lr: 0.0001
sub_1:Test (Best Model) - Loss: 0.5756 - Accuracy: 0.7143 - F1: 0.7128
sub_3:Test (Best Model) - Loss: 0.4027 - Accuracy: 0.7857 - F1: 0.7796
sub_2:Test (Best Model) - Loss: 0.2284 - Accuracy: 0.9405 - F1: 0.9405
sub_1:Test (Best Model) - Loss: 0.7315 - Accuracy: 0.7381 - F1: 0.7357
sub_3:Test (Best Model) - Loss: 0.3545 - Accuracy: 0.8333 - F1: 0.8325
sub_2:Test (Best Model) - Loss: 0.5877 - Accuracy: 0.6310 - F1: 0.5810
sub_1:Test (Best Model) - Loss: 0.7611 - Accuracy: 0.6548 - F1: 0.6434
sub_1:Test (Best Model) - Loss: 0.6208 - Accuracy: 0.7381 - F1: 0.7375
sub_2:Test (Best Model) - Loss: 0.1918 - Accuracy: 0.9167 - F1: 0.9166
sub_1:Test (Best Model) - Loss: 0.7440 - Accuracy: 0.7024 - F1: 0.6926
sub_3:Test (Best Model) - Loss: 0.4358 - Accuracy: 0.7976 - F1: 0.7974
sub_1:Test (Best Model) - Loss: 0.3523 - Accuracy: 0.8690 - F1: 0.8675
sub_2:Test (Best Model) - Loss: 0.2219 - Accuracy: 0.9405 - F1: 0.9404
sub_3:Test (Best Model) - Loss: 0.4054 - Accuracy: 0.7857 - F1: 0.7838
sub_2:Test (Best Model) - Loss: 0.7914 - Accuracy: 0.6071 - F1: 0.5452
sub_1:Test (Best Model) - Loss: 0.3065 - Accuracy: 0.9048 - F1: 0.9045
sub_2:Test (Best Model) - Loss: 0.2326 - Accuracy: 0.8929 - F1: 0.8925
sub_3:Test (Best Model) - Loss: 0.5230 - Accuracy: 0.7738 - F1: 0.7699
sub_1:Test (Best Model) - Loss: 0.3445 - Accuracy: 0.8452 - F1: 0.8425
sub_2:Test (Best Model) - Loss: 0.3155 - Accuracy: 0.9048 - F1: 0.9039
sub_1:Test (Best Model) - Loss: 0.3913 - Accuracy: 0.8452 - F1: 0.8425
sub_1:Test (Best Model) - Loss: 0.3578 - Accuracy: 0.8571 - F1: 0.8551
sub_2:Test (Best Model) - Loss: 0.2792 - Accuracy: 0.9286 - F1: 0.9282
sub_1:Test (Best Model) - Loss: 0.4330 - Accuracy: 0.8333 - F1: 0.8330
sub_3:Test (Best Model) - Loss: 0.4223 - Accuracy: 0.8095 - F1: 0.8068
sub_2:Test (Best Model) - Loss: 0.3588 - Accuracy: 0.8690 - F1: 0.8668
sub_1:Test (Best Model) - Loss: 0.3581 - Accuracy: 0.8452 - F1: 0.8452
sub_3:Test (Best Model) - Loss: 0.4766 - Accuracy: 0.7857 - F1: 0.7838
sub_2:Test (Best Model) - Loss: 0.3916 - Accuracy: 0.8810 - F1: 0.8799
sub_1:Test (Best Model) - Loss: 0.4129 - Accuracy: 0.8214 - F1: 0.8214
sub_3:Test (Best Model) - Loss: 0.4140 - Accuracy: 0.7976 - F1: 0.7974
sub_2:Test (Best Model) - Loss: 1.1060 - Accuracy: 0.7976 - F1: 0.7941
sub_1:Test (Best Model) - Loss: 0.4292 - Accuracy: 0.7738 - F1: 0.7738
sub_1:Test (Best Model) - Loss: 0.4014 - Accuracy: 0.8333 - F1: 0.8330
sub_3:Test (Best Model) - Loss: 0.5638 - Accuracy: 0.7619 - F1: 0.7597
sub_2:Test (Best Model) - Loss: 0.9102 - Accuracy: 0.7857 - F1: 0.7826
sub_3:Test (Best Model) - Loss: 0.3974 - Accuracy: 0.8095 - F1: 0.8085
sub_2:Test (Best Model) - Loss: 1.0680 - Accuracy: 0.7619 - F1: 0.7607
sub_3:Test (Best Model) - Loss: 0.5815 - Accuracy: 0.7381 - F1: 0.7343
sub_3:Test (Best Model) - Loss: 0.9104 - Accuracy: 0.6429 - F1: 0.6427
sub_2:Test (Best Model) - Loss: 1.1587 - Accuracy: 0.7143 - F1: 0.7143
sub_2:Test (Best Model) - Loss: 1.0382 - Accuracy: 0.7500 - F1: 0.7483
sub_3:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.6548 - F1: 0.6543
sub_3:Test (Best Model) - Loss: 0.6419 - Accuracy: 0.7500 - F1: 0.7500
sub_3:Test (Best Model) - Loss: 0.4700 - Accuracy: 0.8095 - F1: 0.8078
sub_6:Test (Best Model) - Loss: 0.4068 - Accuracy: 0.8571 - F1: 0.8568
sub_4:Test (Best Model) - Loss: 1.6760 - Accuracy: 0.7619 - F1: 0.7618
sub_6:Test (Best Model) - Loss: 0.3539 - Accuracy: 0.8333 - F1: 0.8332
sub_5:Test (Best Model) - Loss: 2.9617 - Accuracy: 0.5952 - F1: 0.5868
sub_4:Test (Best Model) - Loss: 2.4781 - Accuracy: 0.7381 - F1: 0.7375
sub_6:Test (Best Model) - Loss: 0.3848 - Accuracy: 0.8214 - F1: 0.8212
sub_4:Test (Best Model) - Loss: 1.2912 - Accuracy: 0.7262 - F1: 0.7252
sub_5:Test (Best Model) - Loss: 3.0254 - Accuracy: 0.5833 - F1: 0.5785
sub_6:Test (Best Model) - Loss: 0.4115 - Accuracy: 0.8214 - F1: 0.8208
sub_4:Test (Best Model) - Loss: 2.0292 - Accuracy: 0.8214 - F1: 0.8214
sub_5:Test (Best Model) - Loss: 4.4077 - Accuracy: 0.5476 - F1: 0.5347
sub_6:Test (Best Model) - Loss: 0.3792 - Accuracy: 0.8571 - F1: 0.8564
sub_4:Test (Best Model) - Loss: 1.8664 - Accuracy: 0.7976 - F1: 0.7976
sub_6:Test (Best Model) - Loss: 0.5784 - Accuracy: 0.7857 - F1: 0.7812
sub_5:Test (Best Model) - Loss: 1.8353 - Accuracy: 0.5357 - F1: 0.5276
sub_4:Test (Best Model) - Loss: 0.4504 - Accuracy: 0.7976 - F1: 0.7927
sub_6:Test (Best Model) - Loss: 0.5558 - Accuracy: 0.8095 - F1: 0.8085
sub_5:Test (Best Model) - Loss: 3.6493 - Accuracy: 0.5833 - F1: 0.5761
sub_6:Test (Best Model) - Loss: 0.7952 - Accuracy: 0.7381 - F1: 0.7282
sub_4:Test (Best Model) - Loss: 0.2524 - Accuracy: 0.9048 - F1: 0.9045
sub_5:Test (Best Model) - Loss: 0.3637 - Accuracy: 0.8452 - F1: 0.8442
sub_6:Test (Best Model) - Loss: 1.0980 - Accuracy: 0.7857 - F1: 0.7826
sub_4:Test (Best Model) - Loss: 0.4970 - Accuracy: 0.7857 - F1: 0.7776
sub_6:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.8214 - F1: 0.8208
sub_5:Test (Best Model) - Loss: 0.3760 - Accuracy: 0.8095 - F1: 0.8056
sub_4:Test (Best Model) - Loss: 0.6508 - Accuracy: 0.7738 - F1: 0.7712
sub_4:Test (Best Model) - Loss: 0.3929 - Accuracy: 0.8452 - F1: 0.8434
sub_5:Test (Best Model) - Loss: 0.3332 - Accuracy: 0.8571 - F1: 0.8551
sub_6:Test (Best Model) - Loss: 1.2327 - Accuracy: 0.7262 - F1: 0.7243
sub_4:Test (Best Model) - Loss: 0.5044 - Accuracy: 0.8333 - F1: 0.8325
sub_5:Test (Best Model) - Loss: 0.3534 - Accuracy: 0.9167 - F1: 0.9166
sub_6:Test (Best Model) - Loss: 1.4383 - Accuracy: 0.6667 - F1: 0.6619
sub_4:Test (Best Model) - Loss: 0.4518 - Accuracy: 0.8214 - F1: 0.8212
sub_5:Test (Best Model) - Loss: 0.3502 - Accuracy: 0.8929 - F1: 0.8927
sub_6:Test (Best Model) - Loss: 1.6122 - Accuracy: 0.6786 - F1: 0.6730
sub_4:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.8214 - F1: 0.8212
sub_5:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.6905 - F1: 0.6756
sub_4:Test (Best Model) - Loss: 0.4713 - Accuracy: 0.8214 - F1: 0.8194
sub_6:Test (Best Model) - Loss: 1.0964 - Accuracy: 0.7143 - F1: 0.7083
sub_5:Test (Best Model) - Loss: 0.5111 - Accuracy: 0.7262 - F1: 0.7145
sub_4:Test (Best Model) - Loss: 0.4873 - Accuracy: 0.7857 - F1: 0.7846
sub_6:Test (Best Model) - Loss: 0.6728 - Accuracy: 0.7738 - F1: 0.7722
sub_5:Test (Best Model) - Loss: 0.5914 - Accuracy: 0.7024 - F1: 0.6783
sub_5:Test (Best Model) - Loss: 0.6170 - Accuracy: 0.6905 - F1: 0.6630
sub_5:Test (Best Model) - Loss: 0.5085 - Accuracy: 0.7262 - F1: 0.7079
sub_8:Test (Best Model) - Loss: 0.3806 - Accuracy: 0.8452 - F1: 0.8434
sub_9:Test (Best Model) - Loss: 2.4525 - Accuracy: 0.6429 - F1: 0.5906
sub_7:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.7143 - F1: 0.7061
sub_8:Test (Best Model) - Loss: 0.1491 - Accuracy: 0.9405 - F1: 0.9404
sub_9:Test (Best Model) - Loss: 0.8564 - Accuracy: 0.7143 - F1: 0.6889
sub_7:Test (Best Model) - Loss: 0.9119 - Accuracy: 0.7500 - F1: 0.7418
sub_8:Test (Best Model) - Loss: 0.1100 - Accuracy: 0.9762 - F1: 0.9762
sub_7:Test (Best Model) - Loss: 0.5607 - Accuracy: 0.7738 - F1: 0.7699
sub_9:Test (Best Model) - Loss: 0.8504 - Accuracy: 0.7262 - F1: 0.7040
sub_8:Test (Best Model) - Loss: 0.2001 - Accuracy: 0.9405 - F1: 0.9404
sub_8:Test (Best Model) - Loss: 0.2268 - Accuracy: 0.9167 - F1: 0.9164
sub_7:Test (Best Model) - Loss: 0.9278 - Accuracy: 0.7143 - F1: 0.7035
sub_9:Test (Best Model) - Loss: 1.3123 - Accuracy: 0.6905 - F1: 0.6577
sub_7:Test (Best Model) - Loss: 1.0683 - Accuracy: 0.7143 - F1: 0.7005
sub_8:Test (Best Model) - Loss: 0.1835 - Accuracy: 0.9286 - F1: 0.9282
sub_9:Test (Best Model) - Loss: 1.3952 - Accuracy: 0.6786 - F1: 0.6415
sub_7:Test (Best Model) - Loss: 0.4067 - Accuracy: 0.8214 - F1: 0.8202
sub_9:Test (Best Model) - Loss: 0.5686 - Accuracy: 0.7024 - F1: 0.7023
sub_8:Test (Best Model) - Loss: 0.0688 - Accuracy: 0.9762 - F1: 0.9762
sub_7:Test (Best Model) - Loss: 0.3210 - Accuracy: 0.8333 - F1: 0.8332
sub_9:Test (Best Model) - Loss: 0.4734 - Accuracy: 0.8214 - F1: 0.8212
sub_8:Test (Best Model) - Loss: 0.1425 - Accuracy: 0.9167 - F1: 0.9161
sub_7:Test (Best Model) - Loss: 0.2753 - Accuracy: 0.8690 - F1: 0.8690
sub_9:Test (Best Model) - Loss: 0.9892 - Accuracy: 0.6190 - F1: 0.6156
sub_8:Test (Best Model) - Loss: 0.1107 - Accuracy: 0.9286 - F1: 0.9282
sub_7:Test (Best Model) - Loss: 0.2545 - Accuracy: 0.9048 - F1: 0.9048
sub_8:Test (Best Model) - Loss: 0.1155 - Accuracy: 0.9286 - F1: 0.9282
sub_9:Test (Best Model) - Loss: 1.1202 - Accuracy: 0.6310 - F1: 0.6219
sub_7:Test (Best Model) - Loss: 0.2725 - Accuracy: 0.9048 - F1: 0.9047
sub_8:Test (Best Model) - Loss: 1.0142 - Accuracy: 0.7024 - F1: 0.6783
sub_9:Test (Best Model) - Loss: 0.7171 - Accuracy: 0.6429 - F1: 0.6427
sub_7:Test (Best Model) - Loss: 1.0802 - Accuracy: 0.6667 - F1: 0.6571
sub_8:Test (Best Model) - Loss: 0.9674 - Accuracy: 0.8690 - F1: 0.8668
sub_9:Test (Best Model) - Loss: 1.0050 - Accuracy: 0.5833 - F1: 0.5353
sub_8:Test (Best Model) - Loss: 0.6622 - Accuracy: 0.7857 - F1: 0.7776
sub_7:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.7024 - F1: 0.6926
sub_9:Test (Best Model) - Loss: 0.8675 - Accuracy: 0.7381 - F1: 0.7282
sub_8:Test (Best Model) - Loss: 0.5662 - Accuracy: 0.8452 - F1: 0.8425
sub_7:Test (Best Model) - Loss: 0.7664 - Accuracy: 0.7024 - F1: 0.6951
sub_8:Test (Best Model) - Loss: 0.5006 - Accuracy: 0.8333 - F1: 0.8299
sub_9:Test (Best Model) - Loss: 1.0544 - Accuracy: 0.6905 - F1: 0.6816
sub_7:Test (Best Model) - Loss: 0.6009 - Accuracy: 0.7143 - F1: 0.6971
sub_9:Test (Best Model) - Loss: 0.6075 - Accuracy: 0.7857 - F1: 0.7826
sub_7:Test (Best Model) - Loss: 0.7497 - Accuracy: 0.7024 - F1: 0.6897
sub_9:Test (Best Model) - Loss: 0.8503 - Accuracy: 0.5476 - F1: 0.4458
sub_10:Test (Best Model) - Loss: 0.4695 - Accuracy: 0.7381 - F1: 0.7282
sub_12:Test (Best Model) - Loss: 0.5197 - Accuracy: 0.7619 - F1: 0.7619
sub_11:Test (Best Model) - Loss: 1.0681 - Accuracy: 0.8095 - F1: 0.8068
sub_12:Test (Best Model) - Loss: 0.3933 - Accuracy: 0.8333 - F1: 0.8333
sub_10:Test (Best Model) - Loss: 0.4627 - Accuracy: 0.9048 - F1: 0.9043
sub_12:Test (Best Model) - Loss: 0.3535 - Accuracy: 0.8452 - F1: 0.8452
sub_11:Test (Best Model) - Loss: 1.2410 - Accuracy: 0.8214 - F1: 0.8214
sub_10:Test (Best Model) - Loss: 0.2440 - Accuracy: 0.9167 - F1: 0.9167
sub_12:Test (Best Model) - Loss: 0.2085 - Accuracy: 0.9167 - F1: 0.9166
sub_10:Test (Best Model) - Loss: 0.3259 - Accuracy: 0.8810 - F1: 0.8809
sub_11:Test (Best Model) - Loss: 0.7223 - Accuracy: 0.8571 - F1: 0.8558
sub_10:Test (Best Model) - Loss: 0.4247 - Accuracy: 0.7500 - F1: 0.7393
sub_12:Test (Best Model) - Loss: 0.2895 - Accuracy: 0.8810 - F1: 0.8809
sub_11:Test (Best Model) - Loss: 0.8234 - Accuracy: 0.8452 - F1: 0.8434
sub_10:Test (Best Model) - Loss: 0.6065 - Accuracy: 0.8214 - F1: 0.8183
sub_12:Test (Best Model) - Loss: 0.1122 - Accuracy: 0.9405 - F1: 0.9404
sub_11:Test (Best Model) - Loss: 1.0479 - Accuracy: 0.7976 - F1: 0.7927
sub_12:Test (Best Model) - Loss: 0.1938 - Accuracy: 0.9286 - F1: 0.9284
sub_10:Test (Best Model) - Loss: 0.3057 - Accuracy: 0.8452 - F1: 0.8434
sub_11:Test (Best Model) - Loss: 0.3519 - Accuracy: 0.8452 - F1: 0.8450
sub_12:Test (Best Model) - Loss: 0.1411 - Accuracy: 0.9286 - F1: 0.9284
sub_11:Test (Best Model) - Loss: 0.2861 - Accuracy: 0.8929 - F1: 0.8921
sub_12:Test (Best Model) - Loss: 0.2293 - Accuracy: 0.8929 - F1: 0.8921
sub_11:Test (Best Model) - Loss: 0.2791 - Accuracy: 0.8810 - F1: 0.8799
sub_10:Test (Best Model) - Loss: 0.1564 - Accuracy: 0.9286 - F1: 0.9284
sub_10:Test (Best Model) - Loss: 0.3493 - Accuracy: 0.8571 - F1: 0.8558
sub_11:Test (Best Model) - Loss: 0.3078 - Accuracy: 0.8690 - F1: 0.8690
sub_12:Test (Best Model) - Loss: 0.1685 - Accuracy: 0.9405 - F1: 0.9403
sub_10:Test (Best Model) - Loss: 0.4001 - Accuracy: 0.7976 - F1: 0.7941
sub_12:Test (Best Model) - Loss: 0.4900 - Accuracy: 0.7857 - F1: 0.7826
sub_11:Test (Best Model) - Loss: 0.3193 - Accuracy: 0.8810 - F1: 0.8809
sub_12:Test (Best Model) - Loss: 1.8328 - Accuracy: 0.6310 - F1: 0.6010
sub_11:Test (Best Model) - Loss: 0.4118 - Accuracy: 0.7619 - F1: 0.7614
sub_10:Test (Best Model) - Loss: 0.5793 - Accuracy: 0.6786 - F1: 0.6785
sub_11:Test (Best Model) - Loss: 0.7283 - Accuracy: 0.5476 - F1: 0.5466
sub_12:Test (Best Model) - Loss: 1.1192 - Accuracy: 0.7500 - F1: 0.7471
sub_10:Test (Best Model) - Loss: 0.8255 - Accuracy: 0.6429 - F1: 0.5906
sub_11:Test (Best Model) - Loss: 0.5749 - Accuracy: 0.6310 - F1: 0.6267
sub_10:Test (Best Model) - Loss: 1.3142 - Accuracy: 0.5952 - F1: 0.5159
sub_12:Test (Best Model) - Loss: 0.9572 - Accuracy: 0.7024 - F1: 0.6989
sub_11:Test (Best Model) - Loss: 0.2625 - Accuracy: 0.9167 - F1: 0.9167
sub_10:Test (Best Model) - Loss: 1.0997 - Accuracy: 0.6190 - F1: 0.5544
sub_12:Test (Best Model) - Loss: 0.3895 - Accuracy: 0.8571 - F1: 0.8571
sub_10:Test (Best Model) - Loss: 1.1808 - Accuracy: 0.5952 - F1: 0.5159
sub_11:Test (Best Model) - Loss: 0.2502 - Accuracy: 0.8929 - F1: 0.8925
sub_13:Test (Best Model) - Loss: 0.2681 - Accuracy: 0.8810 - F1: 0.8792
sub_14:Test (Best Model) - Loss: 0.8431 - Accuracy: 0.8214 - F1: 0.8212
sub_13:Test (Best Model) - Loss: 0.2238 - Accuracy: 0.8929 - F1: 0.8916
sub_14:Test (Best Model) - Loss: 0.3841 - Accuracy: 0.8214 - F1: 0.8214
sub_13:Test (Best Model) - Loss: 0.1063 - Accuracy: 0.9762 - F1: 0.9762
sub_14:Test (Best Model) - Loss: 0.7421 - Accuracy: 0.7857 - F1: 0.7846
sub_13:Test (Best Model) - Loss: 0.1996 - Accuracy: 0.9048 - F1: 0.9039
sub_13:Test (Best Model) - Loss: 0.1875 - Accuracy: 0.9167 - F1: 0.9161
sub_13:Test (Best Model) - Loss: 0.3517 - Accuracy: 0.8810 - F1: 0.8809
sub_14:Test (Best Model) - Loss: 0.3133 - Accuracy: 0.8810 - F1: 0.8803
sub_13:Test (Best Model) - Loss: 0.3389 - Accuracy: 0.8929 - F1: 0.8928
sub_14:Test (Best Model) - Loss: 0.5446 - Accuracy: 0.8095 - F1: 0.8091
sub_13:Test (Best Model) - Loss: 0.4217 - Accuracy: 0.8452 - F1: 0.8434
sub_13:Test (Best Model) - Loss: 0.3286 - Accuracy: 0.8571 - F1: 0.8558
sub_14:Test (Best Model) - Loss: 0.3569 - Accuracy: 0.8214 - F1: 0.8155
sub_13:Test (Best Model) - Loss: 0.2549 - Accuracy: 0.8929 - F1: 0.8925
sub_14:Test (Best Model) - Loss: 0.4091 - Accuracy: 0.8095 - F1: 0.8024
sub_13:Test (Best Model) - Loss: 0.2947 - Accuracy: 0.8929 - F1: 0.8927
sub_14:Test (Best Model) - Loss: 0.4483 - Accuracy: 0.7976 - F1: 0.7890
sub_13:Test (Best Model) - Loss: 0.3021 - Accuracy: 0.9286 - F1: 0.9286
sub_14:Test (Best Model) - Loss: 0.1367 - Accuracy: 0.9524 - F1: 0.9523
sub_13:Test (Best Model) - Loss: 0.4453 - Accuracy: 0.8810 - F1: 0.8799
sub_14:Test (Best Model) - Loss: 0.1864 - Accuracy: 0.9048 - F1: 0.9039
sub_13:Test (Best Model) - Loss: 0.4905 - Accuracy: 0.8810 - F1: 0.8803
sub_14:Test (Best Model) - Loss: 1.2857 - Accuracy: 0.5952 - F1: 0.5361
sub_13:Test (Best Model) - Loss: 0.3241 - Accuracy: 0.8929 - F1: 0.8921
sub_14:Test (Best Model) - Loss: 1.6481 - Accuracy: 0.5833 - F1: 0.5176
sub_14:Test (Best Model) - Loss: 1.4409 - Accuracy: 0.5952 - F1: 0.5265
sub_14:Test (Best Model) - Loss: 1.5432 - Accuracy: 0.5952 - F1: 0.5446
sub_14:Test (Best Model) - Loss: 1.4727 - Accuracy: 0.6071 - F1: 0.5540

=== Summary Results ===

acc: 79.29 ± 5.68
F1: 78.53 ± 6.22
acc-in: 89.73 ± 3.53
F1-in: 89.46 ± 3.71
runing time: 1421.68 seconds
