lr: 0.0001
sub_1:Test (Best Model) - Loss: 4.2063 - Accuracy: 0.7262 - F1: 0.7079
sub_1:Test (Best Model) - Loss: 4.6767 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 3.0523 - Accuracy: 0.6905 - F1: 0.6630
sub_1:Test (Best Model) - Loss: 3.1023 - Accuracy: 0.7500 - F1: 0.7333
sub_1:Test (Best Model) - Loss: 3.3117 - Accuracy: 0.7381 - F1: 0.7188
sub_1:Test (Best Model) - Loss: 0.9789 - Accuracy: 0.8929 - F1: 0.8928
sub_1:Test (Best Model) - Loss: 1.6737 - Accuracy: 0.6905 - F1: 0.6816
sub_1:Test (Best Model) - Loss: 1.7984 - Accuracy: 0.7619 - F1: 0.7614
sub_1:Test (Best Model) - Loss: 0.8680 - Accuracy: 0.8452 - F1: 0.8442
sub_1:Test (Best Model) - Loss: 1.1015 - Accuracy: 0.8095 - F1: 0.8085
sub_1:Test (Best Model) - Loss: 1.8910 - Accuracy: 0.7976 - F1: 0.7890
sub_1:Test (Best Model) - Loss: 1.1763 - Accuracy: 0.8214 - F1: 0.8183
sub_1:Test (Best Model) - Loss: 1.5853 - Accuracy: 0.7381 - F1: 0.7188
sub_1:Test (Best Model) - Loss: 1.1101 - Accuracy: 0.7857 - F1: 0.7754
sub_1:Test (Best Model) - Loss: 1.3239 - Accuracy: 0.7500 - F1: 0.7333
sub_2:Test (Best Model) - Loss: 1.5136 - Accuracy: 0.6429 - F1: 0.6327
sub_2:Test (Best Model) - Loss: 0.7049 - Accuracy: 0.7976 - F1: 0.7974
sub_2:Test (Best Model) - Loss: 0.6664 - Accuracy: 0.7619 - F1: 0.7618
sub_2:Test (Best Model) - Loss: 0.8771 - Accuracy: 0.7619 - F1: 0.7551
sub_2:Test (Best Model) - Loss: 1.6471 - Accuracy: 0.6429 - F1: 0.5982
sub_2:Test (Best Model) - Loss: 0.8583 - Accuracy: 0.7381 - F1: 0.7282
sub_2:Test (Best Model) - Loss: 1.0396 - Accuracy: 0.7500 - F1: 0.7418
sub_2:Test (Best Model) - Loss: 0.6137 - Accuracy: 0.8452 - F1: 0.8447
sub_2:Test (Best Model) - Loss: 0.3353 - Accuracy: 0.8452 - F1: 0.8447
sub_2:Test (Best Model) - Loss: 1.1904 - Accuracy: 0.7738 - F1: 0.7616
sub_2:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.8095 - F1: 0.8094
sub_2:Test (Best Model) - Loss: 0.7480 - Accuracy: 0.7857 - F1: 0.7856
sub_2:Test (Best Model) - Loss: 0.8383 - Accuracy: 0.7619 - F1: 0.7607
sub_2:Test (Best Model) - Loss: 0.6027 - Accuracy: 0.8214 - F1: 0.8183
sub_2:Test (Best Model) - Loss: 0.9771 - Accuracy: 0.7738 - F1: 0.7722
sub_3:Test (Best Model) - Loss: 3.1689 - Accuracy: 0.5714 - F1: 0.4875
sub_3:Test (Best Model) - Loss: 4.9438 - Accuracy: 0.5476 - F1: 0.4312
sub_3:Test (Best Model) - Loss: 3.0579 - Accuracy: 0.5833 - F1: 0.5353
sub_3:Test (Best Model) - Loss: 2.3691 - Accuracy: 0.6310 - F1: 0.5810
sub_3:Test (Best Model) - Loss: 4.5369 - Accuracy: 0.5476 - F1: 0.4458
sub_3:Test (Best Model) - Loss: 1.7059 - Accuracy: 0.6667 - F1: 0.6659
sub_3:Test (Best Model) - Loss: 1.3103 - Accuracy: 0.6429 - F1: 0.6427
sub_3:Test (Best Model) - Loss: 1.6602 - Accuracy: 0.6786 - F1: 0.6774
sub_3:Test (Best Model) - Loss: 1.2222 - Accuracy: 0.7262 - F1: 0.7252
sub_3:Test (Best Model) - Loss: 1.6417 - Accuracy: 0.7024 - F1: 0.6926
sub_3:Test (Best Model) - Loss: 2.8627 - Accuracy: 0.6190 - F1: 0.5544
sub_3:Test (Best Model) - Loss: 3.3383 - Accuracy: 0.6667 - F1: 0.6250
sub_3:Test (Best Model) - Loss: 2.7527 - Accuracy: 0.6786 - F1: 0.6415
sub_3:Test (Best Model) - Loss: 2.6906 - Accuracy: 0.6429 - F1: 0.5906
sub_3:Test (Best Model) - Loss: 2.8146 - Accuracy: 0.6786 - F1: 0.6473
sub_4:Test (Best Model) - Loss: 1.2705 - Accuracy: 0.7500 - F1: 0.7500
sub_4:Test (Best Model) - Loss: 1.5437 - Accuracy: 0.6548 - F1: 0.6487
sub_4:Test (Best Model) - Loss: 1.7135 - Accuracy: 0.7500 - F1: 0.7456
sub_4:Test (Best Model) - Loss: 1.2300 - Accuracy: 0.7381 - F1: 0.7375
sub_4:Test (Best Model) - Loss: 1.7712 - Accuracy: 0.7500 - F1: 0.7439
sub_4:Test (Best Model) - Loss: 1.6987 - Accuracy: 0.6667 - F1: 0.6571
sub_4:Test (Best Model) - Loss: 1.7586 - Accuracy: 0.6786 - F1: 0.6680
sub_4:Test (Best Model) - Loss: 0.8322 - Accuracy: 0.7976 - F1: 0.7953
sub_4:Test (Best Model) - Loss: 0.7217 - Accuracy: 0.8333 - F1: 0.8332
sub_4:Test (Best Model) - Loss: 0.7174 - Accuracy: 0.7738 - F1: 0.7735
sub_4:Test (Best Model) - Loss: 0.8171 - Accuracy: 0.7738 - F1: 0.7738
sub_4:Test (Best Model) - Loss: 0.7705 - Accuracy: 0.7857 - F1: 0.7852
sub_4:Test (Best Model) - Loss: 2.1552 - Accuracy: 0.7024 - F1: 0.6863
sub_4:Test (Best Model) - Loss: 0.8889 - Accuracy: 0.8095 - F1: 0.8068
sub_4:Test (Best Model) - Loss: 0.6146 - Accuracy: 0.8571 - F1: 0.8571
sub_5:Test (Best Model) - Loss: 0.4681 - Accuracy: 0.8929 - F1: 0.8928
sub_5:Test (Best Model) - Loss: 1.0480 - Accuracy: 0.8333 - F1: 0.8309
sub_5:Test (Best Model) - Loss: 0.6613 - Accuracy: 0.8452 - F1: 0.8434
sub_5:Test (Best Model) - Loss: 0.9062 - Accuracy: 0.8452 - F1: 0.8442
sub_5:Test (Best Model) - Loss: 1.0576 - Accuracy: 0.8452 - F1: 0.8447
sub_5:Test (Best Model) - Loss: 0.5349 - Accuracy: 0.8810 - F1: 0.8807
sub_5:Test (Best Model) - Loss: 0.4794 - Accuracy: 0.7976 - F1: 0.7974
sub_5:Test (Best Model) - Loss: 0.4293 - Accuracy: 0.8929 - F1: 0.8928
sub_5:Test (Best Model) - Loss: 0.7529 - Accuracy: 0.7976 - F1: 0.7974
sub_5:Test (Best Model) - Loss: 0.7776 - Accuracy: 0.8214 - F1: 0.8212
sub_5:Test (Best Model) - Loss: 1.0601 - Accuracy: 0.7738 - F1: 0.7664
sub_5:Test (Best Model) - Loss: 0.6524 - Accuracy: 0.8095 - F1: 0.8091
sub_5:Test (Best Model) - Loss: 0.6774 - Accuracy: 0.8810 - F1: 0.8807
sub_5:Test (Best Model) - Loss: 1.1568 - Accuracy: 0.8333 - F1: 0.8318
sub_5:Test (Best Model) - Loss: 0.6559 - Accuracy: 0.8690 - F1: 0.8675
sub_6:Test (Best Model) - Loss: 1.5211 - Accuracy: 0.7024 - F1: 0.7023
sub_6:Test (Best Model) - Loss: 1.9555 - Accuracy: 0.6310 - F1: 0.6309
sub_6:Test (Best Model) - Loss: 2.1269 - Accuracy: 0.5714 - F1: 0.5692
sub_6:Test (Best Model) - Loss: 2.0377 - Accuracy: 0.6429 - F1: 0.6427
sub_6:Test (Best Model) - Loss: 1.9432 - Accuracy: 0.6071 - F1: 0.6066
sub_6:Test (Best Model) - Loss: 1.7885 - Accuracy: 0.6667 - F1: 0.6659
sub_6:Test (Best Model) - Loss: 1.1730 - Accuracy: 0.7262 - F1: 0.7243
sub_6:Test (Best Model) - Loss: 1.7326 - Accuracy: 0.6905 - F1: 0.6889
sub_6:Test (Best Model) - Loss: 2.1370 - Accuracy: 0.6190 - F1: 0.6156
sub_6:Test (Best Model) - Loss: 1.7763 - Accuracy: 0.7024 - F1: 0.7023
sub_6:Test (Best Model) - Loss: 1.1181 - Accuracy: 0.7143 - F1: 0.7128
sub_6:Test (Best Model) - Loss: 1.2449 - Accuracy: 0.7262 - F1: 0.7258
sub_6:Test (Best Model) - Loss: 1.4187 - Accuracy: 0.7262 - F1: 0.7243
sub_6:Test (Best Model) - Loss: 1.4697 - Accuracy: 0.6190 - F1: 0.6047
sub_6:Test (Best Model) - Loss: 1.2830 - Accuracy: 0.6548 - F1: 0.6523
sub_7:Test (Best Model) - Loss: 1.8005 - Accuracy: 0.6548 - F1: 0.6361
sub_7:Test (Best Model) - Loss: 2.4105 - Accuracy: 0.5476 - F1: 0.5411
sub_7:Test (Best Model) - Loss: 3.1506 - Accuracy: 0.5833 - F1: 0.5785
sub_7:Test (Best Model) - Loss: 1.9336 - Accuracy: 0.6429 - F1: 0.6377
sub_7:Test (Best Model) - Loss: 2.2837 - Accuracy: 0.6310 - F1: 0.6245
sub_7:Test (Best Model) - Loss: 1.3113 - Accuracy: 0.5714 - F1: 0.5457
sub_7:Test (Best Model) - Loss: 0.6553 - Accuracy: 0.7500 - F1: 0.7471
sub_7:Test (Best Model) - Loss: 1.6530 - Accuracy: 0.6071 - F1: 0.5942
sub_7:Test (Best Model) - Loss: 1.5730 - Accuracy: 0.5833 - F1: 0.5828
sub_7:Test (Best Model) - Loss: 1.1611 - Accuracy: 0.6429 - F1: 0.6377
sub_7:Test (Best Model) - Loss: 1.4420 - Accuracy: 0.5595 - F1: 0.5590
sub_7:Test (Best Model) - Loss: 1.5451 - Accuracy: 0.5952 - F1: 0.5952
sub_7:Test (Best Model) - Loss: 1.3028 - Accuracy: 0.6548 - F1: 0.6463
sub_7:Test (Best Model) - Loss: 1.4250 - Accuracy: 0.6310 - F1: 0.6309
sub_7:Test (Best Model) - Loss: 1.5851 - Accuracy: 0.5238 - F1: 0.5195
sub_8:Test (Best Model) - Loss: 1.6806 - Accuracy: 0.7738 - F1: 0.7730
sub_8:Test (Best Model) - Loss: 1.2664 - Accuracy: 0.8214 - F1: 0.8212
sub_8:Test (Best Model) - Loss: 1.9466 - Accuracy: 0.7381 - F1: 0.7326
sub_8:Test (Best Model) - Loss: 1.0121 - Accuracy: 0.8095 - F1: 0.8078
sub_8:Test (Best Model) - Loss: 1.1506 - Accuracy: 0.8333 - F1: 0.8333
sub_8:Test (Best Model) - Loss: 0.8003 - Accuracy: 0.8690 - F1: 0.8689
sub_8:Test (Best Model) - Loss: 1.3340 - Accuracy: 0.7738 - F1: 0.7712
sub_8:Test (Best Model) - Loss: 1.0246 - Accuracy: 0.8333 - F1: 0.8299
sub_8:Test (Best Model) - Loss: 0.9571 - Accuracy: 0.8571 - F1: 0.8558
sub_8:Test (Best Model) - Loss: 0.8112 - Accuracy: 0.8333 - F1: 0.8309
sub_8:Test (Best Model) - Loss: 0.7481 - Accuracy: 0.8214 - F1: 0.8155
sub_8:Test (Best Model) - Loss: 0.6054 - Accuracy: 0.8333 - F1: 0.8309
sub_8:Test (Best Model) - Loss: 0.6798 - Accuracy: 0.8214 - F1: 0.8183
sub_8:Test (Best Model) - Loss: 0.1301 - Accuracy: 0.9524 - F1: 0.9524
sub_8:Test (Best Model) - Loss: 0.2988 - Accuracy: 0.9286 - F1: 0.9286
sub_9:Test (Best Model) - Loss: 1.1744 - Accuracy: 0.7262 - F1: 0.7114
sub_9:Test (Best Model) - Loss: 2.2826 - Accuracy: 0.6548 - F1: 0.6212
sub_9:Test (Best Model) - Loss: 2.4062 - Accuracy: 0.6429 - F1: 0.5982
sub_9:Test (Best Model) - Loss: 2.1842 - Accuracy: 0.7262 - F1: 0.7114
sub_9:Test (Best Model) - Loss: 2.5105 - Accuracy: 0.6786 - F1: 0.6473
sub_9:Test (Best Model) - Loss: 1.5892 - Accuracy: 0.7381 - F1: 0.7255
sub_9:Test (Best Model) - Loss: 1.2508 - Accuracy: 0.7500 - F1: 0.7456
sub_9:Test (Best Model) - Loss: 0.7460 - Accuracy: 0.7976 - F1: 0.7962
sub_9:Test (Best Model) - Loss: 0.8012 - Accuracy: 0.8214 - F1: 0.8202
sub_9:Test (Best Model) - Loss: 1.1203 - Accuracy: 0.7857 - F1: 0.7826
sub_9:Test (Best Model) - Loss: 0.9510 - Accuracy: 0.7500 - F1: 0.7365
sub_9:Test (Best Model) - Loss: 1.7040 - Accuracy: 0.7024 - F1: 0.6735
sub_9:Test (Best Model) - Loss: 1.0160 - Accuracy: 0.7500 - F1: 0.7365
sub_9:Test (Best Model) - Loss: 2.5184 - Accuracy: 0.6190 - F1: 0.5544
sub_9:Test (Best Model) - Loss: 1.5463 - Accuracy: 0.7500 - F1: 0.7333
sub_10:Test (Best Model) - Loss: 1.1152 - Accuracy: 0.6667 - F1: 0.6667
sub_10:Test (Best Model) - Loss: 1.1007 - Accuracy: 0.7024 - F1: 0.6951
sub_10:Test (Best Model) - Loss: 1.3257 - Accuracy: 0.6310 - F1: 0.6296
sub_10:Test (Best Model) - Loss: 1.9128 - Accuracy: 0.6786 - F1: 0.6707
sub_10:Test (Best Model) - Loss: 1.6895 - Accuracy: 0.6786 - F1: 0.6707
sub_10:Test (Best Model) - Loss: 1.7827 - Accuracy: 0.6786 - F1: 0.6774
sub_10:Test (Best Model) - Loss: 1.7104 - Accuracy: 0.6548 - F1: 0.6508
sub_10:Test (Best Model) - Loss: 1.4773 - Accuracy: 0.5476 - F1: 0.5453
sub_10:Test (Best Model) - Loss: 1.2573 - Accuracy: 0.6905 - F1: 0.6898
sub_10:Test (Best Model) - Loss: 1.5580 - Accuracy: 0.6667 - F1: 0.6650
sub_10:Test (Best Model) - Loss: 1.4464 - Accuracy: 0.6786 - F1: 0.6763
sub_10:Test (Best Model) - Loss: 1.7206 - Accuracy: 0.6667 - F1: 0.6665
sub_10:Test (Best Model) - Loss: 0.9065 - Accuracy: 0.7857 - F1: 0.7857
sub_10:Test (Best Model) - Loss: 1.1136 - Accuracy: 0.7024 - F1: 0.7013
sub_10:Test (Best Model) - Loss: 1.1400 - Accuracy: 0.6429 - F1: 0.6427
sub_11:Test (Best Model) - Loss: 1.3252 - Accuracy: 0.6310 - F1: 0.6309
sub_11:Test (Best Model) - Loss: 1.5155 - Accuracy: 0.6429 - F1: 0.6420
sub_11:Test (Best Model) - Loss: 1.5125 - Accuracy: 0.7500 - F1: 0.7471
sub_11:Test (Best Model) - Loss: 1.8731 - Accuracy: 0.6190 - F1: 0.6190
sub_11:Test (Best Model) - Loss: 1.6551 - Accuracy: 0.7143 - F1: 0.6971
sub_11:Test (Best Model) - Loss: 0.6122 - Accuracy: 0.8452 - F1: 0.8450
sub_11:Test (Best Model) - Loss: 0.8717 - Accuracy: 0.7143 - F1: 0.7141
sub_11:Test (Best Model) - Loss: 0.9610 - Accuracy: 0.7024 - F1: 0.7013
sub_11:Test (Best Model) - Loss: 1.1912 - Accuracy: 0.7738 - F1: 0.7664
sub_11:Test (Best Model) - Loss: 1.2958 - Accuracy: 0.7024 - F1: 0.6897
sub_11:Test (Best Model) - Loss: 1.3743 - Accuracy: 0.6786 - F1: 0.6680
sub_11:Test (Best Model) - Loss: 1.6800 - Accuracy: 0.6905 - F1: 0.6876
sub_11:Test (Best Model) - Loss: 1.4546 - Accuracy: 0.7262 - F1: 0.7258
sub_11:Test (Best Model) - Loss: 1.1013 - Accuracy: 0.7738 - F1: 0.7712
sub_11:Test (Best Model) - Loss: 1.5159 - Accuracy: 0.7262 - F1: 0.7243
sub_12:Test (Best Model) - Loss: 0.7529 - Accuracy: 0.7857 - F1: 0.7856
sub_12:Test (Best Model) - Loss: 0.4208 - Accuracy: 0.8929 - F1: 0.8925
sub_12:Test (Best Model) - Loss: 0.7040 - Accuracy: 0.8571 - F1: 0.8571
sub_12:Test (Best Model) - Loss: 0.5795 - Accuracy: 0.8810 - F1: 0.8803
sub_12:Test (Best Model) - Loss: 0.6739 - Accuracy: 0.7976 - F1: 0.7953
sub_12:Test (Best Model) - Loss: 2.1757 - Accuracy: 0.7500 - F1: 0.7418
sub_12:Test (Best Model) - Loss: 1.6476 - Accuracy: 0.7262 - F1: 0.7079
sub_12:Test (Best Model) - Loss: 1.7544 - Accuracy: 0.7857 - F1: 0.7796
sub_12:Test (Best Model) - Loss: 2.1923 - Accuracy: 0.7500 - F1: 0.7365
sub_12:Test (Best Model) - Loss: 1.2766 - Accuracy: 0.7500 - F1: 0.7439
sub_12:Test (Best Model) - Loss: 1.0869 - Accuracy: 0.7738 - F1: 0.7712
sub_12:Test (Best Model) - Loss: 0.9969 - Accuracy: 0.7976 - F1: 0.7910
sub_12:Test (Best Model) - Loss: 0.6316 - Accuracy: 0.8571 - F1: 0.8564
sub_12:Test (Best Model) - Loss: 1.3478 - Accuracy: 0.7619 - F1: 0.7607
sub_12:Test (Best Model) - Loss: 1.4176 - Accuracy: 0.7738 - F1: 0.7712
sub_13:Test (Best Model) - Loss: 0.7756 - Accuracy: 0.6667 - F1: 0.6650
sub_13:Test (Best Model) - Loss: 1.0584 - Accuracy: 0.7143 - F1: 0.7117
sub_13:Test (Best Model) - Loss: 1.1798 - Accuracy: 0.7024 - F1: 0.6951
sub_13:Test (Best Model) - Loss: 0.7151 - Accuracy: 0.7738 - F1: 0.7735
sub_13:Test (Best Model) - Loss: 0.9325 - Accuracy: 0.6905 - F1: 0.6816
sub_13:Test (Best Model) - Loss: 1.2161 - Accuracy: 0.7024 - F1: 0.6972
sub_13:Test (Best Model) - Loss: 1.0181 - Accuracy: 0.7262 - F1: 0.7230
sub_13:Test (Best Model) - Loss: 1.2433 - Accuracy: 0.7381 - F1: 0.7381
sub_13:Test (Best Model) - Loss: 1.4820 - Accuracy: 0.7143 - F1: 0.7141
sub_13:Test (Best Model) - Loss: 1.0263 - Accuracy: 0.7857 - F1: 0.7857
sub_13:Test (Best Model) - Loss: 1.1729 - Accuracy: 0.7500 - F1: 0.7393
sub_13:Test (Best Model) - Loss: 0.8942 - Accuracy: 0.6905 - F1: 0.6788
sub_13:Test (Best Model) - Loss: 1.1891 - Accuracy: 0.7262 - F1: 0.7114
sub_13:Test (Best Model) - Loss: 0.7446 - Accuracy: 0.7976 - F1: 0.7927
sub_13:Test (Best Model) - Loss: 1.0252 - Accuracy: 0.8095 - F1: 0.8085
sub_14:Test (Best Model) - Loss: 0.5804 - Accuracy: 0.8095 - F1: 0.8041
sub_14:Test (Best Model) - Loss: 1.3588 - Accuracy: 0.7381 - F1: 0.7326
sub_14:Test (Best Model) - Loss: 1.1459 - Accuracy: 0.7976 - F1: 0.7969
sub_14:Test (Best Model) - Loss: 0.9252 - Accuracy: 0.8571 - F1: 0.8568
sub_14:Test (Best Model) - Loss: 0.9795 - Accuracy: 0.7976 - F1: 0.7953
sub_14:Test (Best Model) - Loss: 0.8287 - Accuracy: 0.8214 - F1: 0.8194
sub_14:Test (Best Model) - Loss: 1.4742 - Accuracy: 0.7619 - F1: 0.7597
sub_14:Test (Best Model) - Loss: 1.6274 - Accuracy: 0.7381 - F1: 0.7381
sub_14:Test (Best Model) - Loss: 0.8931 - Accuracy: 0.7976 - F1: 0.7941
sub_14:Test (Best Model) - Loss: 1.2747 - Accuracy: 0.7619 - F1: 0.7529
sub_14:Test (Best Model) - Loss: 0.8846 - Accuracy: 0.8571 - F1: 0.8558
sub_14:Test (Best Model) - Loss: 0.4427 - Accuracy: 0.8571 - F1: 0.8571
sub_14:Test (Best Model) - Loss: 0.6207 - Accuracy: 0.7857 - F1: 0.7826
sub_14:Test (Best Model) - Loss: 1.0313 - Accuracy: 0.7619 - F1: 0.7597
sub_14:Test (Best Model) - Loss: 0.9330 - Accuracy: 0.6786 - F1: 0.6782

=== Summary Results ===

acc: 73.64 ± 6.75
F1: 72.82 ± 7.26
acc-in: 81.12 ± 6.37
F1-in: 80.73 ± 6.69
