lr: 0.0001
sub_1:Test (Best Model) - Loss: 0.2484 - Accuracy: 0.9375 - F1: 0.9365
sub_2:Test (Best Model) - Loss: 0.8969 - Accuracy: 0.5152 - F1: 0.4923
sub_3:Test (Best Model) - Loss: 0.0961 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 0.5599 - Accuracy: 0.7188 - F1: 0.7185
sub_3:Test (Best Model) - Loss: 0.3851 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.8922 - Accuracy: 0.6364 - F1: 0.6360
sub_3:Test (Best Model) - Loss: 0.1198 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 0.1761 - Accuracy: 0.9375 - F1: 0.9373
sub_2:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.6364 - F1: 0.6333
sub_1:Test (Best Model) - Loss: 0.5555 - Accuracy: 0.7500 - F1: 0.7490
sub_2:Test (Best Model) - Loss: 0.6027 - Accuracy: 0.6364 - F1: 0.6333
sub_3:Test (Best Model) - Loss: 0.1156 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.7368 - Accuracy: 0.5152 - F1: 0.4923
sub_1:Test (Best Model) - Loss: 0.2450 - Accuracy: 0.9062 - F1: 0.9054
sub_3:Test (Best Model) - Loss: 0.0271 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.1748 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 0.2972 - Accuracy: 0.9394 - F1: 0.9389
sub_3:Test (Best Model) - Loss: 1.0170 - Accuracy: 0.5758 - F1: 0.5558
sub_2:Test (Best Model) - Loss: 0.3252 - Accuracy: 0.9062 - F1: 0.9039
sub_1:Test (Best Model) - Loss: 0.4949 - Accuracy: 0.7273 - F1: 0.7232
sub_3:Test (Best Model) - Loss: 0.8771 - Accuracy: 0.6364 - F1: 0.6071
sub_2:Test (Best Model) - Loss: 0.3231 - Accuracy: 0.9375 - F1: 0.9373
sub_1:Test (Best Model) - Loss: 0.4051 - Accuracy: 0.7879 - F1: 0.7871
sub_3:Test (Best Model) - Loss: 0.7291 - Accuracy: 0.6061 - F1: 0.5662
sub_2:Test (Best Model) - Loss: 0.2023 - Accuracy: 0.9688 - F1: 0.9685
sub_1:Test (Best Model) - Loss: 0.3358 - Accuracy: 0.8182 - F1: 0.8180
sub_3:Test (Best Model) - Loss: 0.6447 - Accuracy: 0.6061 - F1: 0.5662
sub_2:Test (Best Model) - Loss: 0.3223 - Accuracy: 0.9375 - F1: 0.9373
sub_3:Test (Best Model) - Loss: 0.6777 - Accuracy: 0.6667 - F1: 0.6459
sub_1:Test (Best Model) - Loss: 0.3733 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.2937 - Accuracy: 1.0000 - F1: 1.0000
sub_3:Test (Best Model) - Loss: 0.3661 - Accuracy: 0.8788 - F1: 0.8759
sub_2:Test (Best Model) - Loss: 0.4041 - Accuracy: 0.9394 - F1: 0.9380
sub_1:Test (Best Model) - Loss: 0.3944 - Accuracy: 0.8750 - F1: 0.8750
sub_3:Test (Best Model) - Loss: 0.3731 - Accuracy: 0.9394 - F1: 0.9380
sub_2:Test (Best Model) - Loss: 0.2294 - Accuracy: 0.8788 - F1: 0.8731
sub_1:Test (Best Model) - Loss: 0.4059 - Accuracy: 0.9062 - F1: 0.9015
sub_3:Test (Best Model) - Loss: 0.4298 - Accuracy: 0.8788 - F1: 0.8778
sub_2:Test (Best Model) - Loss: 0.1829 - Accuracy: 0.9697 - F1: 0.9692
sub_1:Test (Best Model) - Loss: 0.3298 - Accuracy: 0.9688 - F1: 0.9685
sub_3:Test (Best Model) - Loss: 0.4245 - Accuracy: 0.8788 - F1: 0.8731
sub_2:Test (Best Model) - Loss: 0.1674 - Accuracy: 0.9394 - F1: 0.9380
sub_3:Test (Best Model) - Loss: 0.3659 - Accuracy: 0.9394 - F1: 0.9380
sub_1:Test (Best Model) - Loss: 0.4145 - Accuracy: 0.9375 - F1: 0.9373
sub_1:Test (Best Model) - Loss: 0.2911 - Accuracy: 0.9688 - F1: 0.9685
sub_5:Test (Best Model) - Loss: 0.3032 - Accuracy: 0.8750 - F1: 0.8750
sub_6:Test (Best Model) - Loss: 3.5984 - Accuracy: 0.3750 - F1: 0.2727
sub_5:Test (Best Model) - Loss: 0.2202 - Accuracy: 0.9375 - F1: 0.9373
sub_4:Test (Best Model) - Loss: 0.3534 - Accuracy: 0.9697 - F1: 0.9696
sub_6:Test (Best Model) - Loss: 1.2226 - Accuracy: 0.3438 - F1: 0.2558
sub_5:Test (Best Model) - Loss: 0.1382 - Accuracy: 0.9688 - F1: 0.9685
sub_6:Test (Best Model) - Loss: 2.2544 - Accuracy: 0.4375 - F1: 0.3455
sub_5:Test (Best Model) - Loss: 0.3343 - Accuracy: 1.0000 - F1: 1.0000
sub_4:Test (Best Model) - Loss: 0.3543 - Accuracy: 0.9091 - F1: 0.9088
sub_5:Test (Best Model) - Loss: 0.2999 - Accuracy: 0.8750 - F1: 0.8750
sub_6:Test (Best Model) - Loss: 1.9120 - Accuracy: 0.5312 - F1: 0.4684
sub_5:Test (Best Model) - Loss: 0.8060 - Accuracy: 0.5000 - F1: 0.4182
sub_4:Test (Best Model) - Loss: 0.4617 - Accuracy: 0.9091 - F1: 0.9060
sub_6:Test (Best Model) - Loss: 1.2731 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.5280 - Accuracy: 0.7576 - F1: 0.7273
sub_5:Test (Best Model) - Loss: 0.9990 - Accuracy: 0.5000 - F1: 0.4182
sub_4:Test (Best Model) - Loss: 0.5517 - Accuracy: 0.7576 - F1: 0.7273
sub_5:Test (Best Model) - Loss: 0.6633 - Accuracy: 0.5000 - F1: 0.4182
sub_6:Test (Best Model) - Loss: 0.4419 - Accuracy: 0.8788 - F1: 0.8778
sub_6:Test (Best Model) - Loss: 0.6472 - Accuracy: 0.4545 - F1: 0.3125
sub_5:Test (Best Model) - Loss: 1.1647 - Accuracy: 0.4688 - F1: 0.3637
sub_4:Test (Best Model) - Loss: 1.0989 - Accuracy: 0.4545 - F1: 0.4107
sub_6:Test (Best Model) - Loss: 0.6122 - Accuracy: 0.4848 - F1: 0.3718
sub_5:Test (Best Model) - Loss: 0.8165 - Accuracy: 0.4688 - F1: 0.3637
sub_4:Test (Best Model) - Loss: 0.5472 - Accuracy: 0.6667 - F1: 0.6654
sub_6:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.4848 - F1: 0.4328
sub_5:Test (Best Model) - Loss: 0.2263 - Accuracy: 0.9062 - F1: 0.9015
sub_4:Test (Best Model) - Loss: 0.6409 - Accuracy: 0.5758 - F1: 0.5658
sub_6:Test (Best Model) - Loss: 0.6748 - Accuracy: 0.5455 - F1: 0.5387
sub_5:Test (Best Model) - Loss: 0.4095 - Accuracy: 0.7812 - F1: 0.7519
sub_4:Test (Best Model) - Loss: 0.7858 - Accuracy: 0.4242 - F1: 0.3660
sub_5:Test (Best Model) - Loss: 0.2921 - Accuracy: 0.9375 - F1: 0.9352
sub_6:Test (Best Model) - Loss: 0.4508 - Accuracy: 0.9697 - F1: 0.9696
sub_4:Test (Best Model) - Loss: 0.6326 - Accuracy: 0.5152 - F1: 0.4923
sub_6:Test (Best Model) - Loss: 0.6051 - Accuracy: 0.6061 - F1: 0.5662
sub_5:Test (Best Model) - Loss: 0.3169 - Accuracy: 0.9688 - F1: 0.9680
sub_5:Test (Best Model) - Loss: 0.3603 - Accuracy: 0.8438 - F1: 0.8303
sub_4:Test (Best Model) - Loss: 0.7591 - Accuracy: 0.7273 - F1: 0.7273
sub_6:Test (Best Model) - Loss: 0.3395 - Accuracy: 0.9697 - F1: 0.9696
sub_6:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.6061 - F1: 0.6046
sub_4:Test (Best Model) - Loss: 0.5586 - Accuracy: 0.8182 - F1: 0.8180
sub_6:Test (Best Model) - Loss: 0.5481 - Accuracy: 0.9091 - F1: 0.9088
sub_4:Test (Best Model) - Loss: 0.5855 - Accuracy: 0.6667 - F1: 0.6617
sub_4:Test (Best Model) - Loss: 0.6563 - Accuracy: 0.6364 - F1: 0.6333
sub_4:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.6667 - F1: 0.6459
sub_9:Test (Best Model) - Loss: 0.5457 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.4056 - Accuracy: 0.6875 - F1: 0.6761
sub_7:Test (Best Model) - Loss: 0.1937 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.5241 - Accuracy: 0.6250 - F1: 0.6000
sub_7:Test (Best Model) - Loss: 0.2060 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 0.3582 - Accuracy: 0.8438 - F1: 0.8436
sub_9:Test (Best Model) - Loss: 0.5615 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.0820 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.4935 - Accuracy: 0.6250 - F1: 0.6000
sub_9:Test (Best Model) - Loss: 0.5056 - Accuracy: 0.7812 - F1: 0.7625
sub_7:Test (Best Model) - Loss: 0.0053 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 0.4044 - Accuracy: 0.9688 - F1: 0.9685
sub_8:Test (Best Model) - Loss: 0.5941 - Accuracy: 0.6562 - F1: 0.6390
sub_7:Test (Best Model) - Loss: 0.0292 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 1.0327 - Accuracy: 0.5000 - F1: 0.4182
sub_9:Test (Best Model) - Loss: 0.5131 - Accuracy: 0.6562 - F1: 0.6390
sub_7:Test (Best Model) - Loss: 0.4467 - Accuracy: 0.7500 - F1: 0.7333
sub_8:Test (Best Model) - Loss: 0.4970 - Accuracy: 0.8750 - F1: 0.8704
sub_9:Test (Best Model) - Loss: 0.5890 - Accuracy: 0.4375 - F1: 0.3043
sub_9:Test (Best Model) - Loss: 0.5564 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.2479 - Accuracy: 0.8750 - F1: 0.8667
sub_8:Test (Best Model) - Loss: 0.4674 - Accuracy: 0.7812 - F1: 0.7793
sub_7:Test (Best Model) - Loss: 0.3607 - Accuracy: 0.8125 - F1: 0.8057
sub_9:Test (Best Model) - Loss: 0.5036 - Accuracy: 0.7188 - F1: 0.7117
sub_8:Test (Best Model) - Loss: 0.6640 - Accuracy: 0.7500 - F1: 0.7490
sub_7:Test (Best Model) - Loss: 0.3355 - Accuracy: 0.8750 - F1: 0.8667
sub_9:Test (Best Model) - Loss: 0.5141 - Accuracy: 0.9375 - F1: 0.9352
sub_8:Test (Best Model) - Loss: 0.5011 - Accuracy: 0.8125 - F1: 0.8095
sub_9:Test (Best Model) - Loss: 0.6216 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.3695 - Accuracy: 0.8438 - F1: 0.8303
sub_8:Test (Best Model) - Loss: 0.5991 - Accuracy: 0.5938 - F1: 0.5934
sub_7:Test (Best Model) - Loss: 0.6194 - Accuracy: 0.8125 - F1: 0.8125
sub_9:Test (Best Model) - Loss: 0.4836 - Accuracy: 0.8438 - F1: 0.8436
sub_7:Test (Best Model) - Loss: 0.5954 - Accuracy: 0.8438 - F1: 0.8436
sub_8:Test (Best Model) - Loss: 0.1161 - Accuracy: 0.9688 - F1: 0.9680
sub_9:Test (Best Model) - Loss: 0.5863 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.1926 - Accuracy: 0.9375 - F1: 0.9352
sub_9:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.4062 - F1: 0.3552
sub_7:Test (Best Model) - Loss: 1.2373 - Accuracy: 0.8750 - F1: 0.8750
sub_9:Test (Best Model) - Loss: 0.5530 - Accuracy: 0.7188 - F1: 0.7117
sub_7:Test (Best Model) - Loss: 0.5917 - Accuracy: 0.7812 - F1: 0.7793
sub_8:Test (Best Model) - Loss: 0.2352 - Accuracy: 1.0000 - F1: 1.0000
sub_7:Test (Best Model) - Loss: 0.5375 - Accuracy: 0.8438 - F1: 0.8436
sub_8:Test (Best Model) - Loss: 0.3223 - Accuracy: 0.9688 - F1: 0.9680
sub_8:Test (Best Model) - Loss: 0.3996 - Accuracy: 0.8438 - F1: 0.8303
sub_12:Test (Best Model) - Loss: 0.5941 - Accuracy: 0.5625 - F1: 0.5152
sub_11:Test (Best Model) - Loss: 0.4638 - Accuracy: 0.8788 - F1: 0.8731
sub_12:Test (Best Model) - Loss: 0.6282 - Accuracy: 0.4375 - F1: 0.3043
sub_10:Test (Best Model) - Loss: 0.2263 - Accuracy: 0.9375 - F1: 0.9373
sub_11:Test (Best Model) - Loss: 0.4830 - Accuracy: 0.8182 - F1: 0.8096
sub_12:Test (Best Model) - Loss: 0.6331 - Accuracy: 0.4375 - F1: 0.3043
sub_10:Test (Best Model) - Loss: 0.6237 - Accuracy: 0.5625 - F1: 0.5152
sub_12:Test (Best Model) - Loss: 0.5781 - Accuracy: 0.7500 - F1: 0.7500
sub_11:Test (Best Model) - Loss: 0.5533 - Accuracy: 0.8182 - F1: 0.8096
sub_10:Test (Best Model) - Loss: 0.3068 - Accuracy: 0.8750 - F1: 0.8745
sub_12:Test (Best Model) - Loss: 0.4423 - Accuracy: 0.8125 - F1: 0.8118
sub_11:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.6970 - F1: 0.6591
sub_12:Test (Best Model) - Loss: 0.6154 - Accuracy: 0.6061 - F1: 0.5662
sub_11:Test (Best Model) - Loss: 0.5493 - Accuracy: 0.7879 - F1: 0.7806
sub_10:Test (Best Model) - Loss: 0.1612 - Accuracy: 0.9375 - F1: 0.9365
sub_12:Test (Best Model) - Loss: 0.3684 - Accuracy: 0.8788 - F1: 0.8731
sub_11:Test (Best Model) - Loss: 0.6082 - Accuracy: 0.7273 - F1: 0.7179
sub_10:Test (Best Model) - Loss: 0.2442 - Accuracy: 0.9062 - F1: 0.9054
sub_10:Test (Best Model) - Loss: 0.4002 - Accuracy: 0.9688 - F1: 0.9685
sub_12:Test (Best Model) - Loss: 0.5927 - Accuracy: 0.7273 - F1: 0.7179
sub_11:Test (Best Model) - Loss: 0.7476 - Accuracy: 0.8788 - F1: 0.8787
sub_11:Test (Best Model) - Loss: 0.7202 - Accuracy: 0.4848 - F1: 0.3718
sub_12:Test (Best Model) - Loss: 0.5621 - Accuracy: 0.6970 - F1: 0.6726
sub_10:Test (Best Model) - Loss: 0.1084 - Accuracy: 0.9688 - F1: 0.9685
sub_12:Test (Best Model) - Loss: 0.6121 - Accuracy: 0.7273 - F1: 0.6997
sub_12:Test (Best Model) - Loss: 0.7657 - Accuracy: 0.4375 - F1: 0.3043
sub_10:Test (Best Model) - Loss: 0.1828 - Accuracy: 0.9688 - F1: 0.9685
sub_11:Test (Best Model) - Loss: 0.4391 - Accuracy: 0.8788 - F1: 0.8787
sub_10:Test (Best Model) - Loss: 0.2754 - Accuracy: 0.9688 - F1: 0.9685
sub_12:Test (Best Model) - Loss: 0.4057 - Accuracy: 0.8438 - F1: 0.8436
sub_11:Test (Best Model) - Loss: 0.5544 - Accuracy: 0.7273 - F1: 0.7179
sub_10:Test (Best Model) - Loss: 0.0618 - Accuracy: 0.9688 - F1: 0.9685
sub_10:Test (Best Model) - Loss: 0.5698 - Accuracy: 0.5152 - F1: 0.4261
sub_12:Test (Best Model) - Loss: 0.5980 - Accuracy: 0.5312 - F1: 0.4684
sub_11:Test (Best Model) - Loss: 0.5050 - Accuracy: 0.6667 - F1: 0.6459
sub_10:Test (Best Model) - Loss: 0.1837 - Accuracy: 0.9394 - F1: 0.9380
sub_11:Test (Best Model) - Loss: 0.6649 - Accuracy: 0.4545 - F1: 0.3125
sub_12:Test (Best Model) - Loss: 0.4409 - Accuracy: 0.8750 - F1: 0.8750
sub_11:Test (Best Model) - Loss: 0.6545 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.1810 - Accuracy: 0.9091 - F1: 0.9060
sub_12:Test (Best Model) - Loss: 0.3857 - Accuracy: 0.8750 - F1: 0.8745
sub_11:Test (Best Model) - Loss: 0.3578 - Accuracy: 0.8485 - F1: 0.8479
sub_10:Test (Best Model) - Loss: 0.2915 - Accuracy: 0.9697 - F1: 0.9692
sub_11:Test (Best Model) - Loss: 0.6005 - Accuracy: 0.6061 - F1: 0.5662
sub_10:Test (Best Model) - Loss: 0.2280 - Accuracy: 0.9394 - F1: 0.9380
sub_13:Test (Best Model) - Loss: 0.2786 - Accuracy: 0.9062 - F1: 0.9054
sub_14:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.5938 - F1: 0.4340
sub_13:Test (Best Model) - Loss: 0.2137 - Accuracy: 0.9062 - F1: 0.9054
sub_14:Test (Best Model) - Loss: 2.7885 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.1634 - Accuracy: 0.9375 - F1: 0.9352
sub_13:Test (Best Model) - Loss: 0.3357 - Accuracy: 0.9375 - F1: 0.9373
sub_14:Test (Best Model) - Loss: 1.0474 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.4201 - Accuracy: 0.9062 - F1: 0.9054
sub_13:Test (Best Model) - Loss: 0.2062 - Accuracy: 0.9062 - F1: 0.9054
sub_14:Test (Best Model) - Loss: 1.3122 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.1934 - Accuracy: 1.0000 - F1: 1.0000
sub_14:Test (Best Model) - Loss: 3.6072 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.2469 - Accuracy: 0.9062 - F1: 0.9054
sub_15:Test (Best Model) - Loss: 0.3719 - Accuracy: 0.9688 - F1: 0.9680
sub_14:Test (Best Model) - Loss: 0.7840 - Accuracy: 0.4688 - F1: 0.3637
sub_13:Test (Best Model) - Loss: 0.7116 - Accuracy: 0.5758 - F1: 0.5227
sub_15:Test (Best Model) - Loss: 0.2035 - Accuracy: 1.0000 - F1: 1.0000
sub_14:Test (Best Model) - Loss: 1.2504 - Accuracy: 0.5000 - F1: 0.4182
sub_13:Test (Best Model) - Loss: 0.5451 - Accuracy: 0.6364 - F1: 0.6192
sub_15:Test (Best Model) - Loss: 0.3535 - Accuracy: 1.0000 - F1: 1.0000
sub_13:Test (Best Model) - Loss: 0.5670 - Accuracy: 0.6061 - F1: 0.6002
sub_14:Test (Best Model) - Loss: 0.7549 - Accuracy: 0.4688 - F1: 0.3976
sub_13:Test (Best Model) - Loss: 0.6536 - Accuracy: 0.6061 - F1: 0.5662
sub_14:Test (Best Model) - Loss: 0.8320 - Accuracy: 0.4688 - F1: 0.3976
sub_15:Test (Best Model) - Loss: 0.2818 - Accuracy: 0.9375 - F1: 0.9352
sub_13:Test (Best Model) - Loss: 0.5410 - Accuracy: 0.6667 - F1: 0.6459
sub_14:Test (Best Model) - Loss: 0.8613 - Accuracy: 0.4688 - F1: 0.3637
sub_15:Test (Best Model) - Loss: 0.2601 - Accuracy: 1.0000 - F1: 1.0000
sub_13:Test (Best Model) - Loss: 0.4085 - Accuracy: 0.7500 - F1: 0.7333
sub_14:Test (Best Model) - Loss: 0.4642 - Accuracy: 0.8125 - F1: 0.8118
sub_14:Test (Best Model) - Loss: 0.4928 - Accuracy: 0.7812 - F1: 0.7793
sub_13:Test (Best Model) - Loss: 0.6497 - Accuracy: 0.8125 - F1: 0.8000
sub_14:Test (Best Model) - Loss: 0.4764 - Accuracy: 0.7188 - F1: 0.7117
sub_15:Test (Best Model) - Loss: 0.0189 - Accuracy: 1.0000 - F1: 1.0000
sub_13:Test (Best Model) - Loss: 0.3793 - Accuracy: 0.8125 - F1: 0.8057
sub_14:Test (Best Model) - Loss: 0.4648 - Accuracy: 0.7812 - F1: 0.7793
sub_13:Test (Best Model) - Loss: 0.4380 - Accuracy: 0.7812 - F1: 0.7703
sub_15:Test (Best Model) - Loss: 0.2417 - Accuracy: 1.0000 - F1: 1.0000
sub_14:Test (Best Model) - Loss: 0.4244 - Accuracy: 0.7188 - F1: 0.7117
sub_13:Test (Best Model) - Loss: 0.4807 - Accuracy: 0.8125 - F1: 0.8057
sub_15:Test (Best Model) - Loss: 0.1826 - Accuracy: 0.9688 - F1: 0.9685
sub_15:Test (Best Model) - Loss: 0.4610 - Accuracy: 0.9688 - F1: 0.9685
sub_15:Test (Best Model) - Loss: 0.4018 - Accuracy: 0.9688 - F1: 0.9685
sub_15:Test (Best Model) - Loss: 0.3859 - Accuracy: 0.9688 - F1: 0.9685
sub_15:Test (Best Model) - Loss: 0.4643 - Accuracy: 0.9688 - F1: 0.9685
sub_16:Test (Best Model) - Loss: 0.5040 - Accuracy: 0.9062 - F1: 0.9039
sub_17:Test (Best Model) - Loss: 0.2514 - Accuracy: 0.8788 - F1: 0.8787
sub_18:Test (Best Model) - Loss: 0.4290 - Accuracy: 0.9697 - F1: 0.9696
sub_16:Test (Best Model) - Loss: 0.4241 - Accuracy: 0.9062 - F1: 0.9054
sub_17:Test (Best Model) - Loss: 0.2452 - Accuracy: 0.9091 - F1: 0.9091
sub_18:Test (Best Model) - Loss: 0.5143 - Accuracy: 0.9394 - F1: 0.9389
sub_16:Test (Best Model) - Loss: 0.6184 - Accuracy: 0.4688 - F1: 0.3637
sub_17:Test (Best Model) - Loss: 0.2363 - Accuracy: 0.9091 - F1: 0.9088
sub_16:Test (Best Model) - Loss: 0.5203 - Accuracy: 0.8438 - F1: 0.8424
sub_18:Test (Best Model) - Loss: 0.5990 - Accuracy: 0.5455 - F1: 0.4762
sub_17:Test (Best Model) - Loss: 0.4703 - Accuracy: 0.8485 - F1: 0.8462
sub_16:Test (Best Model) - Loss: 0.3319 - Accuracy: 0.9688 - F1: 0.9680
sub_18:Test (Best Model) - Loss: 0.3136 - Accuracy: 0.8788 - F1: 0.8759
sub_16:Test (Best Model) - Loss: 0.5845 - Accuracy: 0.6875 - F1: 0.6364
sub_17:Test (Best Model) - Loss: 0.2029 - Accuracy: 0.9091 - F1: 0.9088
sub_18:Test (Best Model) - Loss: 0.5856 - Accuracy: 0.7273 - F1: 0.7263
sub_16:Test (Best Model) - Loss: 0.5169 - Accuracy: 0.7812 - F1: 0.7703
sub_17:Test (Best Model) - Loss: 0.2373 - Accuracy: 0.9091 - F1: 0.9088
sub_18:Test (Best Model) - Loss: 0.7610 - Accuracy: 0.6875 - F1: 0.6761
sub_16:Test (Best Model) - Loss: 0.4842 - Accuracy: 0.6875 - F1: 0.6825
sub_17:Test (Best Model) - Loss: 0.2445 - Accuracy: 0.9394 - F1: 0.9389
sub_16:Test (Best Model) - Loss: 0.5763 - Accuracy: 0.6875 - F1: 0.6364
sub_18:Test (Best Model) - Loss: 0.4268 - Accuracy: 0.7500 - F1: 0.7460
sub_17:Test (Best Model) - Loss: 0.1829 - Accuracy: 0.9394 - F1: 0.9389
sub_16:Test (Best Model) - Loss: 0.5891 - Accuracy: 0.6875 - F1: 0.6364
sub_18:Test (Best Model) - Loss: 0.6346 - Accuracy: 0.5625 - F1: 0.5152
sub_17:Test (Best Model) - Loss: 0.4369 - Accuracy: 0.8485 - F1: 0.8462
sub_16:Test (Best Model) - Loss: 2.0106 - Accuracy: 0.5000 - F1: 0.4182
sub_18:Test (Best Model) - Loss: 0.5893 - Accuracy: 0.5938 - F1: 0.5589
sub_17:Test (Best Model) - Loss: 0.4393 - Accuracy: 0.8485 - F1: 0.8462
sub_16:Test (Best Model) - Loss: 0.8359 - Accuracy: 0.5000 - F1: 0.4182
sub_18:Test (Best Model) - Loss: 0.4582 - Accuracy: 0.8438 - F1: 0.8424
sub_17:Test (Best Model) - Loss: 0.7703 - Accuracy: 0.4375 - F1: 0.4000
sub_16:Test (Best Model) - Loss: 1.2836 - Accuracy: 0.4688 - F1: 0.3637
sub_17:Test (Best Model) - Loss: 0.6710 - Accuracy: 0.5000 - F1: 0.4459
sub_18:Test (Best Model) - Loss: 0.4855 - Accuracy: 0.8750 - F1: 0.8704
sub_17:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.4688 - F1: 0.4231
sub_16:Test (Best Model) - Loss: 0.9685 - Accuracy: 0.4688 - F1: 0.3976
sub_18:Test (Best Model) - Loss: 0.4186 - Accuracy: 1.0000 - F1: 1.0000
sub_17:Test (Best Model) - Loss: 0.5636 - Accuracy: 0.7812 - F1: 0.7793
sub_16:Test (Best Model) - Loss: 0.9331 - Accuracy: 0.5000 - F1: 0.4182
sub_18:Test (Best Model) - Loss: 0.2342 - Accuracy: 0.9375 - F1: 0.9365
sub_17:Test (Best Model) - Loss: 0.3963 - Accuracy: 0.7500 - F1: 0.7460
sub_18:Test (Best Model) - Loss: 0.3180 - Accuracy: 0.8750 - F1: 0.8730
sub_18:Test (Best Model) - Loss: 0.5178 - Accuracy: 0.8750 - F1: 0.8730
sub_19:Test (Best Model) - Loss: 4.1954 - Accuracy: 0.5625 - F1: 0.4909
sub_21:Test (Best Model) - Loss: 0.1231 - Accuracy: 0.9062 - F1: 0.9015
sub_20:Test (Best Model) - Loss: 0.8327 - Accuracy: 0.6250 - F1: 0.6000
sub_21:Test (Best Model) - Loss: 0.2306 - Accuracy: 0.8750 - F1: 0.8667
sub_19:Test (Best Model) - Loss: 3.3058 - Accuracy: 0.5938 - F1: 0.5135
sub_21:Test (Best Model) - Loss: 0.2663 - Accuracy: 0.9062 - F1: 0.9015
sub_19:Test (Best Model) - Loss: 0.9465 - Accuracy: 0.5625 - F1: 0.4909
sub_21:Test (Best Model) - Loss: 0.1705 - Accuracy: 0.9062 - F1: 0.9015
sub_20:Test (Best Model) - Loss: 0.6069 - Accuracy: 0.6250 - F1: 0.6000
sub_19:Test (Best Model) - Loss: 1.9816 - Accuracy: 0.5312 - F1: 0.3992
sub_19:Test (Best Model) - Loss: 1.3498 - Accuracy: 0.5625 - F1: 0.4909
sub_21:Test (Best Model) - Loss: 0.1896 - Accuracy: 0.9688 - F1: 0.9680
sub_20:Test (Best Model) - Loss: 0.6107 - Accuracy: 0.6250 - F1: 0.6000
sub_19:Test (Best Model) - Loss: 0.4820 - Accuracy: 0.6875 - F1: 0.6761
sub_20:Test (Best Model) - Loss: 0.6005 - Accuracy: 0.5938 - F1: 0.5733
sub_19:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.8750 - F1: 0.8750
sub_21:Test (Best Model) - Loss: 0.3025 - Accuracy: 0.8750 - F1: 0.8704
sub_19:Test (Best Model) - Loss: 0.4208 - Accuracy: 0.9062 - F1: 0.9062
sub_20:Test (Best Model) - Loss: 0.5264 - Accuracy: 0.6875 - F1: 0.6875
sub_21:Test (Best Model) - Loss: 0.4826 - Accuracy: 0.8438 - F1: 0.8359
sub_19:Test (Best Model) - Loss: 0.4207 - Accuracy: 0.9688 - F1: 0.9685
sub_20:Test (Best Model) - Loss: 0.3594 - Accuracy: 0.9688 - F1: 0.9680
sub_19:Test (Best Model) - Loss: 0.3596 - Accuracy: 0.9688 - F1: 0.9685
sub_21:Test (Best Model) - Loss: 0.3960 - Accuracy: 0.8438 - F1: 0.8359
sub_19:Test (Best Model) - Loss: 0.4537 - Accuracy: 0.7500 - F1: 0.7460
sub_21:Test (Best Model) - Loss: 0.4138 - Accuracy: 0.8125 - F1: 0.8095
sub_21:Test (Best Model) - Loss: 0.3977 - Accuracy: 0.8438 - F1: 0.8398
sub_21:Test (Best Model) - Loss: 0.6149 - Accuracy: 0.5312 - F1: 0.4910
sub_20:Test (Best Model) - Loss: 0.5708 - Accuracy: 0.8750 - F1: 0.8750
sub_19:Test (Best Model) - Loss: 0.3742 - Accuracy: 0.8125 - F1: 0.8118
sub_20:Test (Best Model) - Loss: 0.5921 - Accuracy: 0.4688 - F1: 0.3637
sub_21:Test (Best Model) - Loss: 0.9644 - Accuracy: 0.5625 - F1: 0.5333
sub_19:Test (Best Model) - Loss: 0.3102 - Accuracy: 0.8438 - F1: 0.8436
sub_21:Test (Best Model) - Loss: 0.6083 - Accuracy: 0.5312 - F1: 0.4910
sub_20:Test (Best Model) - Loss: 0.4479 - Accuracy: 0.8125 - F1: 0.8118
sub_19:Test (Best Model) - Loss: 0.3445 - Accuracy: 0.8438 - F1: 0.8436
sub_20:Test (Best Model) - Loss: 0.5296 - Accuracy: 0.7812 - F1: 0.7519
sub_21:Test (Best Model) - Loss: 0.8966 - Accuracy: 0.5312 - F1: 0.4910
sub_20:Test (Best Model) - Loss: 0.8048 - Accuracy: 0.4545 - F1: 0.3125
sub_19:Test (Best Model) - Loss: 0.2939 - Accuracy: 0.9375 - F1: 0.9373
sub_21:Test (Best Model) - Loss: 0.6058 - Accuracy: 0.5625 - F1: 0.5333
sub_20:Test (Best Model) - Loss: 0.6337 - Accuracy: 0.7273 - F1: 0.7263
sub_20:Test (Best Model) - Loss: 0.4753 - Accuracy: 0.7273 - F1: 0.7273
sub_20:Test (Best Model) - Loss: 0.6962 - Accuracy: 0.5455 - F1: 0.5299
sub_20:Test (Best Model) - Loss: 0.7278 - Accuracy: 0.5455 - F1: 0.5455
sub_24:Test (Best Model) - Loss: 0.2771 - Accuracy: 0.9375 - F1: 0.9365
sub_23:Test (Best Model) - Loss: 0.2190 - Accuracy: 0.9394 - F1: 0.9380
sub_24:Test (Best Model) - Loss: 0.2233 - Accuracy: 0.9375 - F1: 0.9352
sub_22:Test (Best Model) - Loss: 0.2594 - Accuracy: 0.8750 - F1: 0.8667
sub_23:Test (Best Model) - Loss: 0.4339 - Accuracy: 0.9394 - F1: 0.9389
sub_24:Test (Best Model) - Loss: 0.4172 - Accuracy: 0.8438 - F1: 0.8436
sub_22:Test (Best Model) - Loss: 0.2990 - Accuracy: 0.9375 - F1: 0.9352
sub_24:Test (Best Model) - Loss: 0.4012 - Accuracy: 0.9375 - F1: 0.9352
sub_23:Test (Best Model) - Loss: 0.5142 - Accuracy: 0.7273 - F1: 0.7102
sub_22:Test (Best Model) - Loss: 0.6618 - Accuracy: 0.4375 - F1: 0.3043
sub_22:Test (Best Model) - Loss: 0.6192 - Accuracy: 0.7812 - F1: 0.7625
sub_24:Test (Best Model) - Loss: 0.3406 - Accuracy: 0.8438 - F1: 0.8436
sub_23:Test (Best Model) - Loss: 0.6012 - Accuracy: 0.7576 - F1: 0.7273
sub_24:Test (Best Model) - Loss: 0.3619 - Accuracy: 0.9375 - F1: 0.9373
sub_23:Test (Best Model) - Loss: 0.5582 - Accuracy: 0.7576 - F1: 0.7273
sub_22:Test (Best Model) - Loss: 0.4501 - Accuracy: 0.8125 - F1: 0.7922
sub_24:Test (Best Model) - Loss: 0.4225 - Accuracy: 0.9062 - F1: 0.9062
sub_23:Test (Best Model) - Loss: 0.1292 - Accuracy: 0.9375 - F1: 0.9373
sub_22:Test (Best Model) - Loss: 1.2001 - Accuracy: 0.4242 - F1: 0.3660
sub_24:Test (Best Model) - Loss: 0.2889 - Accuracy: 0.9375 - F1: 0.9373
sub_24:Test (Best Model) - Loss: 0.3270 - Accuracy: 0.9062 - F1: 0.9062
sub_23:Test (Best Model) - Loss: 0.2323 - Accuracy: 0.9688 - F1: 0.9685
sub_22:Test (Best Model) - Loss: 0.7650 - Accuracy: 0.5152 - F1: 0.4545
sub_24:Test (Best Model) - Loss: 0.3431 - Accuracy: 0.9375 - F1: 0.9373
sub_24:Test (Best Model) - Loss: 0.2783 - Accuracy: 0.8438 - F1: 0.8303
sub_23:Test (Best Model) - Loss: 0.3685 - Accuracy: 0.9062 - F1: 0.9039
sub_22:Test (Best Model) - Loss: 0.7080 - Accuracy: 0.5455 - F1: 0.4995
sub_24:Test (Best Model) - Loss: 0.3372 - Accuracy: 0.8750 - F1: 0.8667
sub_23:Test (Best Model) - Loss: 0.4546 - Accuracy: 0.8438 - F1: 0.8359
sub_24:Test (Best Model) - Loss: 0.2787 - Accuracy: 0.9375 - F1: 0.9352
sub_22:Test (Best Model) - Loss: 0.6474 - Accuracy: 0.5152 - F1: 0.4545
sub_23:Test (Best Model) - Loss: 0.5018 - Accuracy: 0.8125 - F1: 0.8057
sub_24:Test (Best Model) - Loss: 0.2729 - Accuracy: 0.9062 - F1: 0.9015
sub_22:Test (Best Model) - Loss: 0.5476 - Accuracy: 0.7879 - F1: 0.7847
sub_24:Test (Best Model) - Loss: 0.3324 - Accuracy: 0.8750 - F1: 0.8667
sub_22:Test (Best Model) - Loss: 0.7051 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.6648 - Accuracy: 0.8182 - F1: 0.8036
sub_23:Test (Best Model) - Loss: 0.8998 - Accuracy: 0.7879 - F1: 0.7664
sub_22:Test (Best Model) - Loss: 0.4796 - Accuracy: 0.7188 - F1: 0.7185
sub_22:Test (Best Model) - Loss: 0.6049 - Accuracy: 0.6250 - F1: 0.6113
sub_23:Test (Best Model) - Loss: 0.9514 - Accuracy: 0.7576 - F1: 0.7273
sub_22:Test (Best Model) - Loss: 0.6511 - Accuracy: 0.5312 - F1: 0.5308
sub_23:Test (Best Model) - Loss: 0.4070 - Accuracy: 0.8485 - F1: 0.8433
sub_22:Test (Best Model) - Loss: 0.5725 - Accuracy: 0.6875 - F1: 0.6761
sub_23:Test (Best Model) - Loss: 0.5372 - Accuracy: 0.7879 - F1: 0.7664
sub_25:Test (Best Model) - Loss: 0.6301 - Accuracy: 0.5152 - F1: 0.4261
sub_27:Test (Best Model) - Loss: 0.2514 - Accuracy: 0.8788 - F1: 0.8787
sub_26:Test (Best Model) - Loss: 0.2954 - Accuracy: 0.9091 - F1: 0.9091
sub_25:Test (Best Model) - Loss: 0.4909 - Accuracy: 0.8182 - F1: 0.8180
sub_26:Test (Best Model) - Loss: 0.5204 - Accuracy: 0.6970 - F1: 0.6827
sub_27:Test (Best Model) - Loss: 0.2452 - Accuracy: 0.9091 - F1: 0.9091
sub_25:Test (Best Model) - Loss: 0.4146 - Accuracy: 0.7879 - F1: 0.7871
sub_25:Test (Best Model) - Loss: 0.4723 - Accuracy: 0.8788 - F1: 0.8787
sub_27:Test (Best Model) - Loss: 0.2363 - Accuracy: 0.9091 - F1: 0.9088
sub_26:Test (Best Model) - Loss: 0.1730 - Accuracy: 0.9091 - F1: 0.9088
sub_25:Test (Best Model) - Loss: 0.1898 - Accuracy: 0.9394 - F1: 0.9389
sub_27:Test (Best Model) - Loss: 0.4703 - Accuracy: 0.8485 - F1: 0.8462
sub_26:Test (Best Model) - Loss: 0.3627 - Accuracy: 0.9697 - F1: 0.9696
sub_27:Test (Best Model) - Loss: 0.2029 - Accuracy: 0.9091 - F1: 0.9088
sub_26:Test (Best Model) - Loss: 0.4240 - Accuracy: 0.9091 - F1: 0.9088
sub_25:Test (Best Model) - Loss: 0.0533 - Accuracy: 0.9688 - F1: 0.9680
sub_27:Test (Best Model) - Loss: 0.2373 - Accuracy: 0.9091 - F1: 0.9088
sub_26:Test (Best Model) - Loss: 0.4389 - Accuracy: 0.8125 - F1: 0.8118
sub_25:Test (Best Model) - Loss: 0.3927 - Accuracy: 0.9062 - F1: 0.9015
sub_27:Test (Best Model) - Loss: 0.2445 - Accuracy: 0.9394 - F1: 0.9389
sub_25:Test (Best Model) - Loss: 0.2227 - Accuracy: 0.9688 - F1: 0.9680
sub_26:Test (Best Model) - Loss: 0.3399 - Accuracy: 0.9688 - F1: 0.9685
sub_25:Test (Best Model) - Loss: 0.4879 - Accuracy: 0.9688 - F1: 0.9680
sub_27:Test (Best Model) - Loss: 0.1829 - Accuracy: 0.9394 - F1: 0.9389
sub_26:Test (Best Model) - Loss: 0.1671 - Accuracy: 1.0000 - F1: 1.0000
sub_25:Test (Best Model) - Loss: 0.3617 - Accuracy: 1.0000 - F1: 1.0000
sub_27:Test (Best Model) - Loss: 0.4369 - Accuracy: 0.8485 - F1: 0.8462
sub_25:Test (Best Model) - Loss: 0.3305 - Accuracy: 0.8750 - F1: 0.8730
sub_27:Test (Best Model) - Loss: 0.4393 - Accuracy: 0.8485 - F1: 0.8462
sub_26:Test (Best Model) - Loss: 0.2475 - Accuracy: 0.9688 - F1: 0.9685
sub_27:Test (Best Model) - Loss: 0.7703 - Accuracy: 0.4375 - F1: 0.4000
sub_26:Test (Best Model) - Loss: 0.5900 - Accuracy: 0.7500 - F1: 0.7409
sub_25:Test (Best Model) - Loss: 0.0350 - Accuracy: 1.0000 - F1: 1.0000
sub_27:Test (Best Model) - Loss: 0.6710 - Accuracy: 0.5000 - F1: 0.4459
sub_27:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.4688 - F1: 0.4231
sub_26:Test (Best Model) - Loss: 0.1797 - Accuracy: 0.9688 - F1: 0.9680
sub_25:Test (Best Model) - Loss: 0.1116 - Accuracy: 1.0000 - F1: 1.0000
sub_27:Test (Best Model) - Loss: 0.5636 - Accuracy: 0.7812 - F1: 0.7793
sub_25:Test (Best Model) - Loss: 0.4342 - Accuracy: 0.9688 - F1: 0.9685
sub_26:Test (Best Model) - Loss: 0.1455 - Accuracy: 0.9375 - F1: 0.9352
sub_25:Test (Best Model) - Loss: 0.3673 - Accuracy: 1.0000 - F1: 1.0000
sub_27:Test (Best Model) - Loss: 0.3963 - Accuracy: 0.7500 - F1: 0.7460
sub_26:Test (Best Model) - Loss: 0.1918 - Accuracy: 0.9688 - F1: 0.9680
sub_26:Test (Best Model) - Loss: 0.3320 - Accuracy: 0.9062 - F1: 0.9015
sub_26:Test (Best Model) - Loss: 0.5321 - Accuracy: 0.8125 - F1: 0.7922
sub_29:Test (Best Model) - Loss: 0.2207 - Accuracy: 0.9375 - F1: 0.9373
sub_28:Test (Best Model) - Loss: 0.4105 - Accuracy: 0.9062 - F1: 0.9015
sub_28:Test (Best Model) - Loss: 0.5345 - Accuracy: 0.7812 - F1: 0.7793
sub_29:Test (Best Model) - Loss: 0.0952 - Accuracy: 0.9688 - F1: 0.9685
sub_29:Test (Best Model) - Loss: 0.5708 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.4402 - Accuracy: 0.8125 - F1: 0.8095
sub_28:Test (Best Model) - Loss: 0.5395 - Accuracy: 0.6562 - F1: 0.6532
sub_29:Test (Best Model) - Loss: 0.5683 - Accuracy: 0.5938 - F1: 0.5589
sub_28:Test (Best Model) - Loss: 0.4521 - Accuracy: 0.7812 - F1: 0.7810
sub_29:Test (Best Model) - Loss: 0.5778 - Accuracy: 0.6562 - F1: 0.6532
sub_29:Test (Best Model) - Loss: 0.4136 - Accuracy: 0.8438 - F1: 0.8398
sub_28:Test (Best Model) - Loss: 0.1215 - Accuracy: 0.9688 - F1: 0.9685
sub_28:Test (Best Model) - Loss: 0.5326 - Accuracy: 0.6562 - F1: 0.6390
sub_29:Test (Best Model) - Loss: 0.4120 - Accuracy: 0.7500 - F1: 0.7460
sub_28:Test (Best Model) - Loss: 0.3658 - Accuracy: 0.7812 - F1: 0.7793
sub_29:Test (Best Model) - Loss: 0.4990 - Accuracy: 0.8125 - F1: 0.8095
sub_28:Test (Best Model) - Loss: 0.4632 - Accuracy: 0.7500 - F1: 0.7460
sub_29:Test (Best Model) - Loss: 0.5219 - Accuracy: 0.8750 - F1: 0.8704
sub_28:Test (Best Model) - Loss: 0.2503 - Accuracy: 0.9062 - F1: 0.9062
sub_29:Test (Best Model) - Loss: 0.6455 - Accuracy: 0.8750 - F1: 0.8667
sub_28:Test (Best Model) - Loss: 0.4242 - Accuracy: 0.8750 - F1: 0.8667
sub_28:Test (Best Model) - Loss: 0.4523 - Accuracy: 0.8125 - F1: 0.7922
sub_29:Test (Best Model) - Loss: 0.2515 - Accuracy: 0.9091 - F1: 0.9060
sub_28:Test (Best Model) - Loss: 0.5803 - Accuracy: 0.7812 - F1: 0.7519
sub_29:Test (Best Model) - Loss: 0.1788 - Accuracy: 0.9394 - F1: 0.9380
sub_28:Test (Best Model) - Loss: 0.5411 - Accuracy: 0.8438 - F1: 0.8359
sub_29:Test (Best Model) - Loss: 0.2565 - Accuracy: 0.9091 - F1: 0.9060
sub_28:Test (Best Model) - Loss: 0.5628 - Accuracy: 0.8438 - F1: 0.8303
sub_29:Test (Best Model) - Loss: 0.6797 - Accuracy: 0.4545 - F1: 0.3125
sub_29:Test (Best Model) - Loss: 0.2911 - Accuracy: 0.9394 - F1: 0.9380

=== Summary Results ===

acc: 77.92 ± 9.77
F1: 75.72 ± 11.64
acc-in: 86.64 ± 8.34
F1-in: 85.30 ± 9.59
runing time: 1292.77 seconds
