lr: 0.001
sub_1:Test (Best Model) - Loss: 1.3740 - Accuracy: 0.2647 - F1: 0.2682
sub_1:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.2794 - F1: 0.2058
sub_1:Test (Best Model) - Loss: 1.3762 - Accuracy: 0.2647 - F1: 0.2276
sub_1:Test (Best Model) - Loss: 1.3774 - Accuracy: 0.1912 - F1: 0.1290
sub_1:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2059 - F1: 0.1225
sub_1:Test (Best Model) - Loss: 1.4422 - Accuracy: 0.2464 - F1: 0.1924
sub_1:Test (Best Model) - Loss: 1.4981 - Accuracy: 0.3188 - F1: 0.3041
sub_1:Test (Best Model) - Loss: 1.4574 - Accuracy: 0.2754 - F1: 0.2480
sub_1:Test (Best Model) - Loss: 1.5084 - Accuracy: 0.2029 - F1: 0.1765
sub_1:Test (Best Model) - Loss: 1.4358 - Accuracy: 0.2319 - F1: 0.1969
sub_1:Test (Best Model) - Loss: 1.3513 - Accuracy: 0.3382 - F1: 0.2597
sub_1:Test (Best Model) - Loss: 1.3491 - Accuracy: 0.3382 - F1: 0.3049
sub_1:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2059 - F1: 0.1347
sub_1:Test (Best Model) - Loss: 1.3516 - Accuracy: 0.3382 - F1: 0.2899
sub_1:Test (Best Model) - Loss: 1.3661 - Accuracy: 0.2647 - F1: 0.2095
sub_2:Test (Best Model) - Loss: 1.3535 - Accuracy: 0.3188 - F1: 0.2325
sub_2:Test (Best Model) - Loss: 1.3459 - Accuracy: 0.3188 - F1: 0.2696
sub_2:Test (Best Model) - Loss: 1.3515 - Accuracy: 0.3043 - F1: 0.2222
sub_2:Test (Best Model) - Loss: 1.3403 - Accuracy: 0.3188 - F1: 0.3332
sub_2:Test (Best Model) - Loss: 1.3584 - Accuracy: 0.2899 - F1: 0.1935
sub_2:Test (Best Model) - Loss: 1.3747 - Accuracy: 0.2794 - F1: 0.2444
sub_2:Test (Best Model) - Loss: 1.3502 - Accuracy: 0.3088 - F1: 0.1998
sub_2:Test (Best Model) - Loss: 1.3717 - Accuracy: 0.2794 - F1: 0.1965
sub_2:Test (Best Model) - Loss: 1.3656 - Accuracy: 0.2647 - F1: 0.2989
sub_2:Test (Best Model) - Loss: 1.3412 - Accuracy: 0.2941 - F1: 0.2748
sub_2:Test (Best Model) - Loss: 1.3999 - Accuracy: 0.3333 - F1: 0.2794
sub_2:Test (Best Model) - Loss: 1.3451 - Accuracy: 0.3333 - F1: 0.2986
sub_2:Test (Best Model) - Loss: 1.3768 - Accuracy: 0.2609 - F1: 0.2602
sub_2:Test (Best Model) - Loss: 1.3957 - Accuracy: 0.3333 - F1: 0.3262
sub_2:Test (Best Model) - Loss: 1.4845 - Accuracy: 0.2319 - F1: 0.2029
sub_3:Test (Best Model) - Loss: 1.4107 - Accuracy: 0.2794 - F1: 0.2281
sub_3:Test (Best Model) - Loss: 1.4245 - Accuracy: 0.2353 - F1: 0.2308
sub_3:Test (Best Model) - Loss: 1.3919 - Accuracy: 0.2941 - F1: 0.2386
sub_3:Test (Best Model) - Loss: 1.4158 - Accuracy: 0.2500 - F1: 0.2087
sub_3:Test (Best Model) - Loss: 1.4078 - Accuracy: 0.2647 - F1: 0.2166
sub_3:Test (Best Model) - Loss: 1.3677 - Accuracy: 0.2899 - F1: 0.2179
sub_3:Test (Best Model) - Loss: 1.4196 - Accuracy: 0.2754 - F1: 0.2695
sub_3:Test (Best Model) - Loss: 1.3755 - Accuracy: 0.2899 - F1: 0.2128
sub_3:Test (Best Model) - Loss: 1.3683 - Accuracy: 0.3478 - F1: 0.3000
sub_3:Test (Best Model) - Loss: 1.3798 - Accuracy: 0.3043 - F1: 0.2249
sub_3:Test (Best Model) - Loss: 1.4153 - Accuracy: 0.2174 - F1: 0.1839
sub_3:Test (Best Model) - Loss: 1.4461 - Accuracy: 0.1884 - F1: 0.2012
sub_3:Test (Best Model) - Loss: 1.4842 - Accuracy: 0.1594 - F1: 0.1225
sub_3:Test (Best Model) - Loss: 1.4281 - Accuracy: 0.2029 - F1: 0.1612
sub_3:Test (Best Model) - Loss: 1.4029 - Accuracy: 0.2029 - F1: 0.1658
sub_4:Test (Best Model) - Loss: 1.3785 - Accuracy: 0.3768 - F1: 0.2421
sub_4:Test (Best Model) - Loss: 1.3655 - Accuracy: 0.3333 - F1: 0.2227
sub_4:Test (Best Model) - Loss: 1.3694 - Accuracy: 0.3188 - F1: 0.2102
sub_4:Test (Best Model) - Loss: 1.3616 - Accuracy: 0.4058 - F1: 0.2669
sub_4:Test (Best Model) - Loss: 1.3544 - Accuracy: 0.3333 - F1: 0.2139
sub_4:Test (Best Model) - Loss: 1.3649 - Accuracy: 0.2754 - F1: 0.1935
sub_4:Test (Best Model) - Loss: 1.3462 - Accuracy: 0.3478 - F1: 0.3035
sub_4:Test (Best Model) - Loss: 1.3665 - Accuracy: 0.3623 - F1: 0.2809
sub_4:Test (Best Model) - Loss: 1.3500 - Accuracy: 0.3478 - F1: 0.2278
sub_4:Test (Best Model) - Loss: 1.3581 - Accuracy: 0.2754 - F1: 0.2214
sub_4:Test (Best Model) - Loss: 1.3544 - Accuracy: 0.3623 - F1: 0.3514
sub_4:Test (Best Model) - Loss: 1.3994 - Accuracy: 0.2319 - F1: 0.2204
sub_4:Test (Best Model) - Loss: 1.3819 - Accuracy: 0.2609 - F1: 0.2558
sub_4:Test (Best Model) - Loss: 1.3600 - Accuracy: 0.2899 - F1: 0.2682
sub_4:Test (Best Model) - Loss: 1.3614 - Accuracy: 0.3478 - F1: 0.3375
sub_5:Test (Best Model) - Loss: 1.3371 - Accuracy: 0.3235 - F1: 0.2324
sub_5:Test (Best Model) - Loss: 1.3046 - Accuracy: 0.4559 - F1: 0.4025
sub_5:Test (Best Model) - Loss: 1.3305 - Accuracy: 0.4265 - F1: 0.3541
sub_5:Test (Best Model) - Loss: 1.3170 - Accuracy: 0.5000 - F1: 0.4494
sub_5:Test (Best Model) - Loss: 1.3221 - Accuracy: 0.3676 - F1: 0.2742
sub_5:Test (Best Model) - Loss: 1.3445 - Accuracy: 0.2059 - F1: 0.1128
sub_5:Test (Best Model) - Loss: 1.3347 - Accuracy: 0.2794 - F1: 0.2125
sub_5:Test (Best Model) - Loss: 1.2793 - Accuracy: 0.2206 - F1: 0.1908
sub_5:Test (Best Model) - Loss: 1.3432 - Accuracy: 0.2206 - F1: 0.1579
sub_5:Test (Best Model) - Loss: 1.2843 - Accuracy: 0.3382 - F1: 0.2329
sub_5:Test (Best Model) - Loss: 1.3092 - Accuracy: 0.4118 - F1: 0.3188
sub_5:Test (Best Model) - Loss: 1.3659 - Accuracy: 0.3382 - F1: 0.3172
sub_5:Test (Best Model) - Loss: 1.3568 - Accuracy: 0.3382 - F1: 0.2854
sub_5:Test (Best Model) - Loss: 1.3383 - Accuracy: 0.3971 - F1: 0.3178
sub_5:Test (Best Model) - Loss: 1.3727 - Accuracy: 0.2941 - F1: 0.2753
sub_6:Test (Best Model) - Loss: 1.3481 - Accuracy: 0.3088 - F1: 0.2663
sub_6:Test (Best Model) - Loss: 1.3446 - Accuracy: 0.4412 - F1: 0.4198
sub_6:Test (Best Model) - Loss: 1.3688 - Accuracy: 0.3529 - F1: 0.3461
sub_6:Test (Best Model) - Loss: 1.3431 - Accuracy: 0.4265 - F1: 0.4006
sub_6:Test (Best Model) - Loss: 1.3251 - Accuracy: 0.3235 - F1: 0.2843
sub_6:Test (Best Model) - Loss: 1.3276 - Accuracy: 0.3623 - F1: 0.2371
sub_6:Test (Best Model) - Loss: 1.3735 - Accuracy: 0.2754 - F1: 0.1580
sub_6:Test (Best Model) - Loss: 1.3387 - Accuracy: 0.2464 - F1: 0.1181
sub_6:Test (Best Model) - Loss: 1.3831 - Accuracy: 0.2609 - F1: 0.1111
sub_6:Test (Best Model) - Loss: 1.3704 - Accuracy: 0.2899 - F1: 0.1617
sub_6:Test (Best Model) - Loss: 1.3543 - Accuracy: 0.3333 - F1: 0.2232
sub_6:Test (Best Model) - Loss: 1.3446 - Accuracy: 0.3333 - F1: 0.2975
sub_6:Test (Best Model) - Loss: 1.3805 - Accuracy: 0.2319 - F1: 0.1856
sub_6:Test (Best Model) - Loss: 1.3480 - Accuracy: 0.3333 - F1: 0.2222
sub_6:Test (Best Model) - Loss: 1.3604 - Accuracy: 0.3333 - F1: 0.2995
sub_7:Test (Best Model) - Loss: 1.3985 - Accuracy: 0.2353 - F1: 0.2164
sub_7:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.3088 - F1: 0.2907
sub_7:Test (Best Model) - Loss: 1.3911 - Accuracy: 0.2500 - F1: 0.2345
sub_7:Test (Best Model) - Loss: 1.4171 - Accuracy: 0.2353 - F1: 0.1979
sub_7:Test (Best Model) - Loss: 1.4040 - Accuracy: 0.2941 - F1: 0.2482
sub_7:Test (Best Model) - Loss: 1.3694 - Accuracy: 0.2941 - F1: 0.1845
sub_7:Test (Best Model) - Loss: 1.3721 - Accuracy: 0.3529 - F1: 0.2753
sub_7:Test (Best Model) - Loss: 1.3440 - Accuracy: 0.3824 - F1: 0.3300
sub_7:Test (Best Model) - Loss: 1.3745 - Accuracy: 0.3235 - F1: 0.2629
sub_7:Test (Best Model) - Loss: 1.3527 - Accuracy: 0.2794 - F1: 0.2071
sub_7:Test (Best Model) - Loss: 1.3958 - Accuracy: 0.1912 - F1: 0.1582
sub_7:Test (Best Model) - Loss: 1.3999 - Accuracy: 0.2059 - F1: 0.1387
sub_7:Test (Best Model) - Loss: 1.3984 - Accuracy: 0.2206 - F1: 0.1628
sub_7:Test (Best Model) - Loss: 1.3655 - Accuracy: 0.3088 - F1: 0.2715
sub_7:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2500 - F1: 0.1855
sub_8:Test (Best Model) - Loss: 1.3553 - Accuracy: 0.3529 - F1: 0.3206
sub_8:Test (Best Model) - Loss: 1.3464 - Accuracy: 0.3529 - F1: 0.3432
sub_8:Test (Best Model) - Loss: 1.3790 - Accuracy: 0.2647 - F1: 0.2323
sub_8:Test (Best Model) - Loss: 1.3577 - Accuracy: 0.3235 - F1: 0.2774
sub_8:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2794 - F1: 0.2510
sub_8:Test (Best Model) - Loss: 1.3775 - Accuracy: 0.3529 - F1: 0.2970
sub_8:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2500 - F1: 0.1729
sub_8:Test (Best Model) - Loss: 1.3960 - Accuracy: 0.2647 - F1: 0.1071
sub_8:Test (Best Model) - Loss: 1.3733 - Accuracy: 0.3235 - F1: 0.2078
sub_8:Test (Best Model) - Loss: 1.3940 - Accuracy: 0.3088 - F1: 0.2022
sub_8:Test (Best Model) - Loss: 1.3657 - Accuracy: 0.2353 - F1: 0.1520
sub_8:Test (Best Model) - Loss: 1.3562 - Accuracy: 0.2941 - F1: 0.1964
sub_8:Test (Best Model) - Loss: 1.3064 - Accuracy: 0.4706 - F1: 0.3917
sub_8:Test (Best Model) - Loss: 1.3211 - Accuracy: 0.3971 - F1: 0.3125
sub_8:Test (Best Model) - Loss: 1.3375 - Accuracy: 0.3235 - F1: 0.2514
sub_9:Test (Best Model) - Loss: 1.4224 - Accuracy: 0.2941 - F1: 0.1580
sub_9:Test (Best Model) - Loss: 1.4288 - Accuracy: 0.2206 - F1: 0.1832
sub_9:Test (Best Model) - Loss: 1.4871 - Accuracy: 0.2206 - F1: 0.1723
sub_9:Test (Best Model) - Loss: 1.4412 - Accuracy: 0.2206 - F1: 0.1945
sub_9:Test (Best Model) - Loss: 1.4433 - Accuracy: 0.2206 - F1: 0.1969
sub_9:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2794 - F1: 0.2431
sub_9:Test (Best Model) - Loss: 1.3777 - Accuracy: 0.3235 - F1: 0.2106
sub_9:Test (Best Model) - Loss: 1.3778 - Accuracy: 0.2500 - F1: 0.1684
sub_9:Test (Best Model) - Loss: 1.3649 - Accuracy: 0.3088 - F1: 0.2282
sub_9:Test (Best Model) - Loss: 1.3688 - Accuracy: 0.3382 - F1: 0.2535
sub_9:Test (Best Model) - Loss: 1.3752 - Accuracy: 0.2941 - F1: 0.1991
sub_9:Test (Best Model) - Loss: 1.3784 - Accuracy: 0.3529 - F1: 0.2548
sub_9:Test (Best Model) - Loss: 1.3704 - Accuracy: 0.3235 - F1: 0.2153
sub_9:Test (Best Model) - Loss: 1.3750 - Accuracy: 0.2941 - F1: 0.2348
sub_9:Test (Best Model) - Loss: 1.3742 - Accuracy: 0.3235 - F1: 0.2341
sub_10:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2059 - F1: 0.1662
sub_10:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.3235 - F1: 0.2729
sub_10:Test (Best Model) - Loss: 1.3762 - Accuracy: 0.2647 - F1: 0.2187
sub_10:Test (Best Model) - Loss: 1.4182 - Accuracy: 0.1912 - F1: 0.1569
sub_10:Test (Best Model) - Loss: 1.3700 - Accuracy: 0.3088 - F1: 0.1938
sub_10:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2794 - F1: 0.2240
sub_10:Test (Best Model) - Loss: 1.4084 - Accuracy: 0.2794 - F1: 0.1384
sub_10:Test (Best Model) - Loss: 1.3893 - Accuracy: 0.2647 - F1: 0.1264
sub_10:Test (Best Model) - Loss: 1.3893 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.4123 - Accuracy: 0.2647 - F1: 0.1111
sub_10:Test (Best Model) - Loss: 1.4023 - Accuracy: 0.2754 - F1: 0.2086
sub_10:Test (Best Model) - Loss: 1.4062 - Accuracy: 0.2464 - F1: 0.2063
sub_10:Test (Best Model) - Loss: 1.4155 - Accuracy: 0.2464 - F1: 0.1615
sub_10:Test (Best Model) - Loss: 1.4080 - Accuracy: 0.2174 - F1: 0.2119
sub_10:Test (Best Model) - Loss: 1.4139 - Accuracy: 0.2464 - F1: 0.1500
sub_11:Test (Best Model) - Loss: 1.3925 - Accuracy: 0.2899 - F1: 0.1753
sub_11:Test (Best Model) - Loss: 1.3561 - Accuracy: 0.3623 - F1: 0.3204
sub_11:Test (Best Model) - Loss: 1.3896 - Accuracy: 0.2319 - F1: 0.1835
sub_11:Test (Best Model) - Loss: 1.3747 - Accuracy: 0.2754 - F1: 0.1733
sub_11:Test (Best Model) - Loss: 1.3831 - Accuracy: 0.3333 - F1: 0.2200
sub_11:Test (Best Model) - Loss: 1.3744 - Accuracy: 0.2609 - F1: 0.2208
sub_11:Test (Best Model) - Loss: 1.3793 - Accuracy: 0.2899 - F1: 0.2893
sub_11:Test (Best Model) - Loss: 1.3726 - Accuracy: 0.3478 - F1: 0.3568
sub_11:Test (Best Model) - Loss: 1.3700 - Accuracy: 0.3333 - F1: 0.3126
sub_11:Test (Best Model) - Loss: 1.3610 - Accuracy: 0.3188 - F1: 0.2612
sub_11:Test (Best Model) - Loss: 1.3807 - Accuracy: 0.2464 - F1: 0.2048
sub_11:Test (Best Model) - Loss: 1.3658 - Accuracy: 0.3478 - F1: 0.3343
sub_11:Test (Best Model) - Loss: 1.3412 - Accuracy: 0.4203 - F1: 0.3608
sub_11:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.2464 - F1: 0.2113
sub_11:Test (Best Model) - Loss: 1.3754 - Accuracy: 0.2609 - F1: 0.1528
sub_12:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2647 - F1: 0.2603
sub_12:Test (Best Model) - Loss: 1.3925 - Accuracy: 0.2500 - F1: 0.2031
sub_12:Test (Best Model) - Loss: 1.3604 - Accuracy: 0.2941 - F1: 0.1944
sub_12:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2794 - F1: 0.2593
sub_12:Test (Best Model) - Loss: 1.3701 - Accuracy: 0.2059 - F1: 0.1405
sub_12:Test (Best Model) - Loss: 1.3797 - Accuracy: 0.2754 - F1: 0.2253
sub_12:Test (Best Model) - Loss: 1.4917 - Accuracy: 0.1739 - F1: 0.1435
sub_12:Test (Best Model) - Loss: 1.4331 - Accuracy: 0.1449 - F1: 0.1227
sub_12:Test (Best Model) - Loss: 1.4003 - Accuracy: 0.2319 - F1: 0.1983
sub_12:Test (Best Model) - Loss: 1.4175 - Accuracy: 0.2319 - F1: 0.1193
sub_12:Test (Best Model) - Loss: 1.3964 - Accuracy: 0.3088 - F1: 0.2104
sub_12:Test (Best Model) - Loss: 1.4230 - Accuracy: 0.2794 - F1: 0.2198
sub_12:Test (Best Model) - Loss: 1.3898 - Accuracy: 0.2353 - F1: 0.1373
sub_12:Test (Best Model) - Loss: 1.3949 - Accuracy: 0.2794 - F1: 0.2362
sub_12:Test (Best Model) - Loss: 1.3919 - Accuracy: 0.2794 - F1: 0.1623
sub_13:Test (Best Model) - Loss: 1.4139 - Accuracy: 0.3382 - F1: 0.2387
sub_13:Test (Best Model) - Loss: 1.4478 - Accuracy: 0.2647 - F1: 0.1299
sub_13:Test (Best Model) - Loss: 1.3740 - Accuracy: 0.2941 - F1: 0.1907
sub_13:Test (Best Model) - Loss: 1.4524 - Accuracy: 0.2206 - F1: 0.2018
sub_13:Test (Best Model) - Loss: 1.4189 - Accuracy: 0.2794 - F1: 0.1763
sub_13:Test (Best Model) - Loss: 1.4622 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.4319 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.4309 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.4265 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.4133 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.3469 - Accuracy: 0.3676 - F1: 0.2787
sub_13:Test (Best Model) - Loss: 1.3910 - Accuracy: 0.2206 - F1: 0.2091
sub_13:Test (Best Model) - Loss: 1.3689 - Accuracy: 0.2794 - F1: 0.2139
sub_13:Test (Best Model) - Loss: 1.3894 - Accuracy: 0.2353 - F1: 0.1687
sub_13:Test (Best Model) - Loss: 1.3931 - Accuracy: 0.2059 - F1: 0.1830
sub_14:Test (Best Model) - Loss: 1.3888 - Accuracy: 0.2941 - F1: 0.2411
sub_14:Test (Best Model) - Loss: 1.3714 - Accuracy: 0.3382 - F1: 0.2641
sub_14:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2794 - F1: 0.1716
sub_14:Test (Best Model) - Loss: 1.3747 - Accuracy: 0.2941 - F1: 0.2315
sub_14:Test (Best Model) - Loss: 1.3565 - Accuracy: 0.3382 - F1: 0.2146
sub_14:Test (Best Model) - Loss: 1.3588 - Accuracy: 0.2794 - F1: 0.1704
sub_14:Test (Best Model) - Loss: 1.3668 - Accuracy: 0.3382 - F1: 0.2736
sub_14:Test (Best Model) - Loss: 1.3634 - Accuracy: 0.2794 - F1: 0.2194
sub_14:Test (Best Model) - Loss: 1.3446 - Accuracy: 0.3971 - F1: 0.3129
sub_14:Test (Best Model) - Loss: 1.3750 - Accuracy: 0.3676 - F1: 0.2581
sub_14:Test (Best Model) - Loss: 1.3776 - Accuracy: 0.3676 - F1: 0.3048
sub_14:Test (Best Model) - Loss: 1.3710 - Accuracy: 0.2941 - F1: 0.2161
sub_14:Test (Best Model) - Loss: 1.3979 - Accuracy: 0.3088 - F1: 0.2163
sub_14:Test (Best Model) - Loss: 1.3802 - Accuracy: 0.3088 - F1: 0.2294
sub_14:Test (Best Model) - Loss: 1.3704 - Accuracy: 0.3676 - F1: 0.2872
sub_15:Test (Best Model) - Loss: 1.4010 - Accuracy: 0.3529 - F1: 0.3046
sub_15:Test (Best Model) - Loss: 1.4819 - Accuracy: 0.2206 - F1: 0.1624
sub_15:Test (Best Model) - Loss: 1.4185 - Accuracy: 0.2647 - F1: 0.2363
sub_15:Test (Best Model) - Loss: 1.3822 - Accuracy: 0.2647 - F1: 0.1732
sub_15:Test (Best Model) - Loss: 1.4382 - Accuracy: 0.2353 - F1: 0.2189
sub_15:Test (Best Model) - Loss: 1.4092 - Accuracy: 0.1912 - F1: 0.1234
sub_15:Test (Best Model) - Loss: 1.4102 - Accuracy: 0.3382 - F1: 0.2763
sub_15:Test (Best Model) - Loss: 1.4054 - Accuracy: 0.2206 - F1: 0.1744
sub_15:Test (Best Model) - Loss: 1.4102 - Accuracy: 0.3529 - F1: 0.2709
sub_15:Test (Best Model) - Loss: 1.4118 - Accuracy: 0.2794 - F1: 0.1950
sub_15:Test (Best Model) - Loss: 1.3955 - Accuracy: 0.2500 - F1: 0.1870
sub_15:Test (Best Model) - Loss: 1.3931 - Accuracy: 0.2353 - F1: 0.1563
sub_15:Test (Best Model) - Loss: 1.4184 - Accuracy: 0.2059 - F1: 0.1029
sub_15:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2206 - F1: 0.1445
sub_15:Test (Best Model) - Loss: 1.4290 - Accuracy: 0.1912 - F1: 0.1397
sub_16:Test (Best Model) - Loss: 1.3896 - Accuracy: 0.1618 - F1: 0.1382
sub_16:Test (Best Model) - Loss: 1.3703 - Accuracy: 0.3382 - F1: 0.2774
sub_16:Test (Best Model) - Loss: 1.3970 - Accuracy: 0.2941 - F1: 0.1960
sub_16:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2647 - F1: 0.1991
sub_16:Test (Best Model) - Loss: 1.3831 - Accuracy: 0.2794 - F1: 0.2180
sub_16:Test (Best Model) - Loss: 1.4398 - Accuracy: 0.2647 - F1: 0.1917
sub_16:Test (Best Model) - Loss: 1.3786 - Accuracy: 0.3235 - F1: 0.2587
sub_16:Test (Best Model) - Loss: 1.3628 - Accuracy: 0.2206 - F1: 0.1506
sub_16:Test (Best Model) - Loss: 1.4659 - Accuracy: 0.2941 - F1: 0.2462
sub_16:Test (Best Model) - Loss: 1.4369 - Accuracy: 0.2206 - F1: 0.2010
sub_16:Test (Best Model) - Loss: 1.3456 - Accuracy: 0.3529 - F1: 0.2326
sub_16:Test (Best Model) - Loss: 1.3885 - Accuracy: 0.2500 - F1: 0.2113
sub_16:Test (Best Model) - Loss: 1.3905 - Accuracy: 0.1912 - F1: 0.1388
sub_16:Test (Best Model) - Loss: 1.3694 - Accuracy: 0.3088 - F1: 0.2180
sub_16:Test (Best Model) - Loss: 1.4463 - Accuracy: 0.3088 - F1: 0.2158
sub_17:Test (Best Model) - Loss: 1.4163 - Accuracy: 0.2029 - F1: 0.1306
sub_17:Test (Best Model) - Loss: 1.4058 - Accuracy: 0.2174 - F1: 0.1138
sub_17:Test (Best Model) - Loss: 1.3936 - Accuracy: 0.2609 - F1: 0.1034
sub_17:Test (Best Model) - Loss: 1.3977 - Accuracy: 0.2464 - F1: 0.2053
sub_17:Test (Best Model) - Loss: 1.3904 - Accuracy: 0.2609 - F1: 0.1930
sub_17:Test (Best Model) - Loss: 1.4018 - Accuracy: 0.2899 - F1: 0.2187
sub_17:Test (Best Model) - Loss: 1.3925 - Accuracy: 0.2899 - F1: 0.1525
sub_17:Test (Best Model) - Loss: 1.3994 - Accuracy: 0.2464 - F1: 0.1598
sub_17:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2609 - F1: 0.1693
sub_17:Test (Best Model) - Loss: 1.3980 - Accuracy: 0.3188 - F1: 0.2652
sub_17:Test (Best Model) - Loss: 1.4182 - Accuracy: 0.2941 - F1: 0.2871
sub_17:Test (Best Model) - Loss: 1.4205 - Accuracy: 0.2059 - F1: 0.1876
sub_17:Test (Best Model) - Loss: 1.4037 - Accuracy: 0.3382 - F1: 0.2878
sub_17:Test (Best Model) - Loss: 1.3933 - Accuracy: 0.3382 - F1: 0.2843
sub_17:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2647 - F1: 0.2491
sub_18:Test (Best Model) - Loss: 1.3767 - Accuracy: 0.2609 - F1: 0.1967
sub_18:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2754 - F1: 0.2109
sub_18:Test (Best Model) - Loss: 1.4368 - Accuracy: 0.2609 - F1: 0.2133
sub_18:Test (Best Model) - Loss: 1.4153 - Accuracy: 0.2464 - F1: 0.2033
sub_18:Test (Best Model) - Loss: 1.3896 - Accuracy: 0.2754 - F1: 0.2317
sub_18:Test (Best Model) - Loss: 1.5351 - Accuracy: 0.2059 - F1: 0.1128
sub_18:Test (Best Model) - Loss: 1.4284 - Accuracy: 0.2059 - F1: 0.1329
sub_18:Test (Best Model) - Loss: 1.3734 - Accuracy: 0.2941 - F1: 0.2575
sub_18:Test (Best Model) - Loss: 1.4193 - Accuracy: 0.2206 - F1: 0.1362
sub_18:Test (Best Model) - Loss: 1.4661 - Accuracy: 0.1912 - F1: 0.1524
sub_18:Test (Best Model) - Loss: 1.3989 - Accuracy: 0.2353 - F1: 0.1739
sub_18:Test (Best Model) - Loss: 1.4416 - Accuracy: 0.2353 - F1: 0.1214
sub_18:Test (Best Model) - Loss: 1.3751 - Accuracy: 0.2647 - F1: 0.1931
sub_18:Test (Best Model) - Loss: 1.4156 - Accuracy: 0.2059 - F1: 0.1154
sub_18:Test (Best Model) - Loss: 1.4081 - Accuracy: 0.2206 - F1: 0.1509
sub_19:Test (Best Model) - Loss: 1.4146 - Accuracy: 0.1912 - F1: 0.1704
sub_19:Test (Best Model) - Loss: 1.4272 - Accuracy: 0.2206 - F1: 0.1898
sub_19:Test (Best Model) - Loss: 1.4173 - Accuracy: 0.1618 - F1: 0.1373
sub_19:Test (Best Model) - Loss: 1.4575 - Accuracy: 0.2206 - F1: 0.1971
sub_19:Test (Best Model) - Loss: 1.4148 - Accuracy: 0.3235 - F1: 0.2701
sub_19:Test (Best Model) - Loss: 1.3504 - Accuracy: 0.3676 - F1: 0.2946
sub_19:Test (Best Model) - Loss: 1.3728 - Accuracy: 0.3382 - F1: 0.2730
sub_19:Test (Best Model) - Loss: 1.3768 - Accuracy: 0.2500 - F1: 0.1484
sub_19:Test (Best Model) - Loss: 1.3581 - Accuracy: 0.2941 - F1: 0.2600
sub_19:Test (Best Model) - Loss: 1.3797 - Accuracy: 0.2353 - F1: 0.1544
sub_19:Test (Best Model) - Loss: 1.3510 - Accuracy: 0.3676 - F1: 0.3104
sub_19:Test (Best Model) - Loss: 1.3762 - Accuracy: 0.2647 - F1: 0.1392
sub_19:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2500 - F1: 0.1763
sub_19:Test (Best Model) - Loss: 1.3611 - Accuracy: 0.2794 - F1: 0.2373
sub_19:Test (Best Model) - Loss: 1.4116 - Accuracy: 0.2206 - F1: 0.1429
sub_20:Test (Best Model) - Loss: 1.4298 - Accuracy: 0.2941 - F1: 0.2394
sub_20:Test (Best Model) - Loss: 1.4177 - Accuracy: 0.2794 - F1: 0.2271
sub_20:Test (Best Model) - Loss: 1.4095 - Accuracy: 0.2206 - F1: 0.1215
sub_20:Test (Best Model) - Loss: 1.3980 - Accuracy: 0.2794 - F1: 0.2036
sub_20:Test (Best Model) - Loss: 1.4250 - Accuracy: 0.2353 - F1: 0.1590
sub_20:Test (Best Model) - Loss: 1.3659 - Accuracy: 0.3088 - F1: 0.2221
sub_20:Test (Best Model) - Loss: 1.3675 - Accuracy: 0.2794 - F1: 0.2034
sub_20:Test (Best Model) - Loss: 1.3591 - Accuracy: 0.3382 - F1: 0.2575
sub_20:Test (Best Model) - Loss: 1.3462 - Accuracy: 0.3088 - F1: 0.2412
sub_20:Test (Best Model) - Loss: 1.4219 - Accuracy: 0.3088 - F1: 0.2487
sub_20:Test (Best Model) - Loss: 1.3750 - Accuracy: 0.3478 - F1: 0.2922
sub_20:Test (Best Model) - Loss: 1.4020 - Accuracy: 0.2319 - F1: 0.1871
sub_20:Test (Best Model) - Loss: 1.3859 - Accuracy: 0.3188 - F1: 0.2836
sub_20:Test (Best Model) - Loss: 1.3523 - Accuracy: 0.3623 - F1: 0.3563
sub_20:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2899 - F1: 0.2625
sub_21:Test (Best Model) - Loss: 1.4229 - Accuracy: 0.2794 - F1: 0.2102
sub_21:Test (Best Model) - Loss: 1.4291 - Accuracy: 0.2500 - F1: 0.1716
sub_21:Test (Best Model) - Loss: 1.4290 - Accuracy: 0.1912 - F1: 0.1750
sub_21:Test (Best Model) - Loss: 1.4316 - Accuracy: 0.2353 - F1: 0.1911
sub_21:Test (Best Model) - Loss: 1.4311 - Accuracy: 0.2206 - F1: 0.1502
sub_21:Test (Best Model) - Loss: 1.4265 - Accuracy: 0.2206 - F1: 0.1439
sub_21:Test (Best Model) - Loss: 1.4049 - Accuracy: 0.3088 - F1: 0.2247
sub_21:Test (Best Model) - Loss: 1.5091 - Accuracy: 0.2059 - F1: 0.1548
sub_21:Test (Best Model) - Loss: 1.4605 - Accuracy: 0.2059 - F1: 0.1223
sub_21:Test (Best Model) - Loss: 1.4865 - Accuracy: 0.2059 - F1: 0.0972
sub_21:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.3088 - F1: 0.2521
sub_21:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.3382 - F1: 0.2661
sub_21:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.3235 - F1: 0.2476
sub_21:Test (Best Model) - Loss: 1.4103 - Accuracy: 0.2206 - F1: 0.1384
sub_21:Test (Best Model) - Loss: 1.3990 - Accuracy: 0.3235 - F1: 0.2456
sub_22:Test (Best Model) - Loss: 1.4142 - Accuracy: 0.2941 - F1: 0.2955
sub_22:Test (Best Model) - Loss: 1.4142 - Accuracy: 0.2206 - F1: 0.1960
sub_22:Test (Best Model) - Loss: 1.3910 - Accuracy: 0.2794 - F1: 0.2607
sub_22:Test (Best Model) - Loss: 1.3586 - Accuracy: 0.3676 - F1: 0.3106
sub_22:Test (Best Model) - Loss: 1.3542 - Accuracy: 0.2941 - F1: 0.2868
sub_22:Test (Best Model) - Loss: 1.4330 - Accuracy: 0.2464 - F1: 0.1565
sub_22:Test (Best Model) - Loss: 1.3463 - Accuracy: 0.2609 - F1: 0.2172
sub_22:Test (Best Model) - Loss: 1.3552 - Accuracy: 0.3043 - F1: 0.3021
sub_22:Test (Best Model) - Loss: 1.3511 - Accuracy: 0.3478 - F1: 0.2802
sub_22:Test (Best Model) - Loss: 1.3109 - Accuracy: 0.3478 - F1: 0.3040
sub_22:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.1912 - F1: 0.2168
sub_22:Test (Best Model) - Loss: 1.3540 - Accuracy: 0.2500 - F1: 0.2268
sub_22:Test (Best Model) - Loss: 1.3822 - Accuracy: 0.2206 - F1: 0.1892
sub_22:Test (Best Model) - Loss: 1.3566 - Accuracy: 0.2206 - F1: 0.1915
sub_22:Test (Best Model) - Loss: 1.3494 - Accuracy: 0.3382 - F1: 0.2898
sub_23:Test (Best Model) - Loss: 1.3797 - Accuracy: 0.3188 - F1: 0.2634
sub_23:Test (Best Model) - Loss: 1.3294 - Accuracy: 0.3188 - F1: 0.2852
sub_23:Test (Best Model) - Loss: 1.3280 - Accuracy: 0.3768 - F1: 0.3739
sub_23:Test (Best Model) - Loss: 1.2924 - Accuracy: 0.3623 - F1: 0.2781
sub_23:Test (Best Model) - Loss: 1.3746 - Accuracy: 0.3188 - F1: 0.2624
sub_23:Test (Best Model) - Loss: 1.3303 - Accuracy: 0.3382 - F1: 0.2479
sub_23:Test (Best Model) - Loss: 1.3475 - Accuracy: 0.2353 - F1: 0.1833
sub_23:Test (Best Model) - Loss: 1.3359 - Accuracy: 0.3382 - F1: 0.3119
sub_23:Test (Best Model) - Loss: 1.3193 - Accuracy: 0.3088 - F1: 0.2861
sub_23:Test (Best Model) - Loss: 1.3271 - Accuracy: 0.3235 - F1: 0.2445
sub_23:Test (Best Model) - Loss: 1.4416 - Accuracy: 0.2029 - F1: 0.1588
sub_23:Test (Best Model) - Loss: 1.4529 - Accuracy: 0.2464 - F1: 0.1939
sub_23:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2754 - F1: 0.2519
sub_23:Test (Best Model) - Loss: 1.4531 - Accuracy: 0.2174 - F1: 0.1830
sub_23:Test (Best Model) - Loss: 1.4685 - Accuracy: 0.2029 - F1: 0.1580
sub_24:Test (Best Model) - Loss: 1.3686 - Accuracy: 0.2794 - F1: 0.2412
sub_24:Test (Best Model) - Loss: 1.3756 - Accuracy: 0.3676 - F1: 0.3596
sub_24:Test (Best Model) - Loss: 1.3639 - Accuracy: 0.3235 - F1: 0.3227
sub_24:Test (Best Model) - Loss: 1.3511 - Accuracy: 0.2794 - F1: 0.2711
sub_24:Test (Best Model) - Loss: 1.3704 - Accuracy: 0.2500 - F1: 0.2163
sub_24:Test (Best Model) - Loss: 1.3333 - Accuracy: 0.3382 - F1: 0.2670
sub_24:Test (Best Model) - Loss: 1.4143 - Accuracy: 0.1912 - F1: 0.1205
sub_24:Test (Best Model) - Loss: 1.4125 - Accuracy: 0.2353 - F1: 0.1437
sub_24:Test (Best Model) - Loss: 1.3719 - Accuracy: 0.3088 - F1: 0.1731
sub_24:Test (Best Model) - Loss: 1.3804 - Accuracy: 0.2353 - F1: 0.1370
sub_24:Test (Best Model) - Loss: 1.4279 - Accuracy: 0.2500 - F1: 0.2390
sub_24:Test (Best Model) - Loss: 1.4215 - Accuracy: 0.2647 - F1: 0.2045
sub_24:Test (Best Model) - Loss: 1.4091 - Accuracy: 0.2353 - F1: 0.1582
sub_24:Test (Best Model) - Loss: 1.4151 - Accuracy: 0.2500 - F1: 0.2381
sub_24:Test (Best Model) - Loss: 1.3542 - Accuracy: 0.3382 - F1: 0.3298
sub_25:Test (Best Model) - Loss: 1.3791 - Accuracy: 0.2899 - F1: 0.2220
sub_25:Test (Best Model) - Loss: 1.3746 - Accuracy: 0.2754 - F1: 0.2160
sub_25:Test (Best Model) - Loss: 1.3674 - Accuracy: 0.2319 - F1: 0.2202
sub_25:Test (Best Model) - Loss: 1.3802 - Accuracy: 0.3043 - F1: 0.2537
sub_25:Test (Best Model) - Loss: 1.3443 - Accuracy: 0.3188 - F1: 0.2774
sub_25:Test (Best Model) - Loss: 1.3776 - Accuracy: 0.2794 - F1: 0.1851
sub_25:Test (Best Model) - Loss: 1.3801 - Accuracy: 0.2941 - F1: 0.1702
sub_25:Test (Best Model) - Loss: 1.3684 - Accuracy: 0.3382 - F1: 0.2345
sub_25:Test (Best Model) - Loss: 1.3519 - Accuracy: 0.4118 - F1: 0.3381
sub_25:Test (Best Model) - Loss: 1.3978 - Accuracy: 0.2941 - F1: 0.1891
sub_25:Test (Best Model) - Loss: 1.3968 - Accuracy: 0.2353 - F1: 0.1538
sub_25:Test (Best Model) - Loss: 1.3980 - Accuracy: 0.2647 - F1: 0.2286
sub_25:Test (Best Model) - Loss: 1.3943 - Accuracy: 0.2647 - F1: 0.2530
sub_25:Test (Best Model) - Loss: 1.4319 - Accuracy: 0.2059 - F1: 0.1910
sub_25:Test (Best Model) - Loss: 1.4173 - Accuracy: 0.2353 - F1: 0.1558
sub_26:Test (Best Model) - Loss: 1.3608 - Accuracy: 0.3768 - F1: 0.3253
sub_26:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2609 - F1: 0.2258
sub_26:Test (Best Model) - Loss: 1.3963 - Accuracy: 0.2319 - F1: 0.1554
sub_26:Test (Best Model) - Loss: 1.3803 - Accuracy: 0.2609 - F1: 0.2608
sub_26:Test (Best Model) - Loss: 1.4160 - Accuracy: 0.1884 - F1: 0.1721
sub_26:Test (Best Model) - Loss: 1.4156 - Accuracy: 0.2059 - F1: 0.1061
sub_26:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2500 - F1: 0.1349
sub_26:Test (Best Model) - Loss: 1.3755 - Accuracy: 0.3088 - F1: 0.2673
sub_26:Test (Best Model) - Loss: 1.3712 - Accuracy: 0.3382 - F1: 0.2900
sub_26:Test (Best Model) - Loss: 1.3762 - Accuracy: 0.3088 - F1: 0.2019
sub_26:Test (Best Model) - Loss: 1.3599 - Accuracy: 0.3235 - F1: 0.2640
sub_26:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.3529 - F1: 0.2338
sub_26:Test (Best Model) - Loss: 1.3690 - Accuracy: 0.3676 - F1: 0.2411
sub_26:Test (Best Model) - Loss: 1.3622 - Accuracy: 0.2647 - F1: 0.1754
sub_26:Test (Best Model) - Loss: 1.3741 - Accuracy: 0.3088 - F1: 0.2551
sub_27:Test (Best Model) - Loss: 1.4163 - Accuracy: 0.2029 - F1: 0.1306
sub_27:Test (Best Model) - Loss: 1.4058 - Accuracy: 0.2174 - F1: 0.1138
sub_27:Test (Best Model) - Loss: 1.3936 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3977 - Accuracy: 0.2464 - F1: 0.2053
sub_27:Test (Best Model) - Loss: 1.3904 - Accuracy: 0.2609 - F1: 0.1930
sub_27:Test (Best Model) - Loss: 1.4018 - Accuracy: 0.2899 - F1: 0.2187
sub_27:Test (Best Model) - Loss: 1.3925 - Accuracy: 0.2899 - F1: 0.1525
sub_27:Test (Best Model) - Loss: 1.3994 - Accuracy: 0.2464 - F1: 0.1598
sub_27:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2609 - F1: 0.1693
sub_27:Test (Best Model) - Loss: 1.3980 - Accuracy: 0.3188 - F1: 0.2652
sub_27:Test (Best Model) - Loss: 1.4182 - Accuracy: 0.2941 - F1: 0.2871
sub_27:Test (Best Model) - Loss: 1.4205 - Accuracy: 0.2059 - F1: 0.1876
sub_27:Test (Best Model) - Loss: 1.4037 - Accuracy: 0.3382 - F1: 0.2878
sub_27:Test (Best Model) - Loss: 1.3933 - Accuracy: 0.3382 - F1: 0.2843
sub_27:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2647 - F1: 0.2491
sub_28:Test (Best Model) - Loss: 1.3767 - Accuracy: 0.3088 - F1: 0.3075
sub_28:Test (Best Model) - Loss: 1.4130 - Accuracy: 0.2647 - F1: 0.1750
sub_28:Test (Best Model) - Loss: 1.3978 - Accuracy: 0.2059 - F1: 0.1738
sub_28:Test (Best Model) - Loss: 1.3913 - Accuracy: 0.2353 - F1: 0.2122
sub_28:Test (Best Model) - Loss: 1.3917 - Accuracy: 0.3088 - F1: 0.2532
sub_28:Test (Best Model) - Loss: 1.4116 - Accuracy: 0.2500 - F1: 0.1779
sub_28:Test (Best Model) - Loss: 1.3955 - Accuracy: 0.2647 - F1: 0.1306
sub_28:Test (Best Model) - Loss: 1.4069 - Accuracy: 0.2353 - F1: 0.1873
sub_28:Test (Best Model) - Loss: 1.4004 - Accuracy: 0.2206 - F1: 0.1688
sub_28:Test (Best Model) - Loss: 1.3932 - Accuracy: 0.2353 - F1: 0.1934
sub_28:Test (Best Model) - Loss: 1.4223 - Accuracy: 0.1029 - F1: 0.1051
sub_28:Test (Best Model) - Loss: 1.4424 - Accuracy: 0.0882 - F1: 0.0423
sub_28:Test (Best Model) - Loss: 1.3998 - Accuracy: 0.2500 - F1: 0.1591
sub_28:Test (Best Model) - Loss: 1.4194 - Accuracy: 0.1912 - F1: 0.1498
sub_28:Test (Best Model) - Loss: 1.4017 - Accuracy: 0.2059 - F1: 0.0864
sub_29:Test (Best Model) - Loss: 1.3804 - Accuracy: 0.1765 - F1: 0.1440
sub_29:Test (Best Model) - Loss: 1.4064 - Accuracy: 0.2500 - F1: 0.1868
sub_29:Test (Best Model) - Loss: 1.3765 - Accuracy: 0.2500 - F1: 0.1722
sub_29:Test (Best Model) - Loss: 1.3719 - Accuracy: 0.3382 - F1: 0.2745
sub_29:Test (Best Model) - Loss: 1.3794 - Accuracy: 0.3088 - F1: 0.1936
sub_29:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2941 - F1: 0.2281
sub_29:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.3088 - F1: 0.1965
sub_29:Test (Best Model) - Loss: 1.4056 - Accuracy: 0.2206 - F1: 0.1652
sub_29:Test (Best Model) - Loss: 1.3831 - Accuracy: 0.2647 - F1: 0.1797
sub_29:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2500 - F1: 0.1900
sub_29:Test (Best Model) - Loss: 1.4511 - Accuracy: 0.2319 - F1: 0.1929
sub_29:Test (Best Model) - Loss: 1.5377 - Accuracy: 0.3043 - F1: 0.2312
sub_29:Test (Best Model) - Loss: 1.4933 - Accuracy: 0.2754 - F1: 0.1667
sub_29:Test (Best Model) - Loss: 1.5281 - Accuracy: 0.1739 - F1: 0.1610
sub_29:Test (Best Model) - Loss: 1.6269 - Accuracy: 0.1449 - F1: 0.1293

=== Summary Results ===

acc: 27.95 ± 2.77
F1: 21.68 ± 2.93
acc-in: 38.68 ± 2.76
F1-in: 29.91 ± 3.47
