lr: 1e-06
sub_2:Test (Best Model) - Loss: 1.4879 - Accuracy: 0.3188 - F1: 0.2359
sub_3:Test (Best Model) - Loss: 1.2889 - Accuracy: 0.4118 - F1: 0.3401
sub_1:Test (Best Model) - Loss: 1.6283 - Accuracy: 0.4559 - F1: 0.4042
sub_2:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2174 - F1: 0.0904
sub_3:Test (Best Model) - Loss: 1.4326 - Accuracy: 0.2059 - F1: 0.0854
sub_2:Test (Best Model) - Loss: 1.4922 - Accuracy: 0.4203 - F1: 0.3311
sub_1:Test (Best Model) - Loss: 1.5549 - Accuracy: 0.2353 - F1: 0.1352
sub_3:Test (Best Model) - Loss: 1.5073 - Accuracy: 0.2353 - F1: 0.1231
sub_2:Test (Best Model) - Loss: 1.6737 - Accuracy: 0.2609 - F1: 0.1034
sub_1:Test (Best Model) - Loss: 1.7799 - Accuracy: 0.1471 - F1: 0.1175
sub_2:Test (Best Model) - Loss: 1.3957 - Accuracy: 0.3188 - F1: 0.2699
sub_1:Test (Best Model) - Loss: 1.7615 - Accuracy: 0.2647 - F1: 0.1084
sub_3:Test (Best Model) - Loss: 1.5682 - Accuracy: 0.2794 - F1: 0.1378
sub_1:Test (Best Model) - Loss: 1.9767 - Accuracy: 0.1618 - F1: 0.1381
sub_3:Test (Best Model) - Loss: 1.4288 - Accuracy: 0.0882 - F1: 0.0676
sub_2:Test (Best Model) - Loss: 1.3526 - Accuracy: 0.5735 - F1: 0.4965
sub_3:Test (Best Model) - Loss: 1.3233 - Accuracy: 0.3478 - F1: 0.3499
sub_1:Test (Best Model) - Loss: 1.4370 - Accuracy: 0.2609 - F1: 0.2573
sub_2:Test (Best Model) - Loss: 1.3746 - Accuracy: 0.4265 - F1: 0.3808
sub_3:Test (Best Model) - Loss: 1.3506 - Accuracy: 0.3043 - F1: 0.2013
sub_1:Test (Best Model) - Loss: 1.3940 - Accuracy: 0.2609 - F1: 0.1538
sub_3:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2319 - F1: 0.0964
sub_2:Test (Best Model) - Loss: 1.3653 - Accuracy: 0.3529 - F1: 0.2756
sub_1:Test (Best Model) - Loss: 1.3989 - Accuracy: 0.2754 - F1: 0.1359
sub_2:Test (Best Model) - Loss: 1.4046 - Accuracy: 0.1029 - F1: 0.0602
sub_3:Test (Best Model) - Loss: 1.6845 - Accuracy: 0.1449 - F1: 0.1086
sub_3:Test (Best Model) - Loss: 2.4599 - Accuracy: 0.2609 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.4230 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.7570 - Accuracy: 0.0725 - F1: 0.0482
sub_3:Test (Best Model) - Loss: 1.6526 - Accuracy: 0.1739 - F1: 0.0769
sub_2:Test (Best Model) - Loss: 1.5488 - Accuracy: 0.2029 - F1: 0.0864
sub_1:Test (Best Model) - Loss: 1.6537 - Accuracy: 0.2609 - F1: 0.1034
sub_3:Test (Best Model) - Loss: 1.2638 - Accuracy: 0.2754 - F1: 0.1310
sub_2:Test (Best Model) - Loss: 1.3231 - Accuracy: 0.2464 - F1: 0.0988
sub_1:Test (Best Model) - Loss: 1.4963 - Accuracy: 0.2794 - F1: 0.1931
sub_3:Test (Best Model) - Loss: 1.5700 - Accuracy: 0.2029 - F1: 0.1214
sub_1:Test (Best Model) - Loss: 1.3249 - Accuracy: 0.2500 - F1: 0.1000
sub_3:Test (Best Model) - Loss: 1.3545 - Accuracy: 0.3623 - F1: 0.2593
sub_3:Test (Best Model) - Loss: 1.6275 - Accuracy: 0.2609 - F1: 0.1383
sub_1:Test (Best Model) - Loss: 1.4893 - Accuracy: 0.3235 - F1: 0.2132
sub_2:Test (Best Model) - Loss: 1.4142 - Accuracy: 0.4058 - F1: 0.3397
sub_1:Test (Best Model) - Loss: 1.3907 - Accuracy: 0.2647 - F1: 0.1071
sub_2:Test (Best Model) - Loss: 1.4561 - Accuracy: 0.3043 - F1: 0.1861
sub_1:Test (Best Model) - Loss: 1.4874 - Accuracy: 0.3088 - F1: 0.2152
sub_2:Test (Best Model) - Loss: 1.5555 - Accuracy: 0.2464 - F1: 0.1328
sub_4:Test (Best Model) - Loss: 1.3877 - Accuracy: 0.3333 - F1: 0.2271
sub_5:Test (Best Model) - Loss: 1.3634 - Accuracy: 0.2353 - F1: 0.0964
sub_6:Test (Best Model) - Loss: 1.3741 - Accuracy: 0.3235 - F1: 0.2312
sub_5:Test (Best Model) - Loss: 1.6805 - Accuracy: 0.2059 - F1: 0.0864
sub_4:Test (Best Model) - Loss: 1.3389 - Accuracy: 0.2464 - F1: 0.1384
sub_5:Test (Best Model) - Loss: 1.5213 - Accuracy: 0.1912 - F1: 0.1453
sub_6:Test (Best Model) - Loss: 1.3872 - Accuracy: 0.2059 - F1: 0.0864
sub_4:Test (Best Model) - Loss: 1.4381 - Accuracy: 0.0870 - F1: 0.0652
sub_5:Test (Best Model) - Loss: 1.6305 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3732 - Accuracy: 0.2609 - F1: 0.1034
sub_6:Test (Best Model) - Loss: 1.3975 - Accuracy: 0.2059 - F1: 0.1357
sub_4:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.3333 - F1: 0.2993
sub_6:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.2794 - F1: 0.1392
sub_5:Test (Best Model) - Loss: 1.7551 - Accuracy: 0.2206 - F1: 0.1333
sub_5:Test (Best Model) - Loss: 1.3912 - Accuracy: 0.3529 - F1: 0.3194
sub_6:Test (Best Model) - Loss: 1.3614 - Accuracy: 0.2647 - F1: 0.2498
sub_5:Test (Best Model) - Loss: 1.3961 - Accuracy: 0.2647 - F1: 0.1111
sub_4:Test (Best Model) - Loss: 1.2830 - Accuracy: 0.4783 - F1: 0.4423
sub_6:Test (Best Model) - Loss: 1.3983 - Accuracy: 0.4203 - F1: 0.3671
sub_4:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.3043 - F1: 0.1834
sub_5:Test (Best Model) - Loss: 1.3641 - Accuracy: 0.3235 - F1: 0.2222
sub_4:Test (Best Model) - Loss: 1.3731 - Accuracy: 0.2609 - F1: 0.1034
sub_6:Test (Best Model) - Loss: 1.3932 - Accuracy: 0.2754 - F1: 0.2698
sub_5:Test (Best Model) - Loss: 1.3721 - Accuracy: 0.2794 - F1: 0.2766
sub_5:Test (Best Model) - Loss: 1.3692 - Accuracy: 0.2647 - F1: 0.1059
sub_4:Test (Best Model) - Loss: 1.4153 - Accuracy: 0.1739 - F1: 0.1531
sub_6:Test (Best Model) - Loss: 1.3972 - Accuracy: 0.2609 - F1: 0.1034
sub_5:Test (Best Model) - Loss: 1.4576 - Accuracy: 0.3088 - F1: 0.2042
sub_6:Test (Best Model) - Loss: 1.3967 - Accuracy: 0.1159 - F1: 0.0707
sub_4:Test (Best Model) - Loss: 1.4204 - Accuracy: 0.3913 - F1: 0.2538
sub_5:Test (Best Model) - Loss: 1.3451 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2319 - F1: 0.1013
sub_4:Test (Best Model) - Loss: 1.6205 - Accuracy: 0.2174 - F1: 0.1209
sub_5:Test (Best Model) - Loss: 1.4150 - Accuracy: 0.2206 - F1: 0.1419
sub_6:Test (Best Model) - Loss: 1.5733 - Accuracy: 0.2174 - F1: 0.0987
sub_4:Test (Best Model) - Loss: 1.2849 - Accuracy: 0.2609 - F1: 0.1034
sub_5:Test (Best Model) - Loss: 1.3784 - Accuracy: 0.4118 - F1: 0.3139
sub_6:Test (Best Model) - Loss: 1.3573 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.6575 - Accuracy: 0.2174 - F1: 0.1134
sub_5:Test (Best Model) - Loss: 1.4477 - Accuracy: 0.2794 - F1: 0.1644
sub_6:Test (Best Model) - Loss: 1.5032 - Accuracy: 0.2174 - F1: 0.1220
sub_4:Test (Best Model) - Loss: 1.4366 - Accuracy: 0.3768 - F1: 0.2821
sub_6:Test (Best Model) - Loss: 1.3953 - Accuracy: 0.2899 - F1: 0.1611
sub_4:Test (Best Model) - Loss: 1.5314 - Accuracy: 0.3478 - F1: 0.2311
sub_6:Test (Best Model) - Loss: 1.5673 - Accuracy: 0.3043 - F1: 0.1769
sub_7:Test (Best Model) - Loss: 1.3194 - Accuracy: 0.2794 - F1: 0.1322
sub_9:Test (Best Model) - Loss: 1.3758 - Accuracy: 0.2647 - F1: 0.1084
sub_8:Test (Best Model) - Loss: 1.3766 - Accuracy: 0.3382 - F1: 0.2276
sub_7:Test (Best Model) - Loss: 1.5205 - Accuracy: 0.2059 - F1: 0.0854
sub_9:Test (Best Model) - Loss: 1.3556 - Accuracy: 0.2059 - F1: 0.0854
sub_8:Test (Best Model) - Loss: 1.4202 - Accuracy: 0.2059 - F1: 0.0854
sub_9:Test (Best Model) - Loss: 1.3950 - Accuracy: 0.2941 - F1: 0.2375
sub_8:Test (Best Model) - Loss: 1.3734 - Accuracy: 0.1765 - F1: 0.1557
sub_7:Test (Best Model) - Loss: 1.2992 - Accuracy: 0.3088 - F1: 0.2460
sub_9:Test (Best Model) - Loss: 1.3920 - Accuracy: 0.2647 - F1: 0.1059
sub_8:Test (Best Model) - Loss: 1.3906 - Accuracy: 0.2500 - F1: 0.1000
sub_7:Test (Best Model) - Loss: 1.4275 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.4128 - Accuracy: 0.1765 - F1: 0.1540
sub_8:Test (Best Model) - Loss: 1.3538 - Accuracy: 0.3382 - F1: 0.3094
sub_7:Test (Best Model) - Loss: 1.4071 - Accuracy: 0.1324 - F1: 0.1141
sub_9:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.4412 - F1: 0.4189
sub_9:Test (Best Model) - Loss: 1.3644 - Accuracy: 0.4265 - F1: 0.3611
sub_8:Test (Best Model) - Loss: 1.2041 - Accuracy: 0.4853 - F1: 0.5110
sub_7:Test (Best Model) - Loss: 1.3318 - Accuracy: 0.4412 - F1: 0.3570
sub_7:Test (Best Model) - Loss: 1.3583 - Accuracy: 0.3824 - F1: 0.2954
sub_9:Test (Best Model) - Loss: 1.4110 - Accuracy: 0.2794 - F1: 0.2098
sub_8:Test (Best Model) - Loss: 1.2871 - Accuracy: 0.4412 - F1: 0.4108
sub_9:Test (Best Model) - Loss: 1.3746 - Accuracy: 0.2059 - F1: 0.1481
sub_8:Test (Best Model) - Loss: 1.3156 - Accuracy: 0.2647 - F1: 0.1760
sub_7:Test (Best Model) - Loss: 1.3774 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.5007 - Accuracy: 0.2647 - F1: 0.1125
sub_9:Test (Best Model) - Loss: 1.4488 - Accuracy: 0.2206 - F1: 0.1151
sub_8:Test (Best Model) - Loss: 1.3798 - Accuracy: 0.1912 - F1: 0.1611
sub_7:Test (Best Model) - Loss: 1.3578 - Accuracy: 0.2794 - F1: 0.2209
sub_9:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.2500 - F1: 0.1012
sub_7:Test (Best Model) - Loss: 1.4312 - Accuracy: 0.2647 - F1: 0.1059
sub_8:Test (Best Model) - Loss: 1.5952 - Accuracy: 0.2500 - F1: 0.1793
sub_9:Test (Best Model) - Loss: 1.4157 - Accuracy: 0.2941 - F1: 0.2006
sub_9:Test (Best Model) - Loss: 1.3956 - Accuracy: 0.2794 - F1: 0.1907
sub_7:Test (Best Model) - Loss: 1.5113 - Accuracy: 0.2059 - F1: 0.0875
sub_8:Test (Best Model) - Loss: 1.3542 - Accuracy: 0.2206 - F1: 0.1082
sub_9:Test (Best Model) - Loss: 1.4903 - Accuracy: 0.2206 - F1: 0.1362
sub_8:Test (Best Model) - Loss: 1.5288 - Accuracy: 0.2941 - F1: 0.1545
sub_7:Test (Best Model) - Loss: 1.4312 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.4446 - Accuracy: 0.2794 - F1: 0.1654
sub_8:Test (Best Model) - Loss: 1.4166 - Accuracy: 0.2206 - F1: 0.1126
sub_7:Test (Best Model) - Loss: 1.4129 - Accuracy: 0.2794 - F1: 0.1389
sub_8:Test (Best Model) - Loss: 1.5094 - Accuracy: 0.3235 - F1: 0.2125
sub_7:Test (Best Model) - Loss: 1.4032 - Accuracy: 0.2794 - F1: 0.1378
sub_12:Test (Best Model) - Loss: 1.3814 - Accuracy: 0.3824 - F1: 0.2895
sub_11:Test (Best Model) - Loss: 1.3765 - Accuracy: 0.2609 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3177 - Accuracy: 0.2206 - F1: 0.1127
sub_11:Test (Best Model) - Loss: 1.3445 - Accuracy: 0.2174 - F1: 0.0893
sub_10:Test (Best Model) - Loss: 1.3984 - Accuracy: 0.3235 - F1: 0.2266
sub_11:Test (Best Model) - Loss: 1.4249 - Accuracy: 0.2464 - F1: 0.1426
sub_12:Test (Best Model) - Loss: 1.4033 - Accuracy: 0.1765 - F1: 0.1466
sub_10:Test (Best Model) - Loss: 1.3889 - Accuracy: 0.2059 - F1: 0.0854
sub_11:Test (Best Model) - Loss: 1.4327 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 1.3743 - Accuracy: 0.2794 - F1: 0.1612
sub_10:Test (Best Model) - Loss: 1.4402 - Accuracy: 0.1912 - F1: 0.1332
sub_11:Test (Best Model) - Loss: 1.3525 - Accuracy: 0.2029 - F1: 0.1693
sub_12:Test (Best Model) - Loss: 1.3770 - Accuracy: 0.2941 - F1: 0.2257
sub_10:Test (Best Model) - Loss: 1.4166 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3258 - Accuracy: 0.3623 - F1: 0.3029
sub_12:Test (Best Model) - Loss: 1.4390 - Accuracy: 0.3043 - F1: 0.2227
sub_10:Test (Best Model) - Loss: 1.4518 - Accuracy: 0.2647 - F1: 0.1444
sub_11:Test (Best Model) - Loss: 1.3748 - Accuracy: 0.3188 - F1: 0.3003
sub_11:Test (Best Model) - Loss: 1.3496 - Accuracy: 0.2609 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.4566 - Accuracy: 0.2319 - F1: 0.1744
sub_10:Test (Best Model) - Loss: 1.9114 - Accuracy: 0.3824 - F1: 0.2902
sub_12:Test (Best Model) - Loss: 1.4199 - Accuracy: 0.1449 - F1: 0.1348
sub_11:Test (Best Model) - Loss: 1.6528 - Accuracy: 0.2319 - F1: 0.0941
sub_12:Test (Best Model) - Loss: 1.4714 - Accuracy: 0.2319 - F1: 0.0976
sub_11:Test (Best Model) - Loss: 1.4661 - Accuracy: 0.2174 - F1: 0.0904
sub_10:Test (Best Model) - Loss: 1.4789 - Accuracy: 0.3088 - F1: 0.1976
sub_12:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.1304 - F1: 0.0652
sub_11:Test (Best Model) - Loss: 1.3328 - Accuracy: 0.2754 - F1: 0.1359
sub_12:Test (Best Model) - Loss: 1.3930 - Accuracy: 0.2029 - F1: 0.1359
sub_10:Test (Best Model) - Loss: 1.7520 - Accuracy: 0.2647 - F1: 0.1071
sub_11:Test (Best Model) - Loss: 1.4423 - Accuracy: 0.2029 - F1: 0.1269
sub_12:Test (Best Model) - Loss: 1.5080 - Accuracy: 0.2059 - F1: 0.0854
sub_10:Test (Best Model) - Loss: 1.4982 - Accuracy: 0.1912 - F1: 0.1904
sub_11:Test (Best Model) - Loss: 1.4033 - Accuracy: 0.2899 - F1: 0.1627
sub_12:Test (Best Model) - Loss: 1.3435 - Accuracy: 0.2500 - F1: 0.1297
sub_10:Test (Best Model) - Loss: 2.5481 - Accuracy: 0.1176 - F1: 0.0541
sub_11:Test (Best Model) - Loss: 1.4377 - Accuracy: 0.3043 - F1: 0.1765
sub_10:Test (Best Model) - Loss: 1.5647 - Accuracy: 0.2029 - F1: 0.1248
sub_12:Test (Best Model) - Loss: 1.5051 - Accuracy: 0.3235 - F1: 0.2065
sub_10:Test (Best Model) - Loss: 1.3007 - Accuracy: 0.2319 - F1: 0.0952
sub_10:Test (Best Model) - Loss: 1.4800 - Accuracy: 0.2319 - F1: 0.1127
sub_12:Test (Best Model) - Loss: 1.3631 - Accuracy: 0.3971 - F1: 0.2750
sub_10:Test (Best Model) - Loss: 1.4035 - Accuracy: 0.3768 - F1: 0.2645
sub_12:Test (Best Model) - Loss: 1.4002 - Accuracy: 0.3088 - F1: 0.1875
sub_10:Test (Best Model) - Loss: 1.5113 - Accuracy: 0.3623 - F1: 0.2353
sub_15:Test (Best Model) - Loss: 1.6158 - Accuracy: 0.3235 - F1: 0.2271
sub_13:Test (Best Model) - Loss: 1.3930 - Accuracy: 0.2647 - F1: 0.1071
sub_14:Test (Best Model) - Loss: 1.3457 - Accuracy: 0.3529 - F1: 0.2616
sub_15:Test (Best Model) - Loss: 1.8884 - Accuracy: 0.2500 - F1: 0.1612
sub_13:Test (Best Model) - Loss: 1.4105 - Accuracy: 0.2059 - F1: 0.0854
sub_14:Test (Best Model) - Loss: 1.4530 - Accuracy: 0.2059 - F1: 0.0854
sub_15:Test (Best Model) - Loss: 1.9262 - Accuracy: 0.1471 - F1: 0.1057
sub_14:Test (Best Model) - Loss: 1.5332 - Accuracy: 0.1618 - F1: 0.0764
sub_15:Test (Best Model) - Loss: 1.7636 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3050 - Accuracy: 0.2647 - F1: 0.1514
sub_13:Test (Best Model) - Loss: 1.4150 - Accuracy: 0.3824 - F1: 0.3121
sub_15:Test (Best Model) - Loss: 1.8825 - Accuracy: 0.2647 - F1: 0.1927
sub_14:Test (Best Model) - Loss: 1.4668 - Accuracy: 0.3529 - F1: 0.2554
sub_13:Test (Best Model) - Loss: 1.4231 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.4596 - Accuracy: 0.2647 - F1: 0.1873
sub_15:Test (Best Model) - Loss: 1.3581 - Accuracy: 0.3382 - F1: 0.3153
sub_14:Test (Best Model) - Loss: 1.3553 - Accuracy: 0.3971 - F1: 0.3914
sub_14:Test (Best Model) - Loss: 1.3785 - Accuracy: 0.2794 - F1: 0.1651
sub_15:Test (Best Model) - Loss: 1.3807 - Accuracy: 0.3235 - F1: 0.2719
sub_13:Test (Best Model) - Loss: 1.4454 - Accuracy: 0.3478 - F1: 0.2621
sub_14:Test (Best Model) - Loss: 1.3647 - Accuracy: 0.1912 - F1: 0.0802
sub_15:Test (Best Model) - Loss: 1.3985 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3454 - Accuracy: 0.3768 - F1: 0.2973
sub_14:Test (Best Model) - Loss: 1.3776 - Accuracy: 0.3971 - F1: 0.2886
sub_13:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.2609 - F1: 0.1034
sub_15:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.3529 - F1: 0.3318
sub_14:Test (Best Model) - Loss: 1.4618 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.4343 - Accuracy: 0.2899 - F1: 0.2132
sub_15:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.3235 - F1: 0.2007
sub_14:Test (Best Model) - Loss: 1.4002 - Accuracy: 0.2794 - F1: 0.2060
sub_13:Test (Best Model) - Loss: 1.5767 - Accuracy: 0.2609 - F1: 0.1034
sub_15:Test (Best Model) - Loss: 1.4176 - Accuracy: 0.2059 - F1: 0.0875
sub_14:Test (Best Model) - Loss: 1.4010 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.4789 - Accuracy: 0.1912 - F1: 0.0997
sub_15:Test (Best Model) - Loss: 1.6523 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3967 - Accuracy: 0.2059 - F1: 0.1436
sub_13:Test (Best Model) - Loss: 1.6003 - Accuracy: 0.2500 - F1: 0.1012
sub_15:Test (Best Model) - Loss: 1.3962 - Accuracy: 0.0735 - F1: 0.0490
sub_14:Test (Best Model) - Loss: 1.3932 - Accuracy: 0.2941 - F1: 0.1668
sub_14:Test (Best Model) - Loss: 1.4435 - Accuracy: 0.2647 - F1: 0.1314
sub_15:Test (Best Model) - Loss: 1.4612 - Accuracy: 0.2941 - F1: 0.1723
sub_13:Test (Best Model) - Loss: 1.6723 - Accuracy: 0.3235 - F1: 0.2111
sub_15:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.3529 - F1: 0.2625
sub_13:Test (Best Model) - Loss: 1.5115 - Accuracy: 0.2794 - F1: 0.1392
sub_13:Test (Best Model) - Loss: 1.8461 - Accuracy: 0.2794 - F1: 0.1612
sub_18:Test (Best Model) - Loss: 1.3628 - Accuracy: 0.2174 - F1: 0.1212
sub_17:Test (Best Model) - Loss: 1.3609 - Accuracy: 0.3623 - F1: 0.2485
sub_16:Test (Best Model) - Loss: 1.3923 - Accuracy: 0.3088 - F1: 0.1883
sub_18:Test (Best Model) - Loss: 1.6210 - Accuracy: 0.2464 - F1: 0.1415
sub_17:Test (Best Model) - Loss: 1.4083 - Accuracy: 0.2029 - F1: 0.0843
sub_16:Test (Best Model) - Loss: 1.3915 - Accuracy: 0.2059 - F1: 0.0864
sub_18:Test (Best Model) - Loss: 1.4332 - Accuracy: 0.2464 - F1: 0.1596
sub_16:Test (Best Model) - Loss: 1.4032 - Accuracy: 0.1471 - F1: 0.1098
sub_18:Test (Best Model) - Loss: 1.3540 - Accuracy: 0.2609 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3606 - Accuracy: 0.3188 - F1: 0.2165
sub_16:Test (Best Model) - Loss: 1.4111 - Accuracy: 0.2794 - F1: 0.1375
sub_18:Test (Best Model) - Loss: 1.4951 - Accuracy: 0.3333 - F1: 0.2509
sub_17:Test (Best Model) - Loss: 1.4502 - Accuracy: 0.2754 - F1: 0.1349
sub_16:Test (Best Model) - Loss: 1.4140 - Accuracy: 0.3088 - F1: 0.2215
sub_18:Test (Best Model) - Loss: 1.3614 - Accuracy: 0.4265 - F1: 0.4064
sub_17:Test (Best Model) - Loss: 1.4128 - Accuracy: 0.2464 - F1: 0.1830
sub_16:Test (Best Model) - Loss: 1.4035 - Accuracy: 0.3088 - F1: 0.2229
sub_17:Test (Best Model) - Loss: 1.3741 - Accuracy: 0.3768 - F1: 0.3054
sub_18:Test (Best Model) - Loss: 1.3630 - Accuracy: 0.4412 - F1: 0.4589
sub_17:Test (Best Model) - Loss: 1.3918 - Accuracy: 0.1884 - F1: 0.1230
sub_16:Test (Best Model) - Loss: 1.4012 - Accuracy: 0.1912 - F1: 0.1345
sub_18:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.2941 - F1: 0.1696
sub_17:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2609 - F1: 0.1034
sub_16:Test (Best Model) - Loss: 1.3537 - Accuracy: 0.3088 - F1: 0.1799
sub_18:Test (Best Model) - Loss: 1.4052 - Accuracy: 0.0294 - F1: 0.0156
sub_17:Test (Best Model) - Loss: 1.4002 - Accuracy: 0.1449 - F1: 0.0694
sub_18:Test (Best Model) - Loss: 1.4059 - Accuracy: 0.3088 - F1: 0.1750
sub_16:Test (Best Model) - Loss: 1.4292 - Accuracy: 0.2353 - F1: 0.1524
sub_17:Test (Best Model) - Loss: 1.4008 - Accuracy: 0.2609 - F1: 0.1098
sub_18:Test (Best Model) - Loss: 1.5603 - Accuracy: 0.3382 - F1: 0.2437
sub_18:Test (Best Model) - Loss: 1.4987 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3736 - Accuracy: 0.2206 - F1: 0.1161
sub_16:Test (Best Model) - Loss: 1.4635 - Accuracy: 0.2647 - F1: 0.1059
sub_17:Test (Best Model) - Loss: 1.4359 - Accuracy: 0.2647 - F1: 0.1071
sub_16:Test (Best Model) - Loss: 1.4206 - Accuracy: 0.1912 - F1: 0.1049
sub_18:Test (Best Model) - Loss: 1.4848 - Accuracy: 0.3529 - F1: 0.2785
sub_17:Test (Best Model) - Loss: 1.4465 - Accuracy: 0.2206 - F1: 0.1427
sub_16:Test (Best Model) - Loss: 1.4517 - Accuracy: 0.2500 - F1: 0.1000
sub_17:Test (Best Model) - Loss: 1.4168 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.4853 - Accuracy: 0.2206 - F1: 0.1236
sub_18:Test (Best Model) - Loss: 1.5077 - Accuracy: 0.3382 - F1: 0.2427
sub_17:Test (Best Model) - Loss: 1.4133 - Accuracy: 0.3088 - F1: 0.1989
sub_18:Test (Best Model) - Loss: 1.5459 - Accuracy: 0.2353 - F1: 0.1333
sub_16:Test (Best Model) - Loss: 1.4213 - Accuracy: 0.2500 - F1: 0.1024
sub_16:Test (Best Model) - Loss: 1.4003 - Accuracy: 0.2941 - F1: 0.1625
sub_19:Test (Best Model) - Loss: 1.3797 - Accuracy: 0.3676 - F1: 0.2939
sub_21:Test (Best Model) - Loss: 1.4337 - Accuracy: 0.3382 - F1: 0.2723
sub_19:Test (Best Model) - Loss: 1.4049 - Accuracy: 0.1912 - F1: 0.0823
sub_20:Test (Best Model) - Loss: 1.3587 - Accuracy: 0.3971 - F1: 0.3219
sub_21:Test (Best Model) - Loss: 1.4592 - Accuracy: 0.2059 - F1: 0.0854
sub_19:Test (Best Model) - Loss: 1.4130 - Accuracy: 0.1912 - F1: 0.1084
sub_19:Test (Best Model) - Loss: 1.3829 - Accuracy: 0.2500 - F1: 0.1024
sub_20:Test (Best Model) - Loss: 1.3489 - Accuracy: 0.1912 - F1: 0.0855
sub_21:Test (Best Model) - Loss: 1.4037 - Accuracy: 0.3382 - F1: 0.2226
sub_19:Test (Best Model) - Loss: 1.4072 - Accuracy: 0.2059 - F1: 0.1344
sub_20:Test (Best Model) - Loss: 1.3955 - Accuracy: 0.1912 - F1: 0.1344
sub_21:Test (Best Model) - Loss: 1.4353 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3943 - Accuracy: 0.2647 - F1: 0.1059
sub_21:Test (Best Model) - Loss: 1.5096 - Accuracy: 0.1912 - F1: 0.1460
sub_20:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.1765 - F1: 0.1624
sub_19:Test (Best Model) - Loss: 1.4017 - Accuracy: 0.2206 - F1: 0.1504
sub_19:Test (Best Model) - Loss: 1.4128 - Accuracy: 0.1324 - F1: 0.0789
sub_20:Test (Best Model) - Loss: 1.3398 - Accuracy: 0.5294 - F1: 0.5003
sub_21:Test (Best Model) - Loss: 1.4780 - Accuracy: 0.4265 - F1: 0.3743
sub_19:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.2059 - F1: 0.0886
sub_21:Test (Best Model) - Loss: 1.4816 - Accuracy: 0.4265 - F1: 0.3656
sub_20:Test (Best Model) - Loss: 1.3638 - Accuracy: 0.3824 - F1: 0.3831
sub_19:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.2647 - F1: 0.1837
sub_21:Test (Best Model) - Loss: 1.5609 - Accuracy: 0.2353 - F1: 0.0964
sub_19:Test (Best Model) - Loss: 1.4538 - Accuracy: 0.2647 - F1: 0.1125
sub_20:Test (Best Model) - Loss: 1.3943 - Accuracy: 0.2794 - F1: 0.1841
sub_21:Test (Best Model) - Loss: 1.4147 - Accuracy: 0.2059 - F1: 0.1660
sub_19:Test (Best Model) - Loss: 1.4046 - Accuracy: 0.2059 - F1: 0.0933
sub_21:Test (Best Model) - Loss: 1.4829 - Accuracy: 0.2647 - F1: 0.1084
sub_19:Test (Best Model) - Loss: 1.4047 - Accuracy: 0.2647 - F1: 0.1071
sub_20:Test (Best Model) - Loss: 1.3711 - Accuracy: 0.1176 - F1: 0.1106
sub_20:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2794 - F1: 0.1342
sub_19:Test (Best Model) - Loss: 1.4650 - Accuracy: 0.0735 - F1: 0.0403
sub_21:Test (Best Model) - Loss: 1.3453 - Accuracy: 0.2059 - F1: 0.0986
sub_20:Test (Best Model) - Loss: 1.6399 - Accuracy: 0.2174 - F1: 0.0926
sub_19:Test (Best Model) - Loss: 1.3777 - Accuracy: 0.3382 - F1: 0.2375
sub_21:Test (Best Model) - Loss: 1.3643 - Accuracy: 0.2794 - F1: 0.1321
sub_20:Test (Best Model) - Loss: 1.2732 - Accuracy: 0.2609 - F1: 0.1034
sub_21:Test (Best Model) - Loss: 1.3905 - Accuracy: 0.1912 - F1: 0.1270
sub_20:Test (Best Model) - Loss: 1.5231 - Accuracy: 0.2609 - F1: 0.1306
sub_19:Test (Best Model) - Loss: 1.4254 - Accuracy: 0.2941 - F1: 0.1965
sub_21:Test (Best Model) - Loss: 1.3672 - Accuracy: 0.2941 - F1: 0.1723
sub_20:Test (Best Model) - Loss: 1.4335 - Accuracy: 0.2754 - F1: 0.1517
sub_21:Test (Best Model) - Loss: 1.3831 - Accuracy: 0.2500 - F1: 0.1062
sub_20:Test (Best Model) - Loss: 1.6279 - Accuracy: 0.3913 - F1: 0.2719
sub_23:Test (Best Model) - Loss: 1.3728 - Accuracy: 0.2464 - F1: 0.1000
sub_24:Test (Best Model) - Loss: 1.3529 - Accuracy: 0.2794 - F1: 0.1607
sub_23:Test (Best Model) - Loss: 1.3978 - Accuracy: 0.2899 - F1: 0.2122
sub_24:Test (Best Model) - Loss: 1.4578 - Accuracy: 0.2206 - F1: 0.1124
sub_23:Test (Best Model) - Loss: 1.3720 - Accuracy: 0.4058 - F1: 0.3108
sub_22:Test (Best Model) - Loss: 1.3238 - Accuracy: 0.3971 - F1: 0.3317
sub_24:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2353 - F1: 0.2475
sub_23:Test (Best Model) - Loss: 1.4219 - Accuracy: 0.2464 - F1: 0.1076
sub_24:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3998 - Accuracy: 0.4058 - F1: 0.3402
sub_22:Test (Best Model) - Loss: 1.4622 - Accuracy: 0.2059 - F1: 0.0864
sub_24:Test (Best Model) - Loss: 1.4434 - Accuracy: 0.0882 - F1: 0.0752
sub_23:Test (Best Model) - Loss: 1.7300 - Accuracy: 0.5882 - F1: 0.5820
sub_22:Test (Best Model) - Loss: 1.3912 - Accuracy: 0.2794 - F1: 0.1516
sub_23:Test (Best Model) - Loss: 1.4082 - Accuracy: 0.3676 - F1: 0.2487
sub_22:Test (Best Model) - Loss: 1.2721 - Accuracy: 0.2794 - F1: 0.1392
sub_24:Test (Best Model) - Loss: 1.3700 - Accuracy: 0.3971 - F1: 0.3484
sub_22:Test (Best Model) - Loss: 1.5415 - Accuracy: 0.2500 - F1: 0.1522
sub_23:Test (Best Model) - Loss: 1.3953 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3759 - Accuracy: 0.2500 - F1: 0.2353
sub_22:Test (Best Model) - Loss: 1.3527 - Accuracy: 0.4928 - F1: 0.4608
sub_23:Test (Best Model) - Loss: 1.4196 - Accuracy: 0.2353 - F1: 0.1477
sub_24:Test (Best Model) - Loss: 1.3434 - Accuracy: 0.2500 - F1: 0.1203
sub_22:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.3333 - F1: 0.2531
sub_23:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3930 - Accuracy: 0.2941 - F1: 0.2568
sub_22:Test (Best Model) - Loss: 1.3909 - Accuracy: 0.2899 - F1: 0.1673
sub_23:Test (Best Model) - Loss: 1.6448 - Accuracy: 0.2609 - F1: 0.1878
sub_24:Test (Best Model) - Loss: 1.5450 - Accuracy: 0.2794 - F1: 0.1339
sub_23:Test (Best Model) - Loss: 1.2871 - Accuracy: 0.3188 - F1: 0.1967
sub_24:Test (Best Model) - Loss: 1.5324 - Accuracy: 0.2500 - F1: 0.1564
sub_23:Test (Best Model) - Loss: 1.5161 - Accuracy: 0.2029 - F1: 0.1151
sub_22:Test (Best Model) - Loss: 1.3742 - Accuracy: 0.2029 - F1: 0.1414
sub_24:Test (Best Model) - Loss: 1.3381 - Accuracy: 0.2794 - F1: 0.1329
sub_23:Test (Best Model) - Loss: 1.3301 - Accuracy: 0.2754 - F1: 0.1359
sub_22:Test (Best Model) - Loss: 1.3733 - Accuracy: 0.2754 - F1: 0.1348
sub_24:Test (Best Model) - Loss: 1.5972 - Accuracy: 0.4118 - F1: 0.2692
sub_23:Test (Best Model) - Loss: 1.8037 - Accuracy: 0.3043 - F1: 0.1750
sub_24:Test (Best Model) - Loss: 1.4106 - Accuracy: 0.2647 - F1: 0.1071
sub_22:Test (Best Model) - Loss: 1.7445 - Accuracy: 0.2059 - F1: 0.0875
sub_24:Test (Best Model) - Loss: 1.4509 - Accuracy: 0.2941 - F1: 0.1696
sub_22:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.5216 - Accuracy: 0.2941 - F1: 0.1652
sub_22:Test (Best Model) - Loss: 1.5259 - Accuracy: 0.2500 - F1: 0.1012
sub_22:Test (Best Model) - Loss: 1.4584 - Accuracy: 0.3088 - F1: 0.1967
sub_26:Test (Best Model) - Loss: 1.3781 - Accuracy: 0.2609 - F1: 0.1508
sub_27:Test (Best Model) - Loss: 1.3609 - Accuracy: 0.3623 - F1: 0.2485
sub_25:Test (Best Model) - Loss: 1.3764 - Accuracy: 0.2754 - F1: 0.1310
sub_26:Test (Best Model) - Loss: 1.3740 - Accuracy: 0.2174 - F1: 0.1102
sub_27:Test (Best Model) - Loss: 1.4083 - Accuracy: 0.2029 - F1: 0.0843
sub_25:Test (Best Model) - Loss: 1.3747 - Accuracy: 0.2319 - F1: 0.1164
sub_26:Test (Best Model) - Loss: 1.3684 - Accuracy: 0.2754 - F1: 0.2470
sub_27:Test (Best Model) - Loss: 1.3606 - Accuracy: 0.3188 - F1: 0.2165
sub_25:Test (Best Model) - Loss: 1.4237 - Accuracy: 0.1739 - F1: 0.1166
sub_26:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.2609 - F1: 0.1059
sub_25:Test (Best Model) - Loss: 1.3964 - Accuracy: 0.2464 - F1: 0.1230
sub_27:Test (Best Model) - Loss: 1.4502 - Accuracy: 0.2754 - F1: 0.1349
sub_26:Test (Best Model) - Loss: 1.3748 - Accuracy: 0.3333 - F1: 0.2886
sub_25:Test (Best Model) - Loss: 1.3674 - Accuracy: 0.2029 - F1: 0.1790
sub_27:Test (Best Model) - Loss: 1.4128 - Accuracy: 0.2464 - F1: 0.1830
sub_26:Test (Best Model) - Loss: 1.3366 - Accuracy: 0.4118 - F1: 0.4120
sub_27:Test (Best Model) - Loss: 1.3741 - Accuracy: 0.3768 - F1: 0.3054
sub_26:Test (Best Model) - Loss: 1.3679 - Accuracy: 0.4118 - F1: 0.3483
sub_26:Test (Best Model) - Loss: 1.3968 - Accuracy: 0.2647 - F1: 0.1059
sub_27:Test (Best Model) - Loss: 1.3918 - Accuracy: 0.1884 - F1: 0.1230
sub_26:Test (Best Model) - Loss: 1.4008 - Accuracy: 0.1618 - F1: 0.1362
sub_25:Test (Best Model) - Loss: 1.2888 - Accuracy: 0.7059 - F1: 0.6953
sub_27:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.2647 - F1: 0.1059
sub_26:Test (Best Model) - Loss: 1.6846 - Accuracy: 0.2647 - F1: 0.1907
sub_27:Test (Best Model) - Loss: 1.4002 - Accuracy: 0.1449 - F1: 0.0694
sub_25:Test (Best Model) - Loss: 1.4003 - Accuracy: 0.2647 - F1: 0.2725
sub_26:Test (Best Model) - Loss: 1.2818 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.4008 - Accuracy: 0.2609 - F1: 0.1098
sub_25:Test (Best Model) - Loss: 1.3698 - Accuracy: 0.2059 - F1: 0.1389
sub_25:Test (Best Model) - Loss: 1.4087 - Accuracy: 0.0735 - F1: 0.0525
sub_27:Test (Best Model) - Loss: 1.3736 - Accuracy: 0.2206 - F1: 0.1161
sub_25:Test (Best Model) - Loss: 1.4242 - Accuracy: 0.2794 - F1: 0.1408
sub_26:Test (Best Model) - Loss: 1.5299 - Accuracy: 0.3529 - F1: 0.2895
sub_27:Test (Best Model) - Loss: 1.4359 - Accuracy: 0.2647 - F1: 0.1071
sub_26:Test (Best Model) - Loss: 1.3763 - Accuracy: 0.2941 - F1: 0.1637
sub_25:Test (Best Model) - Loss: 1.5962 - Accuracy: 0.1912 - F1: 0.0903
sub_27:Test (Best Model) - Loss: 1.4465 - Accuracy: 0.2206 - F1: 0.1427
sub_26:Test (Best Model) - Loss: 1.7006 - Accuracy: 0.2794 - F1: 0.1535
sub_25:Test (Best Model) - Loss: 1.2661 - Accuracy: 0.2500 - F1: 0.1202
sub_27:Test (Best Model) - Loss: 1.4168 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.4133 - Accuracy: 0.3088 - F1: 0.1989
sub_25:Test (Best Model) - Loss: 1.4966 - Accuracy: 0.3529 - F1: 0.2925
sub_25:Test (Best Model) - Loss: 1.4276 - Accuracy: 0.2794 - F1: 0.1612
sub_25:Test (Best Model) - Loss: 1.4996 - Accuracy: 0.3529 - F1: 0.2344
sub_28:Test (Best Model) - Loss: 1.3751 - Accuracy: 0.3088 - F1: 0.1993
sub_29:Test (Best Model) - Loss: 1.3743 - Accuracy: 0.4265 - F1: 0.4173
sub_28:Test (Best Model) - Loss: 1.3545 - Accuracy: 0.2206 - F1: 0.1127
sub_29:Test (Best Model) - Loss: 1.4815 - Accuracy: 0.2059 - F1: 0.0854
sub_28:Test (Best Model) - Loss: 1.3955 - Accuracy: 0.2647 - F1: 0.2093
sub_29:Test (Best Model) - Loss: 1.4157 - Accuracy: 0.4118 - F1: 0.3208
sub_28:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2647 - F1: 0.1059
sub_29:Test (Best Model) - Loss: 1.4647 - Accuracy: 0.2794 - F1: 0.1592
sub_28:Test (Best Model) - Loss: 1.3995 - Accuracy: 0.2206 - F1: 0.1550
sub_29:Test (Best Model) - Loss: 1.4246 - Accuracy: 0.3382 - F1: 0.2532
sub_28:Test (Best Model) - Loss: 1.4808 - Accuracy: 0.1471 - F1: 0.1126
sub_29:Test (Best Model) - Loss: 1.2831 - Accuracy: 0.4559 - F1: 0.4148
sub_28:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2941 - F1: 0.1865
sub_29:Test (Best Model) - Loss: 1.3489 - Accuracy: 0.3088 - F1: 0.1932
sub_28:Test (Best Model) - Loss: 1.3560 - Accuracy: 0.2206 - F1: 0.1212
sub_29:Test (Best Model) - Loss: 1.3310 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.4680 - Accuracy: 0.3088 - F1: 0.2087
sub_29:Test (Best Model) - Loss: 1.3919 - Accuracy: 0.4118 - F1: 0.2996
sub_28:Test (Best Model) - Loss: 1.4510 - Accuracy: 0.2794 - F1: 0.1741
sub_29:Test (Best Model) - Loss: 1.5426 - Accuracy: 0.4265 - F1: 0.2770
sub_28:Test (Best Model) - Loss: 2.3153 - Accuracy: 0.1912 - F1: 0.0823
sub_29:Test (Best Model) - Loss: 1.5450 - Accuracy: 0.2174 - F1: 0.0938
sub_28:Test (Best Model) - Loss: 1.4202 - Accuracy: 0.1618 - F1: 0.1171
sub_29:Test (Best Model) - Loss: 1.3180 - Accuracy: 0.2609 - F1: 0.1034
sub_28:Test (Best Model) - Loss: 2.0138 - Accuracy: 0.3382 - F1: 0.2047
sub_29:Test (Best Model) - Loss: 1.5293 - Accuracy: 0.3043 - F1: 0.1963
sub_28:Test (Best Model) - Loss: 1.6395 - Accuracy: 0.1912 - F1: 0.1255
sub_28:Test (Best Model) - Loss: 1.8751 - Accuracy: 0.2794 - F1: 0.1533
sub_29:Test (Best Model) - Loss: 1.4162 - Accuracy: 0.2319 - F1: 0.1332
sub_29:Test (Best Model) - Loss: 1.4623 - Accuracy: 0.2609 - F1: 0.1643

=== Summary Results ===

acc: 27.32 ± 1.96
F1: 17.35 ± 2.10
acc-in: 27.49 ± 1.84
F1-in: 17.71 ± 1.93
runing time: 1549.46 seconds
