lr: 0.001
sub_2:Test (Best Model) - Loss: 0.2083 - Accuracy: 0.9524 - F1: 0.9523
sub_8:Test (Best Model) - Loss: 1.3641 - Accuracy: 0.6429 - F1: 0.6111
sub_4:Test (Best Model) - Loss: 0.6678 - Accuracy: 0.7619 - F1: 0.7597
sub_10:Test (Best Model) - Loss: 0.5182 - Accuracy: 0.7857 - F1: 0.7826
sub_7:Test (Best Model) - Loss: 0.9113 - Accuracy: 0.7381 - F1: 0.7306
sub_3:Test (Best Model) - Loss: 0.6312 - Accuracy: 0.6905 - F1: 0.6876
sub_6:Test (Best Model) - Loss: 0.6643 - Accuracy: 0.6548 - F1: 0.6080
sub_5:Test (Best Model) - Loss: 0.6359 - Accuracy: 0.7857 - F1: 0.7812
sub_9:Test (Best Model) - Loss: 0.2747 - Accuracy: 0.8690 - F1: 0.8690
sub_1:Test (Best Model) - Loss: 0.0805 - Accuracy: 0.9643 - F1: 0.9642
sub_3:Test (Best Model) - Loss: 0.4099 - Accuracy: 0.7976 - F1: 0.7941
sub_4:Test (Best Model) - Loss: 0.8363 - Accuracy: 0.6667 - F1: 0.6665
sub_2:Test (Best Model) - Loss: 0.0405 - Accuracy: 0.9881 - F1: 0.9881
sub_8:Test (Best Model) - Loss: 0.7693 - Accuracy: 0.7738 - F1: 0.7641
sub_10:Test (Best Model) - Loss: 0.4300 - Accuracy: 0.8214 - F1: 0.8202
sub_7:Test (Best Model) - Loss: 0.6412 - Accuracy: 0.7976 - F1: 0.7969
sub_9:Test (Best Model) - Loss: 0.2855 - Accuracy: 0.8452 - F1: 0.8425
sub_5:Test (Best Model) - Loss: 1.0889 - Accuracy: 0.6548 - F1: 0.6212
sub_2:Test (Best Model) - Loss: 0.0463 - Accuracy: 0.9762 - F1: 0.9762
sub_10:Test (Best Model) - Loss: 0.3807 - Accuracy: 0.8810 - F1: 0.8807
sub_4:Test (Best Model) - Loss: 0.8102 - Accuracy: 0.6905 - F1: 0.6898
sub_3:Test (Best Model) - Loss: 1.7407 - Accuracy: 0.5357 - F1: 0.4081
sub_1:Test (Best Model) - Loss: 1.1998 - Accuracy: 0.7024 - F1: 0.6735
sub_6:Test (Best Model) - Loss: 0.6483 - Accuracy: 0.6905 - F1: 0.6630
sub_5:Test (Best Model) - Loss: 0.4488 - Accuracy: 0.8214 - F1: 0.8214
sub_2:Test (Best Model) - Loss: 0.0537 - Accuracy: 0.9762 - F1: 0.9762
sub_7:Test (Best Model) - Loss: 0.7111 - Accuracy: 0.7143 - F1: 0.7035
sub_8:Test (Best Model) - Loss: 0.7088 - Accuracy: 0.7738 - F1: 0.7730
sub_4:Test (Best Model) - Loss: 0.6216 - Accuracy: 0.6667 - F1: 0.6597
sub_10:Test (Best Model) - Loss: 0.4848 - Accuracy: 0.8571 - F1: 0.8558
sub_9:Test (Best Model) - Loss: 0.6572 - Accuracy: 0.8095 - F1: 0.8041
sub_1:Test (Best Model) - Loss: 0.1473 - Accuracy: 0.9405 - F1: 0.9405
sub_4:Test (Best Model) - Loss: 1.2161 - Accuracy: 0.6190 - F1: 0.6156
sub_9:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5714 - F1: 0.5508
sub_5:Test (Best Model) - Loss: 0.6409 - Accuracy: 0.6786 - F1: 0.6730
sub_7:Test (Best Model) - Loss: 0.7255 - Accuracy: 0.7738 - F1: 0.7664
sub_2:Test (Best Model) - Loss: 0.0555 - Accuracy: 0.9881 - F1: 0.9881
sub_6:Test (Best Model) - Loss: 0.8596 - Accuracy: 0.7738 - F1: 0.7730
sub_10:Test (Best Model) - Loss: 0.3873 - Accuracy: 0.8810 - F1: 0.8803
sub_3:Test (Best Model) - Loss: 0.4816 - Accuracy: 0.8452 - F1: 0.8442
sub_1:Test (Best Model) - Loss: 0.2225 - Accuracy: 0.9286 - F1: 0.9285
sub_8:Test (Best Model) - Loss: 0.9595 - Accuracy: 0.7976 - F1: 0.7927
sub_5:Test (Best Model) - Loss: 0.7487 - Accuracy: 0.6310 - F1: 0.5810
sub_9:Test (Best Model) - Loss: 0.3237 - Accuracy: 0.8810 - F1: 0.8809
sub_2:Test (Best Model) - Loss: 0.1563 - Accuracy: 0.9167 - F1: 0.9164
sub_3:Test (Best Model) - Loss: 0.3438 - Accuracy: 0.8690 - F1: 0.8690
sub_7:Test (Best Model) - Loss: 1.2054 - Accuracy: 0.7500 - F1: 0.7456
sub_10:Test (Best Model) - Loss: 0.1779 - Accuracy: 0.9286 - F1: 0.9285
sub_1:Test (Best Model) - Loss: 0.5022 - Accuracy: 0.7024 - F1: 0.6735
sub_6:Test (Best Model) - Loss: 1.9907 - Accuracy: 0.6071 - F1: 0.5452
sub_4:Test (Best Model) - Loss: 0.4769 - Accuracy: 0.8333 - F1: 0.8332
sub_5:Test (Best Model) - Loss: 0.4256 - Accuracy: 0.7976 - F1: 0.7953
sub_8:Test (Best Model) - Loss: 1.6834 - Accuracy: 0.7024 - F1: 0.6783
sub_2:Test (Best Model) - Loss: 0.1063 - Accuracy: 0.9762 - F1: 0.9762
sub_10:Test (Best Model) - Loss: 0.3950 - Accuracy: 0.8333 - F1: 0.8299
sub_9:Test (Best Model) - Loss: 0.5757 - Accuracy: 0.8452 - F1: 0.8414
sub_7:Test (Best Model) - Loss: 0.1264 - Accuracy: 0.9524 - F1: 0.9524
sub_3:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.7500 - F1: 0.7439
sub_2:Test (Best Model) - Loss: 0.2254 - Accuracy: 0.8929 - F1: 0.8916
sub_10:Test (Best Model) - Loss: 0.2026 - Accuracy: 0.9286 - F1: 0.9286
sub_6:Test (Best Model) - Loss: 0.3471 - Accuracy: 0.8571 - F1: 0.8571
sub_4:Test (Best Model) - Loss: 1.0364 - Accuracy: 0.5833 - F1: 0.5176
sub_5:Test (Best Model) - Loss: 0.4103 - Accuracy: 0.8571 - F1: 0.8558
sub_1:Test (Best Model) - Loss: 0.4928 - Accuracy: 0.7738 - F1: 0.7641
sub_9:Test (Best Model) - Loss: 0.2704 - Accuracy: 0.9405 - F1: 0.9404
sub_8:Test (Best Model) - Loss: 0.6384 - Accuracy: 0.6548 - F1: 0.6080
sub_2:Test (Best Model) - Loss: 0.0898 - Accuracy: 0.9762 - F1: 0.9762
sub_7:Test (Best Model) - Loss: 0.2493 - Accuracy: 0.8810 - F1: 0.8799
sub_5:Test (Best Model) - Loss: 0.5167 - Accuracy: 0.7381 - F1: 0.7357
sub_3:Test (Best Model) - Loss: 0.5163 - Accuracy: 0.7857 - F1: 0.7857
sub_6:Test (Best Model) - Loss: 1.0913 - Accuracy: 0.7500 - F1: 0.7471
sub_10:Test (Best Model) - Loss: 0.3259 - Accuracy: 0.8929 - F1: 0.8916
sub_4:Test (Best Model) - Loss: 0.4159 - Accuracy: 0.8333 - F1: 0.8332
sub_1:Test (Best Model) - Loss: 0.2714 - Accuracy: 0.9048 - F1: 0.9039
sub_7:Test (Best Model) - Loss: 0.3396 - Accuracy: 0.8690 - F1: 0.8668
sub_8:Test (Best Model) - Loss: 0.5553 - Accuracy: 0.7976 - F1: 0.7890
sub_9:Test (Best Model) - Loss: 1.1942 - Accuracy: 0.6548 - F1: 0.6080
sub_2:Test (Best Model) - Loss: 0.2207 - Accuracy: 0.8929 - F1: 0.8916
sub_8:Test (Best Model) - Loss: 0.5690 - Accuracy: 0.7024 - F1: 0.6926
sub_3:Test (Best Model) - Loss: 1.1376 - Accuracy: 0.7262 - F1: 0.7040
sub_5:Test (Best Model) - Loss: 0.8506 - Accuracy: 0.7619 - F1: 0.7597
sub_7:Test (Best Model) - Loss: 0.1765 - Accuracy: 0.9405 - F1: 0.9405
sub_6:Test (Best Model) - Loss: 1.4760 - Accuracy: 0.7381 - F1: 0.7188
sub_4:Test (Best Model) - Loss: 0.4063 - Accuracy: 0.8452 - F1: 0.8447
sub_10:Test (Best Model) - Loss: 0.2184 - Accuracy: 0.9048 - F1: 0.9043
sub_2:Test (Best Model) - Loss: 1.6033 - Accuracy: 0.5714 - F1: 0.4750
sub_9:Test (Best Model) - Loss: 0.8436 - Accuracy: 0.7738 - F1: 0.7738
sub_4:Test (Best Model) - Loss: 0.7575 - Accuracy: 0.5595 - F1: 0.4535
sub_3:Test (Best Model) - Loss: 0.6392 - Accuracy: 0.6786 - F1: 0.6525
sub_8:Test (Best Model) - Loss: 0.2690 - Accuracy: 0.8810 - F1: 0.8799
sub_10:Test (Best Model) - Loss: 0.5211 - Accuracy: 0.7976 - F1: 0.7941
sub_5:Test (Best Model) - Loss: 0.7986 - Accuracy: 0.8095 - F1: 0.8078
sub_1:Test (Best Model) - Loss: 0.8247 - Accuracy: 0.7143 - F1: 0.6889
sub_7:Test (Best Model) - Loss: 0.4637 - Accuracy: 0.8690 - F1: 0.8675
sub_6:Test (Best Model) - Loss: 2.6452 - Accuracy: 0.6786 - F1: 0.6525
sub_4:Test (Best Model) - Loss: 1.0906 - Accuracy: 0.7143 - F1: 0.7083
sub_9:Test (Best Model) - Loss: 1.8383 - Accuracy: 0.6548 - F1: 0.6400
sub_2:Test (Best Model) - Loss: 0.1103 - Accuracy: 0.9762 - F1: 0.9762
sub_10:Test (Best Model) - Loss: 0.3600 - Accuracy: 0.8810 - F1: 0.8803
sub_1:Test (Best Model) - Loss: 0.8960 - Accuracy: 0.6786 - F1: 0.6415
sub_8:Test (Best Model) - Loss: 0.4223 - Accuracy: 0.8214 - F1: 0.8155
sub_3:Test (Best Model) - Loss: 1.5222 - Accuracy: 0.5833 - F1: 0.4958
sub_4:Test (Best Model) - Loss: 1.7222 - Accuracy: 0.5238 - F1: 0.4013
sub_5:Test (Best Model) - Loss: 1.0546 - Accuracy: 0.7619 - F1: 0.7618
sub_7:Test (Best Model) - Loss: 0.5132 - Accuracy: 0.8333 - F1: 0.8299
sub_3:Test (Best Model) - Loss: 0.5520 - Accuracy: 0.7024 - F1: 0.6783
sub_9:Test (Best Model) - Loss: 2.5053 - Accuracy: 0.5833 - F1: 0.4958
sub_4:Test (Best Model) - Loss: 0.7835 - Accuracy: 0.5952 - F1: 0.5943
sub_2:Test (Best Model) - Loss: 0.6522 - Accuracy: 0.7619 - F1: 0.7476
sub_6:Test (Best Model) - Loss: 2.2112 - Accuracy: 0.6548 - F1: 0.6547
sub_10:Test (Best Model) - Loss: 2.2989 - Accuracy: 0.5952 - F1: 0.5446
sub_7:Test (Best Model) - Loss: 0.4192 - Accuracy: 0.8333 - F1: 0.8286
sub_6:Test (Best Model) - Loss: 0.7618 - Accuracy: 0.7262 - F1: 0.7195
sub_1:Test (Best Model) - Loss: 0.5230 - Accuracy: 0.7976 - F1: 0.7890
sub_4:Test (Best Model) - Loss: 0.9851 - Accuracy: 0.5714 - F1: 0.4750
sub_8:Test (Best Model) - Loss: 0.4508 - Accuracy: 0.7857 - F1: 0.7796
sub_9:Test (Best Model) - Loss: 3.4181 - Accuracy: 0.5119 - F1: 0.3593
sub_10:Test (Best Model) - Loss: 0.6172 - Accuracy: 0.6905 - F1: 0.6677
sub_5:Test (Best Model) - Loss: 0.5609 - Accuracy: 0.7500 - F1: 0.7500
sub_2:Test (Best Model) - Loss: 0.2222 - Accuracy: 0.8810 - F1: 0.8803
sub_3:Test (Best Model) - Loss: 1.4689 - Accuracy: 0.5714 - F1: 0.4875
sub_2:Test (Best Model) - Loss: 2.1355 - Accuracy: 0.5952 - F1: 0.5159
sub_7:Test (Best Model) - Loss: 1.7721 - Accuracy: 0.5119 - F1: 0.3593
sub_1:Test (Best Model) - Loss: 2.1342 - Accuracy: 0.5119 - F1: 0.3778
sub_6:Test (Best Model) - Loss: 0.4144 - Accuracy: 0.7976 - F1: 0.7910
sub_4:Test (Best Model) - Loss: 0.5072 - Accuracy: 0.8095 - F1: 0.8095
sub_5:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5000 - F1: 0.3875
sub_9:Test (Best Model) - Loss: 2.7678 - Accuracy: 0.5238 - F1: 0.3842
sub_10:Test (Best Model) - Loss: 0.7884 - Accuracy: 0.7024 - F1: 0.6863
sub_7:Test (Best Model) - Loss: 0.5040 - Accuracy: 0.7619 - F1: 0.7476
sub_8:Test (Best Model) - Loss: 0.6206 - Accuracy: 0.7738 - F1: 0.7664
sub_1:Test (Best Model) - Loss: 1.0470 - Accuracy: 0.6310 - F1: 0.6245
sub_3:Test (Best Model) - Loss: 0.8174 - Accuracy: 0.6548 - F1: 0.6150
sub_5:Test (Best Model) - Loss: 0.5559 - Accuracy: 0.7738 - F1: 0.7738
sub_6:Test (Best Model) - Loss: 0.5151 - Accuracy: 0.7500 - F1: 0.7333
sub_9:Test (Best Model) - Loss: 0.9812 - Accuracy: 0.5833 - F1: 0.5270
sub_5:Test (Best Model) - Loss: 0.7952 - Accuracy: 0.7857 - F1: 0.7754
sub_6:Test (Best Model) - Loss: 0.6664 - Accuracy: 0.5595 - F1: 0.4535
sub_7:Test (Best Model) - Loss: 0.3971 - Accuracy: 0.8214 - F1: 0.8212
sub_8:Test (Best Model) - Loss: 0.4510 - Accuracy: 0.8214 - F1: 0.8194
sub_1:Test (Best Model) - Loss: 1.7903 - Accuracy: 0.5595 - F1: 0.4901
sub_9:Test (Best Model) - Loss: 0.5626 - Accuracy: 0.7381 - F1: 0.7357
sub_3:Test (Best Model) - Loss: 0.4778 - Accuracy: 0.8095 - F1: 0.8024
sub_8:Test (Best Model) - Loss: 1.1498 - Accuracy: 0.6786 - F1: 0.6571
sub_3:Test (Best Model) - Loss: 1.0101 - Accuracy: 0.6071 - F1: 0.5810
sub_1:Test (Best Model) - Loss: 1.0975 - Accuracy: 0.6310 - F1: 0.6111
sub_6:Test (Best Model) - Loss: 0.2965 - Accuracy: 0.8810 - F1: 0.8799
sub_8:Test (Best Model) - Loss: 0.6275 - Accuracy: 0.8095 - F1: 0.8078
sub_1:Test (Best Model) - Loss: 1.2770 - Accuracy: 0.6071 - F1: 0.6044
sub_6:Test (Best Model) - Loss: 0.6685 - Accuracy: 0.7143 - F1: 0.6889
sub_14:Test (Best Model) - Loss: 0.9053 - Accuracy: 0.6190 - F1: 0.5962
sub_13:Test (Best Model) - Loss: 1.0900 - Accuracy: 0.6190 - F1: 0.5634
sub_11:Test (Best Model) - Loss: 0.7802 - Accuracy: 0.7857 - F1: 0.7776
sub_12:Test (Best Model) - Loss: 0.4939 - Accuracy: 0.7976 - F1: 0.7953
sub_14:Test (Best Model) - Loss: 0.7699 - Accuracy: 0.6905 - F1: 0.6840
sub_12:Test (Best Model) - Loss: 0.9712 - Accuracy: 0.6190 - F1: 0.6007
sub_13:Test (Best Model) - Loss: 0.2867 - Accuracy: 0.9048 - F1: 0.9047
sub_11:Test (Best Model) - Loss: 0.9254 - Accuracy: 0.7143 - F1: 0.6889
sub_13:Test (Best Model) - Loss: 0.5884 - Accuracy: 0.6905 - F1: 0.6840
sub_14:Test (Best Model) - Loss: 1.0622 - Accuracy: 0.8571 - F1: 0.8568
sub_12:Test (Best Model) - Loss: 0.6062 - Accuracy: 0.6786 - F1: 0.6648
sub_13:Test (Best Model) - Loss: 0.5672 - Accuracy: 0.7024 - F1: 0.6989
sub_11:Test (Best Model) - Loss: 0.2759 - Accuracy: 0.8690 - F1: 0.8690
sub_14:Test (Best Model) - Loss: 0.6978 - Accuracy: 0.8214 - F1: 0.8214
sub_13:Test (Best Model) - Loss: 0.4996 - Accuracy: 0.7619 - F1: 0.7585
sub_11:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5476 - F1: 0.5411
sub_12:Test (Best Model) - Loss: 1.2440 - Accuracy: 0.6310 - F1: 0.5728
sub_14:Test (Best Model) - Loss: 1.1639 - Accuracy: 0.6905 - F1: 0.6630
sub_13:Test (Best Model) - Loss: 0.7456 - Accuracy: 0.7381 - F1: 0.7224
sub_11:Test (Best Model) - Loss: 0.9136 - Accuracy: 0.7500 - F1: 0.7491
sub_12:Test (Best Model) - Loss: 0.8765 - Accuracy: 0.6905 - F1: 0.6816
sub_14:Test (Best Model) - Loss: 0.2756 - Accuracy: 0.9286 - F1: 0.9286
sub_12:Test (Best Model) - Loss: 1.4171 - Accuracy: 0.5238 - F1: 0.3842
sub_13:Test (Best Model) - Loss: 1.0008 - Accuracy: 0.7143 - F1: 0.7061
sub_11:Test (Best Model) - Loss: 0.3321 - Accuracy: 0.8214 - F1: 0.8202
sub_12:Test (Best Model) - Loss: 0.6602 - Accuracy: 0.6190 - F1: 0.6136
sub_13:Test (Best Model) - Loss: 0.6729 - Accuracy: 0.5357 - F1: 0.4822
sub_14:Test (Best Model) - Loss: 0.7036 - Accuracy: 0.7500 - F1: 0.7333
sub_14:Test (Best Model) - Loss: 0.3758 - Accuracy: 0.7976 - F1: 0.7927
sub_12:Test (Best Model) - Loss: 0.8835 - Accuracy: 0.5952 - F1: 0.5837
sub_11:Test (Best Model) - Loss: 0.6980 - Accuracy: 0.7262 - F1: 0.7172
sub_13:Test (Best Model) - Loss: 0.9097 - Accuracy: 0.6548 - F1: 0.6212
sub_14:Test (Best Model) - Loss: 0.9836 - Accuracy: 0.7143 - F1: 0.6889
sub_12:Test (Best Model) - Loss: 0.5050 - Accuracy: 0.7857 - F1: 0.7846
sub_14:Test (Best Model) - Loss: 1.3155 - Accuracy: 0.6310 - F1: 0.5728
sub_13:Test (Best Model) - Loss: 0.6267 - Accuracy: 0.6190 - F1: 0.5910
sub_11:Test (Best Model) - Loss: 0.2718 - Accuracy: 0.9167 - F1: 0.9161
sub_14:Test (Best Model) - Loss: 3.0166 - Accuracy: 0.5357 - F1: 0.4081
sub_12:Test (Best Model) - Loss: 1.2672 - Accuracy: 0.6786 - F1: 0.6612
sub_11:Test (Best Model) - Loss: 2.0706 - Accuracy: 0.5476 - F1: 0.4312
sub_14:Test (Best Model) - Loss: 0.9054 - Accuracy: 0.5833 - F1: 0.5073
sub_12:Test (Best Model) - Loss: 1.5051 - Accuracy: 0.5238 - F1: 0.4013
sub_13:Test (Best Model) - Loss: 1.0698 - Accuracy: 0.7262 - F1: 0.7114
sub_12:Test (Best Model) - Loss: 1.6604 - Accuracy: 0.6429 - F1: 0.5906
sub_11:Test (Best Model) - Loss: 0.7862 - Accuracy: 0.7500 - F1: 0.7393
sub_14:Test (Best Model) - Loss: 0.6508 - Accuracy: 0.6667 - F1: 0.6421
sub_13:Test (Best Model) - Loss: 0.5411 - Accuracy: 0.7381 - F1: 0.7379
sub_11:Test (Best Model) - Loss: 0.5090 - Accuracy: 0.8810 - F1: 0.8792
sub_12:Test (Best Model) - Loss: 1.1711 - Accuracy: 0.6071 - F1: 0.5753
sub_13:Test (Best Model) - Loss: 0.6848 - Accuracy: 0.7976 - F1: 0.7976
sub_11:Test (Best Model) - Loss: 0.5320 - Accuracy: 0.8333 - F1: 0.8286
sub_14:Test (Best Model) - Loss: 1.0076 - Accuracy: 0.5952 - F1: 0.5593
sub_12:Test (Best Model) - Loss: 0.9018 - Accuracy: 0.6429 - F1: 0.5982
sub_13:Test (Best Model) - Loss: 1.7975 - Accuracy: 0.5714 - F1: 0.4750
sub_14:Test (Best Model) - Loss: 1.3126 - Accuracy: 0.7262 - F1: 0.7040
sub_11:Test (Best Model) - Loss: 1.0129 - Accuracy: 0.7738 - F1: 0.7641
sub_13:Test (Best Model) - Loss: 1.9241 - Accuracy: 0.5357 - F1: 0.4081
sub_12:Test (Best Model) - Loss: 1.8651 - Accuracy: 0.5714 - F1: 0.4875
sub_11:Test (Best Model) - Loss: 0.8727 - Accuracy: 0.7024 - F1: 0.6735
sub_11:Test (Best Model) - Loss: 0.1105 - Accuracy: 0.9405 - F1: 0.9404

=== Summary Results ===

acc: 74.24 ± 6.16
F1: 71.97 ± 7.00
acc-in: 86.53 ± 5.39
F1-in: 85.87 ± 5.87
runing time: 2352.29 seconds
