lr: 0.001
sub_4:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5000 - F1: 0.4269
sub_6:Test (Best Model) - Loss: 0.5582 - Accuracy: 0.7262 - F1: 0.7079
sub_7:Test (Best Model) - Loss: 0.6340 - Accuracy: 0.7262 - F1: 0.7214
sub_1:Test (Best Model) - Loss: 0.1506 - Accuracy: 0.9762 - F1: 0.9762
sub_3:Test (Best Model) - Loss: 0.7316 - Accuracy: 0.5833 - F1: 0.5073
sub_2:Test (Best Model) - Loss: 0.1941 - Accuracy: 0.9286 - F1: 0.9286
sub_5:Test (Best Model) - Loss: 0.6752 - Accuracy: 0.7738 - F1: 0.7712
sub_6:Test (Best Model) - Loss: 0.5065 - Accuracy: 0.8333 - F1: 0.8333
sub_2:Test (Best Model) - Loss: 0.0731 - Accuracy: 0.9881 - F1: 0.9881
sub_7:Test (Best Model) - Loss: 1.3033 - Accuracy: 0.5357 - F1: 0.4081
sub_4:Test (Best Model) - Loss: 0.5545 - Accuracy: 0.8214 - F1: 0.8208
sub_1:Test (Best Model) - Loss: 0.3747 - Accuracy: 0.8333 - F1: 0.8299
sub_3:Test (Best Model) - Loss: 1.0856 - Accuracy: 0.7619 - F1: 0.7551
sub_5:Test (Best Model) - Loss: 0.6197 - Accuracy: 0.7738 - F1: 0.7712
sub_6:Test (Best Model) - Loss: 0.5425 - Accuracy: 0.8095 - F1: 0.8078
sub_2:Test (Best Model) - Loss: 0.1418 - Accuracy: 0.9524 - F1: 0.9524
sub_7:Test (Best Model) - Loss: 0.7879 - Accuracy: 0.7857 - F1: 0.7826
sub_4:Test (Best Model) - Loss: 1.1507 - Accuracy: 0.6310 - F1: 0.6010
sub_5:Test (Best Model) - Loss: 1.0832 - Accuracy: 0.5833 - F1: 0.5176
sub_1:Test (Best Model) - Loss: 0.1370 - Accuracy: 0.9405 - F1: 0.9403
sub_3:Test (Best Model) - Loss: 0.9176 - Accuracy: 0.6548 - F1: 0.6080
sub_6:Test (Best Model) - Loss: 0.4820 - Accuracy: 0.7976 - F1: 0.7927
sub_2:Test (Best Model) - Loss: 0.1336 - Accuracy: 0.9643 - F1: 0.9642
sub_5:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.6786 - F1: 0.6571
sub_4:Test (Best Model) - Loss: 0.3708 - Accuracy: 0.8214 - F1: 0.8212
sub_7:Test (Best Model) - Loss: 1.0537 - Accuracy: 0.7619 - F1: 0.7569
sub_2:Test (Best Model) - Loss: 0.4055 - Accuracy: 0.8929 - F1: 0.8916
sub_3:Test (Best Model) - Loss: 0.4915 - Accuracy: 0.7857 - F1: 0.7826
sub_6:Test (Best Model) - Loss: 0.5043 - Accuracy: 0.7738 - F1: 0.7641
sub_1:Test (Best Model) - Loss: 0.3351 - Accuracy: 0.8810 - F1: 0.8809
sub_5:Test (Best Model) - Loss: 0.8106 - Accuracy: 0.7262 - F1: 0.7172
sub_3:Test (Best Model) - Loss: 0.4738 - Accuracy: 0.7976 - F1: 0.7941
sub_7:Test (Best Model) - Loss: 0.9645 - Accuracy: 0.6548 - F1: 0.6317
sub_4:Test (Best Model) - Loss: 1.0089 - Accuracy: 0.7381 - F1: 0.7379
sub_2:Test (Best Model) - Loss: 0.1798 - Accuracy: 0.9524 - F1: 0.9523
sub_3:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.8564 - Accuracy: 0.7738 - F1: 0.7616
sub_1:Test (Best Model) - Loss: 0.1584 - Accuracy: 0.9405 - F1: 0.9404
sub_4:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.4169 - Accuracy: 0.8452 - F1: 0.8450
sub_7:Test (Best Model) - Loss: 0.2949 - Accuracy: 0.8810 - F1: 0.8810
sub_6:Test (Best Model) - Loss: 0.8683 - Accuracy: 0.6786 - F1: 0.6473
sub_3:Test (Best Model) - Loss: 0.6321 - Accuracy: 0.7619 - F1: 0.7597
sub_2:Test (Best Model) - Loss: 0.1447 - Accuracy: 0.9524 - F1: 0.9524
sub_1:Test (Best Model) - Loss: 0.1842 - Accuracy: 0.9167 - F1: 0.9167
sub_5:Test (Best Model) - Loss: 0.4978 - Accuracy: 0.8214 - F1: 0.8202
sub_4:Test (Best Model) - Loss: 0.4987 - Accuracy: 0.8214 - F1: 0.8202
sub_6:Test (Best Model) - Loss: 1.1836 - Accuracy: 0.6310 - F1: 0.5728
sub_7:Test (Best Model) - Loss: 0.1359 - Accuracy: 0.9405 - F1: 0.9405
sub_3:Test (Best Model) - Loss: 0.6557 - Accuracy: 0.6071 - F1: 0.5975
sub_2:Test (Best Model) - Loss: 0.1339 - Accuracy: 0.9643 - F1: 0.9643
sub_1:Test (Best Model) - Loss: 0.2297 - Accuracy: 0.9405 - F1: 0.9404
sub_7:Test (Best Model) - Loss: 0.2054 - Accuracy: 0.9167 - F1: 0.9166
sub_4:Test (Best Model) - Loss: 0.6233 - Accuracy: 0.7262 - F1: 0.7258
sub_3:Test (Best Model) - Loss: 0.7879 - Accuracy: 0.7143 - F1: 0.7117
sub_6:Test (Best Model) - Loss: 0.9906 - Accuracy: 0.7143 - F1: 0.6971
sub_5:Test (Best Model) - Loss: 0.5907 - Accuracy: 0.7619 - F1: 0.7551
sub_4:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.1118 - Accuracy: 0.9405 - F1: 0.9405
sub_6:Test (Best Model) - Loss: 0.7993 - Accuracy: 0.7143 - F1: 0.6889
sub_1:Test (Best Model) - Loss: 0.2904 - Accuracy: 0.9048 - F1: 0.9039
sub_3:Test (Best Model) - Loss: 0.7975 - Accuracy: 0.7738 - F1: 0.7722
sub_7:Test (Best Model) - Loss: 0.2920 - Accuracy: 0.8571 - F1: 0.8564
sub_2:Test (Best Model) - Loss: 0.1747 - Accuracy: 0.9286 - F1: 0.9284
sub_4:Test (Best Model) - Loss: 0.8843 - Accuracy: 0.5952 - F1: 0.5593
sub_5:Test (Best Model) - Loss: 0.7636 - Accuracy: 0.7143 - F1: 0.7141
sub_3:Test (Best Model) - Loss: 0.7335 - Accuracy: 0.6429 - F1: 0.6050
sub_6:Test (Best Model) - Loss: 0.4155 - Accuracy: 0.8571 - F1: 0.8568
sub_1:Test (Best Model) - Loss: 0.1064 - Accuracy: 0.9762 - F1: 0.9762
sub_7:Test (Best Model) - Loss: 0.3748 - Accuracy: 0.8810 - F1: 0.8792
sub_2:Test (Best Model) - Loss: 0.5179 - Accuracy: 0.7857 - F1: 0.7754
sub_3:Test (Best Model) - Loss: 0.7694 - Accuracy: 0.6071 - F1: 0.5354
sub_1:Test (Best Model) - Loss: 0.1367 - Accuracy: 0.9405 - F1: 0.9403
sub_2:Test (Best Model) - Loss: 0.1871 - Accuracy: 0.9167 - F1: 0.9167
sub_5:Test (Best Model) - Loss: 0.4069 - Accuracy: 0.8333 - F1: 0.8325
sub_4:Test (Best Model) - Loss: 0.7021 - Accuracy: 0.7976 - F1: 0.7962
sub_7:Test (Best Model) - Loss: 0.2494 - Accuracy: 0.9286 - F1: 0.9284
sub_6:Test (Best Model) - Loss: 0.4903 - Accuracy: 0.8095 - F1: 0.8085
sub_4:Test (Best Model) - Loss: 0.6403 - Accuracy: 0.7381 - F1: 0.7381
sub_5:Test (Best Model) - Loss: 0.5178 - Accuracy: 0.7857 - F1: 0.7826
sub_2:Test (Best Model) - Loss: 0.2595 - Accuracy: 0.9167 - F1: 0.9166
sub_3:Test (Best Model) - Loss: 0.6174 - Accuracy: 0.7619 - F1: 0.7619
sub_7:Test (Best Model) - Loss: 0.4546 - Accuracy: 0.7619 - F1: 0.7618
sub_1:Test (Best Model) - Loss: 0.5512 - Accuracy: 0.7857 - F1: 0.7776
sub_5:Test (Best Model) - Loss: 0.4320 - Accuracy: 0.8690 - F1: 0.8689
sub_6:Test (Best Model) - Loss: 0.5246 - Accuracy: 0.7619 - F1: 0.7597
sub_3:Test (Best Model) - Loss: 0.9639 - Accuracy: 0.6071 - F1: 0.5452
sub_2:Test (Best Model) - Loss: 0.0876 - Accuracy: 0.9762 - F1: 0.9762
sub_4:Test (Best Model) - Loss: 0.7846 - Accuracy: 0.7500 - F1: 0.7471
sub_1:Test (Best Model) - Loss: 0.7659 - Accuracy: 0.7143 - F1: 0.7061
sub_7:Test (Best Model) - Loss: 0.6555 - Accuracy: 0.5595 - F1: 0.5302
sub_3:Test (Best Model) - Loss: 0.6756 - Accuracy: 0.6190 - F1: 0.6136
sub_2:Test (Best Model) - Loss: 0.1920 - Accuracy: 0.8810 - F1: 0.8809
sub_4:Test (Best Model) - Loss: 0.8403 - Accuracy: 0.7024 - F1: 0.6989
sub_6:Test (Best Model) - Loss: 0.4794 - Accuracy: 0.8214 - F1: 0.8170
sub_1:Test (Best Model) - Loss: 0.7447 - Accuracy: 0.8095 - F1: 0.8078
sub_6:Test (Best Model) - Loss: 0.6198 - Accuracy: 0.8690 - F1: 0.8668
sub_5:Test (Best Model) - Loss: 0.5469 - Accuracy: 0.8095 - F1: 0.8068
sub_1:Test (Best Model) - Loss: 0.7606 - Accuracy: 0.7976 - F1: 0.7976
sub_7:Test (Best Model) - Loss: 0.4252 - Accuracy: 0.8452 - F1: 0.8450
sub_4:Test (Best Model) - Loss: 1.0117 - Accuracy: 0.6548 - F1: 0.6508
sub_1:Test (Best Model) - Loss: 2.1531 - Accuracy: 0.5952 - F1: 0.5265
sub_7:Test (Best Model) - Loss: 0.4725 - Accuracy: 0.7976 - F1: 0.7962
sub_5:Test (Best Model) - Loss: 0.7364 - Accuracy: 0.8095 - F1: 0.8056
sub_5:Test (Best Model) - Loss: 0.4745 - Accuracy: 0.8452 - F1: 0.8442
sub_14:Test (Best Model) - Loss: 0.6180 - Accuracy: 0.8095 - F1: 0.8094
sub_8:Test (Best Model) - Loss: 0.6536 - Accuracy: 0.8214 - F1: 0.8214
sub_11:Test (Best Model) - Loss: 0.5829 - Accuracy: 0.7857 - F1: 0.7852
sub_10:Test (Best Model) - Loss: 0.2846 - Accuracy: 0.8690 - F1: 0.8686
sub_12:Test (Best Model) - Loss: 0.7926 - Accuracy: 0.6667 - F1: 0.6650
sub_9:Test (Best Model) - Loss: 0.6770 - Accuracy: 0.8214 - F1: 0.8170
sub_14:Test (Best Model) - Loss: 0.6140 - Accuracy: 0.7619 - F1: 0.7551
sub_13:Test (Best Model) - Loss: 0.8025 - Accuracy: 0.6548 - F1: 0.6212
sub_8:Test (Best Model) - Loss: 0.4282 - Accuracy: 0.8333 - F1: 0.8330
sub_12:Test (Best Model) - Loss: 0.4910 - Accuracy: 0.7857 - F1: 0.7856
sub_10:Test (Best Model) - Loss: 0.2440 - Accuracy: 0.8929 - F1: 0.8927
sub_11:Test (Best Model) - Loss: 0.2992 - Accuracy: 0.8929 - F1: 0.8927
sub_9:Test (Best Model) - Loss: 1.6743 - Accuracy: 0.6071 - F1: 0.5452
sub_13:Test (Best Model) - Loss: 0.5621 - Accuracy: 0.7857 - F1: 0.7776
sub_14:Test (Best Model) - Loss: 0.8854 - Accuracy: 0.7500 - F1: 0.7491
sub_10:Test (Best Model) - Loss: 0.6064 - Accuracy: 0.7024 - F1: 0.6825
sub_11:Test (Best Model) - Loss: 0.4460 - Accuracy: 0.8214 - F1: 0.8170
sub_12:Test (Best Model) - Loss: 0.9396 - Accuracy: 0.6310 - F1: 0.6111
sub_8:Test (Best Model) - Loss: 0.6616 - Accuracy: 0.7976 - F1: 0.7969
sub_13:Test (Best Model) - Loss: 0.4452 - Accuracy: 0.8452 - F1: 0.8425
sub_12:Test (Best Model) - Loss: 0.5197 - Accuracy: 0.7857 - F1: 0.7812
sub_11:Test (Best Model) - Loss: 0.4214 - Accuracy: 0.8214 - F1: 0.8214
sub_9:Test (Best Model) - Loss: 0.3701 - Accuracy: 0.8929 - F1: 0.8925
sub_14:Test (Best Model) - Loss: 0.6717 - Accuracy: 0.5952 - F1: 0.5159
sub_10:Test (Best Model) - Loss: 0.9715 - Accuracy: 0.7619 - F1: 0.7569
sub_8:Test (Best Model) - Loss: 0.5657 - Accuracy: 0.8571 - F1: 0.8571
sub_12:Test (Best Model) - Loss: 0.9801 - Accuracy: 0.5952 - F1: 0.5894
sub_13:Test (Best Model) - Loss: 0.6332 - Accuracy: 0.6429 - F1: 0.5906
sub_11:Test (Best Model) - Loss: 0.8517 - Accuracy: 0.6786 - F1: 0.6763
sub_9:Test (Best Model) - Loss: 2.4034 - Accuracy: 0.5119 - F1: 0.3778
sub_10:Test (Best Model) - Loss: 0.7816 - Accuracy: 0.6786 - F1: 0.6473
sub_14:Test (Best Model) - Loss: 0.8261 - Accuracy: 0.7381 - F1: 0.7368
sub_12:Test (Best Model) - Loss: 0.5613 - Accuracy: 0.7024 - F1: 0.6735
sub_8:Test (Best Model) - Loss: 0.7843 - Accuracy: 0.7857 - F1: 0.7796
sub_13:Test (Best Model) - Loss: 0.3701 - Accuracy: 0.8095 - F1: 0.8024
sub_14:Test (Best Model) - Loss: 0.3260 - Accuracy: 0.8690 - F1: 0.8668
sub_11:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.7381 - F1: 0.7224
sub_9:Test (Best Model) - Loss: 0.1502 - Accuracy: 0.9286 - F1: 0.9282
sub_10:Test (Best Model) - Loss: 0.5474 - Accuracy: 0.8333 - F1: 0.8309
sub_13:Test (Best Model) - Loss: 0.8382 - Accuracy: 0.6548 - F1: 0.6463
sub_14:Test (Best Model) - Loss: 0.2570 - Accuracy: 0.8810 - F1: 0.8807
sub_8:Test (Best Model) - Loss: 0.2521 - Accuracy: 0.9048 - F1: 0.9039
sub_12:Test (Best Model) - Loss: 1.0667 - Accuracy: 0.6190 - F1: 0.6171
sub_9:Test (Best Model) - Loss: 0.4566 - Accuracy: 0.7976 - F1: 0.7974
sub_11:Test (Best Model) - Loss: 0.3599 - Accuracy: 0.8929 - F1: 0.8928
sub_10:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.6667 - F1: 0.6313
sub_13:Test (Best Model) - Loss: 0.6367 - Accuracy: 0.7857 - F1: 0.7846
sub_14:Test (Best Model) - Loss: 0.2746 - Accuracy: 0.8810 - F1: 0.8799
sub_8:Test (Best Model) - Loss: 1.1325 - Accuracy: 0.6786 - F1: 0.6571
sub_11:Test (Best Model) - Loss: 0.2992 - Accuracy: 0.8690 - F1: 0.8675
sub_12:Test (Best Model) - Loss: 1.9660 - Accuracy: 0.6310 - F1: 0.6296
sub_13:Test (Best Model) - Loss: 1.0140 - Accuracy: 0.6905 - F1: 0.6630
sub_10:Test (Best Model) - Loss: 0.4129 - Accuracy: 0.7976 - F1: 0.7927
sub_14:Test (Best Model) - Loss: 0.9154 - Accuracy: 0.5357 - F1: 0.4239
sub_9:Test (Best Model) - Loss: 0.7055 - Accuracy: 0.6786 - F1: 0.6774
sub_11:Test (Best Model) - Loss: 0.8160 - Accuracy: 0.7024 - F1: 0.6783
sub_12:Test (Best Model) - Loss: 0.5804 - Accuracy: 0.7381 - F1: 0.7282
sub_8:Test (Best Model) - Loss: 0.8476 - Accuracy: 0.7262 - F1: 0.7172
sub_10:Test (Best Model) - Loss: 0.2761 - Accuracy: 0.8690 - F1: 0.8689
sub_13:Test (Best Model) - Loss: 0.8806 - Accuracy: 0.6786 - F1: 0.6763
sub_14:Test (Best Model) - Loss: 0.4790 - Accuracy: 0.7738 - F1: 0.7641
sub_9:Test (Best Model) - Loss: 0.3438 - Accuracy: 0.8810 - F1: 0.8810
sub_12:Test (Best Model) - Loss: 0.4329 - Accuracy: 0.8333 - F1: 0.8325
sub_10:Test (Best Model) - Loss: 0.3704 - Accuracy: 0.8452 - F1: 0.8450
sub_13:Test (Best Model) - Loss: 0.4162 - Accuracy: 0.7976 - F1: 0.7962
sub_8:Test (Best Model) - Loss: 0.3628 - Accuracy: 0.8571 - F1: 0.8571
sub_11:Test (Best Model) - Loss: 0.5347 - Accuracy: 0.7976 - F1: 0.7890
sub_14:Test (Best Model) - Loss: 0.7943 - Accuracy: 0.6548 - F1: 0.6317
sub_10:Test (Best Model) - Loss: 0.9212 - Accuracy: 0.5714 - F1: 0.4875
sub_12:Test (Best Model) - Loss: 1.1201 - Accuracy: 0.5476 - F1: 0.5204
sub_8:Test (Best Model) - Loss: 0.7709 - Accuracy: 0.6786 - F1: 0.6612
sub_9:Test (Best Model) - Loss: 0.4940 - Accuracy: 0.8571 - F1: 0.8571
sub_14:Test (Best Model) - Loss: 0.3559 - Accuracy: 0.8452 - F1: 0.8452
sub_13:Test (Best Model) - Loss: 0.5186 - Accuracy: 0.7857 - F1: 0.7838
sub_11:Test (Best Model) - Loss: 0.7146 - Accuracy: 0.7262 - F1: 0.7114
sub_8:Test (Best Model) - Loss: 0.4220 - Accuracy: 0.8810 - F1: 0.8809
sub_12:Test (Best Model) - Loss: 0.8253 - Accuracy: 0.6190 - F1: 0.6007
sub_10:Test (Best Model) - Loss: 1.0191 - Accuracy: 0.6548 - F1: 0.6317
sub_13:Test (Best Model) - Loss: 0.9355 - Accuracy: 0.7738 - F1: 0.7616
sub_9:Test (Best Model) - Loss: 0.5915 - Accuracy: 0.7738 - F1: 0.7730
sub_11:Test (Best Model) - Loss: 0.4420 - Accuracy: 0.7738 - F1: 0.7641
sub_14:Test (Best Model) - Loss: 0.4933 - Accuracy: 0.8214 - F1: 0.8208
sub_8:Test (Best Model) - Loss: 0.4239 - Accuracy: 0.8095 - F1: 0.8068
sub_10:Test (Best Model) - Loss: 0.7596 - Accuracy: 0.6667 - F1: 0.6667
sub_13:Test (Best Model) - Loss: 0.7916 - Accuracy: 0.6548 - F1: 0.6212
sub_9:Test (Best Model) - Loss: 0.4842 - Accuracy: 0.7738 - F1: 0.7712
sub_12:Test (Best Model) - Loss: 0.9278 - Accuracy: 0.6548 - F1: 0.6535
sub_14:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.6429 - F1: 0.5982
sub_11:Test (Best Model) - Loss: 0.3157 - Accuracy: 0.8690 - F1: 0.8686
sub_8:Test (Best Model) - Loss: 0.4617 - Accuracy: 0.8929 - F1: 0.8921
sub_13:Test (Best Model) - Loss: 0.4779 - Accuracy: 0.8214 - F1: 0.8214
sub_12:Test (Best Model) - Loss: 0.8361 - Accuracy: 0.5952 - F1: 0.5524
sub_10:Test (Best Model) - Loss: 0.9958 - Accuracy: 0.6429 - F1: 0.6427
sub_9:Test (Best Model) - Loss: 0.7780 - Accuracy: 0.7381 - F1: 0.7381
sub_11:Test (Best Model) - Loss: 0.6107 - Accuracy: 0.6548 - F1: 0.6080
sub_13:Test (Best Model) - Loss: 0.7860 - Accuracy: 0.7143 - F1: 0.6971
sub_14:Test (Best Model) - Loss: 0.3035 - Accuracy: 0.9048 - F1: 0.9047
sub_8:Test (Best Model) - Loss: 1.2435 - Accuracy: 0.6310 - F1: 0.5884
sub_10:Test (Best Model) - Loss: 0.7748 - Accuracy: 0.6905 - F1: 0.6816
sub_11:Test (Best Model) - Loss: 0.5854 - Accuracy: 0.7857 - F1: 0.7796
sub_9:Test (Best Model) - Loss: 0.5700 - Accuracy: 0.8095 - F1: 0.8078
sub_12:Test (Best Model) - Loss: 1.6787 - Accuracy: 0.6071 - F1: 0.5452
sub_8:Test (Best Model) - Loss: 0.5189 - Accuracy: 0.7143 - F1: 0.7117
sub_9:Test (Best Model) - Loss: 1.2399 - Accuracy: 0.6071 - F1: 0.5452
sub_9:Test (Best Model) - Loss: 0.3646 - Accuracy: 0.7976 - F1: 0.7974

=== Summary Results ===

acc: 76.80 ± 6.70
F1: 75.35 ± 7.42
acc-in: 86.76 ± 5.29
F1-in: 86.05 ± 6.07
runing time: 708.90 seconds
