lr: 0.001
sub_5:Test (Best Model) - Loss: 1.4558 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 0.2342 - Accuracy: 0.9405 - F1: 0.9404
sub_3:Test (Best Model) - Loss: 0.8009 - Accuracy: 0.6667 - F1: 0.6250
sub_9:Test (Best Model) - Loss: 0.0410 - Accuracy: 0.9881 - F1: 0.9881
sub_7:Test (Best Model) - Loss: 1.7081 - Accuracy: 0.5238 - F1: 0.3842
sub_4:Test (Best Model) - Loss: 0.6069 - Accuracy: 0.9048 - F1: 0.9039
sub_8:Test (Best Model) - Loss: 0.0909 - Accuracy: 0.9643 - F1: 0.9642
sub_2:Test (Best Model) - Loss: 1.1658 - Accuracy: 0.7381 - F1: 0.7188
sub_6:Test (Best Model) - Loss: 3.1186 - Accuracy: 0.5476 - F1: 0.4312
sub_1:Test (Best Model) - Loss: 0.2877 - Accuracy: 0.9405 - F1: 0.9404
sub_10:Test (Best Model) - Loss: 0.1579 - Accuracy: 0.9524 - F1: 0.9524
sub_7:Test (Best Model) - Loss: 1.5193 - Accuracy: 0.5238 - F1: 0.3842
sub_5:Test (Best Model) - Loss: 0.9674 - Accuracy: 0.8214 - F1: 0.8170
sub_8:Test (Best Model) - Loss: 0.1144 - Accuracy: 0.9762 - F1: 0.9762
sub_3:Test (Best Model) - Loss: 1.1949 - Accuracy: 0.7381 - F1: 0.7188
sub_9:Test (Best Model) - Loss: 0.0051 - Accuracy: 1.0000 - F1: 1.0000
sub_4:Test (Best Model) - Loss: 0.4123 - Accuracy: 0.8571 - F1: 0.8568
sub_2:Test (Best Model) - Loss: 0.4941 - Accuracy: 0.9167 - F1: 0.9161
sub_3:Test (Best Model) - Loss: 0.2237 - Accuracy: 0.9405 - F1: 0.9403
sub_10:Test (Best Model) - Loss: 0.1822 - Accuracy: 0.9286 - F1: 0.9284
sub_6:Test (Best Model) - Loss: 1.6209 - Accuracy: 0.7619 - F1: 0.7476
sub_1:Test (Best Model) - Loss: 0.2462 - Accuracy: 0.9405 - F1: 0.9404
sub_9:Test (Best Model) - Loss: 0.0043 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.1475 - Accuracy: 0.9643 - F1: 0.9642
sub_4:Test (Best Model) - Loss: 0.2279 - Accuracy: 0.9405 - F1: 0.9403
sub_2:Test (Best Model) - Loss: 0.8999 - Accuracy: 0.8214 - F1: 0.8155
sub_7:Test (Best Model) - Loss: 3.6118 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.7668 - Accuracy: 0.7857 - F1: 0.7754
sub_10:Test (Best Model) - Loss: 0.2835 - Accuracy: 0.9167 - F1: 0.9164
sub_5:Test (Best Model) - Loss: 2.6600 - Accuracy: 0.6310 - F1: 0.5810
sub_8:Test (Best Model) - Loss: 0.2696 - Accuracy: 0.9524 - F1: 0.9524
sub_3:Test (Best Model) - Loss: 0.1880 - Accuracy: 0.9048 - F1: 0.9039
sub_9:Test (Best Model) - Loss: 0.1915 - Accuracy: 0.9286 - F1: 0.9282
sub_7:Test (Best Model) - Loss: 3.5116 - Accuracy: 0.5238 - F1: 0.3842
sub_8:Test (Best Model) - Loss: 0.0889 - Accuracy: 0.9643 - F1: 0.9643
sub_1:Test (Best Model) - Loss: 0.2008 - Accuracy: 0.9643 - F1: 0.9643
sub_6:Test (Best Model) - Loss: 0.3012 - Accuracy: 0.8929 - F1: 0.8916
sub_4:Test (Best Model) - Loss: 0.4651 - Accuracy: 0.8452 - F1: 0.8414
sub_2:Test (Best Model) - Loss: 1.2741 - Accuracy: 0.7262 - F1: 0.7040
sub_9:Test (Best Model) - Loss: 0.0002 - Accuracy: 1.0000 - F1: 1.0000
sub_10:Test (Best Model) - Loss: 0.4049 - Accuracy: 0.9048 - F1: 0.9045
sub_8:Test (Best Model) - Loss: 0.0162 - Accuracy: 0.9881 - F1: 0.9881
sub_3:Test (Best Model) - Loss: 0.0905 - Accuracy: 0.9762 - F1: 0.9762
sub_7:Test (Best Model) - Loss: 8.4624 - Accuracy: 0.5119 - F1: 0.3593
sub_1:Test (Best Model) - Loss: 0.0366 - Accuracy: 0.9881 - F1: 0.9881
sub_4:Test (Best Model) - Loss: 0.2612 - Accuracy: 0.8929 - F1: 0.8916
sub_5:Test (Best Model) - Loss: 0.7213 - Accuracy: 0.7976 - F1: 0.7910
sub_9:Test (Best Model) - Loss: 0.7733 - Accuracy: 0.7857 - F1: 0.7852
sub_6:Test (Best Model) - Loss: 0.8251 - Accuracy: 0.7738 - F1: 0.7616
sub_1:Test (Best Model) - Loss: 0.1720 - Accuracy: 0.9405 - F1: 0.9403
sub_10:Test (Best Model) - Loss: 0.3425 - Accuracy: 0.8810 - F1: 0.8799
sub_2:Test (Best Model) - Loss: 0.3283 - Accuracy: 0.8929 - F1: 0.8916
sub_3:Test (Best Model) - Loss: 0.3250 - Accuracy: 0.9167 - F1: 0.9167
sub_4:Test (Best Model) - Loss: 0.0490 - Accuracy: 0.9762 - F1: 0.9762
sub_8:Test (Best Model) - Loss: 0.0071 - Accuracy: 1.0000 - F1: 1.0000
sub_5:Test (Best Model) - Loss: 0.5496 - Accuracy: 0.8452 - F1: 0.8447
sub_9:Test (Best Model) - Loss: 0.8758 - Accuracy: 0.8690 - F1: 0.8668
sub_1:Test (Best Model) - Loss: 0.1369 - Accuracy: 0.9643 - F1: 0.9643
sub_6:Test (Best Model) - Loss: 0.8803 - Accuracy: 0.7619 - F1: 0.7476
sub_10:Test (Best Model) - Loss: 0.2309 - Accuracy: 0.9167 - F1: 0.9161
sub_7:Test (Best Model) - Loss: 0.6368 - Accuracy: 0.7619 - F1: 0.7476
sub_2:Test (Best Model) - Loss: 0.1410 - Accuracy: 0.9643 - F1: 0.9642
sub_8:Test (Best Model) - Loss: 0.0882 - Accuracy: 0.9881 - F1: 0.9881
sub_3:Test (Best Model) - Loss: 0.3009 - Accuracy: 0.8810 - F1: 0.8799
sub_1:Test (Best Model) - Loss: 2.0882 - Accuracy: 0.5119 - F1: 0.3593
sub_6:Test (Best Model) - Loss: 0.4365 - Accuracy: 0.7619 - F1: 0.7607
sub_9:Test (Best Model) - Loss: 0.8752 - Accuracy: 0.8333 - F1: 0.8286
sub_5:Test (Best Model) - Loss: 0.5062 - Accuracy: 0.8452 - F1: 0.8414
sub_4:Test (Best Model) - Loss: 0.1235 - Accuracy: 0.9643 - F1: 0.9642
sub_2:Test (Best Model) - Loss: 0.1033 - Accuracy: 0.9762 - F1: 0.9762
sub_8:Test (Best Model) - Loss: 0.0053 - Accuracy: 1.0000 - F1: 1.0000
sub_10:Test (Best Model) - Loss: 0.1281 - Accuracy: 0.9405 - F1: 0.9403
sub_5:Test (Best Model) - Loss: 0.7650 - Accuracy: 0.7738 - F1: 0.7664
sub_6:Test (Best Model) - Loss: 1.3023 - Accuracy: 0.7024 - F1: 0.6735
sub_9:Test (Best Model) - Loss: 2.0040 - Accuracy: 0.8095 - F1: 0.8024
sub_2:Test (Best Model) - Loss: 0.1010 - Accuracy: 0.9643 - F1: 0.9643
sub_7:Test (Best Model) - Loss: 0.3615 - Accuracy: 0.8452 - F1: 0.8425
sub_1:Test (Best Model) - Loss: 0.0514 - Accuracy: 0.9762 - F1: 0.9762
sub_4:Test (Best Model) - Loss: 0.4508 - Accuracy: 0.8929 - F1: 0.8916
sub_3:Test (Best Model) - Loss: 0.4108 - Accuracy: 0.8929 - F1: 0.8916
sub_8:Test (Best Model) - Loss: 0.0075 - Accuracy: 1.0000 - F1: 1.0000
sub_6:Test (Best Model) - Loss: 1.3163 - Accuracy: 0.6786 - F1: 0.6415
sub_1:Test (Best Model) - Loss: 0.0554 - Accuracy: 0.9881 - F1: 0.9881
sub_8:Test (Best Model) - Loss: 0.9264 - Accuracy: 0.8333 - F1: 0.8309
sub_2:Test (Best Model) - Loss: 0.3026 - Accuracy: 0.8810 - F1: 0.8792
sub_10:Test (Best Model) - Loss: 0.2095 - Accuracy: 0.9286 - F1: 0.9285
sub_9:Test (Best Model) - Loss: 0.3525 - Accuracy: 0.9405 - F1: 0.9403
sub_4:Test (Best Model) - Loss: 0.8187 - Accuracy: 0.8690 - F1: 0.8668
sub_7:Test (Best Model) - Loss: 0.1818 - Accuracy: 0.9286 - F1: 0.9284
sub_3:Test (Best Model) - Loss: 0.7685 - Accuracy: 0.7619 - F1: 0.7476
sub_5:Test (Best Model) - Loss: 0.8218 - Accuracy: 0.8571 - F1: 0.8551
sub_8:Test (Best Model) - Loss: 0.0986 - Accuracy: 0.9405 - F1: 0.9404
sub_1:Test (Best Model) - Loss: 0.4092 - Accuracy: 0.7976 - F1: 0.7890
sub_6:Test (Best Model) - Loss: 0.3545 - Accuracy: 0.8571 - F1: 0.8558
sub_3:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.6905 - F1: 0.6630
sub_10:Test (Best Model) - Loss: 0.2355 - Accuracy: 0.9286 - F1: 0.9282
sub_4:Test (Best Model) - Loss: 0.7564 - Accuracy: 0.9167 - F1: 0.9161
sub_9:Test (Best Model) - Loss: 0.0228 - Accuracy: 0.9881 - F1: 0.9881
sub_2:Test (Best Model) - Loss: 0.7232 - Accuracy: 0.8571 - F1: 0.8542
sub_5:Test (Best Model) - Loss: 0.4272 - Accuracy: 0.7857 - F1: 0.7776
sub_8:Test (Best Model) - Loss: 0.0969 - Accuracy: 0.9643 - F1: 0.9643
sub_4:Test (Best Model) - Loss: 1.0685 - Accuracy: 0.7024 - F1: 0.6735
sub_6:Test (Best Model) - Loss: 0.6015 - Accuracy: 0.8690 - F1: 0.8681
sub_10:Test (Best Model) - Loss: 0.5648 - Accuracy: 0.7738 - F1: 0.7616
sub_1:Test (Best Model) - Loss: 0.7167 - Accuracy: 0.7143 - F1: 0.6889
sub_7:Test (Best Model) - Loss: 0.4105 - Accuracy: 0.8333 - F1: 0.8318
sub_9:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.8452 - F1: 0.8414
sub_3:Test (Best Model) - Loss: 2.1318 - Accuracy: 0.6071 - F1: 0.6003
sub_8:Test (Best Model) - Loss: 0.3014 - Accuracy: 0.8810 - F1: 0.8799
sub_2:Test (Best Model) - Loss: 1.1562 - Accuracy: 0.7381 - F1: 0.7379
sub_10:Test (Best Model) - Loss: 1.0482 - Accuracy: 0.6429 - F1: 0.5906
sub_1:Test (Best Model) - Loss: 2.0575 - Accuracy: 0.5119 - F1: 0.3593
sub_3:Test (Best Model) - Loss: 0.7716 - Accuracy: 0.7857 - F1: 0.7776
sub_5:Test (Best Model) - Loss: 0.1865 - Accuracy: 0.9524 - F1: 0.9523
sub_9:Test (Best Model) - Loss: 0.4788 - Accuracy: 0.8095 - F1: 0.8024
sub_4:Test (Best Model) - Loss: 0.5245 - Accuracy: 0.8452 - F1: 0.8425
sub_10:Test (Best Model) - Loss: 0.3163 - Accuracy: 0.8690 - F1: 0.8668
sub_6:Test (Best Model) - Loss: 2.0773 - Accuracy: 0.6905 - F1: 0.6577
sub_2:Test (Best Model) - Loss: 0.0772 - Accuracy: 0.9643 - F1: 0.9642
sub_5:Test (Best Model) - Loss: 1.2000 - Accuracy: 0.5714 - F1: 0.4750
sub_9:Test (Best Model) - Loss: 0.0346 - Accuracy: 0.9881 - F1: 0.9881
sub_8:Test (Best Model) - Loss: 0.7010 - Accuracy: 0.8690 - F1: 0.8675
sub_1:Test (Best Model) - Loss: 0.0808 - Accuracy: 0.9524 - F1: 0.9524
sub_7:Test (Best Model) - Loss: 0.3332 - Accuracy: 0.8690 - F1: 0.8668
sub_4:Test (Best Model) - Loss: 0.4460 - Accuracy: 0.8571 - F1: 0.8551
sub_10:Test (Best Model) - Loss: 0.2200 - Accuracy: 0.9167 - F1: 0.9167
sub_5:Test (Best Model) - Loss: 4.6224 - Accuracy: 0.5595 - F1: 0.4901
sub_9:Test (Best Model) - Loss: 0.0130 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.2472 - Accuracy: 0.9167 - F1: 0.9161
sub_3:Test (Best Model) - Loss: 0.5961 - Accuracy: 0.8095 - F1: 0.8085
sub_4:Test (Best Model) - Loss: 0.2344 - Accuracy: 0.9048 - F1: 0.9043
sub_3:Test (Best Model) - Loss: 0.6515 - Accuracy: 0.6905 - F1: 0.6876
sub_6:Test (Best Model) - Loss: 1.6755 - Accuracy: 0.6190 - F1: 0.5962
sub_7:Test (Best Model) - Loss: 1.1751 - Accuracy: 0.7262 - F1: 0.7114
sub_5:Test (Best Model) - Loss: 1.8682 - Accuracy: 0.6905 - F1: 0.6630
sub_10:Test (Best Model) - Loss: 0.8786 - Accuracy: 0.7143 - F1: 0.6932
sub_2:Test (Best Model) - Loss: 0.0954 - Accuracy: 0.9762 - F1: 0.9762
sub_4:Test (Best Model) - Loss: 1.6470 - Accuracy: 0.6548 - F1: 0.6080
sub_3:Test (Best Model) - Loss: 1.0899 - Accuracy: 0.6667 - F1: 0.6466
sub_5:Test (Best Model) - Loss: 1.6497 - Accuracy: 0.6429 - F1: 0.5906
sub_7:Test (Best Model) - Loss: 0.3307 - Accuracy: 0.8571 - F1: 0.8558
sub_10:Test (Best Model) - Loss: 1.3994 - Accuracy: 0.6190 - F1: 0.5544
sub_6:Test (Best Model) - Loss: 0.6038 - Accuracy: 0.8214 - F1: 0.8202
sub_5:Test (Best Model) - Loss: 0.7201 - Accuracy: 0.6548 - F1: 0.6361
sub_2:Test (Best Model) - Loss: 0.3806 - Accuracy: 0.8810 - F1: 0.8809
sub_6:Test (Best Model) - Loss: 0.9980 - Accuracy: 0.7024 - F1: 0.6926
sub_7:Test (Best Model) - Loss: 0.1916 - Accuracy: 0.9286 - F1: 0.9285
sub_6:Test (Best Model) - Loss: 1.2739 - Accuracy: 0.7143 - F1: 0.6889
sub_7:Test (Best Model) - Loss: 0.8913 - Accuracy: 0.7262 - F1: 0.7079
sub_7:Test (Best Model) - Loss: 1.3539 - Accuracy: 0.7857 - F1: 0.7796
sub_13:Test (Best Model) - Loss: 0.2468 - Accuracy: 0.8810 - F1: 0.8792
sub_11:Test (Best Model) - Loss: 0.8428 - Accuracy: 0.8333 - F1: 0.8286
sub_14:Test (Best Model) - Loss: 0.8272 - Accuracy: 0.8214 - F1: 0.8208
sub_12:Test (Best Model) - Loss: 0.3314 - Accuracy: 0.8571 - F1: 0.8542
sub_12:Test (Best Model) - Loss: 0.4099 - Accuracy: 0.8333 - F1: 0.8286
sub_14:Test (Best Model) - Loss: 0.5700 - Accuracy: 0.8810 - F1: 0.8809
sub_13:Test (Best Model) - Loss: 0.5051 - Accuracy: 0.8571 - F1: 0.8542
sub_11:Test (Best Model) - Loss: 0.3314 - Accuracy: 0.9167 - F1: 0.9161
sub_11:Test (Best Model) - Loss: 0.1133 - Accuracy: 0.9762 - F1: 0.9762
sub_12:Test (Best Model) - Loss: 0.0404 - Accuracy: 0.9881 - F1: 0.9881
sub_11:Test (Best Model) - Loss: 0.7431 - Accuracy: 0.8333 - F1: 0.8309
sub_13:Test (Best Model) - Loss: 1.1774 - Accuracy: 0.5714 - F1: 0.4750
sub_14:Test (Best Model) - Loss: 0.4835 - Accuracy: 0.8690 - F1: 0.8668
sub_12:Test (Best Model) - Loss: 0.0378 - Accuracy: 0.9881 - F1: 0.9881
sub_11:Test (Best Model) - Loss: 0.4760 - Accuracy: 0.8452 - F1: 0.8414
sub_12:Test (Best Model) - Loss: 0.3178 - Accuracy: 0.9048 - F1: 0.9039
sub_13:Test (Best Model) - Loss: 0.3146 - Accuracy: 0.8452 - F1: 0.8414
sub_11:Test (Best Model) - Loss: 0.2313 - Accuracy: 0.9048 - F1: 0.9043
sub_14:Test (Best Model) - Loss: 0.1398 - Accuracy: 0.9643 - F1: 0.9642
sub_11:Test (Best Model) - Loss: 0.1436 - Accuracy: 0.9524 - F1: 0.9523
sub_13:Test (Best Model) - Loss: 0.8777 - Accuracy: 0.6786 - F1: 0.6473
sub_12:Test (Best Model) - Loss: 0.0918 - Accuracy: 0.9762 - F1: 0.9762
sub_14:Test (Best Model) - Loss: 0.6254 - Accuracy: 0.8929 - F1: 0.8921
sub_11:Test (Best Model) - Loss: 0.0706 - Accuracy: 0.9881 - F1: 0.9881
sub_12:Test (Best Model) - Loss: 0.3293 - Accuracy: 0.8690 - F1: 0.8668
sub_13:Test (Best Model) - Loss: 0.4044 - Accuracy: 0.8690 - F1: 0.8681
sub_14:Test (Best Model) - Loss: 0.0748 - Accuracy: 0.9762 - F1: 0.9762
sub_11:Test (Best Model) - Loss: 0.0931 - Accuracy: 0.9643 - F1: 0.9642
sub_12:Test (Best Model) - Loss: 0.3364 - Accuracy: 0.9048 - F1: 0.9043
sub_11:Test (Best Model) - Loss: 0.8617 - Accuracy: 0.8690 - F1: 0.8668
sub_14:Test (Best Model) - Loss: 0.0908 - Accuracy: 0.9643 - F1: 0.9642
sub_13:Test (Best Model) - Loss: 0.2854 - Accuracy: 0.8810 - F1: 0.8792
sub_12:Test (Best Model) - Loss: 0.2078 - Accuracy: 0.9524 - F1: 0.9523
sub_14:Test (Best Model) - Loss: 0.3012 - Accuracy: 0.8571 - F1: 0.8542
sub_11:Test (Best Model) - Loss: 0.2058 - Accuracy: 0.9167 - F1: 0.9164
sub_13:Test (Best Model) - Loss: 0.5474 - Accuracy: 0.6667 - F1: 0.6250
sub_12:Test (Best Model) - Loss: 0.7062 - Accuracy: 0.9286 - F1: 0.9282
sub_11:Test (Best Model) - Loss: 2.0385 - Accuracy: 0.5833 - F1: 0.4958
sub_13:Test (Best Model) - Loss: 0.2132 - Accuracy: 0.9405 - F1: 0.9403
sub_14:Test (Best Model) - Loss: 0.5977 - Accuracy: 0.8452 - F1: 0.8414
sub_12:Test (Best Model) - Loss: 2.4038 - Accuracy: 0.6667 - F1: 0.6250
sub_13:Test (Best Model) - Loss: 0.2382 - Accuracy: 0.9167 - F1: 0.9167
sub_14:Test (Best Model) - Loss: 0.3559 - Accuracy: 0.8810 - F1: 0.8792
sub_11:Test (Best Model) - Loss: 0.6395 - Accuracy: 0.7619 - F1: 0.7476
sub_12:Test (Best Model) - Loss: 0.2744 - Accuracy: 0.8929 - F1: 0.8927
sub_11:Test (Best Model) - Loss: 0.2321 - Accuracy: 0.8690 - F1: 0.8668
sub_12:Test (Best Model) - Loss: 0.3391 - Accuracy: 0.9167 - F1: 0.9167
sub_11:Test (Best Model) - Loss: 0.3747 - Accuracy: 0.8929 - F1: 0.8927
sub_13:Test (Best Model) - Loss: 1.0682 - Accuracy: 0.8333 - F1: 0.8286
sub_14:Test (Best Model) - Loss: 1.6837 - Accuracy: 0.6667 - F1: 0.6313
sub_13:Test (Best Model) - Loss: 0.1243 - Accuracy: 0.9643 - F1: 0.9642
sub_12:Test (Best Model) - Loss: 0.7056 - Accuracy: 0.8929 - F1: 0.8916
sub_14:Test (Best Model) - Loss: 1.5836 - Accuracy: 0.5952 - F1: 0.5159
sub_12:Test (Best Model) - Loss: 0.6475 - Accuracy: 0.7143 - F1: 0.7128
sub_13:Test (Best Model) - Loss: 0.5698 - Accuracy: 0.8333 - F1: 0.8318
sub_14:Test (Best Model) - Loss: 1.3514 - Accuracy: 0.6310 - F1: 0.5810
sub_13:Test (Best Model) - Loss: 0.6488 - Accuracy: 0.8690 - F1: 0.8681
sub_14:Test (Best Model) - Loss: 1.3941 - Accuracy: 0.5714 - F1: 0.4750
sub_13:Test (Best Model) - Loss: 0.1921 - Accuracy: 0.9167 - F1: 0.9161
sub_14:Test (Best Model) - Loss: 5.7822 - Accuracy: 0.5357 - F1: 0.4081

=== Summary Results ===

acc: 83.82 ± 6.62
F1: 82.35 ± 7.78
acc-in: 96.66 ± 2.63
F1-in: 96.55 ± 2.78
runing time: 1732.39 seconds
