lr: 0.001
sub_1:Test (Best Model) - Loss: 3.0046 - Accuracy: 0.6786 - F1: 0.6525
sub_1:Test (Best Model) - Loss: 4.4996 - Accuracy: 0.7024 - F1: 0.6783
sub_1:Test (Best Model) - Loss: 4.5340 - Accuracy: 0.7024 - F1: 0.6735
sub_1:Test (Best Model) - Loss: 3.4104 - Accuracy: 0.7143 - F1: 0.7005
sub_1:Test (Best Model) - Loss: 3.5662 - Accuracy: 0.7262 - F1: 0.7079
sub_1:Test (Best Model) - Loss: 3.2972 - Accuracy: 0.6905 - F1: 0.6889
sub_1:Test (Best Model) - Loss: 1.5846 - Accuracy: 0.7500 - F1: 0.7456
sub_1:Test (Best Model) - Loss: 1.5777 - Accuracy: 0.8095 - F1: 0.8095
sub_1:Test (Best Model) - Loss: 1.6891 - Accuracy: 0.7857 - F1: 0.7838
sub_1:Test (Best Model) - Loss: 2.3309 - Accuracy: 0.7381 - F1: 0.7357
sub_1:Test (Best Model) - Loss: 2.4405 - Accuracy: 0.6905 - F1: 0.6719
sub_1:Test (Best Model) - Loss: 4.3348 - Accuracy: 0.6905 - F1: 0.6577
sub_1:Test (Best Model) - Loss: 2.9336 - Accuracy: 0.7143 - F1: 0.6889
sub_1:Test (Best Model) - Loss: 2.9682 - Accuracy: 0.6429 - F1: 0.5906
sub_1:Test (Best Model) - Loss: 2.0339 - Accuracy: 0.7143 - F1: 0.6889
sub_2:Test (Best Model) - Loss: 1.4322 - Accuracy: 0.6905 - F1: 0.6840
sub_2:Test (Best Model) - Loss: 1.3025 - Accuracy: 0.8095 - F1: 0.8078
sub_2:Test (Best Model) - Loss: 1.2438 - Accuracy: 0.7381 - F1: 0.7375
sub_2:Test (Best Model) - Loss: 1.4053 - Accuracy: 0.6190 - F1: 0.6047
sub_2:Test (Best Model) - Loss: 1.4568 - Accuracy: 0.6667 - F1: 0.6250
sub_2:Test (Best Model) - Loss: 1.1886 - Accuracy: 0.7262 - F1: 0.7252
sub_2:Test (Best Model) - Loss: 1.4140 - Accuracy: 0.7381 - F1: 0.7282
sub_2:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.8333 - F1: 0.8332
sub_2:Test (Best Model) - Loss: 1.0222 - Accuracy: 0.7738 - F1: 0.7664
sub_2:Test (Best Model) - Loss: 0.5899 - Accuracy: 0.8571 - F1: 0.8571
sub_2:Test (Best Model) - Loss: 2.1912 - Accuracy: 0.7381 - F1: 0.7368
sub_2:Test (Best Model) - Loss: 1.4434 - Accuracy: 0.7619 - F1: 0.7618
sub_2:Test (Best Model) - Loss: 2.7825 - Accuracy: 0.6429 - F1: 0.6420
sub_2:Test (Best Model) - Loss: 2.3261 - Accuracy: 0.6905 - F1: 0.6889
sub_2:Test (Best Model) - Loss: 1.4325 - Accuracy: 0.7500 - F1: 0.7491
sub_3:Test (Best Model) - Loss: 2.9148 - Accuracy: 0.5595 - F1: 0.5088
sub_3:Test (Best Model) - Loss: 3.5366 - Accuracy: 0.5357 - F1: 0.4382
sub_3:Test (Best Model) - Loss: 2.1931 - Accuracy: 0.5833 - F1: 0.5609
sub_3:Test (Best Model) - Loss: 2.2632 - Accuracy: 0.5833 - F1: 0.5353
sub_3:Test (Best Model) - Loss: 4.7384 - Accuracy: 0.5833 - F1: 0.4958
sub_3:Test (Best Model) - Loss: 1.8322 - Accuracy: 0.6905 - F1: 0.6889
sub_3:Test (Best Model) - Loss: 1.5602 - Accuracy: 0.6905 - F1: 0.6903
sub_3:Test (Best Model) - Loss: 1.4810 - Accuracy: 0.6429 - F1: 0.6427
sub_3:Test (Best Model) - Loss: 1.5409 - Accuracy: 0.7024 - F1: 0.7013
sub_3:Test (Best Model) - Loss: 1.7129 - Accuracy: 0.7024 - F1: 0.7020
sub_3:Test (Best Model) - Loss: 2.6273 - Accuracy: 0.6548 - F1: 0.6080
sub_3:Test (Best Model) - Loss: 2.2580 - Accuracy: 0.6310 - F1: 0.5810
sub_3:Test (Best Model) - Loss: 2.7948 - Accuracy: 0.6667 - F1: 0.6370
sub_3:Test (Best Model) - Loss: 3.0607 - Accuracy: 0.6905 - F1: 0.6630
sub_3:Test (Best Model) - Loss: 3.9353 - Accuracy: 0.6071 - F1: 0.5354
sub_4:Test (Best Model) - Loss: 2.5422 - Accuracy: 0.6786 - F1: 0.6774
sub_4:Test (Best Model) - Loss: 2.2860 - Accuracy: 0.5952 - F1: 0.5943
sub_4:Test (Best Model) - Loss: 2.4076 - Accuracy: 0.6786 - F1: 0.6785
sub_4:Test (Best Model) - Loss: 2.4414 - Accuracy: 0.5952 - F1: 0.5950
sub_4:Test (Best Model) - Loss: 2.3232 - Accuracy: 0.6310 - F1: 0.6267
sub_4:Test (Best Model) - Loss: 2.8398 - Accuracy: 0.6310 - F1: 0.6309
sub_4:Test (Best Model) - Loss: 0.9146 - Accuracy: 0.7857 - F1: 0.7846
sub_4:Test (Best Model) - Loss: 1.5133 - Accuracy: 0.7500 - F1: 0.7491
sub_4:Test (Best Model) - Loss: 1.1662 - Accuracy: 0.7262 - F1: 0.7230
sub_4:Test (Best Model) - Loss: 1.7792 - Accuracy: 0.6905 - F1: 0.6889
sub_4:Test (Best Model) - Loss: 1.4102 - Accuracy: 0.7143 - F1: 0.7136
sub_4:Test (Best Model) - Loss: 1.6051 - Accuracy: 0.6786 - F1: 0.6774
sub_4:Test (Best Model) - Loss: 1.8848 - Accuracy: 0.7262 - F1: 0.7252
sub_4:Test (Best Model) - Loss: 1.3962 - Accuracy: 0.7619 - F1: 0.7607
sub_4:Test (Best Model) - Loss: 1.5431 - Accuracy: 0.5714 - F1: 0.5705
sub_5:Test (Best Model) - Loss: 1.0042 - Accuracy: 0.8095 - F1: 0.8068
sub_5:Test (Best Model) - Loss: 0.8819 - Accuracy: 0.8214 - F1: 0.8212
sub_5:Test (Best Model) - Loss: 1.0148 - Accuracy: 0.7976 - F1: 0.7976
sub_5:Test (Best Model) - Loss: 1.4594 - Accuracy: 0.6905 - F1: 0.6860
sub_5:Test (Best Model) - Loss: 0.8180 - Accuracy: 0.7619 - F1: 0.7619
sub_5:Test (Best Model) - Loss: 0.8170 - Accuracy: 0.8810 - F1: 0.8799
sub_5:Test (Best Model) - Loss: 1.6541 - Accuracy: 0.7143 - F1: 0.7136
sub_5:Test (Best Model) - Loss: 0.8851 - Accuracy: 0.7619 - F1: 0.7618
sub_5:Test (Best Model) - Loss: 1.1152 - Accuracy: 0.7262 - F1: 0.7243
sub_5:Test (Best Model) - Loss: 0.8827 - Accuracy: 0.7262 - F1: 0.7262
sub_5:Test (Best Model) - Loss: 0.9217 - Accuracy: 0.8214 - F1: 0.8212
sub_5:Test (Best Model) - Loss: 1.2896 - Accuracy: 0.7619 - F1: 0.7607
sub_5:Test (Best Model) - Loss: 1.1631 - Accuracy: 0.7738 - F1: 0.7735
sub_5:Test (Best Model) - Loss: 0.5674 - Accuracy: 0.8333 - F1: 0.8333
sub_5:Test (Best Model) - Loss: 0.8884 - Accuracy: 0.6667 - F1: 0.6650
sub_6:Test (Best Model) - Loss: 2.4920 - Accuracy: 0.5238 - F1: 0.5214
sub_6:Test (Best Model) - Loss: 1.9172 - Accuracy: 0.5833 - F1: 0.5833
sub_6:Test (Best Model) - Loss: 3.2796 - Accuracy: 0.5238 - F1: 0.5102
sub_6:Test (Best Model) - Loss: 2.8030 - Accuracy: 0.6071 - F1: 0.6003
sub_6:Test (Best Model) - Loss: 3.3864 - Accuracy: 0.5357 - F1: 0.5325
sub_6:Test (Best Model) - Loss: 2.1199 - Accuracy: 0.6190 - F1: 0.6188
sub_6:Test (Best Model) - Loss: 4.1647 - Accuracy: 0.6071 - F1: 0.6057
sub_6:Test (Best Model) - Loss: 2.1957 - Accuracy: 0.6190 - F1: 0.6190
sub_6:Test (Best Model) - Loss: 2.0685 - Accuracy: 0.6071 - F1: 0.6071
sub_6:Test (Best Model) - Loss: 2.2836 - Accuracy: 0.5714 - F1: 0.5653
sub_6:Test (Best Model) - Loss: 2.0537 - Accuracy: 0.5952 - F1: 0.5943
sub_6:Test (Best Model) - Loss: 3.0178 - Accuracy: 0.5595 - F1: 0.5580
sub_6:Test (Best Model) - Loss: 1.6077 - Accuracy: 0.6667 - F1: 0.6636
sub_6:Test (Best Model) - Loss: 2.2031 - Accuracy: 0.5476 - F1: 0.5435
sub_6:Test (Best Model) - Loss: 2.4283 - Accuracy: 0.6071 - F1: 0.6026
sub_7:Test (Best Model) - Loss: 1.8932 - Accuracy: 0.6310 - F1: 0.6267
sub_7:Test (Best Model) - Loss: 2.2189 - Accuracy: 0.6190 - F1: 0.6156
sub_7:Test (Best Model) - Loss: 2.2223 - Accuracy: 0.6667 - F1: 0.6650
sub_7:Test (Best Model) - Loss: 2.9870 - Accuracy: 0.5833 - F1: 0.5804
sub_7:Test (Best Model) - Loss: 3.1626 - Accuracy: 0.6190 - F1: 0.6082
sub_7:Test (Best Model) - Loss: 2.8737 - Accuracy: 0.5833 - F1: 0.5828
sub_7:Test (Best Model) - Loss: 2.1202 - Accuracy: 0.6548 - F1: 0.6508
sub_7:Test (Best Model) - Loss: 2.4695 - Accuracy: 0.5476 - F1: 0.5306
sub_7:Test (Best Model) - Loss: 3.1639 - Accuracy: 0.5238 - F1: 0.5170
sub_7:Test (Best Model) - Loss: 2.1994 - Accuracy: 0.5952 - F1: 0.5800
sub_7:Test (Best Model) - Loss: 1.9207 - Accuracy: 0.5952 - F1: 0.5915
sub_7:Test (Best Model) - Loss: 3.1477 - Accuracy: 0.4881 - F1: 0.4880
sub_7:Test (Best Model) - Loss: 1.6893 - Accuracy: 0.5833 - F1: 0.5804
sub_7:Test (Best Model) - Loss: 2.5778 - Accuracy: 0.5000 - F1: 0.4928
sub_7:Test (Best Model) - Loss: 2.3763 - Accuracy: 0.4762 - F1: 0.4750
sub_8:Test (Best Model) - Loss: 1.6208 - Accuracy: 0.7381 - F1: 0.7379
sub_8:Test (Best Model) - Loss: 1.6602 - Accuracy: 0.7857 - F1: 0.7852
sub_8:Test (Best Model) - Loss: 1.7755 - Accuracy: 0.7857 - F1: 0.7838
sub_8:Test (Best Model) - Loss: 1.5505 - Accuracy: 0.8214 - F1: 0.8202
sub_8:Test (Best Model) - Loss: 1.1737 - Accuracy: 0.7738 - F1: 0.7722
sub_8:Test (Best Model) - Loss: 0.9520 - Accuracy: 0.8095 - F1: 0.8068
sub_8:Test (Best Model) - Loss: 1.5604 - Accuracy: 0.8214 - F1: 0.8212
sub_8:Test (Best Model) - Loss: 1.3279 - Accuracy: 0.8095 - F1: 0.8095
sub_8:Test (Best Model) - Loss: 1.0358 - Accuracy: 0.7619 - F1: 0.7569
sub_8:Test (Best Model) - Loss: 1.1295 - Accuracy: 0.7619 - F1: 0.7618
sub_8:Test (Best Model) - Loss: 0.6428 - Accuracy: 0.8690 - F1: 0.8686
sub_8:Test (Best Model) - Loss: 0.8775 - Accuracy: 0.8095 - F1: 0.8094
sub_8:Test (Best Model) - Loss: 1.4421 - Accuracy: 0.8452 - F1: 0.8434
sub_8:Test (Best Model) - Loss: 0.5569 - Accuracy: 0.9048 - F1: 0.9048
sub_8:Test (Best Model) - Loss: 1.0497 - Accuracy: 0.7976 - F1: 0.7974
sub_9:Test (Best Model) - Loss: 2.1574 - Accuracy: 0.6190 - F1: 0.6136
sub_9:Test (Best Model) - Loss: 1.7957 - Accuracy: 0.6667 - F1: 0.6650
sub_9:Test (Best Model) - Loss: 1.7875 - Accuracy: 0.6786 - F1: 0.6648
sub_9:Test (Best Model) - Loss: 2.9716 - Accuracy: 0.6190 - F1: 0.6136
sub_9:Test (Best Model) - Loss: 1.2337 - Accuracy: 0.7143 - F1: 0.7102
sub_9:Test (Best Model) - Loss: 2.0724 - Accuracy: 0.6667 - F1: 0.6667
sub_9:Test (Best Model) - Loss: 1.3165 - Accuracy: 0.6905 - F1: 0.6898
sub_9:Test (Best Model) - Loss: 2.0556 - Accuracy: 0.6310 - F1: 0.6309
sub_9:Test (Best Model) - Loss: 1.0513 - Accuracy: 0.7381 - F1: 0.7379
sub_9:Test (Best Model) - Loss: 1.6667 - Accuracy: 0.6905 - F1: 0.6898
sub_9:Test (Best Model) - Loss: 1.8457 - Accuracy: 0.7024 - F1: 0.6825
sub_9:Test (Best Model) - Loss: 1.6234 - Accuracy: 0.7381 - F1: 0.7255
sub_9:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.7143 - F1: 0.7061
sub_9:Test (Best Model) - Loss: 1.5269 - Accuracy: 0.6667 - F1: 0.6250
sub_9:Test (Best Model) - Loss: 1.8873 - Accuracy: 0.7500 - F1: 0.7333
sub_10:Test (Best Model) - Loss: 2.4790 - Accuracy: 0.5357 - F1: 0.5356
sub_10:Test (Best Model) - Loss: 1.5769 - Accuracy: 0.6071 - F1: 0.6026
sub_10:Test (Best Model) - Loss: 2.1817 - Accuracy: 0.5952 - F1: 0.5868
sub_10:Test (Best Model) - Loss: 2.3403 - Accuracy: 0.6905 - F1: 0.6816
sub_10:Test (Best Model) - Loss: 2.2864 - Accuracy: 0.5833 - F1: 0.5731
sub_10:Test (Best Model) - Loss: 1.4125 - Accuracy: 0.6429 - F1: 0.6420
sub_10:Test (Best Model) - Loss: 1.6509 - Accuracy: 0.6429 - F1: 0.6427
sub_10:Test (Best Model) - Loss: 2.7477 - Accuracy: 0.5714 - F1: 0.5712
sub_10:Test (Best Model) - Loss: 2.1979 - Accuracy: 0.5952 - F1: 0.5932
sub_10:Test (Best Model) - Loss: 2.1108 - Accuracy: 0.6548 - F1: 0.6535
sub_10:Test (Best Model) - Loss: 2.6024 - Accuracy: 0.5833 - F1: 0.5828
sub_10:Test (Best Model) - Loss: 1.3197 - Accuracy: 0.6667 - F1: 0.6650
sub_10:Test (Best Model) - Loss: 2.0391 - Accuracy: 0.6548 - F1: 0.6535
sub_10:Test (Best Model) - Loss: 1.8924 - Accuracy: 0.6310 - F1: 0.6305
sub_10:Test (Best Model) - Loss: 2.7126 - Accuracy: 0.5833 - F1: 0.5761
sub_11:Test (Best Model) - Loss: 2.8659 - Accuracy: 0.5476 - F1: 0.5435
sub_11:Test (Best Model) - Loss: 1.5727 - Accuracy: 0.5357 - F1: 0.5351
sub_11:Test (Best Model) - Loss: 2.0946 - Accuracy: 0.6071 - F1: 0.5904
sub_11:Test (Best Model) - Loss: 2.1053 - Accuracy: 0.5476 - F1: 0.5474
sub_11:Test (Best Model) - Loss: 1.4997 - Accuracy: 0.6786 - F1: 0.6763
sub_11:Test (Best Model) - Loss: 1.3929 - Accuracy: 0.6905 - F1: 0.6903
sub_11:Test (Best Model) - Loss: 1.8151 - Accuracy: 0.6667 - F1: 0.6665
sub_11:Test (Best Model) - Loss: 1.0129 - Accuracy: 0.7857 - F1: 0.7856
sub_11:Test (Best Model) - Loss: 1.6341 - Accuracy: 0.7143 - F1: 0.7128
sub_11:Test (Best Model) - Loss: 1.8362 - Accuracy: 0.6429 - F1: 0.6410
sub_11:Test (Best Model) - Loss: 1.6852 - Accuracy: 0.6548 - F1: 0.6543
sub_11:Test (Best Model) - Loss: 1.5132 - Accuracy: 0.6310 - F1: 0.6267
sub_11:Test (Best Model) - Loss: 1.5877 - Accuracy: 0.6786 - F1: 0.6785
sub_11:Test (Best Model) - Loss: 1.5286 - Accuracy: 0.6429 - F1: 0.6377
sub_11:Test (Best Model) - Loss: 1.5687 - Accuracy: 0.6667 - F1: 0.6665
sub_12:Test (Best Model) - Loss: 1.3314 - Accuracy: 0.7143 - F1: 0.7128
sub_12:Test (Best Model) - Loss: 1.2300 - Accuracy: 0.7024 - F1: 0.6926
sub_12:Test (Best Model) - Loss: 1.0869 - Accuracy: 0.7024 - F1: 0.7003
sub_12:Test (Best Model) - Loss: 1.1833 - Accuracy: 0.7738 - F1: 0.7683
sub_12:Test (Best Model) - Loss: 1.6686 - Accuracy: 0.6905 - F1: 0.6898
sub_12:Test (Best Model) - Loss: 2.3456 - Accuracy: 0.7024 - F1: 0.6825
sub_12:Test (Best Model) - Loss: 2.9950 - Accuracy: 0.6667 - F1: 0.6466
sub_12:Test (Best Model) - Loss: 1.9559 - Accuracy: 0.7262 - F1: 0.7145
sub_12:Test (Best Model) - Loss: 2.1334 - Accuracy: 0.7500 - F1: 0.7439
sub_12:Test (Best Model) - Loss: 3.3066 - Accuracy: 0.6429 - F1: 0.6166
sub_12:Test (Best Model) - Loss: 1.1113 - Accuracy: 0.7262 - F1: 0.7145
sub_12:Test (Best Model) - Loss: 0.7564 - Accuracy: 0.8214 - F1: 0.8214
sub_12:Test (Best Model) - Loss: 1.2987 - Accuracy: 0.7976 - F1: 0.7941
sub_12:Test (Best Model) - Loss: 1.6329 - Accuracy: 0.7619 - F1: 0.7618
sub_12:Test (Best Model) - Loss: 2.2927 - Accuracy: 0.7143 - F1: 0.7061
sub_13:Test (Best Model) - Loss: 1.2349 - Accuracy: 0.6548 - F1: 0.6508
sub_13:Test (Best Model) - Loss: 1.5097 - Accuracy: 0.6786 - F1: 0.6748
sub_13:Test (Best Model) - Loss: 2.7561 - Accuracy: 0.6905 - F1: 0.6756
sub_13:Test (Best Model) - Loss: 2.0884 - Accuracy: 0.6667 - F1: 0.6659
sub_13:Test (Best Model) - Loss: 1.3260 - Accuracy: 0.7143 - F1: 0.7128
sub_13:Test (Best Model) - Loss: 4.2383 - Accuracy: 0.6071 - F1: 0.6026
sub_13:Test (Best Model) - Loss: 1.9247 - Accuracy: 0.7143 - F1: 0.7136
sub_13:Test (Best Model) - Loss: 2.0487 - Accuracy: 0.5952 - F1: 0.5932
sub_13:Test (Best Model) - Loss: 2.0540 - Accuracy: 0.6667 - F1: 0.6619
sub_13:Test (Best Model) - Loss: 1.6587 - Accuracy: 0.7381 - F1: 0.7375
sub_13:Test (Best Model) - Loss: 1.6843 - Accuracy: 0.6786 - F1: 0.6680
sub_13:Test (Best Model) - Loss: 1.4970 - Accuracy: 0.7143 - F1: 0.7083
sub_13:Test (Best Model) - Loss: 2.3499 - Accuracy: 0.7976 - F1: 0.7974
sub_13:Test (Best Model) - Loss: 1.2099 - Accuracy: 0.7619 - F1: 0.7597
sub_13:Test (Best Model) - Loss: 2.2613 - Accuracy: 0.7738 - F1: 0.7722
sub_14:Test (Best Model) - Loss: 1.2454 - Accuracy: 0.7500 - F1: 0.7497
sub_14:Test (Best Model) - Loss: 2.7124 - Accuracy: 0.5476 - F1: 0.5347
sub_14:Test (Best Model) - Loss: 1.5426 - Accuracy: 0.7381 - F1: 0.7368
sub_14:Test (Best Model) - Loss: 3.2757 - Accuracy: 0.6190 - F1: 0.6188
sub_14:Test (Best Model) - Loss: 1.6249 - Accuracy: 0.7262 - F1: 0.7258
sub_14:Test (Best Model) - Loss: 0.7868 - Accuracy: 0.8452 - F1: 0.8442
sub_14:Test (Best Model) - Loss: 1.5528 - Accuracy: 0.7857 - F1: 0.7826
sub_14:Test (Best Model) - Loss: 1.1548 - Accuracy: 0.7500 - F1: 0.7483
sub_14:Test (Best Model) - Loss: 2.1697 - Accuracy: 0.7024 - F1: 0.6951
sub_14:Test (Best Model) - Loss: 0.8171 - Accuracy: 0.7857 - F1: 0.7852
sub_14:Test (Best Model) - Loss: 1.2560 - Accuracy: 0.7262 - F1: 0.7214
sub_14:Test (Best Model) - Loss: 1.0862 - Accuracy: 0.7619 - F1: 0.7597
sub_14:Test (Best Model) - Loss: 1.1384 - Accuracy: 0.6310 - F1: 0.6296
sub_14:Test (Best Model) - Loss: 1.3380 - Accuracy: 0.7024 - F1: 0.7013
sub_14:Test (Best Model) - Loss: 0.9542 - Accuracy: 0.7500 - F1: 0.7491

=== Summary Results ===

acc: 68.57 ± 6.49
F1: 67.84 ± 6.71
acc-in: 74.96 ± 6.50
F1-in: 74.66 ± 6.59
