lr: 0.001
sub_1:Test (Best Model) - Loss: 1.9629 - Accuracy: 0.7024 - F1: 0.6863
sub_1:Test (Best Model) - Loss: 2.4927 - Accuracy: 0.6667 - F1: 0.6250
sub_1:Test (Best Model) - Loss: 2.4163 - Accuracy: 0.7143 - F1: 0.6889
sub_1:Test (Best Model) - Loss: 1.7936 - Accuracy: 0.7262 - F1: 0.7114
sub_1:Test (Best Model) - Loss: 2.4437 - Accuracy: 0.6905 - F1: 0.6630
sub_1:Test (Best Model) - Loss: 2.3431 - Accuracy: 0.6310 - F1: 0.6296
sub_1:Test (Best Model) - Loss: 1.7545 - Accuracy: 0.7024 - F1: 0.6989
sub_1:Test (Best Model) - Loss: 2.1263 - Accuracy: 0.7262 - F1: 0.7258
sub_1:Test (Best Model) - Loss: 1.7789 - Accuracy: 0.6786 - F1: 0.6785
sub_1:Test (Best Model) - Loss: 1.7865 - Accuracy: 0.7500 - F1: 0.7497
sub_1:Test (Best Model) - Loss: 2.0337 - Accuracy: 0.7143 - F1: 0.6932
sub_1:Test (Best Model) - Loss: 1.7043 - Accuracy: 0.7143 - F1: 0.6889
sub_1:Test (Best Model) - Loss: 1.5174 - Accuracy: 0.6905 - F1: 0.6577
sub_1:Test (Best Model) - Loss: 2.0974 - Accuracy: 0.7262 - F1: 0.7079
sub_1:Test (Best Model) - Loss: 2.0879 - Accuracy: 0.7024 - F1: 0.6783
sub_2:Test (Best Model) - Loss: 1.5264 - Accuracy: 0.6429 - F1: 0.6377
sub_2:Test (Best Model) - Loss: 1.3345 - Accuracy: 0.6786 - F1: 0.6782
sub_2:Test (Best Model) - Loss: 1.3226 - Accuracy: 0.7143 - F1: 0.7117
sub_2:Test (Best Model) - Loss: 1.2028 - Accuracy: 0.7143 - F1: 0.7005
sub_2:Test (Best Model) - Loss: 1.5021 - Accuracy: 0.6786 - F1: 0.6612
sub_2:Test (Best Model) - Loss: 1.1132 - Accuracy: 0.6429 - F1: 0.6410
sub_2:Test (Best Model) - Loss: 1.1465 - Accuracy: 0.6310 - F1: 0.6245
sub_2:Test (Best Model) - Loss: 1.2451 - Accuracy: 0.6667 - F1: 0.6650
sub_2:Test (Best Model) - Loss: 1.2039 - Accuracy: 0.6786 - F1: 0.6730
sub_2:Test (Best Model) - Loss: 1.0790 - Accuracy: 0.6667 - F1: 0.6636
sub_2:Test (Best Model) - Loss: 2.7492 - Accuracy: 0.5952 - F1: 0.5894
sub_2:Test (Best Model) - Loss: 2.5841 - Accuracy: 0.6190 - F1: 0.6082
sub_2:Test (Best Model) - Loss: 2.0695 - Accuracy: 0.6310 - F1: 0.6284
sub_2:Test (Best Model) - Loss: 1.4895 - Accuracy: 0.7500 - F1: 0.7456
sub_2:Test (Best Model) - Loss: 1.7402 - Accuracy: 0.7381 - F1: 0.7357
sub_3:Test (Best Model) - Loss: 2.3134 - Accuracy: 0.5833 - F1: 0.5496
sub_3:Test (Best Model) - Loss: 1.7994 - Accuracy: 0.5952 - F1: 0.5654
sub_3:Test (Best Model) - Loss: 1.4213 - Accuracy: 0.6190 - F1: 0.5910
sub_3:Test (Best Model) - Loss: 1.8980 - Accuracy: 0.5833 - F1: 0.5556
sub_3:Test (Best Model) - Loss: 2.7576 - Accuracy: 0.5714 - F1: 0.4875
sub_3:Test (Best Model) - Loss: 1.3393 - Accuracy: 0.7024 - F1: 0.7020
sub_3:Test (Best Model) - Loss: 1.3460 - Accuracy: 0.7262 - F1: 0.7262
sub_3:Test (Best Model) - Loss: 1.4246 - Accuracy: 0.5714 - F1: 0.5712
sub_3:Test (Best Model) - Loss: 1.2228 - Accuracy: 0.6071 - F1: 0.6071
sub_3:Test (Best Model) - Loss: 1.0273 - Accuracy: 0.6905 - F1: 0.6903
sub_3:Test (Best Model) - Loss: 2.1942 - Accuracy: 0.6190 - F1: 0.5962
sub_3:Test (Best Model) - Loss: 2.2141 - Accuracy: 0.6429 - F1: 0.5982
sub_3:Test (Best Model) - Loss: 1.5636 - Accuracy: 0.6190 - F1: 0.6047
sub_3:Test (Best Model) - Loss: 1.0397 - Accuracy: 0.6190 - F1: 0.6171
sub_3:Test (Best Model) - Loss: 1.0286 - Accuracy: 0.7143 - F1: 0.7005
sub_4:Test (Best Model) - Loss: 2.4775 - Accuracy: 0.5952 - F1: 0.5943
sub_4:Test (Best Model) - Loss: 3.0666 - Accuracy: 0.4286 - F1: 0.4204
sub_4:Test (Best Model) - Loss: 2.0677 - Accuracy: 0.5119 - F1: 0.5102
sub_4:Test (Best Model) - Loss: 2.5869 - Accuracy: 0.4762 - F1: 0.4759
sub_4:Test (Best Model) - Loss: 2.1560 - Accuracy: 0.5357 - F1: 0.5356
sub_4:Test (Best Model) - Loss: 1.6933 - Accuracy: 0.6786 - F1: 0.6763
sub_4:Test (Best Model) - Loss: 1.6737 - Accuracy: 0.6190 - F1: 0.6188
sub_4:Test (Best Model) - Loss: 1.6870 - Accuracy: 0.5833 - F1: 0.5731
sub_4:Test (Best Model) - Loss: 1.4476 - Accuracy: 0.6071 - F1: 0.6044
sub_4:Test (Best Model) - Loss: 1.3969 - Accuracy: 0.5714 - F1: 0.5692
sub_4:Test (Best Model) - Loss: 1.5074 - Accuracy: 0.4643 - F1: 0.4605
sub_4:Test (Best Model) - Loss: 2.1903 - Accuracy: 0.5952 - F1: 0.5932
sub_4:Test (Best Model) - Loss: 1.2973 - Accuracy: 0.5952 - F1: 0.5950
sub_4:Test (Best Model) - Loss: 1.9258 - Accuracy: 0.5238 - F1: 0.5214
sub_4:Test (Best Model) - Loss: 1.7348 - Accuracy: 0.5476 - F1: 0.5476
sub_5:Test (Best Model) - Loss: 1.0129 - Accuracy: 0.6667 - F1: 0.6667
sub_5:Test (Best Model) - Loss: 1.4673 - Accuracy: 0.5119 - F1: 0.5102
sub_5:Test (Best Model) - Loss: 1.4779 - Accuracy: 0.6667 - F1: 0.6665
sub_5:Test (Best Model) - Loss: 1.5481 - Accuracy: 0.6310 - F1: 0.6284
sub_5:Test (Best Model) - Loss: 0.9780 - Accuracy: 0.6310 - F1: 0.6309
sub_5:Test (Best Model) - Loss: 1.1860 - Accuracy: 0.5595 - F1: 0.5450
sub_5:Test (Best Model) - Loss: 1.3701 - Accuracy: 0.6190 - F1: 0.6188
sub_5:Test (Best Model) - Loss: 1.1636 - Accuracy: 0.5595 - F1: 0.5580
sub_5:Test (Best Model) - Loss: 1.0148 - Accuracy: 0.6429 - F1: 0.6420
sub_5:Test (Best Model) - Loss: 1.3963 - Accuracy: 0.6429 - F1: 0.6429
sub_5:Test (Best Model) - Loss: 1.2765 - Accuracy: 0.6548 - F1: 0.6535
sub_5:Test (Best Model) - Loss: 0.9881 - Accuracy: 0.6786 - F1: 0.6782
sub_5:Test (Best Model) - Loss: 1.0779 - Accuracy: 0.7143 - F1: 0.7141
sub_5:Test (Best Model) - Loss: 1.7344 - Accuracy: 0.6429 - F1: 0.6427
sub_5:Test (Best Model) - Loss: 0.9636 - Accuracy: 0.7381 - F1: 0.7375
sub_6:Test (Best Model) - Loss: 2.2906 - Accuracy: 0.4762 - F1: 0.4735
sub_6:Test (Best Model) - Loss: 1.7248 - Accuracy: 0.5119 - F1: 0.5034
sub_6:Test (Best Model) - Loss: 3.1152 - Accuracy: 0.5238 - F1: 0.5235
sub_6:Test (Best Model) - Loss: 3.1741 - Accuracy: 0.5595 - F1: 0.5590
sub_6:Test (Best Model) - Loss: 2.5128 - Accuracy: 0.5357 - F1: 0.5356
sub_6:Test (Best Model) - Loss: 2.5752 - Accuracy: 0.6071 - F1: 0.6057
sub_6:Test (Best Model) - Loss: 2.6117 - Accuracy: 0.5476 - F1: 0.5435
sub_6:Test (Best Model) - Loss: 2.0613 - Accuracy: 0.6190 - F1: 0.6190
sub_6:Test (Best Model) - Loss: 2.6412 - Accuracy: 0.6071 - F1: 0.6066
sub_6:Test (Best Model) - Loss: 1.4063 - Accuracy: 0.5952 - F1: 0.5868
sub_6:Test (Best Model) - Loss: 1.7257 - Accuracy: 0.6071 - F1: 0.6071
sub_6:Test (Best Model) - Loss: 1.9355 - Accuracy: 0.4881 - F1: 0.4880
sub_6:Test (Best Model) - Loss: 1.3642 - Accuracy: 0.5952 - F1: 0.5943
sub_6:Test (Best Model) - Loss: 2.3603 - Accuracy: 0.5238 - F1: 0.5227
sub_6:Test (Best Model) - Loss: 2.5836 - Accuracy: 0.5000 - F1: 0.4954
sub_7:Test (Best Model) - Loss: 1.6213 - Accuracy: 0.5714 - F1: 0.5712
sub_7:Test (Best Model) - Loss: 1.6886 - Accuracy: 0.5357 - F1: 0.5325
sub_7:Test (Best Model) - Loss: 1.7309 - Accuracy: 0.5952 - F1: 0.5950
sub_7:Test (Best Model) - Loss: 1.8455 - Accuracy: 0.5833 - F1: 0.5833
sub_7:Test (Best Model) - Loss: 1.8062 - Accuracy: 0.6667 - F1: 0.6667
sub_7:Test (Best Model) - Loss: 1.8670 - Accuracy: 0.5595 - F1: 0.5590
sub_7:Test (Best Model) - Loss: 1.7906 - Accuracy: 0.5714 - F1: 0.5653
sub_7:Test (Best Model) - Loss: 2.1199 - Accuracy: 0.5000 - F1: 0.4954
sub_7:Test (Best Model) - Loss: 2.8060 - Accuracy: 0.4762 - F1: 0.4759
sub_7:Test (Best Model) - Loss: 1.5166 - Accuracy: 0.5595 - F1: 0.5544
sub_7:Test (Best Model) - Loss: 1.3890 - Accuracy: 0.5119 - F1: 0.5062
sub_7:Test (Best Model) - Loss: 1.8129 - Accuracy: 0.5357 - F1: 0.5356
sub_7:Test (Best Model) - Loss: 1.5831 - Accuracy: 0.6071 - F1: 0.6066
sub_7:Test (Best Model) - Loss: 1.5507 - Accuracy: 0.5952 - F1: 0.5943
sub_7:Test (Best Model) - Loss: 2.0895 - Accuracy: 0.4405 - F1: 0.4404
sub_8:Test (Best Model) - Loss: 1.1846 - Accuracy: 0.7619 - F1: 0.7619
sub_8:Test (Best Model) - Loss: 1.0409 - Accuracy: 0.8095 - F1: 0.8085
sub_8:Test (Best Model) - Loss: 1.4755 - Accuracy: 0.7619 - F1: 0.7597
sub_8:Test (Best Model) - Loss: 1.5438 - Accuracy: 0.7381 - F1: 0.7379
sub_8:Test (Best Model) - Loss: 1.2776 - Accuracy: 0.7381 - F1: 0.7357
sub_8:Test (Best Model) - Loss: 1.3304 - Accuracy: 0.7024 - F1: 0.6989
sub_8:Test (Best Model) - Loss: 1.4283 - Accuracy: 0.7381 - F1: 0.7381
sub_8:Test (Best Model) - Loss: 0.8802 - Accuracy: 0.7381 - F1: 0.7368
sub_8:Test (Best Model) - Loss: 1.1059 - Accuracy: 0.7143 - F1: 0.7136
sub_8:Test (Best Model) - Loss: 1.2042 - Accuracy: 0.7143 - F1: 0.7128
sub_8:Test (Best Model) - Loss: 1.2811 - Accuracy: 0.7738 - F1: 0.7730
sub_8:Test (Best Model) - Loss: 0.8755 - Accuracy: 0.6905 - F1: 0.6903
sub_8:Test (Best Model) - Loss: 0.7449 - Accuracy: 0.7500 - F1: 0.7500
sub_8:Test (Best Model) - Loss: 0.9104 - Accuracy: 0.7738 - F1: 0.7738
sub_8:Test (Best Model) - Loss: 1.6862 - Accuracy: 0.6071 - F1: 0.5975
sub_9:Test (Best Model) - Loss: 1.6357 - Accuracy: 0.6548 - F1: 0.6523
sub_9:Test (Best Model) - Loss: 2.1954 - Accuracy: 0.6190 - F1: 0.6188
sub_9:Test (Best Model) - Loss: 1.6369 - Accuracy: 0.6667 - F1: 0.6636
sub_9:Test (Best Model) - Loss: 1.9226 - Accuracy: 0.6548 - F1: 0.6535
sub_9:Test (Best Model) - Loss: 1.5951 - Accuracy: 0.6667 - F1: 0.6659
sub_9:Test (Best Model) - Loss: 2.0199 - Accuracy: 0.5595 - F1: 0.5544
sub_9:Test (Best Model) - Loss: 2.3492 - Accuracy: 0.5714 - F1: 0.5675
sub_9:Test (Best Model) - Loss: 3.2699 - Accuracy: 0.5595 - F1: 0.5580
sub_9:Test (Best Model) - Loss: 2.2468 - Accuracy: 0.5952 - F1: 0.5932
sub_9:Test (Best Model) - Loss: 1.9987 - Accuracy: 0.5595 - F1: 0.5595
sub_9:Test (Best Model) - Loss: 2.0393 - Accuracy: 0.5714 - F1: 0.5333
sub_9:Test (Best Model) - Loss: 1.6770 - Accuracy: 0.6905 - F1: 0.6788
sub_9:Test (Best Model) - Loss: 1.4051 - Accuracy: 0.6667 - F1: 0.6619
sub_9:Test (Best Model) - Loss: 1.2072 - Accuracy: 0.6190 - F1: 0.6136
sub_9:Test (Best Model) - Loss: 1.1720 - Accuracy: 0.7024 - F1: 0.6951
sub_10:Test (Best Model) - Loss: 2.2120 - Accuracy: 0.5238 - F1: 0.5235
sub_10:Test (Best Model) - Loss: 1.5286 - Accuracy: 0.6071 - F1: 0.6066
sub_10:Test (Best Model) - Loss: 1.5529 - Accuracy: 0.5833 - F1: 0.5696
sub_10:Test (Best Model) - Loss: 2.1036 - Accuracy: 0.5476 - F1: 0.5474
sub_10:Test (Best Model) - Loss: 1.7190 - Accuracy: 0.5714 - F1: 0.5712
sub_10:Test (Best Model) - Loss: 1.1240 - Accuracy: 0.5714 - F1: 0.5625
sub_10:Test (Best Model) - Loss: 1.4889 - Accuracy: 0.5476 - F1: 0.5476
sub_10:Test (Best Model) - Loss: 2.1556 - Accuracy: 0.5595 - F1: 0.5590
sub_10:Test (Best Model) - Loss: 1.6083 - Accuracy: 0.6071 - F1: 0.6066
sub_10:Test (Best Model) - Loss: 1.5713 - Accuracy: 0.6786 - F1: 0.6782
sub_10:Test (Best Model) - Loss: 1.8009 - Accuracy: 0.5833 - F1: 0.5828
sub_10:Test (Best Model) - Loss: 2.2022 - Accuracy: 0.6310 - F1: 0.6296
sub_10:Test (Best Model) - Loss: 2.0699 - Accuracy: 0.6786 - F1: 0.6707
sub_10:Test (Best Model) - Loss: 2.1126 - Accuracy: 0.6190 - F1: 0.6082
sub_10:Test (Best Model) - Loss: 1.9124 - Accuracy: 0.5952 - F1: 0.5932
sub_11:Test (Best Model) - Loss: 2.2137 - Accuracy: 0.4881 - F1: 0.4874
sub_11:Test (Best Model) - Loss: 2.0960 - Accuracy: 0.5357 - F1: 0.5325
sub_11:Test (Best Model) - Loss: 2.6146 - Accuracy: 0.5000 - F1: 0.4997
sub_11:Test (Best Model) - Loss: 2.5500 - Accuracy: 0.4405 - F1: 0.4398
sub_11:Test (Best Model) - Loss: 1.8101 - Accuracy: 0.5119 - F1: 0.5085
sub_11:Test (Best Model) - Loss: 0.9803 - Accuracy: 0.5952 - F1: 0.5952
sub_11:Test (Best Model) - Loss: 2.1234 - Accuracy: 0.6190 - F1: 0.6171
sub_11:Test (Best Model) - Loss: 1.1509 - Accuracy: 0.5952 - F1: 0.5952
sub_11:Test (Best Model) - Loss: 1.8585 - Accuracy: 0.6429 - F1: 0.6427
sub_11:Test (Best Model) - Loss: 2.0205 - Accuracy: 0.6905 - F1: 0.6889
sub_11:Test (Best Model) - Loss: 2.2946 - Accuracy: 0.5952 - F1: 0.5950
sub_11:Test (Best Model) - Loss: 1.8708 - Accuracy: 0.5595 - F1: 0.5544
sub_11:Test (Best Model) - Loss: 1.7442 - Accuracy: 0.5952 - F1: 0.5800
sub_11:Test (Best Model) - Loss: 2.1127 - Accuracy: 0.5714 - F1: 0.5653
sub_11:Test (Best Model) - Loss: 2.1649 - Accuracy: 0.6190 - F1: 0.6171
sub_12:Test (Best Model) - Loss: 2.2939 - Accuracy: 0.5476 - F1: 0.5466
sub_12:Test (Best Model) - Loss: 1.3893 - Accuracy: 0.5476 - F1: 0.5474
sub_12:Test (Best Model) - Loss: 1.1515 - Accuracy: 0.6548 - F1: 0.6535
sub_12:Test (Best Model) - Loss: 0.9526 - Accuracy: 0.7024 - F1: 0.6926
sub_12:Test (Best Model) - Loss: 1.2308 - Accuracy: 0.6667 - F1: 0.6636
sub_12:Test (Best Model) - Loss: 2.3066 - Accuracy: 0.7024 - F1: 0.6951
sub_12:Test (Best Model) - Loss: 1.5538 - Accuracy: 0.6190 - F1: 0.6082
sub_12:Test (Best Model) - Loss: 2.6532 - Accuracy: 0.6310 - F1: 0.5884
sub_12:Test (Best Model) - Loss: 1.7968 - Accuracy: 0.6310 - F1: 0.6152
sub_12:Test (Best Model) - Loss: 2.4068 - Accuracy: 0.6429 - F1: 0.6214
sub_12:Test (Best Model) - Loss: 1.5820 - Accuracy: 0.5952 - F1: 0.5943
sub_12:Test (Best Model) - Loss: 1.5178 - Accuracy: 0.6429 - F1: 0.6410
sub_12:Test (Best Model) - Loss: 1.4321 - Accuracy: 0.6786 - F1: 0.6763
sub_12:Test (Best Model) - Loss: 1.5161 - Accuracy: 0.6548 - F1: 0.6535
sub_12:Test (Best Model) - Loss: 2.0108 - Accuracy: 0.6190 - F1: 0.6047
sub_13:Test (Best Model) - Loss: 1.1815 - Accuracy: 0.6905 - F1: 0.6903
sub_13:Test (Best Model) - Loss: 1.3790 - Accuracy: 0.7024 - F1: 0.6989
sub_13:Test (Best Model) - Loss: 1.6820 - Accuracy: 0.6667 - F1: 0.6506
sub_13:Test (Best Model) - Loss: 1.6401 - Accuracy: 0.6905 - F1: 0.6840
sub_13:Test (Best Model) - Loss: 1.0516 - Accuracy: 0.7262 - F1: 0.7262
sub_13:Test (Best Model) - Loss: 1.7080 - Accuracy: 0.6548 - F1: 0.6523
sub_13:Test (Best Model) - Loss: 1.3371 - Accuracy: 0.6071 - F1: 0.6026
sub_13:Test (Best Model) - Loss: 1.3981 - Accuracy: 0.6429 - F1: 0.6410
sub_13:Test (Best Model) - Loss: 0.9869 - Accuracy: 0.7262 - F1: 0.7252
sub_13:Test (Best Model) - Loss: 1.2758 - Accuracy: 0.7024 - F1: 0.7023
sub_13:Test (Best Model) - Loss: 1.5372 - Accuracy: 0.7024 - F1: 0.7013
sub_13:Test (Best Model) - Loss: 1.4220 - Accuracy: 0.6667 - F1: 0.6650
sub_13:Test (Best Model) - Loss: 1.3228 - Accuracy: 0.6310 - F1: 0.6309
sub_13:Test (Best Model) - Loss: 1.2260 - Accuracy: 0.7619 - F1: 0.7551
sub_13:Test (Best Model) - Loss: 1.2852 - Accuracy: 0.6905 - F1: 0.6860
sub_14:Test (Best Model) - Loss: 1.5397 - Accuracy: 0.6310 - F1: 0.6245
sub_14:Test (Best Model) - Loss: 1.5883 - Accuracy: 0.7024 - F1: 0.6989
sub_14:Test (Best Model) - Loss: 1.7081 - Accuracy: 0.6429 - F1: 0.6427
sub_14:Test (Best Model) - Loss: 1.5519 - Accuracy: 0.6667 - F1: 0.6665
sub_14:Test (Best Model) - Loss: 2.0799 - Accuracy: 0.5238 - F1: 0.5170
sub_14:Test (Best Model) - Loss: 0.9495 - Accuracy: 0.7381 - F1: 0.7343
sub_14:Test (Best Model) - Loss: 1.6766 - Accuracy: 0.5238 - F1: 0.5214
sub_14:Test (Best Model) - Loss: 1.6686 - Accuracy: 0.5833 - F1: 0.5785
sub_14:Test (Best Model) - Loss: 1.4964 - Accuracy: 0.6786 - F1: 0.6774
sub_14:Test (Best Model) - Loss: 1.2144 - Accuracy: 0.6667 - F1: 0.6650
sub_14:Test (Best Model) - Loss: 1.5947 - Accuracy: 0.5595 - F1: 0.5595
sub_14:Test (Best Model) - Loss: 1.0883 - Accuracy: 0.6905 - F1: 0.6905
sub_14:Test (Best Model) - Loss: 1.2439 - Accuracy: 0.6310 - F1: 0.6245
sub_14:Test (Best Model) - Loss: 1.3999 - Accuracy: 0.6667 - F1: 0.6665
sub_14:Test (Best Model) - Loss: 1.0392 - Accuracy: 0.6310 - F1: 0.6309

=== Summary Results ===

acc: 62.72 ± 5.52
F1: 62.16 ± 5.38
acc-in: 68.71 ± 5.34
F1-in: 68.39 ± 5.38
