lr: 0.0001
sub_1:Test (Best Model) - Loss: 0.4906 - Accuracy: 0.7857 - F1: 0.7754
sub_2:Test (Best Model) - Loss: 0.6162 - Accuracy: 0.6667 - F1: 0.6250
sub_3:Test (Best Model) - Loss: 1.4252 - Accuracy: 0.8333 - F1: 0.8286
sub_1:Test (Best Model) - Loss: 0.5706 - Accuracy: 0.7976 - F1: 0.7890
sub_2:Test (Best Model) - Loss: 0.5256 - Accuracy: 0.7500 - F1: 0.7365
sub_3:Test (Best Model) - Loss: 1.8606 - Accuracy: 0.7500 - F1: 0.7333
sub_2:Test (Best Model) - Loss: 3.1329 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 0.3871 - Accuracy: 0.8690 - F1: 0.8668
sub_3:Test (Best Model) - Loss: 2.3516 - Accuracy: 0.8214 - F1: 0.8155
sub_2:Test (Best Model) - Loss: 0.5865 - Accuracy: 0.7024 - F1: 0.6783
sub_2:Test (Best Model) - Loss: 1.0231 - Accuracy: 0.5833 - F1: 0.4958
sub_1:Test (Best Model) - Loss: 0.5585 - Accuracy: 0.7619 - F1: 0.7569
sub_3:Test (Best Model) - Loss: 1.5319 - Accuracy: 0.7976 - F1: 0.7910
sub_2:Test (Best Model) - Loss: 0.2914 - Accuracy: 0.8929 - F1: 0.8916
sub_1:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.7143 - F1: 0.6889
sub_2:Test (Best Model) - Loss: 0.3287 - Accuracy: 0.9048 - F1: 0.9039
sub_3:Test (Best Model) - Loss: 2.2302 - Accuracy: 0.6548 - F1: 0.6080
sub_2:Test (Best Model) - Loss: 0.2298 - Accuracy: 0.9167 - F1: 0.9161
sub_1:Test (Best Model) - Loss: 0.5668 - Accuracy: 0.9048 - F1: 0.9039
sub_3:Test (Best Model) - Loss: 0.2258 - Accuracy: 0.8929 - F1: 0.8928
sub_2:Test (Best Model) - Loss: 0.3499 - Accuracy: 0.8929 - F1: 0.8916
sub_1:Test (Best Model) - Loss: 0.6252 - Accuracy: 0.8810 - F1: 0.8803
sub_3:Test (Best Model) - Loss: 0.2987 - Accuracy: 0.8810 - F1: 0.8809
sub_1:Test (Best Model) - Loss: 0.7369 - Accuracy: 0.8333 - F1: 0.8325
sub_2:Test (Best Model) - Loss: 0.4307 - Accuracy: 0.8929 - F1: 0.8916
sub_3:Test (Best Model) - Loss: 0.2411 - Accuracy: 0.9167 - F1: 0.9166
sub_2:Test (Best Model) - Loss: 2.1676 - Accuracy: 0.8333 - F1: 0.8318
sub_1:Test (Best Model) - Loss: 0.4954 - Accuracy: 0.9286 - F1: 0.9282
sub_3:Test (Best Model) - Loss: 0.2580 - Accuracy: 0.9048 - F1: 0.9048
sub_2:Test (Best Model) - Loss: 2.3153 - Accuracy: 0.7857 - F1: 0.7838
sub_3:Test (Best Model) - Loss: 0.2573 - Accuracy: 0.9048 - F1: 0.9048
sub_1:Test (Best Model) - Loss: 0.5066 - Accuracy: 0.8452 - F1: 0.8442
sub_3:Test (Best Model) - Loss: 0.5946 - Accuracy: 0.8690 - F1: 0.8675
sub_1:Test (Best Model) - Loss: 0.5580 - Accuracy: 0.8571 - F1: 0.8568
sub_2:Test (Best Model) - Loss: 1.8382 - Accuracy: 0.7976 - F1: 0.7969
sub_3:Test (Best Model) - Loss: 0.5595 - Accuracy: 0.8571 - F1: 0.8564
sub_2:Test (Best Model) - Loss: 5.2645 - Accuracy: 0.7857 - F1: 0.7812
sub_1:Test (Best Model) - Loss: 0.5092 - Accuracy: 0.9286 - F1: 0.9285
sub_3:Test (Best Model) - Loss: 1.0133 - Accuracy: 0.8571 - F1: 0.8542
sub_2:Test (Best Model) - Loss: 1.3420 - Accuracy: 0.8571 - F1: 0.8564
sub_1:Test (Best Model) - Loss: 0.7801 - Accuracy: 0.8571 - F1: 0.8571
sub_3:Test (Best Model) - Loss: 0.8378 - Accuracy: 0.8452 - F1: 0.8414
sub_3:Test (Best Model) - Loss: 0.6489 - Accuracy: 0.8929 - F1: 0.8921
sub_1:Test (Best Model) - Loss: 0.7883 - Accuracy: 0.7976 - F1: 0.7976
sub_1:Test (Best Model) - Loss: 0.5384 - Accuracy: 0.9286 - F1: 0.9286
sub_4:Test (Best Model) - Loss: 1.6916 - Accuracy: 0.8333 - F1: 0.8286
sub_5:Test (Best Model) - Loss: 3.0329 - Accuracy: 0.6071 - F1: 0.6066
sub_5:Test (Best Model) - Loss: 0.8604 - Accuracy: 0.6905 - F1: 0.6903
sub_4:Test (Best Model) - Loss: 1.5437 - Accuracy: 0.8214 - F1: 0.8155
sub_6:Test (Best Model) - Loss: 0.6377 - Accuracy: 0.8214 - F1: 0.8155
sub_5:Test (Best Model) - Loss: 1.4966 - Accuracy: 0.6310 - F1: 0.6284
sub_4:Test (Best Model) - Loss: 0.6465 - Accuracy: 0.8214 - F1: 0.8170
sub_6:Test (Best Model) - Loss: 0.2818 - Accuracy: 0.8690 - F1: 0.8675
sub_5:Test (Best Model) - Loss: 1.3398 - Accuracy: 0.6905 - F1: 0.6903
sub_6:Test (Best Model) - Loss: 0.3452 - Accuracy: 0.8095 - F1: 0.8041
sub_4:Test (Best Model) - Loss: 0.9983 - Accuracy: 0.8333 - F1: 0.8299
sub_6:Test (Best Model) - Loss: 0.3837 - Accuracy: 0.7619 - F1: 0.7614
sub_5:Test (Best Model) - Loss: 1.4312 - Accuracy: 0.6429 - F1: 0.6427
sub_4:Test (Best Model) - Loss: 0.9185 - Accuracy: 0.8095 - F1: 0.8024
sub_6:Test (Best Model) - Loss: 0.3850 - Accuracy: 0.7857 - F1: 0.7812
sub_5:Test (Best Model) - Loss: 1.0620 - Accuracy: 0.8095 - F1: 0.8094
sub_4:Test (Best Model) - Loss: 0.3737 - Accuracy: 0.8690 - F1: 0.8689
sub_5:Test (Best Model) - Loss: 0.8754 - Accuracy: 0.8810 - F1: 0.8809
sub_6:Test (Best Model) - Loss: 1.3020 - Accuracy: 0.8333 - F1: 0.8286
sub_4:Test (Best Model) - Loss: 0.3119 - Accuracy: 0.8571 - F1: 0.8571
sub_5:Test (Best Model) - Loss: 3.3733 - Accuracy: 0.8452 - F1: 0.8442
sub_4:Test (Best Model) - Loss: 0.3408 - Accuracy: 0.9048 - F1: 0.9047
sub_6:Test (Best Model) - Loss: 0.8250 - Accuracy: 0.8095 - F1: 0.8068
sub_5:Test (Best Model) - Loss: 0.3918 - Accuracy: 0.8452 - F1: 0.8442
sub_4:Test (Best Model) - Loss: 0.4343 - Accuracy: 0.8333 - F1: 0.8330
sub_6:Test (Best Model) - Loss: 0.9677 - Accuracy: 0.8333 - F1: 0.8332
sub_4:Test (Best Model) - Loss: 0.3230 - Accuracy: 0.8929 - F1: 0.8928
sub_5:Test (Best Model) - Loss: 0.3650 - Accuracy: 0.8690 - F1: 0.8686
sub_6:Test (Best Model) - Loss: 1.1406 - Accuracy: 0.8214 - F1: 0.8170
sub_4:Test (Best Model) - Loss: 1.2845 - Accuracy: 0.7857 - F1: 0.7846
sub_6:Test (Best Model) - Loss: 0.9416 - Accuracy: 0.8452 - F1: 0.8414
sub_5:Test (Best Model) - Loss: 0.3900 - Accuracy: 0.8095 - F1: 0.8078
sub_6:Test (Best Model) - Loss: 1.3118 - Accuracy: 0.5476 - F1: 0.5074
sub_4:Test (Best Model) - Loss: 1.2933 - Accuracy: 0.7976 - F1: 0.7941
sub_5:Test (Best Model) - Loss: 0.3939 - Accuracy: 0.8095 - F1: 0.8078
sub_6:Test (Best Model) - Loss: 2.1107 - Accuracy: 0.4881 - F1: 0.4540
sub_4:Test (Best Model) - Loss: 1.2249 - Accuracy: 0.7857 - F1: 0.7826
sub_6:Test (Best Model) - Loss: 1.4046 - Accuracy: 0.5476 - F1: 0.4997
sub_6:Test (Best Model) - Loss: 1.3366 - Accuracy: 0.5476 - F1: 0.5074
sub_5:Test (Best Model) - Loss: 0.7444 - Accuracy: 0.8095 - F1: 0.8091
sub_4:Test (Best Model) - Loss: 1.5777 - Accuracy: 0.7619 - F1: 0.7551
sub_6:Test (Best Model) - Loss: 0.9846 - Accuracy: 0.6190 - F1: 0.5910
sub_4:Test (Best Model) - Loss: 0.9142 - Accuracy: 0.7738 - F1: 0.7641
sub_5:Test (Best Model) - Loss: 0.6066 - Accuracy: 0.7738 - F1: 0.7712
sub_5:Test (Best Model) - Loss: 0.3469 - Accuracy: 0.8690 - F1: 0.8689
sub_9:Test (Best Model) - Loss: 0.9070 - Accuracy: 0.7143 - F1: 0.6932
sub_8:Test (Best Model) - Loss: 0.4172 - Accuracy: 0.9405 - F1: 0.9405
sub_9:Test (Best Model) - Loss: 2.0280 - Accuracy: 0.7024 - F1: 0.6783
sub_7:Test (Best Model) - Loss: 0.5973 - Accuracy: 0.8095 - F1: 0.8078
sub_8:Test (Best Model) - Loss: 0.4080 - Accuracy: 0.9167 - F1: 0.9166
sub_8:Test (Best Model) - Loss: 0.3838 - Accuracy: 0.9405 - F1: 0.9405
sub_9:Test (Best Model) - Loss: 1.7580 - Accuracy: 0.7143 - F1: 0.6889
sub_7:Test (Best Model) - Loss: 0.6406 - Accuracy: 0.7619 - F1: 0.7618
sub_8:Test (Best Model) - Loss: 1.3577 - Accuracy: 0.9167 - F1: 0.9166
sub_8:Test (Best Model) - Loss: 0.4379 - Accuracy: 0.9167 - F1: 0.9166
sub_8:Test (Best Model) - Loss: 0.0853 - Accuracy: 0.9762 - F1: 0.9762
sub_7:Test (Best Model) - Loss: 0.9594 - Accuracy: 0.7738 - F1: 0.7738
sub_9:Test (Best Model) - Loss: 2.3350 - Accuracy: 0.7262 - F1: 0.7040
sub_8:Test (Best Model) - Loss: 0.1081 - Accuracy: 0.9643 - F1: 0.9642
sub_7:Test (Best Model) - Loss: 0.6182 - Accuracy: 0.6786 - F1: 0.6763
sub_8:Test (Best Model) - Loss: 0.2119 - Accuracy: 0.9167 - F1: 0.9161
sub_9:Test (Best Model) - Loss: 2.6972 - Accuracy: 0.6667 - F1: 0.6250
sub_8:Test (Best Model) - Loss: 0.1341 - Accuracy: 0.9643 - F1: 0.9642
sub_9:Test (Best Model) - Loss: 0.8237 - Accuracy: 0.7976 - F1: 0.7927
sub_7:Test (Best Model) - Loss: 0.5583 - Accuracy: 0.8333 - F1: 0.8309
sub_8:Test (Best Model) - Loss: 0.1318 - Accuracy: 0.9524 - F1: 0.9523
sub_9:Test (Best Model) - Loss: 0.7746 - Accuracy: 0.7976 - F1: 0.7927
sub_8:Test (Best Model) - Loss: 1.1954 - Accuracy: 0.8095 - F1: 0.8024
sub_9:Test (Best Model) - Loss: 0.7291 - Accuracy: 0.7857 - F1: 0.7796
sub_8:Test (Best Model) - Loss: 0.5129 - Accuracy: 0.8452 - F1: 0.8425
sub_7:Test (Best Model) - Loss: 0.3555 - Accuracy: 0.8333 - F1: 0.8332
sub_9:Test (Best Model) - Loss: 0.7222 - Accuracy: 0.7976 - F1: 0.7927
sub_7:Test (Best Model) - Loss: 0.5074 - Accuracy: 0.7857 - F1: 0.7796
sub_8:Test (Best Model) - Loss: 0.4548 - Accuracy: 0.8810 - F1: 0.8792
sub_9:Test (Best Model) - Loss: 1.0642 - Accuracy: 0.7619 - F1: 0.7529
sub_8:Test (Best Model) - Loss: 0.4362 - Accuracy: 0.8571 - F1: 0.8551
sub_9:Test (Best Model) - Loss: 0.8471 - Accuracy: 0.6905 - F1: 0.6577
sub_8:Test (Best Model) - Loss: 0.3532 - Accuracy: 0.8690 - F1: 0.8668
sub_9:Test (Best Model) - Loss: 0.5580 - Accuracy: 0.7381 - F1: 0.7188
sub_7:Test (Best Model) - Loss: 0.4380 - Accuracy: 0.8095 - F1: 0.8056
sub_9:Test (Best Model) - Loss: 0.7115 - Accuracy: 0.7143 - F1: 0.6889
sub_7:Test (Best Model) - Loss: 0.2976 - Accuracy: 0.9167 - F1: 0.9164
sub_9:Test (Best Model) - Loss: 0.5075 - Accuracy: 0.7619 - F1: 0.7476
sub_7:Test (Best Model) - Loss: 0.3084 - Accuracy: 0.8690 - F1: 0.8681
sub_9:Test (Best Model) - Loss: 0.5144 - Accuracy: 0.7143 - F1: 0.6889
sub_7:Test (Best Model) - Loss: 0.8666 - Accuracy: 0.7024 - F1: 0.7020
sub_7:Test (Best Model) - Loss: 0.5966 - Accuracy: 0.8095 - F1: 0.8085
sub_7:Test (Best Model) - Loss: 0.7402 - Accuracy: 0.6786 - F1: 0.6785
sub_7:Test (Best Model) - Loss: 0.5160 - Accuracy: 0.7738 - F1: 0.7738
sub_7:Test (Best Model) - Loss: 0.5807 - Accuracy: 0.7024 - F1: 0.7020
sub_10:Test (Best Model) - Loss: 0.3002 - Accuracy: 0.9048 - F1: 0.9045
sub_12:Test (Best Model) - Loss: 0.3965 - Accuracy: 0.8571 - F1: 0.8542
sub_11:Test (Best Model) - Loss: 0.3598 - Accuracy: 0.9405 - F1: 0.9403
sub_10:Test (Best Model) - Loss: 0.2696 - Accuracy: 0.8929 - F1: 0.8925
sub_11:Test (Best Model) - Loss: 0.4710 - Accuracy: 0.9167 - F1: 0.9166
sub_12:Test (Best Model) - Loss: 0.7332 - Accuracy: 0.7976 - F1: 0.7910
sub_10:Test (Best Model) - Loss: 0.2779 - Accuracy: 0.9524 - F1: 0.9524
sub_11:Test (Best Model) - Loss: 0.4323 - Accuracy: 0.8929 - F1: 0.8925
sub_11:Test (Best Model) - Loss: 0.5638 - Accuracy: 0.9048 - F1: 0.9039
sub_12:Test (Best Model) - Loss: 0.6748 - Accuracy: 0.8452 - F1: 0.8414
sub_10:Test (Best Model) - Loss: 0.2144 - Accuracy: 0.9643 - F1: 0.9643
sub_11:Test (Best Model) - Loss: 0.7657 - Accuracy: 0.8690 - F1: 0.8668
sub_12:Test (Best Model) - Loss: 0.4759 - Accuracy: 0.8571 - F1: 0.8542
sub_11:Test (Best Model) - Loss: 0.0569 - Accuracy: 0.9881 - F1: 0.9881
sub_10:Test (Best Model) - Loss: 0.2548 - Accuracy: 0.9524 - F1: 0.9524
sub_12:Test (Best Model) - Loss: 0.3598 - Accuracy: 0.8810 - F1: 0.8792
sub_11:Test (Best Model) - Loss: 0.0416 - Accuracy: 0.9762 - F1: 0.9762
sub_10:Test (Best Model) - Loss: 0.2802 - Accuracy: 0.9286 - F1: 0.9286
sub_12:Test (Best Model) - Loss: 0.3549 - Accuracy: 0.7976 - F1: 0.7910
sub_11:Test (Best Model) - Loss: 0.0648 - Accuracy: 0.9643 - F1: 0.9643
sub_10:Test (Best Model) - Loss: 0.2108 - Accuracy: 0.9167 - F1: 0.9167
sub_11:Test (Best Model) - Loss: 0.0602 - Accuracy: 0.9762 - F1: 0.9762
sub_12:Test (Best Model) - Loss: 0.4698 - Accuracy: 0.7857 - F1: 0.7776
sub_11:Test (Best Model) - Loss: 0.0537 - Accuracy: 0.9762 - F1: 0.9762
sub_10:Test (Best Model) - Loss: 0.1725 - Accuracy: 0.9286 - F1: 0.9286
sub_12:Test (Best Model) - Loss: 0.5646 - Accuracy: 0.7857 - F1: 0.7796
sub_11:Test (Best Model) - Loss: 0.2131 - Accuracy: 0.9167 - F1: 0.9167
sub_10:Test (Best Model) - Loss: 0.2024 - Accuracy: 0.9286 - F1: 0.9285
sub_12:Test (Best Model) - Loss: 0.5509 - Accuracy: 0.7024 - F1: 0.6783
sub_10:Test (Best Model) - Loss: 0.2892 - Accuracy: 0.9167 - F1: 0.9167
sub_11:Test (Best Model) - Loss: 0.2253 - Accuracy: 0.9167 - F1: 0.9167
sub_10:Test (Best Model) - Loss: 0.3880 - Accuracy: 0.8214 - F1: 0.8170
sub_12:Test (Best Model) - Loss: 0.5325 - Accuracy: 0.7143 - F1: 0.6889
sub_10:Test (Best Model) - Loss: 0.6099 - Accuracy: 0.7262 - F1: 0.7079
sub_11:Test (Best Model) - Loss: 0.2739 - Accuracy: 0.9048 - F1: 0.9048
sub_12:Test (Best Model) - Loss: 0.6825 - Accuracy: 0.8929 - F1: 0.8925
sub_10:Test (Best Model) - Loss: 1.2037 - Accuracy: 0.6667 - F1: 0.6313
sub_11:Test (Best Model) - Loss: 0.2095 - Accuracy: 0.9405 - F1: 0.9405
sub_12:Test (Best Model) - Loss: 0.5415 - Accuracy: 0.9405 - F1: 0.9403
sub_10:Test (Best Model) - Loss: 1.0809 - Accuracy: 0.6905 - F1: 0.6577
sub_11:Test (Best Model) - Loss: 0.2023 - Accuracy: 0.9405 - F1: 0.9405
sub_10:Test (Best Model) - Loss: 0.4593 - Accuracy: 0.7976 - F1: 0.7941
sub_12:Test (Best Model) - Loss: 0.4377 - Accuracy: 0.9405 - F1: 0.9404
sub_12:Test (Best Model) - Loss: 0.5817 - Accuracy: 0.9167 - F1: 0.9164
sub_12:Test (Best Model) - Loss: 0.2511 - Accuracy: 0.9524 - F1: 0.9523
sub_13:Test (Best Model) - Loss: 0.2780 - Accuracy: 0.9048 - F1: 0.9045
sub_14:Test (Best Model) - Loss: 1.0558 - Accuracy: 0.8095 - F1: 0.8024
sub_14:Test (Best Model) - Loss: 1.1214 - Accuracy: 0.8214 - F1: 0.8155
sub_13:Test (Best Model) - Loss: 0.5121 - Accuracy: 0.8810 - F1: 0.8803
sub_14:Test (Best Model) - Loss: 1.5695 - Accuracy: 0.7976 - F1: 0.7910
sub_13:Test (Best Model) - Loss: 1.0927 - Accuracy: 0.8452 - F1: 0.8434
sub_13:Test (Best Model) - Loss: 0.4230 - Accuracy: 0.7976 - F1: 0.7910
sub_14:Test (Best Model) - Loss: 1.1484 - Accuracy: 0.8452 - F1: 0.8414
sub_13:Test (Best Model) - Loss: 0.4481 - Accuracy: 0.8333 - F1: 0.8299
sub_13:Test (Best Model) - Loss: 0.8285 - Accuracy: 0.9048 - F1: 0.9048
sub_14:Test (Best Model) - Loss: 2.1810 - Accuracy: 0.7738 - F1: 0.7616
sub_14:Test (Best Model) - Loss: 0.1626 - Accuracy: 0.9405 - F1: 0.9404
sub_13:Test (Best Model) - Loss: 0.2454 - Accuracy: 0.9405 - F1: 0.9403
sub_14:Test (Best Model) - Loss: 0.1077 - Accuracy: 0.9762 - F1: 0.9762
sub_13:Test (Best Model) - Loss: 0.3295 - Accuracy: 0.9167 - F1: 0.9167
sub_14:Test (Best Model) - Loss: 0.0962 - Accuracy: 0.9524 - F1: 0.9523
sub_13:Test (Best Model) - Loss: 0.2979 - Accuracy: 0.9524 - F1: 0.9524
sub_13:Test (Best Model) - Loss: 0.3905 - Accuracy: 0.8571 - F1: 0.8568
sub_14:Test (Best Model) - Loss: 0.1203 - Accuracy: 0.9405 - F1: 0.9405
sub_13:Test (Best Model) - Loss: 0.3969 - Accuracy: 0.9167 - F1: 0.9167
sub_14:Test (Best Model) - Loss: 0.1233 - Accuracy: 0.9881 - F1: 0.9881
sub_13:Test (Best Model) - Loss: 0.4224 - Accuracy: 0.9524 - F1: 0.9524
sub_14:Test (Best Model) - Loss: 1.4883 - Accuracy: 0.5833 - F1: 0.4958
sub_14:Test (Best Model) - Loss: 1.8951 - Accuracy: 0.5595 - F1: 0.4535
sub_13:Test (Best Model) - Loss: 1.4152 - Accuracy: 0.9405 - F1: 0.9405
sub_14:Test (Best Model) - Loss: 1.4618 - Accuracy: 0.5952 - F1: 0.5159
sub_13:Test (Best Model) - Loss: 0.8424 - Accuracy: 0.9167 - F1: 0.9166
sub_14:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.5714 - F1: 0.4750
sub_13:Test (Best Model) - Loss: 0.3220 - Accuracy: 0.9643 - F1: 0.9643
sub_14:Test (Best Model) - Loss: 1.9479 - Accuracy: 0.5595 - F1: 0.4535

=== Summary Results ===

acc: 82.70 ± 6.09
F1: 81.90 ± 6.66
acc-in: 90.33 ± 5.12
F1-in: 90.20 ± 5.25
runing time: 1084.71 seconds
