lr: 1e-06
sub_2:Test (Best Model) - Loss: 1.3902 - Accuracy: 0.2609 - F1: 0.1034
sub_3:Test (Best Model) - Loss: 1.3698 - Accuracy: 0.2941 - F1: 0.1584
sub_1:Test (Best Model) - Loss: 1.5489 - Accuracy: 0.2647 - F1: 0.1059
sub_3:Test (Best Model) - Loss: 1.3997 - Accuracy: 0.2059 - F1: 0.0854
sub_2:Test (Best Model) - Loss: 1.3538 - Accuracy: 0.2319 - F1: 0.1314
sub_1:Test (Best Model) - Loss: 1.6506 - Accuracy: 0.2059 - F1: 0.0875
sub_1:Test (Best Model) - Loss: 1.6267 - Accuracy: 0.2206 - F1: 0.1886
sub_2:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.4058 - F1: 0.3490
sub_3:Test (Best Model) - Loss: 1.4815 - Accuracy: 0.1618 - F1: 0.1083
sub_1:Test (Best Model) - Loss: 1.6149 - Accuracy: 0.2794 - F1: 0.1392
sub_2:Test (Best Model) - Loss: 1.4773 - Accuracy: 0.2609 - F1: 0.1034
sub_1:Test (Best Model) - Loss: 1.7141 - Accuracy: 0.1912 - F1: 0.1640
sub_2:Test (Best Model) - Loss: 1.3744 - Accuracy: 0.3188 - F1: 0.2615
sub_3:Test (Best Model) - Loss: 1.6237 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3713 - Accuracy: 0.3088 - F1: 0.2691
sub_1:Test (Best Model) - Loss: 1.3912 - Accuracy: 0.1594 - F1: 0.1480
sub_3:Test (Best Model) - Loss: 1.3829 - Accuracy: 0.2206 - F1: 0.1552
sub_2:Test (Best Model) - Loss: 1.3720 - Accuracy: 0.3382 - F1: 0.2555
sub_1:Test (Best Model) - Loss: 1.3926 - Accuracy: 0.2464 - F1: 0.1722
sub_2:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.3824 - F1: 0.2596
sub_3:Test (Best Model) - Loss: 1.3500 - Accuracy: 0.2319 - F1: 0.1909
sub_1:Test (Best Model) - Loss: 1.3994 - Accuracy: 0.2609 - F1: 0.1059
sub_2:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.2794 - F1: 0.2259
sub_3:Test (Best Model) - Loss: 1.3639 - Accuracy: 0.2754 - F1: 0.1866
sub_1:Test (Best Model) - Loss: 1.8050 - Accuracy: 0.1449 - F1: 0.0817
sub_2:Test (Best Model) - Loss: 1.4128 - Accuracy: 0.2353 - F1: 0.1187
sub_3:Test (Best Model) - Loss: 1.3779 - Accuracy: 0.2754 - F1: 0.1309
sub_1:Test (Best Model) - Loss: 1.6604 - Accuracy: 0.2609 - F1: 0.1034
sub_1:Test (Best Model) - Loss: 1.4352 - Accuracy: 0.2794 - F1: 0.1910
sub_2:Test (Best Model) - Loss: 1.4510 - Accuracy: 0.2319 - F1: 0.1165
sub_3:Test (Best Model) - Loss: 1.6026 - Accuracy: 0.2754 - F1: 0.2180
sub_1:Test (Best Model) - Loss: 1.3509 - Accuracy: 0.2647 - F1: 0.1059
sub_2:Test (Best Model) - Loss: 1.3472 - Accuracy: 0.2319 - F1: 0.0964
sub_3:Test (Best Model) - Loss: 2.0043 - Accuracy: 0.2609 - F1: 0.1034
sub_1:Test (Best Model) - Loss: 1.4458 - Accuracy: 0.2206 - F1: 0.1374
sub_3:Test (Best Model) - Loss: 1.5667 - Accuracy: 0.2319 - F1: 0.1340
sub_1:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.2794 - F1: 0.1384
sub_2:Test (Best Model) - Loss: 1.4320 - Accuracy: 0.2754 - F1: 0.2287
sub_3:Test (Best Model) - Loss: 1.3113 - Accuracy: 0.2464 - F1: 0.1012
sub_1:Test (Best Model) - Loss: 1.4193 - Accuracy: 0.2059 - F1: 0.1208
sub_2:Test (Best Model) - Loss: 1.3917 - Accuracy: 0.2609 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.4929 - Accuracy: 0.2464 - F1: 0.1612
sub_2:Test (Best Model) - Loss: 1.4583 - Accuracy: 0.1304 - F1: 0.0836
sub_3:Test (Best Model) - Loss: 1.4102 - Accuracy: 0.2609 - F1: 0.1071
sub_3:Test (Best Model) - Loss: 1.4866 - Accuracy: 0.2464 - F1: 0.1268
sub_4:Test (Best Model) - Loss: 1.4102 - Accuracy: 0.2754 - F1: 0.1359
sub_6:Test (Best Model) - Loss: 1.4518 - Accuracy: 0.2647 - F1: 0.1059
sub_5:Test (Best Model) - Loss: 1.4551 - Accuracy: 0.2647 - F1: 0.1863
sub_4:Test (Best Model) - Loss: 1.3747 - Accuracy: 0.2174 - F1: 0.0938
sub_6:Test (Best Model) - Loss: 1.5266 - Accuracy: 0.2794 - F1: 0.1933
sub_5:Test (Best Model) - Loss: 1.6129 - Accuracy: 0.2059 - F1: 0.0854
sub_4:Test (Best Model) - Loss: 1.4094 - Accuracy: 0.2029 - F1: 0.1263
sub_6:Test (Best Model) - Loss: 1.4027 - Accuracy: 0.1618 - F1: 0.1225
sub_5:Test (Best Model) - Loss: 1.4592 - Accuracy: 0.2500 - F1: 0.1726
sub_4:Test (Best Model) - Loss: 1.3779 - Accuracy: 0.2609 - F1: 0.1034
sub_6:Test (Best Model) - Loss: 1.3721 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.4986 - Accuracy: 0.2794 - F1: 0.1386
sub_4:Test (Best Model) - Loss: 1.3737 - Accuracy: 0.2754 - F1: 0.2273
sub_5:Test (Best Model) - Loss: 1.7531 - Accuracy: 0.0588 - F1: 0.0555
sub_6:Test (Best Model) - Loss: 1.3993 - Accuracy: 0.2500 - F1: 0.1920
sub_6:Test (Best Model) - Loss: 1.3801 - Accuracy: 0.3478 - F1: 0.3210
sub_4:Test (Best Model) - Loss: 1.3637 - Accuracy: 0.2609 - F1: 0.1815
sub_5:Test (Best Model) - Loss: 1.4091 - Accuracy: 0.2206 - F1: 0.1643
sub_6:Test (Best Model) - Loss: 1.3925 - Accuracy: 0.2754 - F1: 0.1837
sub_4:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2899 - F1: 0.1797
sub_6:Test (Best Model) - Loss: 1.3926 - Accuracy: 0.2754 - F1: 0.1749
sub_5:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2941 - F1: 0.1723
sub_4:Test (Best Model) - Loss: 1.3933 - Accuracy: 0.2899 - F1: 0.1559
sub_6:Test (Best Model) - Loss: 1.3993 - Accuracy: 0.2609 - F1: 0.1895
sub_5:Test (Best Model) - Loss: 1.4006 - Accuracy: 0.2647 - F1: 0.1098
sub_4:Test (Best Model) - Loss: 1.4112 - Accuracy: 0.2029 - F1: 0.1107
sub_6:Test (Best Model) - Loss: 1.4122 - Accuracy: 0.2464 - F1: 0.1012
sub_5:Test (Best Model) - Loss: 1.3638 - Accuracy: 0.3824 - F1: 0.3424
sub_4:Test (Best Model) - Loss: 1.4231 - Accuracy: 0.2754 - F1: 0.1371
sub_6:Test (Best Model) - Loss: 1.4680 - Accuracy: 0.2609 - F1: 0.1690
sub_5:Test (Best Model) - Loss: 1.3578 - Accuracy: 0.2794 - F1: 0.1392
sub_4:Test (Best Model) - Loss: 1.6040 - Accuracy: 0.2174 - F1: 0.0893
sub_6:Test (Best Model) - Loss: 1.3656 - Accuracy: 0.2754 - F1: 0.1488
sub_5:Test (Best Model) - Loss: 1.4217 - Accuracy: 0.4118 - F1: 0.2768
sub_6:Test (Best Model) - Loss: 1.4725 - Accuracy: 0.1594 - F1: 0.1369
sub_4:Test (Best Model) - Loss: 1.3481 - Accuracy: 0.2319 - F1: 0.0941
sub_5:Test (Best Model) - Loss: 1.3585 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.4142 - Accuracy: 0.2464 - F1: 0.1000
sub_5:Test (Best Model) - Loss: 1.4079 - Accuracy: 0.2647 - F1: 0.1838
sub_4:Test (Best Model) - Loss: 1.6189 - Accuracy: 0.2609 - F1: 0.2399
sub_6:Test (Best Model) - Loss: 1.4181 - Accuracy: 0.2899 - F1: 0.1771
sub_4:Test (Best Model) - Loss: 1.4804 - Accuracy: 0.2319 - F1: 0.0941
sub_5:Test (Best Model) - Loss: 1.3919 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.4075 - Accuracy: 0.1324 - F1: 0.0842
sub_4:Test (Best Model) - Loss: 1.4709 - Accuracy: 0.2899 - F1: 0.1746
sub_8:Test (Best Model) - Loss: 1.3818 - Accuracy: 0.2500 - F1: 0.1076
sub_7:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.1912 - F1: 0.0844
sub_9:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.4093 - Accuracy: 0.2353 - F1: 0.1375
sub_7:Test (Best Model) - Loss: 1.4529 - Accuracy: 0.1765 - F1: 0.0932
sub_9:Test (Best Model) - Loss: 1.3713 - Accuracy: 0.1912 - F1: 0.0844
sub_8:Test (Best Model) - Loss: 1.3720 - Accuracy: 0.2794 - F1: 0.2207
sub_9:Test (Best Model) - Loss: 1.3893 - Accuracy: 0.2353 - F1: 0.1404
sub_7:Test (Best Model) - Loss: 1.3242 - Accuracy: 0.3676 - F1: 0.2882
sub_8:Test (Best Model) - Loss: 1.3699 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.4029 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.4399 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3768 - Accuracy: 0.2353 - F1: 0.1590
sub_7:Test (Best Model) - Loss: 1.3714 - Accuracy: 0.1471 - F1: 0.1306
sub_9:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.3824 - F1: 0.2937
sub_8:Test (Best Model) - Loss: 1.2825 - Accuracy: 0.2647 - F1: 0.1786
sub_7:Test (Best Model) - Loss: 1.3657 - Accuracy: 0.3382 - F1: 0.2747
sub_8:Test (Best Model) - Loss: 1.2993 - Accuracy: 0.3382 - F1: 0.2505
sub_9:Test (Best Model) - Loss: 1.3511 - Accuracy: 0.3235 - F1: 0.3145
sub_7:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.2941 - F1: 0.2062
sub_8:Test (Best Model) - Loss: 1.3347 - Accuracy: 0.2794 - F1: 0.1322
sub_8:Test (Best Model) - Loss: 1.3464 - Accuracy: 0.3529 - F1: 0.2997
sub_9:Test (Best Model) - Loss: 1.3815 - Accuracy: 0.3235 - F1: 0.2510
sub_7:Test (Best Model) - Loss: 1.4062 - Accuracy: 0.2794 - F1: 0.1802
sub_8:Test (Best Model) - Loss: 1.6694 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.3676 - F1: 0.2794
sub_7:Test (Best Model) - Loss: 1.3724 - Accuracy: 0.3235 - F1: 0.2522
sub_8:Test (Best Model) - Loss: 1.5121 - Accuracy: 0.2059 - F1: 0.0854
sub_7:Test (Best Model) - Loss: 1.4062 - Accuracy: 0.3088 - F1: 0.1914
sub_9:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.1765 - F1: 0.0962
sub_8:Test (Best Model) - Loss: 1.3800 - Accuracy: 0.2353 - F1: 0.0952
sub_9:Test (Best Model) - Loss: 1.4425 - Accuracy: 0.2647 - F1: 0.1059
sub_7:Test (Best Model) - Loss: 1.4433 - Accuracy: 0.2059 - F1: 0.1071
sub_9:Test (Best Model) - Loss: 1.4074 - Accuracy: 0.2500 - F1: 0.1500
sub_7:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.2353 - F1: 0.1143
sub_8:Test (Best Model) - Loss: 1.4210 - Accuracy: 0.2647 - F1: 0.1526
sub_9:Test (Best Model) - Loss: 1.3755 - Accuracy: 0.2647 - F1: 0.1422
sub_8:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2794 - F1: 0.1322
sub_7:Test (Best Model) - Loss: 1.4193 - Accuracy: 0.1912 - F1: 0.1470
sub_8:Test (Best Model) - Loss: 1.4295 - Accuracy: 0.2647 - F1: 0.1469
sub_7:Test (Best Model) - Loss: 1.4006 - Accuracy: 0.2500 - F1: 0.1276
sub_9:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.3676 - F1: 0.3111
sub_7:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.1618 - F1: 0.0902
sub_9:Test (Best Model) - Loss: 1.3951 - Accuracy: 0.1618 - F1: 0.0833
sub_9:Test (Best Model) - Loss: 1.3741 - Accuracy: 0.2353 - F1: 0.1495
sub_10:Test (Best Model) - Loss: 1.4011 - Accuracy: 0.2647 - F1: 0.1071
sub_12:Test (Best Model) - Loss: 1.3749 - Accuracy: 0.2647 - F1: 0.1071
sub_11:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2754 - F1: 0.1488
sub_10:Test (Best Model) - Loss: 1.4305 - Accuracy: 0.2059 - F1: 0.0854
sub_11:Test (Best Model) - Loss: 1.3543 - Accuracy: 0.2464 - F1: 0.1415
sub_12:Test (Best Model) - Loss: 1.3475 - Accuracy: 0.2353 - F1: 0.1375
sub_10:Test (Best Model) - Loss: 1.4225 - Accuracy: 0.2794 - F1: 0.1937
sub_11:Test (Best Model) - Loss: 1.3937 - Accuracy: 0.2319 - F1: 0.1594
sub_12:Test (Best Model) - Loss: 1.4022 - Accuracy: 0.2500 - F1: 0.2140
sub_10:Test (Best Model) - Loss: 1.4123 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.4634 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.2794 - F1: 0.1392
sub_10:Test (Best Model) - Loss: 1.4619 - Accuracy: 0.2206 - F1: 0.1845
sub_12:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.1912 - F1: 0.1682
sub_11:Test (Best Model) - Loss: 1.3477 - Accuracy: 0.2174 - F1: 0.1885
sub_10:Test (Best Model) - Loss: 2.2041 - Accuracy: 0.2500 - F1: 0.1266
sub_12:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2174 - F1: 0.1629
sub_11:Test (Best Model) - Loss: 1.3512 - Accuracy: 0.3333 - F1: 0.3117
sub_10:Test (Best Model) - Loss: 1.4803 - Accuracy: 0.2941 - F1: 0.2159
sub_11:Test (Best Model) - Loss: 1.3513 - Accuracy: 0.3623 - F1: 0.2525
sub_10:Test (Best Model) - Loss: 2.0064 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3609 - Accuracy: 0.2609 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.5152 - Accuracy: 0.3382 - F1: 0.2278
sub_12:Test (Best Model) - Loss: 1.4021 - Accuracy: 0.3478 - F1: 0.2523
sub_11:Test (Best Model) - Loss: 1.4351 - Accuracy: 0.2609 - F1: 0.1847
sub_10:Test (Best Model) - Loss: 2.1132 - Accuracy: 0.2647 - F1: 0.1275
sub_11:Test (Best Model) - Loss: 1.5428 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 1.3961 - Accuracy: 0.2754 - F1: 0.1309
sub_10:Test (Best Model) - Loss: 1.5375 - Accuracy: 0.2174 - F1: 0.1109
sub_11:Test (Best Model) - Loss: 1.4523 - Accuracy: 0.2174 - F1: 0.0904
sub_12:Test (Best Model) - Loss: 1.3932 - Accuracy: 0.2174 - F1: 0.1493
sub_10:Test (Best Model) - Loss: 1.3366 - Accuracy: 0.2754 - F1: 0.1479
sub_11:Test (Best Model) - Loss: 1.3584 - Accuracy: 0.2754 - F1: 0.1488
sub_12:Test (Best Model) - Loss: 1.3760 - Accuracy: 0.2464 - F1: 0.0988
sub_10:Test (Best Model) - Loss: 1.4622 - Accuracy: 0.3043 - F1: 0.2400
sub_11:Test (Best Model) - Loss: 1.4204 - Accuracy: 0.1884 - F1: 0.1287
sub_10:Test (Best Model) - Loss: 1.4210 - Accuracy: 0.2174 - F1: 0.0926
sub_12:Test (Best Model) - Loss: 1.5359 - Accuracy: 0.2059 - F1: 0.0864
sub_11:Test (Best Model) - Loss: 1.3906 - Accuracy: 0.2029 - F1: 0.0897
sub_10:Test (Best Model) - Loss: 1.4432 - Accuracy: 0.2319 - F1: 0.1127
sub_12:Test (Best Model) - Loss: 1.3358 - Accuracy: 0.2353 - F1: 0.1000
sub_12:Test (Best Model) - Loss: 1.4876 - Accuracy: 0.2941 - F1: 0.1926
sub_11:Test (Best Model) - Loss: 1.4022 - Accuracy: 0.2174 - F1: 0.1379
sub_12:Test (Best Model) - Loss: 1.3988 - Accuracy: 0.2647 - F1: 0.1318
sub_12:Test (Best Model) - Loss: 1.4295 - Accuracy: 0.2647 - F1: 0.1059
sub_15:Test (Best Model) - Loss: 1.6560 - Accuracy: 0.2794 - F1: 0.1424
sub_14:Test (Best Model) - Loss: 1.4303 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.4118 - Accuracy: 0.2647 - F1: 0.1059
sub_15:Test (Best Model) - Loss: 1.9885 - Accuracy: 0.2059 - F1: 0.0864
sub_14:Test (Best Model) - Loss: 1.4393 - Accuracy: 0.2206 - F1: 0.1127
sub_13:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2059 - F1: 0.0864
sub_15:Test (Best Model) - Loss: 1.9558 - Accuracy: 0.1765 - F1: 0.1362
sub_13:Test (Best Model) - Loss: 1.4173 - Accuracy: 0.2353 - F1: 0.1578
sub_14:Test (Best Model) - Loss: 1.4591 - Accuracy: 0.2647 - F1: 0.1098
sub_15:Test (Best Model) - Loss: 1.9950 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3365 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.4070 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.6256 - Accuracy: 0.1912 - F1: 0.1583
sub_13:Test (Best Model) - Loss: 1.4063 - Accuracy: 0.2647 - F1: 0.2297
sub_14:Test (Best Model) - Loss: 1.4724 - Accuracy: 0.1912 - F1: 0.1201
sub_13:Test (Best Model) - Loss: 1.4068 - Accuracy: 0.2609 - F1: 0.1666
sub_15:Test (Best Model) - Loss: 1.3634 - Accuracy: 0.3088 - F1: 0.2782
sub_14:Test (Best Model) - Loss: 1.3976 - Accuracy: 0.2941 - F1: 0.2536
sub_13:Test (Best Model) - Loss: 1.3449 - Accuracy: 0.2319 - F1: 0.1201
sub_15:Test (Best Model) - Loss: 1.3917 - Accuracy: 0.2647 - F1: 0.2181
sub_13:Test (Best Model) - Loss: 1.4510 - Accuracy: 0.2464 - F1: 0.1000
sub_15:Test (Best Model) - Loss: 1.4036 - Accuracy: 0.2647 - F1: 0.1667
sub_14:Test (Best Model) - Loss: 1.3787 - Accuracy: 0.3235 - F1: 0.2233
sub_13:Test (Best Model) - Loss: 1.4100 - Accuracy: 0.3478 - F1: 0.2945
sub_15:Test (Best Model) - Loss: 1.3992 - Accuracy: 0.2059 - F1: 0.1604
sub_14:Test (Best Model) - Loss: 1.3643 - Accuracy: 0.2647 - F1: 0.1059
sub_13:Test (Best Model) - Loss: 1.4444 - Accuracy: 0.2609 - F1: 0.1034
sub_15:Test (Best Model) - Loss: 1.3915 - Accuracy: 0.2500 - F1: 0.1012
sub_13:Test (Best Model) - Loss: 1.3930 - Accuracy: 0.2647 - F1: 0.1778
sub_14:Test (Best Model) - Loss: 1.4171 - Accuracy: 0.2206 - F1: 0.1272
sub_15:Test (Best Model) - Loss: 1.5129 - Accuracy: 0.3088 - F1: 0.2090
sub_13:Test (Best Model) - Loss: 1.5078 - Accuracy: 0.3088 - F1: 0.1739
sub_14:Test (Best Model) - Loss: 1.3952 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.5863 - Accuracy: 0.2353 - F1: 0.0952
sub_13:Test (Best Model) - Loss: 1.4145 - Accuracy: 0.2941 - F1: 0.1922
sub_14:Test (Best Model) - Loss: 1.3814 - Accuracy: 0.2059 - F1: 0.0886
sub_14:Test (Best Model) - Loss: 1.4642 - Accuracy: 0.2500 - F1: 0.1000
sub_15:Test (Best Model) - Loss: 1.3729 - Accuracy: 0.2353 - F1: 0.1786
sub_13:Test (Best Model) - Loss: 1.5607 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3737 - Accuracy: 0.2206 - F1: 0.1503
sub_15:Test (Best Model) - Loss: 1.5061 - Accuracy: 0.2353 - F1: 0.0964
sub_14:Test (Best Model) - Loss: 1.4215 - Accuracy: 0.2500 - F1: 0.1261
sub_13:Test (Best Model) - Loss: 1.8016 - Accuracy: 0.2647 - F1: 0.1318
sub_15:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.1912 - F1: 0.1112
sub_14:Test (Best Model) - Loss: 1.3509 - Accuracy: 0.2647 - F1: 0.1125
sub_16:Test (Best Model) - Loss: 1.4124 - Accuracy: 0.2647 - F1: 0.1059
sub_18:Test (Best Model) - Loss: 1.5176 - Accuracy: 0.2609 - F1: 0.1059
sub_17:Test (Best Model) - Loss: 1.3723 - Accuracy: 0.2609 - F1: 0.1034
sub_16:Test (Best Model) - Loss: 1.3969 - Accuracy: 0.2059 - F1: 0.0854
sub_18:Test (Best Model) - Loss: 1.7251 - Accuracy: 0.2174 - F1: 0.0893
sub_17:Test (Best Model) - Loss: 1.3939 - Accuracy: 0.2029 - F1: 0.1194
sub_16:Test (Best Model) - Loss: 1.4106 - Accuracy: 0.3088 - F1: 0.2468
sub_18:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.2029 - F1: 0.1525
sub_17:Test (Best Model) - Loss: 1.3946 - Accuracy: 0.2319 - F1: 0.1763
sub_16:Test (Best Model) - Loss: 1.4222 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.2894 - Accuracy: 0.2754 - F1: 0.1359
sub_17:Test (Best Model) - Loss: 1.3997 - Accuracy: 0.2609 - F1: 0.1034
sub_17:Test (Best Model) - Loss: 1.3724 - Accuracy: 0.2029 - F1: 0.1966
sub_18:Test (Best Model) - Loss: 1.4526 - Accuracy: 0.1014 - F1: 0.0733
sub_17:Test (Best Model) - Loss: 1.3819 - Accuracy: 0.2754 - F1: 0.2203
sub_16:Test (Best Model) - Loss: 1.4243 - Accuracy: 0.2206 - F1: 0.1927
sub_18:Test (Best Model) - Loss: 1.3795 - Accuracy: 0.3088 - F1: 0.2644
sub_17:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2609 - F1: 0.1577
sub_16:Test (Best Model) - Loss: 1.3955 - Accuracy: 0.2794 - F1: 0.1905
sub_18:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.2353 - F1: 0.1401
sub_17:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2899 - F1: 0.1663
sub_16:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2206 - F1: 0.1432
sub_17:Test (Best Model) - Loss: 1.4001 - Accuracy: 0.1159 - F1: 0.0588
sub_18:Test (Best Model) - Loss: 1.3895 - Accuracy: 0.2794 - F1: 0.1392
sub_17:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2609 - F1: 0.1059
sub_16:Test (Best Model) - Loss: 1.3859 - Accuracy: 0.2647 - F1: 0.1488
sub_18:Test (Best Model) - Loss: 1.3799 - Accuracy: 0.1618 - F1: 0.1235
sub_17:Test (Best Model) - Loss: 1.3704 - Accuracy: 0.1912 - F1: 0.0915
sub_16:Test (Best Model) - Loss: 1.3959 - Accuracy: 0.3088 - F1: 0.2314
sub_18:Test (Best Model) - Loss: 1.4137 - Accuracy: 0.2647 - F1: 0.1059
sub_16:Test (Best Model) - Loss: 1.4187 - Accuracy: 0.2647 - F1: 0.1059
sub_17:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2500 - F1: 0.1104
sub_18:Test (Best Model) - Loss: 1.4957 - Accuracy: 0.2206 - F1: 0.1273
sub_16:Test (Best Model) - Loss: 1.3946 - Accuracy: 0.1912 - F1: 0.0855
sub_17:Test (Best Model) - Loss: 1.3726 - Accuracy: 0.3382 - F1: 0.2586
sub_18:Test (Best Model) - Loss: 1.4816 - Accuracy: 0.3088 - F1: 0.1779
sub_16:Test (Best Model) - Loss: 1.3975 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.4155 - Accuracy: 0.2647 - F1: 0.1059
sub_18:Test (Best Model) - Loss: 1.4349 - Accuracy: 0.3824 - F1: 0.2500
sub_16:Test (Best Model) - Loss: 1.4261 - Accuracy: 0.2059 - F1: 0.1288
sub_17:Test (Best Model) - Loss: 1.3807 - Accuracy: 0.2500 - F1: 0.1267
sub_18:Test (Best Model) - Loss: 1.4441 - Accuracy: 0.2647 - F1: 0.1059
sub_16:Test (Best Model) - Loss: 1.4116 - Accuracy: 0.2647 - F1: 0.1354
sub_18:Test (Best Model) - Loss: 1.4235 - Accuracy: 0.0588 - F1: 0.0345
sub_16:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.2353 - F1: 0.1213
sub_19:Test (Best Model) - Loss: 1.3884 - Accuracy: 0.2794 - F1: 0.1347
sub_20:Test (Best Model) - Loss: 1.3941 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.4119 - Accuracy: 0.2941 - F1: 0.1566
sub_19:Test (Best Model) - Loss: 1.4279 - Accuracy: 0.2206 - F1: 0.1125
sub_20:Test (Best Model) - Loss: 1.3687 - Accuracy: 0.2794 - F1: 0.1791
sub_21:Test (Best Model) - Loss: 1.4188 - Accuracy: 0.2059 - F1: 0.0854
sub_19:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2353 - F1: 0.1306
sub_20:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.2500 - F1: 0.1699
sub_21:Test (Best Model) - Loss: 1.3965 - Accuracy: 0.2353 - F1: 0.2215
sub_19:Test (Best Model) - Loss: 1.3698 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3352 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3681 - Accuracy: 0.3235 - F1: 0.2754
sub_19:Test (Best Model) - Loss: 1.3964 - Accuracy: 0.2647 - F1: 0.2506
sub_21:Test (Best Model) - Loss: 1.4735 - Accuracy: 0.2059 - F1: 0.1692
sub_20:Test (Best Model) - Loss: 1.3810 - Accuracy: 0.2647 - F1: 0.2581
sub_19:Test (Best Model) - Loss: 1.3778 - Accuracy: 0.2794 - F1: 0.2324
sub_21:Test (Best Model) - Loss: 1.3786 - Accuracy: 0.3088 - F1: 0.2304
sub_19:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2647 - F1: 0.1290
sub_19:Test (Best Model) - Loss: 1.4016 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.4195 - Accuracy: 0.2353 - F1: 0.1893
sub_20:Test (Best Model) - Loss: 1.3643 - Accuracy: 0.5294 - F1: 0.5259
sub_21:Test (Best Model) - Loss: 1.5146 - Accuracy: 0.2500 - F1: 0.1024
sub_20:Test (Best Model) - Loss: 1.4079 - Accuracy: 0.2794 - F1: 0.1437
sub_19:Test (Best Model) - Loss: 1.3814 - Accuracy: 0.2206 - F1: 0.1136
sub_21:Test (Best Model) - Loss: 1.3776 - Accuracy: 0.2206 - F1: 0.1713
sub_20:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.1912 - F1: 0.1523
sub_19:Test (Best Model) - Loss: 1.4088 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.4619 - Accuracy: 0.2647 - F1: 0.1059
sub_19:Test (Best Model) - Loss: 1.3587 - Accuracy: 0.2353 - F1: 0.1352
sub_20:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2500 - F1: 0.1012
sub_21:Test (Best Model) - Loss: 1.3564 - Accuracy: 0.2206 - F1: 0.1208
sub_19:Test (Best Model) - Loss: 1.4015 - Accuracy: 0.2353 - F1: 0.0964
sub_20:Test (Best Model) - Loss: 1.6038 - Accuracy: 0.2319 - F1: 0.1165
sub_21:Test (Best Model) - Loss: 1.3814 - Accuracy: 0.2941 - F1: 0.1574
sub_19:Test (Best Model) - Loss: 1.4010 - Accuracy: 0.2647 - F1: 0.1728
sub_20:Test (Best Model) - Loss: 1.2712 - Accuracy: 0.2754 - F1: 0.1359
sub_19:Test (Best Model) - Loss: 1.3964 - Accuracy: 0.2794 - F1: 0.1384
sub_21:Test (Best Model) - Loss: 1.3764 - Accuracy: 0.2059 - F1: 0.1322
sub_20:Test (Best Model) - Loss: 1.4991 - Accuracy: 0.1884 - F1: 0.1468
sub_21:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.2500 - F1: 0.1251
sub_19:Test (Best Model) - Loss: 1.3528 - Accuracy: 0.3088 - F1: 0.2250
sub_20:Test (Best Model) - Loss: 1.3956 - Accuracy: 0.2754 - F1: 0.1665
sub_21:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2500 - F1: 0.1164
sub_20:Test (Best Model) - Loss: 1.5207 - Accuracy: 0.2609 - F1: 0.1595
sub_24:Test (Best Model) - Loss: 1.3724 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.4433 - Accuracy: 0.2647 - F1: 0.1326
sub_23:Test (Best Model) - Loss: 1.3733 - Accuracy: 0.2609 - F1: 0.1034
sub_22:Test (Best Model) - Loss: 1.5905 - Accuracy: 0.2059 - F1: 0.0854
sub_24:Test (Best Model) - Loss: 1.4458 - Accuracy: 0.1912 - F1: 0.0823
sub_23:Test (Best Model) - Loss: 1.3977 - Accuracy: 0.2319 - F1: 0.1167
sub_24:Test (Best Model) - Loss: 1.3451 - Accuracy: 0.3676 - F1: 0.2686
sub_23:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2174 - F1: 0.1260
sub_22:Test (Best Model) - Loss: 1.3582 - Accuracy: 0.2059 - F1: 0.1352
sub_24:Test (Best Model) - Loss: 1.3831 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3987 - Accuracy: 0.2609 - F1: 0.1034
sub_22:Test (Best Model) - Loss: 1.3039 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.4000 - Accuracy: 0.3478 - F1: 0.2741
sub_24:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2647 - F1: 0.1442
sub_22:Test (Best Model) - Loss: 1.4146 - Accuracy: 0.2647 - F1: 0.2003
sub_23:Test (Best Model) - Loss: 1.6909 - Accuracy: 0.3382 - F1: 0.2994
sub_24:Test (Best Model) - Loss: 1.4326 - Accuracy: 0.2206 - F1: 0.1521
sub_22:Test (Best Model) - Loss: 1.3801 - Accuracy: 0.3043 - F1: 0.2938
sub_24:Test (Best Model) - Loss: 1.3922 - Accuracy: 0.2500 - F1: 0.1062
sub_23:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.2794 - F1: 0.1410
sub_24:Test (Best Model) - Loss: 1.3731 - Accuracy: 0.2500 - F1: 0.1037
sub_23:Test (Best Model) - Loss: 1.3928 - Accuracy: 0.2647 - F1: 0.1059
sub_22:Test (Best Model) - Loss: 1.3774 - Accuracy: 0.3478 - F1: 0.3564
sub_23:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.1912 - F1: 0.1133
sub_24:Test (Best Model) - Loss: 1.3983 - Accuracy: 0.3235 - F1: 0.2511
sub_23:Test (Best Model) - Loss: 1.3961 - Accuracy: 0.2647 - F1: 0.1059
sub_24:Test (Best Model) - Loss: 1.4490 - Accuracy: 0.2647 - F1: 0.1084
sub_22:Test (Best Model) - Loss: 1.3971 - Accuracy: 0.2754 - F1: 0.1410
sub_23:Test (Best Model) - Loss: 1.5145 - Accuracy: 0.2609 - F1: 0.1667
sub_24:Test (Best Model) - Loss: 1.4870 - Accuracy: 0.3676 - F1: 0.2495
sub_22:Test (Best Model) - Loss: 1.3760 - Accuracy: 0.2174 - F1: 0.1310
sub_23:Test (Best Model) - Loss: 1.3457 - Accuracy: 0.2464 - F1: 0.1190
sub_24:Test (Best Model) - Loss: 1.3577 - Accuracy: 0.3088 - F1: 0.1859
sub_22:Test (Best Model) - Loss: 1.3852 - Accuracy: 0.2899 - F1: 0.1647
sub_23:Test (Best Model) - Loss: 1.4072 - Accuracy: 0.2174 - F1: 0.1298
sub_24:Test (Best Model) - Loss: 1.5492 - Accuracy: 0.2206 - F1: 0.1371
sub_22:Test (Best Model) - Loss: 1.6169 - Accuracy: 0.1912 - F1: 0.0802
sub_23:Test (Best Model) - Loss: 1.3538 - Accuracy: 0.2174 - F1: 0.1454
sub_24:Test (Best Model) - Loss: 1.4086 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.4352 - Accuracy: 0.2647 - F1: 0.1059
sub_24:Test (Best Model) - Loss: 1.4277 - Accuracy: 0.2500 - F1: 0.1024
sub_23:Test (Best Model) - Loss: 1.4765 - Accuracy: 0.2609 - F1: 0.1649
sub_22:Test (Best Model) - Loss: 1.4636 - Accuracy: 0.3235 - F1: 0.2654
sub_22:Test (Best Model) - Loss: 1.4382 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.4313 - Accuracy: 0.2647 - F1: 0.1489
sub_27:Test (Best Model) - Loss: 1.3723 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 1.3913 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.4082 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3939 - Accuracy: 0.2029 - F1: 0.1194
sub_26:Test (Best Model) - Loss: 1.3915 - Accuracy: 0.2899 - F1: 0.2003
sub_25:Test (Best Model) - Loss: 1.3798 - Accuracy: 0.2464 - F1: 0.1392
sub_27:Test (Best Model) - Loss: 1.3946 - Accuracy: 0.2319 - F1: 0.1763
sub_25:Test (Best Model) - Loss: 1.3935 - Accuracy: 0.2754 - F1: 0.2250
sub_26:Test (Best Model) - Loss: 1.3738 - Accuracy: 0.2609 - F1: 0.1968
sub_27:Test (Best Model) - Loss: 1.3997 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.4254 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 1.3674 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3724 - Accuracy: 0.2029 - F1: 0.1966
sub_25:Test (Best Model) - Loss: 1.3772 - Accuracy: 0.1884 - F1: 0.1330
sub_26:Test (Best Model) - Loss: 1.3702 - Accuracy: 0.3333 - F1: 0.2936
sub_27:Test (Best Model) - Loss: 1.3819 - Accuracy: 0.2754 - F1: 0.2203
sub_27:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2609 - F1: 0.1577
sub_26:Test (Best Model) - Loss: 1.3660 - Accuracy: 0.3824 - F1: 0.3466
sub_27:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2899 - F1: 0.1663
sub_25:Test (Best Model) - Loss: 1.3652 - Accuracy: 0.3971 - F1: 0.3680
sub_26:Test (Best Model) - Loss: 1.3687 - Accuracy: 0.3382 - F1: 0.2397
sub_27:Test (Best Model) - Loss: 1.4001 - Accuracy: 0.1159 - F1: 0.0588
sub_25:Test (Best Model) - Loss: 1.3755 - Accuracy: 0.3088 - F1: 0.2477
sub_26:Test (Best Model) - Loss: 1.4189 - Accuracy: 0.2500 - F1: 0.1037
sub_27:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2609 - F1: 0.1059
sub_25:Test (Best Model) - Loss: 1.3769 - Accuracy: 0.2794 - F1: 0.1339
sub_26:Test (Best Model) - Loss: 1.3712 - Accuracy: 0.1324 - F1: 0.1069
sub_27:Test (Best Model) - Loss: 1.3704 - Accuracy: 0.1912 - F1: 0.0915
sub_25:Test (Best Model) - Loss: 1.3794 - Accuracy: 0.2059 - F1: 0.1680
sub_26:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2794 - F1: 0.1322
sub_27:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2500 - F1: 0.1104
sub_25:Test (Best Model) - Loss: 1.4021 - Accuracy: 0.2500 - F1: 0.1037
sub_26:Test (Best Model) - Loss: 1.6289 - Accuracy: 0.2206 - F1: 0.1124
sub_27:Test (Best Model) - Loss: 1.3726 - Accuracy: 0.3382 - F1: 0.2586
sub_25:Test (Best Model) - Loss: 1.5581 - Accuracy: 0.2206 - F1: 0.1126
sub_27:Test (Best Model) - Loss: 1.4155 - Accuracy: 0.2647 - F1: 0.1059
sub_26:Test (Best Model) - Loss: 1.3406 - Accuracy: 0.2353 - F1: 0.0976
sub_27:Test (Best Model) - Loss: 1.3807 - Accuracy: 0.2500 - F1: 0.1267
sub_25:Test (Best Model) - Loss: 1.3080 - Accuracy: 0.2500 - F1: 0.1000
sub_26:Test (Best Model) - Loss: 1.5008 - Accuracy: 0.2647 - F1: 0.2566
sub_26:Test (Best Model) - Loss: 1.4155 - Accuracy: 0.2059 - F1: 0.0959
sub_25:Test (Best Model) - Loss: 1.4691 - Accuracy: 0.3235 - F1: 0.3171
sub_26:Test (Best Model) - Loss: 1.4772 - Accuracy: 0.2059 - F1: 0.1215
sub_25:Test (Best Model) - Loss: 1.4279 - Accuracy: 0.2647 - F1: 0.1059
sub_25:Test (Best Model) - Loss: 1.4330 - Accuracy: 0.2353 - F1: 0.1143
sub_28:Test (Best Model) - Loss: 1.3891 - Accuracy: 0.2647 - F1: 0.1059
sub_29:Test (Best Model) - Loss: 1.4155 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3686 - Accuracy: 0.2059 - F1: 0.0854
sub_29:Test (Best Model) - Loss: 1.4313 - Accuracy: 0.2059 - F1: 0.0854
sub_28:Test (Best Model) - Loss: 1.3991 - Accuracy: 0.1765 - F1: 0.0845
sub_29:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2794 - F1: 0.2335
sub_28:Test (Best Model) - Loss: 1.3941 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.4367 - Accuracy: 0.2794 - F1: 0.1384
sub_28:Test (Best Model) - Loss: 1.3996 - Accuracy: 0.2206 - F1: 0.1376
sub_29:Test (Best Model) - Loss: 1.3767 - Accuracy: 0.2206 - F1: 0.1880
sub_28:Test (Best Model) - Loss: 1.4031 - Accuracy: 0.3235 - F1: 0.2528
sub_28:Test (Best Model) - Loss: 1.3957 - Accuracy: 0.2647 - F1: 0.1402
sub_29:Test (Best Model) - Loss: 1.3337 - Accuracy: 0.3824 - F1: 0.2939
sub_28:Test (Best Model) - Loss: 1.3787 - Accuracy: 0.2500 - F1: 0.1000
sub_28:Test (Best Model) - Loss: 1.3975 - Accuracy: 0.3235 - F1: 0.2659
sub_29:Test (Best Model) - Loss: 1.3661 - Accuracy: 0.3382 - F1: 0.2639
sub_28:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2500 - F1: 0.1037
sub_29:Test (Best Model) - Loss: 1.3579 - Accuracy: 0.2500 - F1: 0.1012
sub_28:Test (Best Model) - Loss: 2.3050 - Accuracy: 0.2941 - F1: 0.1919
sub_29:Test (Best Model) - Loss: 1.5593 - Accuracy: 0.3382 - F1: 0.2292
sub_28:Test (Best Model) - Loss: 1.3459 - Accuracy: 0.1765 - F1: 0.1009
sub_29:Test (Best Model) - Loss: 1.5167 - Accuracy: 0.2500 - F1: 0.1024
sub_28:Test (Best Model) - Loss: 2.1363 - Accuracy: 0.1912 - F1: 0.1217
sub_29:Test (Best Model) - Loss: 1.5120 - Accuracy: 0.2464 - F1: 0.1374
sub_28:Test (Best Model) - Loss: 1.8645 - Accuracy: 0.2647 - F1: 0.1071
sub_29:Test (Best Model) - Loss: 1.3444 - Accuracy: 0.2464 - F1: 0.0988
sub_28:Test (Best Model) - Loss: 1.9896 - Accuracy: 0.2647 - F1: 0.1321
sub_29:Test (Best Model) - Loss: 1.5374 - Accuracy: 0.2174 - F1: 0.1647
sub_29:Test (Best Model) - Loss: 1.3884 - Accuracy: 0.2464 - F1: 0.1049
sub_29:Test (Best Model) - Loss: 1.4662 - Accuracy: 0.1884 - F1: 0.1140

=== Summary Results ===

acc: 25.58 ± 1.11
F1: 15.12 ± 1.35
acc-in: 25.98 ± 1.53
F1-in: 15.29 ± 1.63
runing time: 1434.64 seconds
