Accuracy: 0.7188 - F1: 0.6946
sub_9:Test (Best Model) - Loss: 1.0464 - Accuracy: 0.6250 - F1: 0.6113
sub_9:Test (Best Model) - Loss: 0.7554 - Accuracy: 0.6562 - F1: 0.6476
sub_9:Test (Best Model) - Loss: 0.8149 - Accuracy: 0.6562 - F1: 0.6267
sub_9:Test (Best Model) - Loss: 0.7945 - Accuracy: 0.6875 - F1: 0.6761
sub_9:Test (Best Model) - Loss: 0.9256 - Accuracy: 0.5312 - F1: 0.5195
sub_9:Test (Best Model) - Loss: 0.8229 - Accuracy: 0.5312 - F1: 0.5077
sub_9:Test (Best Model) - Loss: 0.9968 - Accuracy: 0.6562 - F1: 0.6390
sub_9:Test (Best Model) - Loss: 0.9275 - Accuracy: 0.6250 - F1: 0.6113
sub_9:Test (Best Model) - Loss: 1.0026 - Accuracy: 0.6250 - F1: 0.5844
sub_9:Test (Best Model) - Loss: 1.5275 - Accuracy: 0.5000 - F1: 0.4667
sub_9:Test (Best Model) - Loss: 1.2221 - Accuracy: 0.5938 - F1: 0.5934
sub_9:Test (Best Model) - Loss: 1.1565 - Accuracy: 0.5000 - F1: 0.4980
sub_9:Test (Best Model) - Loss: 1.1847 - Accuracy: 0.5000 - F1: 0.4667
sub_9:Test (Best Model) - Loss: 1.0972 - Accuracy: 0.6875 - F1: 0.6863
sub_10:Test (Best Model) - Loss: 0.9008 - Accuracy: 0.4375 - F1: 0.4286
sub_10:Test (Best Model) - Loss: 0.8488 - Accuracy: 0.5000 - F1: 0.4980
sub_10:Test (Best Model) - Loss: 0.9949 - Accuracy: 0.4688 - F1: 0.4640
sub_10:Test (Best Model) - Loss: 1.0589 - Accuracy: 0.5312 - F1: 0.5077
sub_10:Test (Best Model) - Loss: 1.3501 - Accuracy: 0.4375 - F1: 0.4353
sub_10:Test (Best Model) - Loss: 1.1289 - Accuracy: 0.4688 - F1: 0.4682
sub_10:Test (Best Model) - Loss: 1.2373 - Accuracy: 0.4062 - F1: 0.4057
sub_10:Test (Best Model) - Loss: 1.1882 - Accuracy: 0.4375 - F1: 0.4353
sub_10:Test (Best Model) - Loss: 0.9899 - Accuracy: 0.4375 - F1: 0.4375
sub_10:Test (Best Model) - Loss: 1.3325 - Accuracy: 0.3438 - F1: 0.3431
sub_10:Test (Best Model) - Loss: 1.1743 - Accuracy: 0.4545 - F1: 0.4540
sub_10:Test (Best Model) - Loss: 1.1289 - Accuracy: 0.4545 - F1: 0.4540
sub_10:Test (Best Model) - Loss: 0.9299 - Accuracy: 0.5758 - F1: 0.5754
sub_10:Test (Best Model) - Loss: 0.8362 - Accuracy: 0.5152 - F1: 0.5111
sub_10:Test (Best Model) - Loss: 1.0852 - Accuracy: 0.4848 - F1: 0.4848
sub_11:Test (Best Model) - Loss: 1.3314 - Accuracy: 0.4242 - F1: 0.4157
sub_11:Test (Best Model) - Loss: 1.1785 - Accuracy: 0.4848 - F1: 0.4527
sub_11:Test (Best Model) - Loss: 1.1480 - Accuracy: 0.4848 - F1: 0.4527
sub_11:Test (Best Model) - Loss: 0.9838 - Accuracy: 0.5152 - F1: 0.5111
sub_11:Test (Best Model) - Loss: 1.2009 - Accuracy: 0.4848 - F1: 0.4672
sub_11:Test (Best Model) - Loss: 0.9873 - Accuracy: 0.4848 - F1: 0.3718
sub_11:Test (Best Model) - Loss: 0.9948 - Accuracy: 0.5152 - F1: 0.4261
sub_11:Test (Best Model) - Loss: 0.8654 - Accuracy: 0.6061 - F1: 0.5460
sub_11:Test (Best Model) - Loss: 1.5057 - Accuracy: 0.4848 - F1: 0.4328
sub_11:Test (Best Model) - Loss: 0.9834 - Accuracy: 0.6061 - F1: 0.5196
sub_11:Test (Best Model) - Loss: 0.8930 - Accuracy: 0.5455 - F1: 0.5438
sub_11:Test (Best Model) - Loss: 0.8686 - Accuracy: 0.5455 - F1: 0.4762
sub_11:Test (Best Model) - Loss: 1.1011 - Accuracy: 0.5455 - F1: 0.4762
sub_11:Test (Best Model) - Loss: 0.8340 - Accuracy: 0.5758 - F1: 0.4653
sub_11:Test (Best Model) - Loss: 1.0171 - Accuracy: 0.5152 - F1: 0.4261
sub_12:Test (Best Model) - Loss: 0.7821 - Accuracy: 0.6875 - F1: 0.6667
sub_12:Test (Best Model) - Loss: 0.8265 - Accuracy: 0.5000 - F1: 0.4667
sub_12:Test (Best Model) - Loss: 1.0631 - Accuracy: 0.5938 - F1: 0.5589
sub_12:Test (Best Model) - Loss: 0.9414 - Accuracy: 0.5625 - F1: 0.5333
sub_12:Test (Best Model) - Loss: 1.0423 - Accuracy: 0.4688 - F1: 0.3976
sub_12:Test (Best Model) - Loss: 0.9370 - Accuracy: 0.5455 - F1: 0.5299
sub_12:Test (Best Model) - Loss: 0.8961 - Accuracy: 0.5455 - F1: 0.5171
sub_12:Test (Best Model) - Loss: 0.8576 - Accuracy: 0.5758 - F1: 0.4653
sub_12:Test (Best Model) - Loss: 0.9221 - Accuracy: 0.6364 - F1: 0.5696
sub_12:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.6364 - F1: 0.6071
sub_12:Test (Best Model) - Loss: 1.0516 - Accuracy: 0.5000 - F1: 0.4818
sub_12:Test (Best Model) - Loss: 1.2084 - Accuracy: 0.4688 - F1: 0.4640
sub_12:Test (Best Model) - Loss: 1.1944 - Accuracy: 0.4688 - F1: 0.4555
sub_12:Test (Best Model) - Loss: 0.9883 - Accuracy: 0.5938 - F1: 0.5733
sub_12:Test (Best Model) - Loss: 1.0725 - Accuracy: 0.5312 - F1: 0.5077
sub_13:Test (Best Model) - Loss: 0.8443 - Accuracy: 0.6875 - F1: 0.6875
sub_13:Test (Best Model) - Loss: 0.8012 - Accuracy: 0.7188 - F1: 0.7163
sub_13:Test (Best Model) - Loss: 0.7739 - Accuracy: 0.6875 - F1: 0.6863
sub_13:Test (Best Model) - Loss: 0.7501 - Accuracy: 0.6562 - F1: 0.6559
sub_13:Test (Best Model) - Loss: 0.6626 - Accuracy: 0.7188 - F1: 0.7185
sub_13:Test (Best Model) - Loss: 1.0457 - Accuracy: 0.5152 - F1: 0.5111
sub_13:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.7576 - F1: 0.7574
sub_13:Test (Best Model) - Loss: 0.8825 - Accuracy: 0.4848 - F1: 0.4829
sub_13:Test (Best Model) - Loss: 1.2675 - Accuracy: 0.4848 - F1: 0.4829
sub_13:Test (Best Model) - Loss: 0.9879 - Accuracy: 0.4848 - F1: 0.4848
sub_13:Test (Best Model) - Loss: 0.8059 - Accuracy: 0.5938 - F1: 0.5934
sub_13:Test (Best Model) - Loss: 0.7428 - Accuracy: 0.6562 - F1: 0.6559
sub_13:Test (Best Model) - Loss: 0.7320 - Accuracy: 0.5625 - F1: 0.5608
sub_13:Test (Best Model) - Loss: 0.6968 - Accuracy: 0.6562 - F1: 0.6559
sub_13:Test (Best Model) - Loss: 0.8517 - Accuracy: 0.6562 - F1: 0.6559
sub_14:Test (Best Model) - Loss: 1.0525 - Accuracy: 0.5625 - F1: 0.5556
sub_14:Test (Best Model) - Loss: 0.7730 - Accuracy: 0.5000 - F1: 0.4921
sub_14:Test (Best Model) - Loss: 0.9659 - Accuracy: 0.5312 - F1: 0.5195
sub_14:Test (Best Model) - Loss: 0.8832 - Accuracy: 0.5000 - F1: 0.4980
sub_14:Test (Best Model) - Loss: 0.7688 - Accuracy: 0.5938 - F1: 0.5901
sub_14:Test (Best Model) - Loss: 0.8995 - Accuracy: 0.5000 - F1: 0.4980
sub_14:Test (Best Model) - Loss: 0.8359 - Accuracy: 0.6250 - F1: 0.6113
sub_14:Test (Best Model) - Loss: 0.9290 - Accuracy: 0.3750 - F1: 0.3725
sub_14:Test (Best Model) - Loss: 0.8999 - Accuracy: 0.4688 - F1: 0.4555
sub_14:Test (Best Model) - Loss: 0.8477 - Accuracy: 0.5000 - F1: 0.4667
sub_14:Test (Best Model) - Loss: 0.8144 - Accuracy: 0.5625 - F1: 0.5625
sub_14:Test (Best Model) - Loss: 0.9656 - Accuracy: 0.4375 - F1: 0.4353
sub_14:Test (Best Model) - Loss: 1.1967 - Accuracy: 0.4688 - F1: 0.4682
sub_14:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.3750 - F1: 0.3725
sub_14:Test (Best Model) - Loss: 0.8734 - Accuracy: 0.4375 - F1: 0.4353
sub_15:Test (Best Model) - Loss: 1.0278 - Accuracy: 0.6875 - F1: 0.6761
sub_15:Test (Best Model) - Loss: 1.0011 - Accuracy: 0.5000 - F1: 0.5000
sub_15:Test (Best Model) - Loss: 0.9213 - Accuracy: 0.6562 - F1: 0.6532
sub_15:Test (Best Model) - Loss: 0.9616 - Accuracy: 0.6250 - F1: 0.6235
sub_15:Test (Best Model) - Loss: 0.9382 - Accuracy: 0.5938 - F1: 0.5901
sub_15:Test (Best Model) - Loss: 1.1008 - Accuracy: 0.6562 - F1: 0.6559
sub_15:Test (Best Model) - Loss: 1.3111 - Accuracy: 0.5000 - F1: 0.4921
sub_15:Test (Best Model) - Loss: 0.9302 - Accuracy: 0.6250 - F1: 0.6250
sub_15:Test (Best Model) - Loss: 1.1209 - Accuracy: 0.5312 - F1: 0.5077
sub_15:Test (Best Model) - Loss: 1.5530 - Accuracy: 0.5000 - F1: 0.4980
sub_15:Test (Best Model) - Loss: 0.7715 - Accuracy: 0.6250 - F1: 0.6250
sub_15:Test (Best Model) - Loss: 0.8459 - Accuracy: 0.6875 - F1: 0.6667
sub_15:Test (Best Model) - Loss: 0.9565 - Accuracy: 0.5000 - F1: 0.4921
sub_15:Test (Best Model) - Loss: 0.7586 - Accuracy: 0.6250 - F1: 0.6113
sub_15:Test (Best Model) - Loss: 0.8063 - Accuracy: 0.5000 - F1: 0.4921
sub_16:Test (Best Model) - Loss: 0.8459 - Accuracy: 0.6250 - F1: 0.6250
sub_16:Test (Best Model) - Loss: 0.7513 - Accuracy: 0.6250 - F1: 0.6250
sub_16:Test (Best Model) - Loss: 0.8375 - Accuracy: 0.5312 - F1: 0.5195
sub_16:Test (Best Model) - Loss: 0.7931 - Accuracy: 0.4688 - F1: 0.4640
sub_16:Test (Best Model) - Loss: 0.9888 - Accuracy: 0.5000 - F1: 0.4921
sub_16:Test (Best Model) - Loss: 0.9441 - Accuracy: 0.7188 - F1: 0.7163
sub_16:Test (Best Model) - Loss: 0.8452 - Accuracy: 0.7812 - F1: 0.7758
sub_16:Test (Best Model) - Loss: 1.0420 - Accuracy: 0.6875 - F1: 0.6863
sub_16:Test (Best Model) - Loss: 0.8165 - Accuracy: 0.6250 - F1: 0.6190
sub_16:Test (Best Model) - Loss: 1.0486 - Accuracy: 0.7188 - F1: 0.7163
sub_16:Test (Best Model) - Loss: 1.5772 - Accuracy: 0.5000 - F1: 0.4818
sub_16:Test (Best Model) - Loss: 0.9147 - Accuracy: 0.5312 - F1: 0.4684
sub_16:Test (Best Model) - Loss: 1.0375 - Accuracy: 0.5625 - F1: 0.5333
sub_16:Test (Best Model) - Loss: 0.9349 - Accuracy: 0.5312 - F1: 0.5077
sub_16:Test (Best Model) - Loss: 1.1278 - Accuracy: 0.5000 - F1: 0.4667
sub_17:Test (Best Model) - Loss: 0.7879 - Accuracy: 0.6061 - F1: 0.5926
sub_17:Test (Best Model) - Loss: 0.7948 - Accuracy: 0.6061 - F1: 0.6002
sub_17:Test (Best Model) - Loss: 0.7647 - Accuracy: 0.5152 - F1: 0.5147
sub_17:Test (Best Model) - Loss: 0.8546 - Accuracy: 0.5758 - F1: 0.5227
sub_17:Test (Best Model) - Loss: 0.8692 - Accuracy: 0.4242 - F1: 0.4046
sub_17:Test (Best Model) - Loss: 0.9479 - Accuracy: 0.4242 - F1: 0.4157
sub_17:Test (Best Model) - Loss: 0.9507 - Accuracy: 0.5455 - F1: 0.5455
sub_17:Test (Best Model) - Loss: 1.0521 - Accuracy: 0.5455 - F1: 0.5438
sub_17:Test (Best Model) - Loss: 0.9727 - Accuracy: 0.5152 - F1: 0.4762
sub_17:Test (Best Model) - Loss: 0.8914 - Accuracy: 0.4545 - F1: 0.4107
sub_17:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.5000 - F1: 0.5000
sub_17:Test (Best Model) - Loss: 0.8913 - Accuracy: 0.5625 - F1: 0.5608
sub_17:Test (Best Model) - Loss: 1.0660 - Accuracy: 0.5625 - F1: 0.5556
sub_17:Test (Best Model) - Loss: 0.8566 - Accuracy: 0.5625 - F1: 0.5333
sub_17:Test (Best Model) - Loss: 0.9696 - Accuracy: 0.5000 - F1: 0.4921
sub_18:Test (Best Model) - Loss: 0.7053 - Accuracy: 0.5455 - F1: 0.5438
sub_18:Test (Best Model) - Loss: 0.7034 - Accuracy: 0.5455 - F1: 0.5299
sub_18:Test (Best Model) - Loss: 0.7151 - Accuracy: 0.6061 - F1: 0.6002
sub_18:Test (Best Model) - Loss: 0.7434 - Accuracy: 0.6970 - F1: 0.6827
sub_18:Test (Best Model) - Loss: 0.6063 - Accuracy: 0.6970 - F1: 0.6944
sub_18:Test (Best Model) - Loss: 0.8304 - Accuracy: 0.6562 - F1: 0.6559
sub_18:Test (Best Model) - Loss: 0.7866 - Accuracy: 0.6562 - F1: 0.6559
sub_18:Test (Best Model) - Loss: 0.9680 - Accuracy: 0.5000 - F1: 0.4980
sub_18:Test (Best Model) - Loss: 0.8061 - Accuracy: 0.6562 - F1: 0.6532
sub_18:Test (Best Model) - Loss: 0.8092 - Accuracy: 0.5625 - F1: 0.5608
sub_18:Test (Best Model) - Loss: 0.6703 - Accuracy: 0.6562 - F1: 0.6390
sub_18:Test (Best Model) - Loss: 0.8249 - Accuracy: 0.6562 - F1: 0.6476
sub_18:Test (Best Model) - Loss: 0.8004 - Accuracy: 0.6562 - F1: 0.6267
sub_18:Test (Best Model) - Loss: 0.8091 - Accuracy: 0.6250 - F1: 0.6000
sub_18:Test (Best Model) - Loss: 0.8378 - Accuracy: 0.6250 - F1: 0.6000
sub_19:Test (Best Model) - Loss: 1.0745 - Accuracy: 0.4688 - F1: 0.3976
sub_19:Test (Best Model) - Loss: 0.8261 - Accuracy: 0.4688 - F1: 0.3637
sub_19:Test (Best Model) - Loss: 1.0123 - Accuracy: 0.4375 - F1: 0.3766
sub_19:Test (Best Model) - Loss: 1.1219 - Accuracy: 0.4375 - F1: 0.3455
sub_19:Test (Best Model) - Loss: 0.9641 - Accuracy: 0.5312 - F1: 0.4386
sub_19:Test (Best Model) - Loss: 1.0482 - Accuracy: 0.4062 - F1: 0.3764
sub_19:Test (Best Model) - Loss: 1.1655 - Accuracy: 0.4688 - F1: 0.3976
sub_19:Test (Best Model) - Loss: 1.1010 - Accuracy: 0.4375 - F1: 0.4170
sub_19:Test (Best Model) - Loss: 1.4525 - Accuracy: 0.3750 - F1: 0.3074
sub_19:Test (Best Model) - Loss: 1.6167 - Accuracy: 0.3125 - F1: 0.3016
sub_19:Test (Best Model) - Loss: 1.0676 - Accuracy: 0.4375 - F1: 0.4000
sub_19:Test (Best Model) - Loss: 0.8981 - Accuracy: 0.5312 - F1: 0.5308
sub_19:Test (Best Model) - Loss: 0.7768 - Accuracy: 0.5312 - F1: 0.5271
sub_19:Test (Best Model) - Loss: 0.6666 - Accuracy: 0.6562 - F1: 0.6559
sub_19:Test (Best Model) - Loss: 0.7371 - Accuracy: 0.5625 - F1: 0.5608
sub_20:Test (Best Model) - Loss: 0.8484 - Accuracy: 0.6562 - F1: 0.5883
sub_20:Test (Best Model) - Loss: 0.7553 - Accuracy: 0.5625 - F1: 0.4909
sub_20:Test (Best Model) - Loss: 1.1065 - Accuracy: 0.5938 - F1: 0.5393
sub_20:Test (Best Model) - Loss: 1.0667 - Accuracy: 0.5625 - F1: 0.4589
sub_20:Test (Best Model) - Loss: 1.5715 - Accuracy: 0.5938 - F1: 0.5135
sub_20:Test (Best Model) - Loss: 1.0465 - Accuracy: 0.6875 - F1: 0.6761
sub_20:Test (Best Model) - Loss: 1.0398 - Accuracy: 0.5938 - F1: 0.5733
sub_20:Test (Best Model) - Loss: 1.0716 - Accuracy: 0.5938 - F1: 0.5589
sub_20:Test (Best Model) - Loss: 1.2030 - Accuracy: 0.5312 - F1: 0.4910
sub_20:Test (Best Model) - Loss: 1.1732 - Accuracy: 0.6875 - F1: 0.6667
sub_20:Test (Best Model) - Loss: 1.4231 - Accuracy: 0.4848 - F1: 0.4772
sub_20:Test (Best Model) - Loss: 1.3611 - Accuracy: 0.5152 - F1: 0.4923
sub_20:Test (Best Model) - Loss: 1.3029 - Accuracy: 0.5758 - F1: 0.5558
sub_20:Test (Best Model) - Loss: 1.9247 - Accuracy: 0.5455 - F1: 0.5299
sub_20:Test (Best Model) - Loss: 1.0439 - Accuracy: 0.6970 - F1: 0.6827
sub_21:Test (Best Model) - Loss: 1.0016 - Accuracy: 0.4688 - F1: 0.4555
sub_21:Test (Best Model) - Loss: 1.2596 - Accuracy: 0.3438 - F1: 0.3431
sub_21:Test (Best Model) - Loss: 1.1128 - Accuracy: 0.3750 - F1: 0.3522
sub_21:Test (Best Model) - Loss: 1.1135 - Accuracy: 0.4062 - F1: 0.3552
sub_21:Test (Best Model) - Loss: 1.0752 - Accuracy: 0.4688 - F1: 0.4555
sub_21:Test (Best Model) - Loss: 1.0090 - Accuracy: 0.4688 - F1: 0.4421
sub_21:Test (Best Model) - Loss: 1.0058 - Accuracy: 0.3125 - F1: 0.3098
sub_21:Test (Best Model) - Loss: 1.0669 - Accuracy: 0.3438 - F1: 0.3379
sub_21:Test (Best Model) - Loss: 0.9895 - Accuracy: 0.5938 - F1: 0.5135
sub_21:Test (Best Model) - Loss: 1.0656 - Accuracy: 0.4375 - F1: 0.4353
sub_21:Test (Best Model) - Loss: 1.1127 - Accuracy: 0.3438 - F1: 0.3379
sub_21:Test (Best Model) - Loss: 1.1628 - Accuracy: 0.3438 - F1: 0.3379
sub_21:Test (Best Model) - Loss: 1.3480 - Accuracy: 0.3438 - F1: 0.3108
sub_21:Test (Best Model) - Loss: 1.3540 - Accuracy: 0.2812 - F1: 0.2633
sub_21:Test (Best Model) - Loss: 1.1499 - Accuracy: 0.3438 - F1: 0.3273
sub_22:Test (Best Model) - Loss: 0.6761 - Accuracy: 0.5625 - F1: 0.5466
sub_22:Test (Best Model) - Loss: 0.6593 - Accuracy: 0.6562 - F1: 0.6390
sub_22:Test (Best Model) - Loss: 0.6169 - Accuracy: 0.6875 - F1: 0.6761
sub_22:Test (Best Model) - Loss: 0.6733 - Accuracy: 0.5000 - F1: 0.4459
sub_22:Test (Best Model) - Loss: 0.7315 - Accuracy: 0.6250 - F1: 0.6000
sub_22:Test (Best Model) - Loss: 0.8982 - Accuracy: 0.4848 - F1: 0.4063
sub_22:Test (Best Model) - Loss: 0.7659 - Accuracy: 0.6970 - F1: 0.6591
sub_22:Test (Best Model) - Loss: 1.0914 - Accuracy: 0.6364 - F1: 0.6071
sub_22:Test (Best Model) - Loss: 1.1243 - Accuracy: 0.5758 - F1: 0.4225
sub_22:Test (Best Model) - Loss: 0.8680 - Accuracy: 0.6061 - F1: 0.5662
sub_22:Test (Best Model) - Loss: 0.9104 - Accuracy: 0.6250 - F1: 0.6113
sub_22:Test (Best Model) - Loss: 0.8890 - Accuracy: 0.5938 - F1: 0.5836
sub_22:Test (Best Model) - Loss: 1.0014 - Accuracy: 0.4375 - F1: 0.4000
sub_22:Test (Best Model) - Loss: 0.8040 - Accuracy: 0.5938 - F1: 0.5393
sub_22:Test (Best Model) - Loss: 1.0078 - Accuracy: 0.5625 - F1: 0.5556
sub_23:Test (Best Model) - Loss: 0.8567 - Accuracy: 0.6364 - F1: 0.6071
sub_23:Test (Best Model) - Loss: 0.9118 - Accuracy: 0.5758 - F1: 0.4653
sub_23:Test (Best Model) - Loss: 0.9288 - Accuracy: 0.5455 - F1: 0.4995
sub_23:Test (Best Model) - Loss: 0.9152 - Accuracy: 0.5152 - F1: 0.3400
sub_23:Test (Best Model) - Loss: 1.0219 - Accuracy: 0.5758 - F1: 0.4978
sub_23:Test (Best Model) - Loss: 1.2864 - Accuracy: 0.4375 - F1: 0.4353
sub_23:Test (Best Model) - Loss: 0.9512 - Accuracy: 0.5625 - F1: 0.5608
sub_23:Test (Best Model) - Loss: 0.7645 - Accuracy: 0.6562 - F1: 0.6476
sub_23:Test (Best Model) - Loss: 0.8018 - Accuracy: 0.5312 - F1: 0.5308
sub_23:Test (Best Model) - Loss: 0.9092 - Accuracy: 0.5000 - F1: 0.4980
sub_23:Test (Best Model) - Loss: 1.1129 - Accuracy: 0.5152 - F1: 0.4545
sub_23:Test (Best Model) - Loss: 0.7712 - Accuracy: 0.6364 - F1: 0.5909
sub_23:Test (Best Model) - Loss: 0.9549 - Accuracy: 0.6970 - F1: 0.6591
sub_23:Test (Best Model) - Loss: 1.1289 - Accuracy: 0.5758 - F1: 0.4653
sub_23:Test (Best Model) - Loss: 1.2634 - Accuracy: 0.5758 - F1: 0.4978
sub_24:Test (Best Model) - Loss: 0.8339 - Accuracy: 0.5625 - F1: 0.5556
sub_24:Test (Best Model) - Loss: 1.0694 - Accuracy: 0.4688 - F1: 0.4555
sub_24:Test (Best Model) - Loss: 0.9225 - Accuracy: 0.5000 - F1: 0.4980
sub_24:Test (Best Model) - Loss: 0.9289 - Accuracy: 0.5625 - F1: 0.5556
sub_24:Test (Best Model) - Loss: 0.8485 - Accuracy: 0.5625 - F1: 0.5625
sub_24:Test (Best Model) - Loss: 0.9852 - Accuracy: 0.5625 - F1: 0.5608
sub_24:Test (Best Model) - Loss: 1.0118 - Accuracy: 0.5625 - F1: 0.5556
sub_24:Test (Best Model) - Loss: 0.8083 - Accuracy: 0.5938 - F1: 0.5934
sub_24:Test (Best Model) - Loss: 0.7270 - Accuracy: 0.5625 - F1: 0.5556
sub_24:Test (Best Model) - Loss: 0.7334 - Accuracy: 0.5938 - F1: 0.5836
sub_24:Test (Best Model) - Loss: 1.1494 - Accuracy: 0.5000 - F1: 0.4980
sub_24:Test (Best Model) - Loss: 1.0793 - Accuracy: 0.3438 - F1: 0.3431
sub_24:Test (Best Model) - Loss: 1.1155 - Accuracy: 0.4062 - F1: 0.3914
sub_24:Test (Best Model) - Loss: 1.1267 - Accuracy: 0.5000 - F1: 0.4921
sub_24:Test (Best Model) - Loss: 1.1302 - Accuracy: 0.5625 - F1: 0.5556
sub_25:Test (Best Model) - Loss: 1.1469 - Accuracy: 0.4242 - F1: 0.3365
sub_25:Test (Best Model) - Loss: 0.9793 - Accuracy: 0.4848 - F1: 0.4772
sub_25:Test (Best Model) - Loss: 1.1726 - Accuracy: 0.5152 - F1: 0.5038
sub_25:Test (Best Model) - Loss: 1.1540 - Accuracy: 0.4242 - F1: 0.2979
sub_25:Test (Best Model) - Loss: 1.1781 - Accuracy: 0.4242 - F1: 0.3660
sub_25:Test (Best Model) - Loss: 0.8244 - Accuracy: 0.5625 - F1: 0.5466
sub_25:Test (Best Model) - Loss: 0.6131 - Accuracy: 0.6562 - F1: 0.6102
sub_25:Test (Best Model) - Loss: 0.7612 - Accuracy: 0.6562 - F1: 0.6559
sub_25:Test (Best Model) - Loss: 0.8303 - Accuracy: 0.6562 - F1: 0.5883
sub_25:Test (Best Model) - Loss: 0.7788 - Accuracy: 0.6250 - F1: 0.5636
sub_25:Test (Best Model) - Loss: 0.7382 - Accuracy: 0.6875 - F1: 0.6364
sub_25:Test (Best Model) - Loss: 0.8460 - Accuracy: 0.6875 - F1: 0.6667
sub_25:Test (Best Model) - Loss: 0.8161 - Accuracy: 0.6250 - F1: 0.5362
sub_25:Test (Best Model) - Loss: 0.8834 - Accuracy: 0.5312 - F1: 0.4386
sub_25:Test (Best Model) - Loss: 0.8713 - Accuracy: 0.6562 - F1: 0.6102
sub_26:Test (Best Model) - Loss: 1.1676 - Accuracy: 0.5152 - F1: 0.5038
sub_26:Test (Best Model) - Loss: 1.0569 - Accuracy: 0.5455 - F1: 0.5171
sub_26:Test (Best Model) - Loss: 0.8361 - Accuracy: 0.6364 - F1: 0.6192
sub_26:Test (Best Model) - Loss: 0.7583 - Accuracy: 0.6667 - F1: 0.6330
sub_26:Test (Best Model) - Loss: 0.8578 - Accuracy: 0.6061 - F1: 0.5460
sub_26:Test (Best Model) - Loss: 0.8716 - Accuracy: 0.5312 - F1: 0.5195
sub_26:Test (Best Model) - Loss: 0.7974 - Accuracy: 0.5625 - F1: 0.5625
sub_26:Test (Best Model) - Loss: 0.8918 - Accuracy: 0.6250 - F1: 0.6235
sub_26:Test (Best Model) - Loss: 0.7578 - Accuracy: 0.6875 - F1: 0.6667
sub_26:Test (Best Model) - Loss: 0.8268 - Accuracy: 0.6562 - F1: 0.6476
sub_26:Test (Best Model) - Loss: 0.4175 - Accuracy: 0.8125 - F1: 0.7922
sub_26:Test (Best Model) - Loss: 0.6702 - Accuracy: 0.7500 - F1: 0.7229
sub_26:Test (Best Model) - Loss: 0.7448 - Accuracy: 0.5938 - F1: 0.5836
sub_26:Test (Best Model) - Loss: 0.5409 - Accuracy: 0.7188 - F1: 0.6946
sub_26:Test (Best Model) - Loss: 0.4383 - Accuracy: 0.7500 - F1: 0.7229
sub_27:Test (Best Model) - Loss: 0.7879 - Accuracy: 0.6061 - F1: 0.5926
sub_27:Test (Best Model) - Loss: 0.7948 - Accuracy: 0.6061 - F1: 0.6002
sub_27:Test (Best Model) - Loss: 0.7647 - Accuracy: 0.5152 - F1: 0.5147
sub_27:Test (Best Model) - Loss: 0.8546 - Accuracy: 0.5758 - F1: 0.5227
sub_27:Test (Best Model) - Loss: 0.8692 - Accuracy: 0.4242 - F1: 0.4046
sub_27:Test (Best Model) - Loss: 0.9479 - Accuracy: 0.4242 - F1: 0.4157
sub_27:Test (Best Model) - Loss: 0.9507 - Accuracy: 0.5455 - F1: 0.5455
sub_27:Test (Best Model) - Loss: 1.0521 - Accuracy: 0.5455 - F1: 0.5438
sub_27:Test (Best Model) - Loss: 0.9727 - Accuracy: 0.5152 - F1: 0.4762
sub_27:Test (Best Model) - Loss: 0.8914 - Accuracy: 0.4545 - F1: 0.4107
sub_27:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.5000 - F1: 0.5000
sub_27:Test (Best Model) - Loss: 0.8913 - Accuracy: 0.5625 - F1: 0.5608
sub_27:Test (Best Model) - Loss: 1.0660 - Accuracy: 0.5625 - F1: 0.5556
sub_27:Test (Best Model) - Loss: 0.8566 - Accuracy: 0.5625 - F1: 0.5333
sub_27:Test (Best Model) - Loss: 0.9696 - Accuracy: 0.5000 - F1: 0.4921
sub_28:Test (Best Model) - Loss: 0.4795 - Accuracy: 0.8125 - F1: 0.8118
sub_28:Test (Best Model) - Loss: 0.7762 - Accuracy: 0.5625 - F1: 0.5608
sub_28:Test (Best Model) - Loss: 0.8536 - Accuracy: 0.4375 - F1: 0.4353
sub_28:Test (Best Model) - Loss: 0.9450 - Accuracy: 0.5312 - F1: 0.5195
sub_28:Test (Best Model) - Loss: 1.0148 - Accuracy: 0.3438 - F1: 0.3431
sub_28:Test (Best Model) - Loss: 1.0376 - Accuracy: 0.5312 - F1: 0.4910
sub_28:Test (Best Model) - Loss: 1.2566 - Accuracy: 0.6250 - F1: 0.6000
sub_28:Test (Best Model) - Loss: 1.2746 - Accuracy: 0.4688 - F1: 0.4421
sub_28:Test (Best Model) - Loss: 1.1875 - Accuracy: 0.5312 - F1: 0.4684
sub_28:Test (Best Model) - Loss: 2.0142 - Accuracy: 0.5938 - F1: 0.5836
sub_28:Test (Best Model) - Loss: 0.9931 - Accuracy: 0.5625 - F1: 0.5333
sub_28:Test (Best Model) - Loss: 0.9922 - Accuracy: 0.3750 - F1: 0.3750
sub_28:Test (Best Model) - Loss: 1.0772 - Accuracy: 0.5625 - F1: 0.5466
sub_28:Test (Best Model) - Loss: 0.8640 - Accuracy: 0.6250 - F1: 0.6235
sub_28:Test (Best Model) - Loss: 1.1396 - Accuracy: 0.4375 - F1: 0.4000
sub_29:Test (Best Model) - Loss: 0.7450 - Accuracy: 0.6875 - F1: 0.6667
sub_29:Test (Best Model) - Loss: 0.8184 - Accuracy: 0.6250 - F1: 0.6113
sub_29:Test (Best Model) - Loss: 0.8189 - Accuracy: 0.7500 - F1: 0.7229
sub_29:Test (Best Model) - Loss: 0.8340 - Accuracy: 0.7500 - F1: 0.7091
sub_29:Test (Best Model) - Loss: 0.9544 - Accuracy: 0.7188 - F1: 0.6632
sub_29:Test (Best Model) - Loss: 0.8559 - Accuracy: 0.6250 - F1: 0.6113
sub_29:Test (Best Model) - Loss: 0.6526 - Accuracy: 0.7188 - F1: 0.7117
sub_29:Test (Best Model) - Loss: 0.6417 - Accuracy: 0.7188 - F1: 0.6946
sub_29:Test (Best Model) - Loss: 0.7224 - Accuracy: 0.6562 - F1: 0.5883
sub_29:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.6875 - F1: 0.6364
sub_29:Test (Best Model) - Loss: 0.8037 - Accuracy: 0.6970 - F1: 0.6967
sub_29:Test (Best Model) - Loss: 0.8268 - Accuracy: 0.6667 - F1: 0.6617
sub_29:Test (Best Model) - Loss: 0.7656 - Accuracy: 0.6364 - F1: 0.6333
sub_29:Test (Best Model) - Loss: 0.6420 - Accuracy: 0.8182 - F1: 0.8096
sub_29:Test (Best Model) - Loss: 0.7522 - Accuracy: 0.7879 - F1: 0.7871

=== Summary Results ===

acc: 55.71 ± 7.01
F1: 53.24 ± 7.12
acc-in: 63.82 ± 5.79
F1-in: 61.34 ± 6.22
