lr: 1e-06
sub_2:Test (Best Model) - Loss: 0.6378 - Accuracy: 0.4545 - F1: 0.3125
sub_1:Test (Best Model) - Loss: 0.8878 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 0.7083 - Accuracy: 0.4375 - F1: 0.3043
sub_2:Test (Best Model) - Loss: 0.6210 - Accuracy: 0.8485 - F1: 0.8433
sub_1:Test (Best Model) - Loss: 0.7056 - Accuracy: 0.5938 - F1: 0.5836
sub_2:Test (Best Model) - Loss: 0.8025 - Accuracy: 0.5455 - F1: 0.5299
sub_1:Test (Best Model) - Loss: 0.6330 - Accuracy: 0.7188 - F1: 0.6632
sub_2:Test (Best Model) - Loss: 0.7648 - Accuracy: 0.7273 - F1: 0.6857
sub_1:Test (Best Model) - Loss: 0.6737 - Accuracy: 0.5625 - F1: 0.4909
sub_3:Test (Best Model) - Loss: 0.6407 - Accuracy: 0.7500 - F1: 0.7490
sub_2:Test (Best Model) - Loss: 0.6531 - Accuracy: 0.4242 - F1: 0.2979
sub_1:Test (Best Model) - Loss: 0.6742 - Accuracy: 0.5312 - F1: 0.4684
sub_2:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.6562 - F1: 0.6559
sub_3:Test (Best Model) - Loss: 0.9537 - Accuracy: 0.7188 - F1: 0.6632
sub_1:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.5758 - F1: 0.5558
sub_2:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.3750 - F1: 0.3074
sub_3:Test (Best Model) - Loss: 1.1665 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.7008 - Accuracy: 0.5758 - F1: 0.4225
sub_2:Test (Best Model) - Loss: 0.7108 - Accuracy: 0.2812 - F1: 0.2749
sub_3:Test (Best Model) - Loss: 0.6353 - Accuracy: 0.5625 - F1: 0.5152
sub_1:Test (Best Model) - Loss: 0.7084 - Accuracy: 0.1212 - F1: 0.1212
sub_2:Test (Best Model) - Loss: 0.7198 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 0.6694 - Accuracy: 0.8485 - F1: 0.8479
sub_2:Test (Best Model) - Loss: 0.7300 - Accuracy: 0.4375 - F1: 0.3043
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.4545 - F1: 0.3125
sub_3:Test (Best Model) - Loss: 0.7064 - Accuracy: 0.5152 - F1: 0.3400
sub_1:Test (Best Model) - Loss: 0.6799 - Accuracy: 0.4545 - F1: 0.3125
sub_2:Test (Best Model) - Loss: 0.6798 - Accuracy: 0.5758 - F1: 0.4225
sub_3:Test (Best Model) - Loss: 0.7045 - Accuracy: 0.4242 - F1: 0.3365
sub_1:Test (Best Model) - Loss: 0.6112 - Accuracy: 0.6250 - F1: 0.5000
sub_2:Test (Best Model) - Loss: 0.6753 - Accuracy: 0.6061 - F1: 0.5662
sub_3:Test (Best Model) - Loss: 0.6969 - Accuracy: 0.4545 - F1: 0.3125
sub_1:Test (Best Model) - Loss: 0.6738 - Accuracy: 0.6562 - F1: 0.5883
sub_2:Test (Best Model) - Loss: 0.6522 - Accuracy: 0.7273 - F1: 0.7263
sub_3:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.4848 - F1: 0.3718
sub_1:Test (Best Model) - Loss: 0.6381 - Accuracy: 0.8750 - F1: 0.8667
sub_2:Test (Best Model) - Loss: 0.7362 - Accuracy: 0.4545 - F1: 0.3125
sub_3:Test (Best Model) - Loss: 0.5538 - Accuracy: 0.6970 - F1: 0.6413
sub_1:Test (Best Model) - Loss: 0.7741 - Accuracy: 0.4375 - F1: 0.3043
sub_2:Test (Best Model) - Loss: 0.8086 - Accuracy: 0.5455 - F1: 0.3529
sub_1:Test (Best Model) - Loss: 0.6387 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.7203 - Accuracy: 0.3636 - F1: 0.2993
sub_3:Test (Best Model) - Loss: 0.6539 - Accuracy: 0.8485 - F1: 0.8433
sub_3:Test (Best Model) - Loss: 0.7637 - Accuracy: 0.4545 - F1: 0.3125
sub_3:Test (Best Model) - Loss: 0.6579 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.7190 - Accuracy: 0.4545 - F1: 0.3125
sub_5:Test (Best Model) - Loss: 1.0405 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.7933 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.7171 - Accuracy: 0.3636 - F1: 0.3541
sub_6:Test (Best Model) - Loss: 0.6436 - Accuracy: 0.8125 - F1: 0.8095
sub_5:Test (Best Model) - Loss: 0.6530 - Accuracy: 0.8125 - F1: 0.8125
sub_6:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.5625 - F1: 0.5556
sub_4:Test (Best Model) - Loss: 0.6374 - Accuracy: 0.7273 - F1: 0.6857
sub_5:Test (Best Model) - Loss: 0.4875 - Accuracy: 0.6562 - F1: 0.5594
sub_4:Test (Best Model) - Loss: 0.7137 - Accuracy: 0.4848 - F1: 0.4063
sub_6:Test (Best Model) - Loss: 0.6723 - Accuracy: 0.7188 - F1: 0.6632
sub_4:Test (Best Model) - Loss: 0.6642 - Accuracy: 0.5758 - F1: 0.5227
sub_6:Test (Best Model) - Loss: 0.7394 - Accuracy: 0.4375 - F1: 0.3043
sub_5:Test (Best Model) - Loss: 0.6012 - Accuracy: 0.6250 - F1: 0.5000
sub_4:Test (Best Model) - Loss: 0.6769 - Accuracy: 0.7273 - F1: 0.7179
sub_5:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.6562 - F1: 0.6390
sub_6:Test (Best Model) - Loss: 0.6965 - Accuracy: 0.5758 - F1: 0.5722
sub_4:Test (Best Model) - Loss: 0.6286 - Accuracy: 0.5758 - F1: 0.4225
sub_6:Test (Best Model) - Loss: 0.6398 - Accuracy: 0.6061 - F1: 0.4850
sub_5:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.4688 - F1: 0.4682
sub_4:Test (Best Model) - Loss: 0.6742 - Accuracy: 0.6667 - F1: 0.6654
sub_5:Test (Best Model) - Loss: 0.6568 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.7617 - Accuracy: 0.4545 - F1: 0.3125
sub_6:Test (Best Model) - Loss: 0.6972 - Accuracy: 0.5152 - F1: 0.5111
sub_5:Test (Best Model) - Loss: nan - Accuracy: 0.00 - F1: 0.00
sub_4:Test (Best Model) - Loss: 0.7592 - Accuracy: 0.4545 - F1: 0.3125
sub_6:Test (Best Model) - Loss: 0.7013 - Accuracy: 0.4545 - F1: 0.3125
sub_5:Test (Best Model) - Loss: 0.7704 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.7365 - Accuracy: 0.4545 - F1: 0.3125
sub_4:Test (Best Model) - Loss: 0.7149 - Accuracy: 0.4545 - F1: 0.4288
sub_5:Test (Best Model) - Loss: 0.7458 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.6783 - Accuracy: 0.6061 - F1: 0.4850
sub_4:Test (Best Model) - Loss: 0.6310 - Accuracy: 0.6667 - F1: 0.6159
sub_5:Test (Best Model) - Loss: 0.6514 - Accuracy: 0.7500 - F1: 0.7091
sub_6:Test (Best Model) - Loss: 0.7225 - Accuracy: 0.2727 - F1: 0.2385
sub_4:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.6667 - F1: 0.6617
sub_6:Test (Best Model) - Loss: 0.6496 - Accuracy: 0.7879 - F1: 0.7806
sub_5:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.8056 - Accuracy: 0.3939 - F1: 0.2826
sub_5:Test (Best Model) - Loss: 0.6479 - Accuracy: 1.0000 - F1: 1.0000
sub_6:Test (Best Model) - Loss: 0.7470 - Accuracy: 0.4545 - F1: 0.3125
sub_4:Test (Best Model) - Loss: 0.6197 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 0.6683 - Accuracy: 0.5455 - F1: 0.3529
sub_5:Test (Best Model) - Loss: 0.7037 - Accuracy: 0.4688 - F1: 0.3637
sub_5:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.7270 - Accuracy: 0.4375 - F1: 0.3043
sub_9:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.7077 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.6594 - Accuracy: 0.5938 - F1: 0.5934
sub_9:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.5312 - F1: 0.5195
sub_7:Test (Best Model) - Loss: 0.5910 - Accuracy: 0.8750 - F1: 0.8667
sub_8:Test (Best Model) - Loss: 0.6497 - Accuracy: 0.7500 - F1: 0.7500
sub_9:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.7188 - F1: 0.7046
sub_7:Test (Best Model) - Loss: 0.7012 - Accuracy: 0.4062 - F1: 0.3267
sub_8:Test (Best Model) - Loss: 0.6540 - Accuracy: 0.8750 - F1: 0.8704
sub_9:Test (Best Model) - Loss: 0.7000 - Accuracy: 0.7188 - F1: 0.6632
sub_7:Test (Best Model) - Loss: 0.6785 - Accuracy: 0.5312 - F1: 0.4684
sub_9:Test (Best Model) - Loss: 0.6474 - Accuracy: 0.4688 - F1: 0.3637
sub_8:Test (Best Model) - Loss: 0.6749 - Accuracy: 0.6250 - F1: 0.5000
sub_7:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.4688 - F1: 0.4682
sub_8:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.5312 - F1: 0.4910
sub_9:Test (Best Model) - Loss: 0.6439 - Accuracy: 0.7812 - F1: 0.7810
sub_7:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6578 - Accuracy: 0.7188 - F1: 0.7163
sub_7:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.4688 - F1: 0.4682
sub_9:Test (Best Model) - Loss: 0.7162 - Accuracy: 0.5625 - F1: 0.4167
sub_8:Test (Best Model) - Loss: 0.6802 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.7164 - Accuracy: 0.4062 - F1: 0.2889
sub_9:Test (Best Model) - Loss: 0.7500 - Accuracy: 0.2812 - F1: 0.2195
sub_9:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.7372 - Accuracy: 0.4688 - F1: 0.4421
sub_7:Test (Best Model) - Loss: 0.7295 - Accuracy: 0.4062 - F1: 0.2889
sub_9:Test (Best Model) - Loss: 0.6665 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.8031 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.6694 - Accuracy: 0.6562 - F1: 0.6267
sub_9:Test (Best Model) - Loss: 0.6760 - Accuracy: 0.6875 - F1: 0.6135
sub_8:Test (Best Model) - Loss: 0.8043 - Accuracy: 0.4375 - F1: 0.3043
sub_9:Test (Best Model) - Loss: 0.6982 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6518 - Accuracy: 0.6562 - F1: 0.5594
sub_7:Test (Best Model) - Loss: 0.6629 - Accuracy: 0.7188 - F1: 0.6811
sub_9:Test (Best Model) - Loss: 0.6533 - Accuracy: 0.9688 - F1: 0.9680
sub_7:Test (Best Model) - Loss: 0.6561 - Accuracy: 0.8438 - F1: 0.8436
sub_8:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.6250 - F1: 0.6113
sub_9:Test (Best Model) - Loss: 0.7142 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.7355 - Accuracy: 0.4375 - F1: 0.3043
sub_9:Test (Best Model) - Loss: 0.8269 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6742 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6352 - Accuracy: 0.8750 - F1: 0.8730
sub_8:Test (Best Model) - Loss: 0.7910 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.6387 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6738 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.7419 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.5000 - F1: 0.5000
sub_10:Test (Best Model) - Loss: 0.6459 - Accuracy: 0.8438 - F1: 0.8424
sub_11:Test (Best Model) - Loss: 0.6721 - Accuracy: 0.6364 - F1: 0.6360
sub_12:Test (Best Model) - Loss: 0.7966 - Accuracy: 0.6875 - F1: 0.6135
sub_10:Test (Best Model) - Loss: 0.6551 - Accuracy: 0.7188 - F1: 0.7046
sub_11:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.6061 - F1: 0.4850
sub_12:Test (Best Model) - Loss: 0.7536 - Accuracy: 0.7188 - F1: 0.6632
sub_10:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.6250 - F1: 0.5000
sub_12:Test (Best Model) - Loss: 0.6550 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.8017 - Accuracy: 0.4242 - F1: 0.2979
sub_10:Test (Best Model) - Loss: 0.6555 - Accuracy: 0.5312 - F1: 0.4910
sub_11:Test (Best Model) - Loss: 0.6887 - Accuracy: 0.4545 - F1: 0.3543
sub_12:Test (Best Model) - Loss: 0.7110 - Accuracy: 0.6364 - F1: 0.6360
sub_10:Test (Best Model) - Loss: 0.6685 - Accuracy: 0.5000 - F1: 0.4459
sub_12:Test (Best Model) - Loss: 0.7303 - Accuracy: 0.6364 - F1: 0.5417
sub_11:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.4242 - F1: 0.4046
sub_11:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.5152 - F1: 0.3400
sub_12:Test (Best Model) - Loss: 0.7131 - Accuracy: 0.3636 - F1: 0.3541
sub_10:Test (Best Model) - Loss: 0.4713 - Accuracy: 0.8125 - F1: 0.7922
sub_12:Test (Best Model) - Loss: 0.7022 - Accuracy: 0.4545 - F1: 0.3125
sub_11:Test (Best Model) - Loss: 0.6998 - Accuracy: 0.6061 - F1: 0.6046
sub_12:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.7731 - Accuracy: 0.5312 - F1: 0.5195
sub_11:Test (Best Model) - Loss: 0.6946 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.9838 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.7403 - Accuracy: 0.2500 - F1: 0.2000
sub_11:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5152 - F1: 0.4545
sub_10:Test (Best Model) - Loss: 1.7762 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.6975 - Accuracy: 0.4688 - F1: 0.4555
sub_11:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.6061 - F1: 0.6046
sub_12:Test (Best Model) - Loss: 0.7140 - Accuracy: 0.4062 - F1: 0.3552
sub_10:Test (Best Model) - Loss: 0.6491 - Accuracy: 0.6364 - F1: 0.5417
sub_10:Test (Best Model) - Loss: 0.6809 - Accuracy: 0.6061 - F1: 0.4850
sub_12:Test (Best Model) - Loss: 0.6626 - Accuracy: 0.5625 - F1: 0.5152
sub_11:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.4848 - F1: 0.3265
sub_10:Test (Best Model) - Loss: 0.6604 - Accuracy: 0.8182 - F1: 0.8096
sub_12:Test (Best Model) - Loss: 0.7547 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.7003 - Accuracy: 0.5152 - F1: 0.4261
sub_10:Test (Best Model) - Loss: 0.7393 - Accuracy: 0.4545 - F1: 0.3125
sub_11:Test (Best Model) - Loss: 0.7156 - Accuracy: 0.4848 - F1: 0.3718
sub_10:Test (Best Model) - Loss: 0.7397 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6582 - Accuracy: 0.5455 - F1: 0.3529
sub_13:Test (Best Model) - Loss: 0.7028 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 0.9058 - Accuracy: 0.4375 - F1: 0.3043
sub_14:Test (Best Model) - Loss: 1.0365 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.6756 - Accuracy: 0.6875 - F1: 0.6875
sub_15:Test (Best Model) - Loss: 0.7665 - Accuracy: 0.4062 - F1: 0.3267
sub_13:Test (Best Model) - Loss: 0.6078 - Accuracy: 0.6875 - F1: 0.6135
sub_14:Test (Best Model) - Loss: 0.7111 - Accuracy: 0.6250 - F1: 0.5636
sub_13:Test (Best Model) - Loss: 0.6993 - Accuracy: 0.5312 - F1: 0.3469
sub_14:Test (Best Model) - Loss: 0.5986 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.5073 - Accuracy: 0.6562 - F1: 0.5594
sub_13:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 0.6551 - Accuracy: 0.5000 - F1: 0.4667
sub_15:Test (Best Model) - Loss: 0.6540 - Accuracy: 0.6250 - F1: 0.6000
sub_14:Test (Best Model) - Loss: 0.7128 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6303 - Accuracy: 0.7879 - F1: 0.7806
sub_14:Test (Best Model) - Loss: 0.6403 - Accuracy: 0.6875 - F1: 0.6825
sub_13:Test (Best Model) - Loss: 0.6205 - Accuracy: 0.5455 - F1: 0.3529
sub_15:Test (Best Model) - Loss: 0.6694 - Accuracy: 0.7188 - F1: 0.7117
sub_14:Test (Best Model) - Loss: 0.6417 - Accuracy: 0.9375 - F1: 0.9352
sub_13:Test (Best Model) - Loss: 0.6807 - Accuracy: 0.4848 - F1: 0.3265
sub_14:Test (Best Model) - Loss: 0.6102 - Accuracy: 0.5938 - F1: 0.4340
sub_15:Test (Best Model) - Loss: 0.6383 - Accuracy: 0.6875 - F1: 0.6135
sub_13:Test (Best Model) - Loss: 0.8458 - Accuracy: 0.4545 - F1: 0.3125
sub_14:Test (Best Model) - Loss: 0.7148 - Accuracy: 0.2812 - F1: 0.2749
sub_13:Test (Best Model) - Loss: 0.7373 - Accuracy: 0.4848 - F1: 0.3718
sub_15:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.5938 - F1: 0.5836
sub_14:Test (Best Model) - Loss: 0.7636 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 0.7211 - Accuracy: 0.4375 - F1: 0.3043
sub_14:Test (Best Model) - Loss: 0.7119 - Accuracy: 0.4688 - F1: 0.3637
sub_13:Test (Best Model) - Loss: 1.7070 - Accuracy: 0.6562 - F1: 0.5594
sub_15:Test (Best Model) - Loss: 0.7486 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.6683 - Accuracy: 0.5625 - F1: 0.5152
sub_14:Test (Best Model) - Loss: 0.5933 - Accuracy: 0.5938 - F1: 0.4340
sub_15:Test (Best Model) - Loss: 0.7227 - Accuracy: 0.4062 - F1: 0.3914
sub_14:Test (Best Model) - Loss: 0.7252 - Accuracy: 0.1875 - F1: 0.1746
sub_13:Test (Best Model) - Loss: 0.9378 - Accuracy: 0.6562 - F1: 0.6532
sub_15:Test (Best Model) - Loss: 0.6888 - Accuracy: 0.6875 - F1: 0.6364
sub_14:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.7812 - F1: 0.7810
sub_13:Test (Best Model) - Loss: 0.7056 - Accuracy: 0.4688 - F1: 0.3637
sub_15:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.8750 - F1: 0.8730
sub_13:Test (Best Model) - Loss: 2.4057 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6588 - Accuracy: 0.9062 - F1: 0.9054
sub_14:Test (Best Model) - Loss: 0.6657 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.7185 - Accuracy: 0.3750 - F1: 0.2727
sub_15:Test (Best Model) - Loss: 0.7216 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6962 - Accuracy: 0.4545 - F1: 0.3125
sub_16:Test (Best Model) - Loss: 0.6997 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 1.0682 - Accuracy: 0.4545 - F1: 0.3125
sub_16:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.4062 - F1: 0.3914
sub_17:Test (Best Model) - Loss: 0.6385 - Accuracy: 0.8182 - F1: 0.8036
sub_18:Test (Best Model) - Loss: 0.5907 - Accuracy: 0.8788 - F1: 0.8731
sub_16:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.8438 - F1: 0.8359
sub_17:Test (Best Model) - Loss: 0.6657 - Accuracy: 0.7273 - F1: 0.6857
sub_18:Test (Best Model) - Loss: 0.4827 - Accuracy: 0.8485 - F1: 0.8390
sub_16:Test (Best Model) - Loss: 0.7229 - Accuracy: 0.4688 - F1: 0.3637
sub_17:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.7273 - F1: 0.6997
sub_16:Test (Best Model) - Loss: 0.6633 - Accuracy: 0.4688 - F1: 0.3637
sub_18:Test (Best Model) - Loss: 0.5978 - Accuracy: 0.6364 - F1: 0.5417
sub_17:Test (Best Model) - Loss: 0.6658 - Accuracy: 0.4545 - F1: 0.3125
sub_17:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.3939 - F1: 0.3654
sub_18:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.8788 - F1: 0.8787
sub_16:Test (Best Model) - Loss: 0.6812 - Accuracy: 0.4688 - F1: 0.4231
sub_16:Test (Best Model) - Loss: 0.6558 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6712 - Accuracy: 0.7188 - F1: 0.7046
sub_17:Test (Best Model) - Loss: 0.6983 - Accuracy: 0.3939 - F1: 0.3182
sub_18:Test (Best Model) - Loss: 0.6409 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.7256 - Accuracy: 0.3750 - F1: 0.2727
sub_17:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.3333 - F1: 0.2798
sub_18:Test (Best Model) - Loss: 0.7005 - Accuracy: 0.4375 - F1: 0.4353
sub_16:Test (Best Model) - Loss: 0.7458 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.7068 - Accuracy: 0.4545 - F1: 0.3125
sub_18:Test (Best Model) - Loss: 0.7350 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.6797 - Accuracy: 0.4545 - F1: 0.3125
sub_16:Test (Best Model) - Loss: 0.7186 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.7545 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.7258 - Accuracy: 0.5000 - F1: 0.4459
sub_16:Test (Best Model) - Loss: 0.7773 - Accuracy: 0.5938 - F1: 0.5589
sub_17:Test (Best Model) - Loss: 0.7152 - Accuracy: 0.3750 - F1: 0.3074
sub_16:Test (Best Model) - Loss: 0.8068 - Accuracy: 0.1250 - F1: 0.1250
sub_17:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5312 - F1: 0.5195
sub_18:Test (Best Model) - Loss: 0.6397 - Accuracy: 0.6562 - F1: 0.5594
sub_16:Test (Best Model) - Loss: 0.6956 - Accuracy: 0.5938 - F1: 0.5901
sub_17:Test (Best Model) - Loss: 0.6703 - Accuracy: 0.5312 - F1: 0.4684
sub_16:Test (Best Model) - Loss: 0.6605 - Accuracy: 0.5000 - F1: 0.4459
sub_17:Test (Best Model) - Loss: 0.8641 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.9341 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6168 - Accuracy: 0.8750 - F1: 0.8667
sub_18:Test (Best Model) - Loss: 0.6512 - Accuracy: 0.9062 - F1: 0.9062
sub_18:Test (Best Model) - Loss: 0.7324 - Accuracy: 0.4688 - F1: 0.3637
sub_18:Test (Best Model) - Loss: 0.5861 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.7193 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.7684 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.6665 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.6571 - Accuracy: 0.7500 - F1: 0.7490
sub_21:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.4375 - F1: 0.4170
sub_19:Test (Best Model) - Loss: 0.6807 - Accuracy: 0.6250 - F1: 0.6113
sub_20:Test (Best Model) - Loss: 0.7058 - Accuracy: 0.2500 - F1: 0.2471
sub_21:Test (Best Model) - Loss: 0.6246 - Accuracy: 0.7500 - F1: 0.7091
sub_20:Test (Best Model) - Loss: 0.7017 - Accuracy: 0.5938 - F1: 0.4340
sub_21:Test (Best Model) - Loss: nan - Accuracy: 0.00 - F1: 0.00
sub_19:Test (Best Model) - Loss: 0.6650 - Accuracy: 0.6562 - F1: 0.6267
sub_20:Test (Best Model) - Loss: 0.6645 - Accuracy: 0.4375 - F1: 0.3043
sub_21:Test (Best Model) - Loss: 0.6652 - Accuracy: 0.5000 - F1: 0.4182
sub_19:Test (Best Model) - Loss: 0.6681 - Accuracy: 0.6250 - F1: 0.5000
sub_20:Test (Best Model) - Loss: 0.6777 - Accuracy: 0.5625 - F1: 0.5333
sub_19:Test (Best Model) - Loss: 0.6994 - Accuracy: 0.4375 - F1: 0.3043
sub_21:Test (Best Model) - Loss: 0.9016 - Accuracy: 0.6875 - F1: 0.6863
sub_20:Test (Best Model) - Loss: 0.7075 - Accuracy: 0.6875 - F1: 0.6135
sub_19:Test (Best Model) - Loss: 0.6563 - Accuracy: 0.8438 - F1: 0.8436
sub_21:Test (Best Model) - Loss: 0.7161 - Accuracy: 0.6562 - F1: 0.5594
sub_20:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.5312 - F1: 0.5308
sub_21:Test (Best Model) - Loss: 0.8508 - Accuracy: 0.5625 - F1: 0.5625
sub_19:Test (Best Model) - Loss: 0.6523 - Accuracy: 0.6562 - F1: 0.5883
sub_20:Test (Best Model) - Loss: 0.7082 - Accuracy: 0.4375 - F1: 0.3043
sub_21:Test (Best Model) - Loss: 0.8066 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.7042 - Accuracy: 0.4062 - F1: 0.3267
sub_21:Test (Best Model) - Loss: 1.1494 - Accuracy: 0.4062 - F1: 0.3267
sub_20:Test (Best Model) - Loss: 0.7072 - Accuracy: 0.4545 - F1: 0.4288
sub_19:Test (Best Model) - Loss: 0.7161 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.6757 - Accuracy: 0.5455 - F1: 0.5171
sub_19:Test (Best Model) - Loss: 0.7000 - Accuracy: 0.4688 - F1: 0.3637
sub_21:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5625 - F1: 0.5625
sub_19:Test (Best Model) - Loss: 0.7977 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6696 - Accuracy: 0.6970 - F1: 0.6944
sub_19:Test (Best Model) - Loss: 0.7338 - Accuracy: 0.2812 - F1: 0.2749
sub_20:Test (Best Model) - Loss: 0.8154 - Accuracy: 0.4545 - F1: 0.3125
sub_21:Test (Best Model) - Loss: 0.7023 - Accuracy: 0.5000 - F1: 0.4667
sub_20:Test (Best Model) - Loss: 0.6025 - Accuracy: 0.5455 - F1: 0.3529
sub_19:Test (Best Model) - Loss: 0.7207 - Accuracy: 0.4375 - F1: 0.4353
sub_21:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.5625 - F1: 0.5608
sub_19:Test (Best Model) - Loss: 0.6265 - Accuracy: 0.6562 - F1: 0.6390
sub_21:Test (Best Model) - Loss: 0.6775 - Accuracy: 0.5000 - F1: 0.4182
sub_19:Test (Best Model) - Loss: 0.7690 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.7223 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.9279 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.7120 - Accuracy: 0.4545 - F1: 0.3125
sub_24:Test (Best Model) - Loss: 0.7965 - Accuracy: 0.4062 - F1: 0.2889
sub_22:Test (Best Model) - Loss: 0.7137 - Accuracy: 0.4688 - F1: 0.4421
sub_22:Test (Best Model) - Loss: 0.5071 - Accuracy: 0.7812 - F1: 0.7519
sub_23:Test (Best Model) - Loss: 0.6804 - Accuracy: 0.7273 - F1: 0.7179
sub_22:Test (Best Model) - Loss: 0.6524 - Accuracy: 0.6250 - F1: 0.5362
sub_24:Test (Best Model) - Loss: 0.6575 - Accuracy: 0.6250 - F1: 0.6235
sub_22:Test (Best Model) - Loss: 0.6986 - Accuracy: 0.6875 - F1: 0.6761
sub_24:Test (Best Model) - Loss: 0.5645 - Accuracy: 0.8438 - F1: 0.8303
sub_23:Test (Best Model) - Loss: 0.6618 - Accuracy: 0.7879 - F1: 0.7806
sub_22:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.6970 - F1: 0.6967
sub_23:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.6970 - F1: 0.6591
sub_24:Test (Best Model) - Loss: 0.6692 - Accuracy: 0.4688 - F1: 0.3637
sub_22:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.6061 - F1: 0.4850
sub_22:Test (Best Model) - Loss: 0.7147 - Accuracy: 0.2424 - F1: 0.2396
sub_24:Test (Best Model) - Loss: 0.6563 - Accuracy: 0.5938 - F1: 0.5589
sub_23:Test (Best Model) - Loss: 0.6751 - Accuracy: 0.4848 - F1: 0.3718
sub_22:Test (Best Model) - Loss: 0.7024 - Accuracy: 0.4545 - F1: 0.3125
sub_24:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.5312 - F1: 0.4910
sub_22:Test (Best Model) - Loss: 0.7295 - Accuracy: 0.4545 - F1: 0.3125
sub_24:Test (Best Model) - Loss: 0.6518 - Accuracy: 0.5938 - F1: 0.4340
sub_22:Test (Best Model) - Loss: 0.6629 - Accuracy: 0.6875 - F1: 0.6135
sub_23:Test (Best Model) - Loss: 0.7404 - Accuracy: 0.5000 - F1: 0.4667
sub_22:Test (Best Model) - Loss: 0.6512 - Accuracy: 0.6250 - F1: 0.5362
sub_23:Test (Best Model) - Loss: 0.6518 - Accuracy: 0.6875 - F1: 0.6135
sub_24:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.6250 - F1: 0.6235
sub_23:Test (Best Model) - Loss: 0.6738 - Accuracy: 0.5625 - F1: 0.5333
sub_24:Test (Best Model) - Loss: 0.7161 - Accuracy: 0.4375 - F1: 0.3455
sub_22:Test (Best Model) - Loss: 0.6351 - Accuracy: 0.9062 - F1: 0.9054
sub_23:Test (Best Model) - Loss: 0.7501 - Accuracy: 0.4062 - F1: 0.2889
sub_24:Test (Best Model) - Loss: 0.7430 - Accuracy: 0.4375 - F1: 0.4170
sub_22:Test (Best Model) - Loss: 0.8357 - Accuracy: 0.3125 - F1: 0.2381
sub_23:Test (Best Model) - Loss: 0.8313 - Accuracy: 0.4375 - F1: 0.3043
sub_24:Test (Best Model) - Loss: 0.5834 - Accuracy: 0.6250 - F1: 0.5000
sub_22:Test (Best Model) - Loss: 0.5805 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6241 - Accuracy: 0.6061 - F1: 0.4850
sub_24:Test (Best Model) - Loss: 0.6211 - Accuracy: 0.9062 - F1: 0.9015
sub_23:Test (Best Model) - Loss: 0.7174 - Accuracy: 0.3939 - F1: 0.3654
sub_23:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.5758 - F1: 0.5754
sub_24:Test (Best Model) - Loss: 0.6352 - Accuracy: 0.9062 - F1: 0.9054
sub_23:Test (Best Model) - Loss: 0.7878 - Accuracy: 0.4545 - F1: 0.3125
sub_24:Test (Best Model) - Loss: 0.7987 - Accuracy: 0.4062 - F1: 0.2889
sub_23:Test (Best Model) - Loss: 0.5837 - Accuracy: 0.5455 - F1: 0.3529
sub_24:Test (Best Model) - Loss: 0.6100 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6962 - Accuracy: 0.4545 - F1: 0.3125
sub_25:Test (Best Model) - Loss: 0.7053 - Accuracy: 0.4545 - F1: 0.3125
sub_26:Test (Best Model) - Loss: 0.7226 - Accuracy: 0.4545 - F1: 0.3125
sub_25:Test (Best Model) - Loss: 0.6431 - Accuracy: 0.8485 - F1: 0.8390
sub_27:Test (Best Model) - Loss: 0.6385 - Accuracy: 0.8182 - F1: 0.8036
sub_26:Test (Best Model) - Loss: 0.6398 - Accuracy: 0.8485 - F1: 0.8433
sub_25:Test (Best Model) - Loss: 0.6427 - Accuracy: 0.7576 - F1: 0.7273
sub_26:Test (Best Model) - Loss: 0.6488 - Accuracy: 0.6667 - F1: 0.6667
sub_27:Test (Best Model) - Loss: 0.6657 - Accuracy: 0.7273 - F1: 0.6857
sub_25:Test (Best Model) - Loss: 0.7499 - Accuracy: 0.5455 - F1: 0.3529
sub_26:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.5455 - F1: 0.4058
sub_25:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.4848 - F1: 0.3718
sub_27:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.7273 - F1: 0.6997
sub_25:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.6250 - F1: 0.6235
sub_27:Test (Best Model) - Loss: 0.6658 - Accuracy: 0.4545 - F1: 0.3125
sub_26:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.4848 - F1: 0.3718
sub_27:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.3939 - F1: 0.3654
sub_25:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.5938 - F1: 0.4340
sub_25:Test (Best Model) - Loss: 0.7136 - Accuracy: 0.2812 - F1: 0.2805
sub_27:Test (Best Model) - Loss: 0.6983 - Accuracy: 0.3939 - F1: 0.3182
sub_26:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.5625 - F1: 0.5556
sub_26:Test (Best Model) - Loss: 0.6726 - Accuracy: 0.5312 - F1: 0.3469
sub_25:Test (Best Model) - Loss: 0.6950 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.3333 - F1: 0.2798
sub_25:Test (Best Model) - Loss: 0.6858 - Accuracy: 0.6250 - F1: 0.6113
sub_26:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.5000 - F1: 0.4921
sub_27:Test (Best Model) - Loss: 0.7068 - Accuracy: 0.4545 - F1: 0.3125
sub_25:Test (Best Model) - Loss: nan - Accuracy: 0.00 - F1: 0.00
sub_27:Test (Best Model) - Loss: 0.6797 - Accuracy: 0.4545 - F1: 0.3125
sub_26:Test (Best Model) - Loss: 0.7491 - Accuracy: 0.5000 - F1: 0.4182
sub_25:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.4062 - F1: 0.3914
sub_27:Test (Best Model) - Loss: 0.7258 - Accuracy: 0.5000 - F1: 0.4459
sub_26:Test (Best Model) - Loss: 0.8232 - Accuracy: 0.4375 - F1: 0.3043
sub_25:Test (Best Model) - Loss: 0.6433 - Accuracy: 0.7812 - F1: 0.7758
sub_27:Test (Best Model) - Loss: 0.7152 - Accuracy: 0.3750 - F1: 0.3074
sub_26:Test (Best Model) - Loss: 0.6114 - Accuracy: 0.6562 - F1: 0.6102
sub_25:Test (Best Model) - Loss: 0.8057 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5312 - F1: 0.5195
sub_26:Test (Best Model) - Loss: 0.6802 - Accuracy: 0.5312 - F1: 0.5195
sub_25:Test (Best Model) - Loss: 0.6102 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6703 - Accuracy: 0.5312 - F1: 0.4684
sub_27:Test (Best Model) - Loss: 0.8641 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6398 - Accuracy: 0.8438 - F1: 0.8436
sub_26:Test (Best Model) - Loss: 0.8818 - Accuracy: 0.3125 - F1: 0.2381
sub_26:Test (Best Model) - Loss: 0.5248 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.7359 - Accuracy: 0.4062 - F1: 0.2889
sub_29:Test (Best Model) - Loss: 0.7092 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.7229 - Accuracy: 0.2188 - F1: 0.1992
sub_29:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.4375 - F1: 0.4286
sub_28:Test (Best Model) - Loss: 0.6588 - Accuracy: 0.7500 - F1: 0.7091
sub_29:Test (Best Model) - Loss: 0.6760 - Accuracy: 0.7500 - F1: 0.7091
sub_28:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.4688 - F1: 0.4555
sub_29:Test (Best Model) - Loss: 0.7335 - Accuracy: 0.2812 - F1: 0.2805
sub_28:Test (Best Model) - Loss: 0.6711 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.6557 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.6797 - Accuracy: 0.6562 - F1: 0.6267
sub_29:Test (Best Model) - Loss: 0.7057 - Accuracy: 0.3750 - F1: 0.3074
sub_28:Test (Best Model) - Loss: 0.6431 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6414 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.6250 - F1: 0.5636
sub_28:Test (Best Model) - Loss: 0.7153 - Accuracy: 0.3750 - F1: 0.3074
sub_29:Test (Best Model) - Loss: 0.6464 - Accuracy: 0.8750 - F1: 0.8730
sub_28:Test (Best Model) - Loss: 0.6780 - Accuracy: 0.7188 - F1: 0.7163
sub_29:Test (Best Model) - Loss: 0.7178 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.7110 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.7559 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.5689 - Accuracy: 0.6562 - F1: 0.5883
sub_29:Test (Best Model) - Loss: 0.7159 - Accuracy: 0.5455 - F1: 0.5299
sub_29:Test (Best Model) - Loss: 0.6132 - Accuracy: 0.8182 - F1: 0.8036
sub_28:Test (Best Model) - Loss: 0.5607 - Accuracy: 0.7500 - F1: 0.7091
sub_29:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.7273 - F1: 0.7263
sub_28:Test (Best Model) - Loss: 1.6560 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.8577 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.8491 - Accuracy: 0.3636 - F1: 0.2667
sub_29:Test (Best Model) - Loss: 0.6769 - Accuracy: 0.5455 - F1: 0.3529

=== Summary Results ===

acc: 55.11 ± 3.42
F1: 46.90 ± 3.47
acc-in: 53.37 ± 3.12
F1-in: 44.68 ± 3.46
runing time: 1039.38 seconds
