lr: 1e-05
sub_1:Test (Best Model) - Loss: 0.6439 - Accuracy: 0.7381 - F1: 0.7188
sub_1:Test (Best Model) - Loss: 0.6442 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 0.6375 - Accuracy: 0.7143 - F1: 0.6889
sub_1:Test (Best Model) - Loss: 0.5898 - Accuracy: 0.7500 - F1: 0.7333
sub_1:Test (Best Model) - Loss: 0.6323 - Accuracy: 0.6905 - F1: 0.6677
sub_1:Test (Best Model) - Loss: 0.4667 - Accuracy: 0.8333 - F1: 0.8325
sub_1:Test (Best Model) - Loss: 0.3896 - Accuracy: 0.8690 - F1: 0.8681
sub_1:Test (Best Model) - Loss: 0.4192 - Accuracy: 0.8095 - F1: 0.8094
sub_1:Test (Best Model) - Loss: 0.4095 - Accuracy: 0.8214 - F1: 0.8214
sub_1:Test (Best Model) - Loss: 0.3962 - Accuracy: 0.8452 - F1: 0.8447
sub_1:Test (Best Model) - Loss: 0.5673 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 0.5396 - Accuracy: 0.7738 - F1: 0.7616
sub_1:Test (Best Model) - Loss: 0.4836 - Accuracy: 0.7500 - F1: 0.7333
sub_1:Test (Best Model) - Loss: 0.5859 - Accuracy: 0.7024 - F1: 0.6735
sub_1:Test (Best Model) - Loss: 0.5212 - Accuracy: 0.7262 - F1: 0.7040
sub_2:Test (Best Model) - Loss: 0.3402 - Accuracy: 0.9167 - F1: 0.9167
sub_2:Test (Best Model) - Loss: 0.3672 - Accuracy: 0.8810 - F1: 0.8810
sub_2:Test (Best Model) - Loss: 0.3538 - Accuracy: 0.8929 - F1: 0.8928
sub_2:Test (Best Model) - Loss: 0.4215 - Accuracy: 0.8571 - F1: 0.8564
sub_2:Test (Best Model) - Loss: 0.4183 - Accuracy: 0.8929 - F1: 0.8921
sub_2:Test (Best Model) - Loss: 0.3752 - Accuracy: 0.8214 - F1: 0.8155
sub_2:Test (Best Model) - Loss: 0.4006 - Accuracy: 0.7857 - F1: 0.7754
sub_2:Test (Best Model) - Loss: 0.3304 - Accuracy: 0.8333 - F1: 0.8286
sub_2:Test (Best Model) - Loss: 0.3572 - Accuracy: 0.7619 - F1: 0.7476
sub_2:Test (Best Model) - Loss: 0.3874 - Accuracy: 0.8095 - F1: 0.8024
sub_2:Test (Best Model) - Loss: 0.3588 - Accuracy: 0.8690 - F1: 0.8668
sub_2:Test (Best Model) - Loss: 0.3281 - Accuracy: 0.8810 - F1: 0.8803
sub_2:Test (Best Model) - Loss: 0.3736 - Accuracy: 0.8452 - F1: 0.8434
sub_2:Test (Best Model) - Loss: 0.2826 - Accuracy: 0.8929 - F1: 0.8916
sub_2:Test (Best Model) - Loss: 0.3920 - Accuracy: 0.8452 - F1: 0.8434
sub_3:Test (Best Model) - Loss: 0.7229 - Accuracy: 0.6429 - F1: 0.5982
sub_3:Test (Best Model) - Loss: 0.7664 - Accuracy: 0.5833 - F1: 0.5073
sub_3:Test (Best Model) - Loss: 0.6117 - Accuracy: 0.6310 - F1: 0.5810
sub_3:Test (Best Model) - Loss: 0.7726 - Accuracy: 0.5714 - F1: 0.4875
sub_3:Test (Best Model) - Loss: 0.9638 - Accuracy: 0.5595 - F1: 0.4535
sub_3:Test (Best Model) - Loss: 0.4110 - Accuracy: 0.7976 - F1: 0.7976
sub_3:Test (Best Model) - Loss: 0.4976 - Accuracy: 0.7381 - F1: 0.7375
sub_3:Test (Best Model) - Loss: 0.4982 - Accuracy: 0.7500 - F1: 0.7500
sub_3:Test (Best Model) - Loss: 0.5119 - Accuracy: 0.7500 - F1: 0.7491
sub_3:Test (Best Model) - Loss: 0.4962 - Accuracy: 0.7143 - F1: 0.7141
sub_3:Test (Best Model) - Loss: 0.7675 - Accuracy: 0.7262 - F1: 0.7040
sub_3:Test (Best Model) - Loss: 0.6622 - Accuracy: 0.6548 - F1: 0.6080
sub_3:Test (Best Model) - Loss: 0.6354 - Accuracy: 0.7143 - F1: 0.6889
sub_3:Test (Best Model) - Loss: 0.6092 - Accuracy: 0.7024 - F1: 0.6783
sub_3:Test (Best Model) - Loss: 0.6100 - Accuracy: 0.7024 - F1: 0.6735
sub_4:Test (Best Model) - Loss: 0.4700 - Accuracy: 0.8095 - F1: 0.8095
sub_4:Test (Best Model) - Loss: 0.4600 - Accuracy: 0.8214 - F1: 0.8212
sub_4:Test (Best Model) - Loss: 0.5412 - Accuracy: 0.7976 - F1: 0.7976
sub_4:Test (Best Model) - Loss: 0.4913 - Accuracy: 0.7857 - F1: 0.7857
sub_4:Test (Best Model) - Loss: 0.4801 - Accuracy: 0.7976 - F1: 0.7974
sub_4:Test (Best Model) - Loss: 0.4725 - Accuracy: 0.7976 - F1: 0.7962
sub_4:Test (Best Model) - Loss: 0.4502 - Accuracy: 0.7500 - F1: 0.7471
sub_4:Test (Best Model) - Loss: 0.4451 - Accuracy: 0.8095 - F1: 0.8085
sub_4:Test (Best Model) - Loss: 0.3802 - Accuracy: 0.8571 - F1: 0.8571
sub_4:Test (Best Model) - Loss: 0.4641 - Accuracy: 0.7381 - F1: 0.7357
sub_4:Test (Best Model) - Loss: 0.5019 - Accuracy: 0.7143 - F1: 0.6889
sub_4:Test (Best Model) - Loss: 0.5189 - Accuracy: 0.7381 - F1: 0.7188
sub_4:Test (Best Model) - Loss: 0.4773 - Accuracy: 0.7738 - F1: 0.7641
sub_4:Test (Best Model) - Loss: 0.5269 - Accuracy: 0.7381 - F1: 0.7255
sub_4:Test (Best Model) - Loss: 0.4366 - Accuracy: 0.8095 - F1: 0.8068
sub_5:Test (Best Model) - Loss: 0.3339 - Accuracy: 0.8810 - F1: 0.8809
sub_5:Test (Best Model) - Loss: 0.3628 - Accuracy: 0.8571 - F1: 0.8568
sub_5:Test (Best Model) - Loss: 0.3408 - Accuracy: 0.8929 - F1: 0.8925
sub_5:Test (Best Model) - Loss: 0.3400 - Accuracy: 0.8690 - F1: 0.8689
sub_5:Test (Best Model) - Loss: 0.3697 - Accuracy: 0.8571 - F1: 0.8564
sub_5:Test (Best Model) - Loss: 0.4440 - Accuracy: 0.8095 - F1: 0.8024
sub_5:Test (Best Model) - Loss: 0.4350 - Accuracy: 0.7738 - F1: 0.7616
sub_5:Test (Best Model) - Loss: 0.3860 - Accuracy: 0.7976 - F1: 0.7953
sub_5:Test (Best Model) - Loss: 0.4078 - Accuracy: 0.8214 - F1: 0.8155
sub_5:Test (Best Model) - Loss: 0.3937 - Accuracy: 0.8095 - F1: 0.8068
sub_5:Test (Best Model) - Loss: 0.3698 - Accuracy: 0.7857 - F1: 0.7812
sub_5:Test (Best Model) - Loss: 0.3193 - Accuracy: 0.8571 - F1: 0.8564
sub_5:Test (Best Model) - Loss: 0.2935 - Accuracy: 0.8929 - F1: 0.8927
sub_5:Test (Best Model) - Loss: 0.4059 - Accuracy: 0.7500 - F1: 0.7393
sub_5:Test (Best Model) - Loss: 0.3264 - Accuracy: 0.8929 - F1: 0.8925
sub_6:Test (Best Model) - Loss: 0.6198 - Accuracy: 0.7024 - F1: 0.7020
sub_6:Test (Best Model) - Loss: 0.5868 - Accuracy: 0.6548 - F1: 0.6523
sub_6:Test (Best Model) - Loss: 0.6651 - Accuracy: 0.6310 - F1: 0.6305
sub_6:Test (Best Model) - Loss: 0.6418 - Accuracy: 0.6548 - F1: 0.6523
sub_6:Test (Best Model) - Loss: 0.5924 - Accuracy: 0.6667 - F1: 0.6659
sub_6:Test (Best Model) - Loss: 0.6078 - Accuracy: 0.6190 - F1: 0.6190
sub_6:Test (Best Model) - Loss: 0.6300 - Accuracy: 0.6310 - F1: 0.6267
sub_6:Test (Best Model) - Loss: 0.5615 - Accuracy: 0.7143 - F1: 0.7143
sub_6:Test (Best Model) - Loss: 0.6089 - Accuracy: 0.6905 - F1: 0.6889
sub_6:Test (Best Model) - Loss: 0.5496 - Accuracy: 0.7143 - F1: 0.7117
sub_6:Test (Best Model) - Loss: 0.5870 - Accuracy: 0.6667 - F1: 0.6667
sub_6:Test (Best Model) - Loss: 0.5563 - Accuracy: 0.7381 - F1: 0.7379
sub_6:Test (Best Model) - Loss: 0.4837 - Accuracy: 0.7857 - F1: 0.7856
sub_6:Test (Best Model) - Loss: 0.6235 - Accuracy: 0.6190 - F1: 0.6190
sub_6:Test (Best Model) - Loss: 0.5651 - Accuracy: 0.6905 - F1: 0.6898
sub_7:Test (Best Model) - Loss: 0.6279 - Accuracy: 0.6667 - F1: 0.6636
sub_7:Test (Best Model) - Loss: 0.7062 - Accuracy: 0.5595 - F1: 0.5595
sub_7:Test (Best Model) - Loss: 0.7108 - Accuracy: 0.5952 - F1: 0.5915
sub_7:Test (Best Model) - Loss: 0.7178 - Accuracy: 0.6310 - F1: 0.6152
sub_7:Test (Best Model) - Loss: 0.6698 - Accuracy: 0.5595 - F1: 0.5590
sub_7:Test (Best Model) - Loss: 0.6377 - Accuracy: 0.6190 - F1: 0.5852
sub_7:Test (Best Model) - Loss: 0.5808 - Accuracy: 0.6905 - F1: 0.6677
sub_7:Test (Best Model) - Loss: 0.6083 - Accuracy: 0.6310 - F1: 0.6219
sub_7:Test (Best Model) - Loss: 0.6611 - Accuracy: 0.5714 - F1: 0.5675
sub_7:Test (Best Model) - Loss: 0.5966 - Accuracy: 0.6786 - F1: 0.6473
sub_7:Test (Best Model) - Loss: 0.5858 - Accuracy: 0.6667 - F1: 0.6659
sub_7:Test (Best Model) - Loss: 0.7092 - Accuracy: 0.5833 - F1: 0.5819
sub_7:Test (Best Model) - Loss: 0.6073 - Accuracy: 0.6071 - F1: 0.6044
sub_7:Test (Best Model) - Loss: 0.6698 - Accuracy: 0.6071 - F1: 0.6026
sub_7:Test (Best Model) - Loss: 0.6282 - Accuracy: 0.6310 - F1: 0.6188
sub_8:Test (Best Model) - Loss: 0.3489 - Accuracy: 0.8690 - F1: 0.8686
sub_8:Test (Best Model) - Loss: 0.3797 - Accuracy: 0.8095 - F1: 0.8094
sub_8:Test (Best Model) - Loss: 0.3652 - Accuracy: 0.8571 - F1: 0.8568
sub_8:Test (Best Model) - Loss: 0.3471 - Accuracy: 0.8452 - F1: 0.8450
sub_8:Test (Best Model) - Loss: 0.3484 - Accuracy: 0.8571 - F1: 0.8571
sub_8:Test (Best Model) - Loss: 0.2651 - Accuracy: 0.9286 - F1: 0.9284
sub_8:Test (Best Model) - Loss: 0.3017 - Accuracy: 0.8810 - F1: 0.8792
sub_8:Test (Best Model) - Loss: 0.2617 - Accuracy: 0.9286 - F1: 0.9285
sub_8:Test (Best Model) - Loss: 0.2782 - Accuracy: 0.8810 - F1: 0.8803
sub_8:Test (Best Model) - Loss: 0.2815 - Accuracy: 0.9167 - F1: 0.9164
sub_8:Test (Best Model) - Loss: 0.2532 - Accuracy: 0.9167 - F1: 0.9161
sub_8:Test (Best Model) - Loss: 0.2859 - Accuracy: 0.8810 - F1: 0.8792
sub_8:Test (Best Model) - Loss: 0.2567 - Accuracy: 0.8810 - F1: 0.8799
sub_8:Test (Best Model) - Loss: 0.2269 - Accuracy: 0.9405 - F1: 0.9403
sub_8:Test (Best Model) - Loss: 0.2533 - Accuracy: 0.8929 - F1: 0.8925
sub_9:Test (Best Model) - Loss: 0.4220 - Accuracy: 0.8095 - F1: 0.8091
sub_9:Test (Best Model) - Loss: 0.4028 - Accuracy: 0.8333 - F1: 0.8330
sub_9:Test (Best Model) - Loss: 0.4018 - Accuracy: 0.7976 - F1: 0.7941
sub_9:Test (Best Model) - Loss: 0.4609 - Accuracy: 0.7738 - F1: 0.7699
sub_9:Test (Best Model) - Loss: 0.4528 - Accuracy: 0.7738 - F1: 0.7664
sub_9:Test (Best Model) - Loss: 0.4511 - Accuracy: 0.8095 - F1: 0.8078
sub_9:Test (Best Model) - Loss: 0.4696 - Accuracy: 0.7976 - F1: 0.7962
sub_9:Test (Best Model) - Loss: 0.4894 - Accuracy: 0.7381 - F1: 0.7379
sub_9:Test (Best Model) - Loss: 0.4500 - Accuracy: 0.8333 - F1: 0.8325
sub_9:Test (Best Model) - Loss: 0.4025 - Accuracy: 0.8095 - F1: 0.8095
sub_9:Test (Best Model) - Loss: 0.6043 - Accuracy: 0.7024 - F1: 0.6735
sub_9:Test (Best Model) - Loss: 0.5400 - Accuracy: 0.7024 - F1: 0.6735
sub_9:Test (Best Model) - Loss: 0.4754 - Accuracy: 0.7500 - F1: 0.7333
sub_9:Test (Best Model) - Loss: 0.5170 - Accuracy: 0.7024 - F1: 0.6783
sub_9:Test (Best Model) - Loss: 0.5295 - Accuracy: 0.6786 - F1: 0.6415
sub_10:Test (Best Model) - Loss: 0.5970 - Accuracy: 0.6429 - F1: 0.6427
sub_10:Test (Best Model) - Loss: 0.6055 - Accuracy: 0.6429 - F1: 0.6420
sub_10:Test (Best Model) - Loss: 0.5948 - Accuracy: 0.7024 - F1: 0.6989
sub_10:Test (Best Model) - Loss: 0.6127 - Accuracy: 0.6905 - F1: 0.6876
sub_10:Test (Best Model) - Loss: 0.5838 - Accuracy: 0.6429 - F1: 0.6420
sub_10:Test (Best Model) - Loss: 0.5819 - Accuracy: 0.6667 - F1: 0.6667
sub_10:Test (Best Model) - Loss: 0.6242 - Accuracy: 0.5833 - F1: 0.5833
sub_10:Test (Best Model) - Loss: 0.5979 - Accuracy: 0.6310 - F1: 0.6284
sub_10:Test (Best Model) - Loss: 0.5853 - Accuracy: 0.6786 - F1: 0.6730
sub_10:Test (Best Model) - Loss: 0.5981 - Accuracy: 0.7024 - F1: 0.7023
sub_10:Test (Best Model) - Loss: 0.6138 - Accuracy: 0.6667 - F1: 0.6659
sub_10:Test (Best Model) - Loss: 0.4900 - Accuracy: 0.7500 - F1: 0.7483
sub_10:Test (Best Model) - Loss: 0.5006 - Accuracy: 0.7500 - F1: 0.7491
sub_10:Test (Best Model) - Loss: 0.6439 - Accuracy: 0.6429 - F1: 0.6377
sub_10:Test (Best Model) - Loss: 0.5271 - Accuracy: 0.7262 - F1: 0.7258
sub_11:Test (Best Model) - Loss: 0.5226 - Accuracy: 0.7262 - F1: 0.7243
sub_11:Test (Best Model) - Loss: 0.5650 - Accuracy: 0.6667 - F1: 0.6650
sub_11:Test (Best Model) - Loss: 0.5863 - Accuracy: 0.7024 - F1: 0.7020
sub_11:Test (Best Model) - Loss: 0.6240 - Accuracy: 0.6905 - F1: 0.6905
sub_11:Test (Best Model) - Loss: 0.5182 - Accuracy: 0.7500 - F1: 0.7500
sub_11:Test (Best Model) - Loss: 0.4326 - Accuracy: 0.8095 - F1: 0.8085
sub_11:Test (Best Model) - Loss: 0.4494 - Accuracy: 0.7857 - F1: 0.7852
sub_11:Test (Best Model) - Loss: 0.4178 - Accuracy: 0.7976 - F1: 0.7969
sub_11:Test (Best Model) - Loss: 0.4448 - Accuracy: 0.7976 - F1: 0.7969
sub_11:Test (Best Model) - Loss: 0.4613 - Accuracy: 0.7500 - F1: 0.7491
sub_11:Test (Best Model) - Loss: 0.4925 - Accuracy: 0.7143 - F1: 0.6971
sub_11:Test (Best Model) - Loss: 0.5520 - Accuracy: 0.7262 - F1: 0.7172
sub_11:Test (Best Model) - Loss: 0.4653 - Accuracy: 0.7738 - F1: 0.7722
sub_11:Test (Best Model) - Loss: 0.4412 - Accuracy: 0.7619 - F1: 0.7569
sub_11:Test (Best Model) - Loss: 0.4874 - Accuracy: 0.7619 - F1: 0.7618
sub_12:Test (Best Model) - Loss: 0.4389 - Accuracy: 0.7500 - F1: 0.7500
sub_12:Test (Best Model) - Loss: 0.3090 - Accuracy: 0.9048 - F1: 0.9048
sub_12:Test (Best Model) - Loss: 0.3501 - Accuracy: 0.8452 - F1: 0.8447
sub_12:Test (Best Model) - Loss: 0.3056 - Accuracy: 0.9048 - F1: 0.9047
sub_12:Test (Best Model) - Loss: 0.4040 - Accuracy: 0.8095 - F1: 0.8094
sub_12:Test (Best Model) - Loss: 0.5033 - Accuracy: 0.7619 - F1: 0.7504
sub_12:Test (Best Model) - Loss: 0.4586 - Accuracy: 0.7500 - F1: 0.7393
sub_12:Test (Best Model) - Loss: 0.5320 - Accuracy: 0.7381 - F1: 0.7224
sub_12:Test (Best Model) - Loss: 0.5280 - Accuracy: 0.7738 - F1: 0.7641
sub_12:Test (Best Model) - Loss: 0.5275 - Accuracy: 0.7262 - F1: 0.7172
sub_12:Test (Best Model) - Loss: 0.4460 - Accuracy: 0.7619 - F1: 0.7504
sub_12:Test (Best Model) - Loss: 0.4541 - Accuracy: 0.7619 - F1: 0.7476
sub_12:Test (Best Model) - Loss: 0.4043 - Accuracy: 0.8333 - F1: 0.8299
sub_12:Test (Best Model) - Loss: 0.3746 - Accuracy: 0.8095 - F1: 0.8041
sub_12:Test (Best Model) - Loss: 0.4700 - Accuracy: 0.7857 - F1: 0.7776
sub_13:Test (Best Model) - Loss: 0.5725 - Accuracy: 0.6905 - F1: 0.6903
sub_13:Test (Best Model) - Loss: 0.5717 - Accuracy: 0.7262 - F1: 0.7243
sub_13:Test (Best Model) - Loss: 0.5395 - Accuracy: 0.7143 - F1: 0.7117
sub_13:Test (Best Model) - Loss: 0.5383 - Accuracy: 0.7500 - F1: 0.7491
sub_13:Test (Best Model) - Loss: 0.5227 - Accuracy: 0.7738 - F1: 0.7735
sub_13:Test (Best Model) - Loss: 0.5305 - Accuracy: 0.7381 - F1: 0.7343
sub_13:Test (Best Model) - Loss: 0.5104 - Accuracy: 0.7143 - F1: 0.7102
sub_13:Test (Best Model) - Loss: 0.5132 - Accuracy: 0.7262 - F1: 0.7230
sub_13:Test (Best Model) - Loss: 0.4847 - Accuracy: 0.7857 - F1: 0.7852
sub_13:Test (Best Model) - Loss: 0.4453 - Accuracy: 0.7857 - F1: 0.7856
sub_13:Test (Best Model) - Loss: 0.5000 - Accuracy: 0.7619 - F1: 0.7569
sub_13:Test (Best Model) - Loss: 0.5329 - Accuracy: 0.7500 - F1: 0.7471
sub_13:Test (Best Model) - Loss: 0.4737 - Accuracy: 0.7738 - F1: 0.7722
sub_13:Test (Best Model) - Loss: 0.4863 - Accuracy: 0.7976 - F1: 0.7910
sub_13:Test (Best Model) - Loss: 0.5309 - Accuracy: 0.7857 - F1: 0.7838
sub_14:Test (Best Model) - Loss: 0.3069 - Accuracy: 0.8690 - F1: 0.8681
sub_14:Test (Best Model) - Loss: 0.3294 - Accuracy: 0.8452 - F1: 0.8442
sub_14:Test (Best Model) - Loss: 0.2688 - Accuracy: 0.8690 - F1: 0.8681
sub_14:Test (Best Model) - Loss: 0.3143 - Accuracy: 0.8929 - F1: 0.8927
sub_14:Test (Best Model) - Loss: 0.3373 - Accuracy: 0.9048 - F1: 0.9048
sub_14:Test (Best Model) - Loss: 0.3194 - Accuracy: 0.8690 - F1: 0.8675
sub_14:Test (Best Model) - Loss: 0.4356 - Accuracy: 0.7857 - F1: 0.7796
sub_14:Test (Best Model) - Loss: 0.3559 - Accuracy: 0.8095 - F1: 0.8041
sub_14:Test (Best Model) - Loss: 0.3285 - Accuracy: 0.8571 - F1: 0.8558
sub_14:Test (Best Model) - Loss: 0.2944 - Accuracy: 0.8571 - F1: 0.8551
sub_14:Test (Best Model) - Loss: 0.3796 - Accuracy: 0.8214 - F1: 0.8194
sub_14:Test (Best Model) - Loss: 0.3593 - Accuracy: 0.8810 - F1: 0.8807
sub_14:Test (Best Model) - Loss: 0.3671 - Accuracy: 0.8571 - F1: 0.8568
sub_14:Test (Best Model) - Loss: 0.3434 - Accuracy: 0.9048 - F1: 0.9045
sub_14:Test (Best Model) - Loss: 0.4025 - Accuracy: 0.8095 - F1: 0.8095

=== Summary Results ===

acc: 76.39 ± 7.59
F1: 75.70 ± 7.95
acc-in: 81.41 ± 7.10
F1-in: 81.09 ± 7.32
