lr: 0.0001
sub_1:Test (Best Model) - Loss: 1.6655 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 2.0509 - Accuracy: 0.7143 - F1: 0.6889
sub_1:Test (Best Model) - Loss: 1.7615 - Accuracy: 0.7024 - F1: 0.6735
sub_1:Test (Best Model) - Loss: 1.3926 - Accuracy: 0.7500 - F1: 0.7333
sub_1:Test (Best Model) - Loss: 1.4963 - Accuracy: 0.7024 - F1: 0.6735
sub_1:Test (Best Model) - Loss: 1.1354 - Accuracy: 0.7500 - F1: 0.7471
sub_1:Test (Best Model) - Loss: 0.5165 - Accuracy: 0.8452 - F1: 0.8447
sub_1:Test (Best Model) - Loss: 0.8060 - Accuracy: 0.7738 - F1: 0.7730
sub_1:Test (Best Model) - Loss: 0.9557 - Accuracy: 0.7857 - F1: 0.7856
sub_1:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.8095 - F1: 0.8091
sub_1:Test (Best Model) - Loss: 1.1357 - Accuracy: 0.7024 - F1: 0.6735
sub_1:Test (Best Model) - Loss: 0.9678 - Accuracy: 0.7500 - F1: 0.7333
sub_1:Test (Best Model) - Loss: 0.7439 - Accuracy: 0.7738 - F1: 0.7616
sub_1:Test (Best Model) - Loss: 0.8855 - Accuracy: 0.7500 - F1: 0.7333
sub_1:Test (Best Model) - Loss: 1.0179 - Accuracy: 0.7024 - F1: 0.6735
sub_2:Test (Best Model) - Loss: 0.9035 - Accuracy: 0.6905 - F1: 0.6719
sub_2:Test (Best Model) - Loss: 0.8939 - Accuracy: 0.6548 - F1: 0.6487
sub_2:Test (Best Model) - Loss: 0.8990 - Accuracy: 0.6667 - F1: 0.6650
sub_2:Test (Best Model) - Loss: 0.5018 - Accuracy: 0.8214 - F1: 0.8183
sub_2:Test (Best Model) - Loss: 0.8413 - Accuracy: 0.6905 - F1: 0.6756
sub_2:Test (Best Model) - Loss: 0.6380 - Accuracy: 0.7381 - F1: 0.7343
sub_2:Test (Best Model) - Loss: 0.4146 - Accuracy: 0.7976 - F1: 0.7941
sub_2:Test (Best Model) - Loss: 0.4228 - Accuracy: 0.8095 - F1: 0.8085
sub_2:Test (Best Model) - Loss: 0.5308 - Accuracy: 0.7500 - F1: 0.7471
sub_2:Test (Best Model) - Loss: 0.4717 - Accuracy: 0.7857 - F1: 0.7846
sub_2:Test (Best Model) - Loss: 0.7255 - Accuracy: 0.7143 - F1: 0.7141
sub_2:Test (Best Model) - Loss: 0.7480 - Accuracy: 0.7500 - F1: 0.7491
sub_2:Test (Best Model) - Loss: 0.6946 - Accuracy: 0.7857 - F1: 0.7852
sub_2:Test (Best Model) - Loss: 0.4166 - Accuracy: 0.8333 - F1: 0.8325
sub_2:Test (Best Model) - Loss: 0.7701 - Accuracy: 0.7143 - F1: 0.7128
sub_3:Test (Best Model) - Loss: 1.8320 - Accuracy: 0.5833 - F1: 0.5270
sub_3:Test (Best Model) - Loss: 1.5656 - Accuracy: 0.6190 - F1: 0.5544
sub_3:Test (Best Model) - Loss: 1.7757 - Accuracy: 0.5595 - F1: 0.4670
sub_3:Test (Best Model) - Loss: 1.4432 - Accuracy: 0.5595 - F1: 0.4999
sub_3:Test (Best Model) - Loss: 2.3324 - Accuracy: 0.5595 - F1: 0.4535
sub_3:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.7143 - F1: 0.7141
sub_3:Test (Best Model) - Loss: 0.7352 - Accuracy: 0.6667 - F1: 0.6650
sub_3:Test (Best Model) - Loss: 0.8977 - Accuracy: 0.6667 - F1: 0.6667
sub_3:Test (Best Model) - Loss: 0.8251 - Accuracy: 0.6905 - F1: 0.6903
sub_3:Test (Best Model) - Loss: 0.7444 - Accuracy: 0.6905 - F1: 0.6903
sub_3:Test (Best Model) - Loss: 1.3499 - Accuracy: 0.6548 - F1: 0.6080
sub_3:Test (Best Model) - Loss: 1.5755 - Accuracy: 0.6310 - F1: 0.5728
sub_3:Test (Best Model) - Loss: 1.1747 - Accuracy: 0.6667 - F1: 0.6313
sub_3:Test (Best Model) - Loss: 1.4833 - Accuracy: 0.6071 - F1: 0.5452
sub_3:Test (Best Model) - Loss: 1.0457 - Accuracy: 0.7143 - F1: 0.6889
sub_4:Test (Best Model) - Loss: 0.9795 - Accuracy: 0.7143 - F1: 0.7143
sub_4:Test (Best Model) - Loss: 1.1340 - Accuracy: 0.6310 - F1: 0.6309
sub_4:Test (Best Model) - Loss: 1.1427 - Accuracy: 0.6190 - F1: 0.6171
sub_4:Test (Best Model) - Loss: 1.0534 - Accuracy: 0.6548 - F1: 0.6523
sub_4:Test (Best Model) - Loss: 0.9461 - Accuracy: 0.6548 - F1: 0.6543
sub_4:Test (Best Model) - Loss: 1.0555 - Accuracy: 0.6429 - F1: 0.6410
sub_4:Test (Best Model) - Loss: 0.6721 - Accuracy: 0.7381 - F1: 0.7326
sub_4:Test (Best Model) - Loss: 0.6482 - Accuracy: 0.7976 - F1: 0.7974
sub_4:Test (Best Model) - Loss: 0.7416 - Accuracy: 0.7024 - F1: 0.6972
sub_4:Test (Best Model) - Loss: 0.5520 - Accuracy: 0.7143 - F1: 0.7102
sub_4:Test (Best Model) - Loss: 0.6264 - Accuracy: 0.7500 - F1: 0.7491
sub_4:Test (Best Model) - Loss: 0.7964 - Accuracy: 0.7381 - F1: 0.7357
sub_4:Test (Best Model) - Loss: 0.5783 - Accuracy: 0.7857 - F1: 0.7846
sub_4:Test (Best Model) - Loss: 0.8271 - Accuracy: 0.7024 - F1: 0.7003
sub_4:Test (Best Model) - Loss: 0.7896 - Accuracy: 0.7024 - F1: 0.7023
sub_5:Test (Best Model) - Loss: 0.5141 - Accuracy: 0.8095 - F1: 0.8091
sub_5:Test (Best Model) - Loss: 0.5737 - Accuracy: 0.7619 - F1: 0.7619
sub_5:Test (Best Model) - Loss: 0.4764 - Accuracy: 0.7976 - F1: 0.7974
sub_5:Test (Best Model) - Loss: 0.7289 - Accuracy: 0.7262 - F1: 0.7195
sub_5:Test (Best Model) - Loss: 0.4733 - Accuracy: 0.7738 - F1: 0.7738
sub_5:Test (Best Model) - Loss: 0.3974 - Accuracy: 0.8571 - F1: 0.8551
sub_5:Test (Best Model) - Loss: 0.5690 - Accuracy: 0.7857 - F1: 0.7826
sub_5:Test (Best Model) - Loss: 0.5169 - Accuracy: 0.7857 - F1: 0.7838
sub_5:Test (Best Model) - Loss: 0.3481 - Accuracy: 0.8452 - F1: 0.8425
sub_5:Test (Best Model) - Loss: 0.4696 - Accuracy: 0.7619 - F1: 0.7618
sub_5:Test (Best Model) - Loss: 0.5345 - Accuracy: 0.7619 - F1: 0.7597
sub_5:Test (Best Model) - Loss: 0.4763 - Accuracy: 0.7738 - F1: 0.7735
sub_5:Test (Best Model) - Loss: 0.4144 - Accuracy: 0.8452 - F1: 0.8452
sub_5:Test (Best Model) - Loss: 0.6072 - Accuracy: 0.7738 - F1: 0.7699
sub_5:Test (Best Model) - Loss: 0.5823 - Accuracy: 0.7381 - F1: 0.7368
sub_6:Test (Best Model) - Loss: 1.3455 - Accuracy: 0.5714 - F1: 0.5692
sub_6:Test (Best Model) - Loss: 1.0915 - Accuracy: 0.5952 - F1: 0.5950
sub_6:Test (Best Model) - Loss: 1.4526 - Accuracy: 0.5952 - F1: 0.5932
sub_6:Test (Best Model) - Loss: 1.4915 - Accuracy: 0.5952 - F1: 0.5943
sub_6:Test (Best Model) - Loss: 1.2346 - Accuracy: 0.5952 - F1: 0.5915
sub_6:Test (Best Model) - Loss: 1.2070 - Accuracy: 0.6548 - F1: 0.6463
sub_6:Test (Best Model) - Loss: 1.2706 - Accuracy: 0.6190 - F1: 0.6188
sub_6:Test (Best Model) - Loss: 1.1385 - Accuracy: 0.6548 - F1: 0.6508
sub_6:Test (Best Model) - Loss: 1.3958 - Accuracy: 0.5714 - F1: 0.5675
sub_6:Test (Best Model) - Loss: 1.0121 - Accuracy: 0.6548 - F1: 0.6523
sub_6:Test (Best Model) - Loss: 0.9824 - Accuracy: 0.6190 - F1: 0.6188
sub_6:Test (Best Model) - Loss: 1.0115 - Accuracy: 0.6548 - F1: 0.6523
sub_6:Test (Best Model) - Loss: 0.8152 - Accuracy: 0.6190 - F1: 0.6182
sub_6:Test (Best Model) - Loss: 0.9876 - Accuracy: 0.5714 - F1: 0.5705
sub_6:Test (Best Model) - Loss: 0.9753 - Accuracy: 0.5714 - F1: 0.5714
sub_7:Test (Best Model) - Loss: 1.0019 - Accuracy: 0.6667 - F1: 0.6571
sub_7:Test (Best Model) - Loss: 1.2555 - Accuracy: 0.6071 - F1: 0.6066
sub_7:Test (Best Model) - Loss: 1.0711 - Accuracy: 0.7262 - F1: 0.7145
sub_7:Test (Best Model) - Loss: 1.0429 - Accuracy: 0.6429 - F1: 0.6354
sub_7:Test (Best Model) - Loss: 1.2417 - Accuracy: 0.7024 - F1: 0.6897
sub_7:Test (Best Model) - Loss: 0.9939 - Accuracy: 0.6310 - F1: 0.6111
sub_7:Test (Best Model) - Loss: 0.8382 - Accuracy: 0.6310 - F1: 0.6188
sub_7:Test (Best Model) - Loss: 0.8435 - Accuracy: 0.6071 - F1: 0.5810
sub_7:Test (Best Model) - Loss: 1.2310 - Accuracy: 0.5714 - F1: 0.5692
sub_7:Test (Best Model) - Loss: 0.8989 - Accuracy: 0.6429 - F1: 0.6294
sub_7:Test (Best Model) - Loss: 0.9492 - Accuracy: 0.5952 - F1: 0.5950
sub_7:Test (Best Model) - Loss: 1.0043 - Accuracy: 0.6429 - F1: 0.6420
sub_7:Test (Best Model) - Loss: 0.8457 - Accuracy: 0.6071 - F1: 0.6071
sub_7:Test (Best Model) - Loss: 0.8819 - Accuracy: 0.6310 - F1: 0.6267
sub_7:Test (Best Model) - Loss: 0.9838 - Accuracy: 0.5238 - F1: 0.4952
sub_8:Test (Best Model) - Loss: 0.6335 - Accuracy: 0.8452 - F1: 0.8450
sub_8:Test (Best Model) - Loss: 0.8260 - Accuracy: 0.7857 - F1: 0.7856
sub_8:Test (Best Model) - Loss: 0.6427 - Accuracy: 0.8333 - F1: 0.8332
sub_8:Test (Best Model) - Loss: 0.5406 - Accuracy: 0.8333 - F1: 0.8325
sub_8:Test (Best Model) - Loss: 0.6270 - Accuracy: 0.8452 - F1: 0.8447
sub_8:Test (Best Model) - Loss: 0.3824 - Accuracy: 0.8690 - F1: 0.8690
sub_8:Test (Best Model) - Loss: 0.5889 - Accuracy: 0.7857 - F1: 0.7852
sub_8:Test (Best Model) - Loss: 0.5577 - Accuracy: 0.7738 - F1: 0.7730
sub_8:Test (Best Model) - Loss: 0.5525 - Accuracy: 0.8333 - F1: 0.8332
sub_8:Test (Best Model) - Loss: 0.4809 - Accuracy: 0.8333 - F1: 0.8318
sub_8:Test (Best Model) - Loss: 0.3706 - Accuracy: 0.8333 - F1: 0.8332
sub_8:Test (Best Model) - Loss: 0.2560 - Accuracy: 0.9048 - F1: 0.9045
sub_8:Test (Best Model) - Loss: 0.3374 - Accuracy: 0.8929 - F1: 0.8921
sub_8:Test (Best Model) - Loss: 0.3175 - Accuracy: 0.8929 - F1: 0.8928
sub_8:Test (Best Model) - Loss: 0.4787 - Accuracy: 0.7976 - F1: 0.7974
sub_9:Test (Best Model) - Loss: 0.7184 - Accuracy: 0.7381 - F1: 0.7306
sub_9:Test (Best Model) - Loss: 0.8237 - Accuracy: 0.6548 - F1: 0.6523
sub_9:Test (Best Model) - Loss: 0.7680 - Accuracy: 0.6786 - F1: 0.6648
sub_9:Test (Best Model) - Loss: 1.0074 - Accuracy: 0.6905 - F1: 0.6788
sub_9:Test (Best Model) - Loss: 0.8980 - Accuracy: 0.7262 - F1: 0.7214
sub_9:Test (Best Model) - Loss: 0.7044 - Accuracy: 0.7500 - F1: 0.7500
sub_9:Test (Best Model) - Loss: 0.7065 - Accuracy: 0.7738 - F1: 0.7735
sub_9:Test (Best Model) - Loss: 1.0758 - Accuracy: 0.6429 - F1: 0.6420
sub_9:Test (Best Model) - Loss: 0.5836 - Accuracy: 0.7976 - F1: 0.7976
sub_9:Test (Best Model) - Loss: 0.7737 - Accuracy: 0.7976 - F1: 0.7969
sub_9:Test (Best Model) - Loss: 1.1003 - Accuracy: 0.6905 - F1: 0.6577
sub_9:Test (Best Model) - Loss: 0.8107 - Accuracy: 0.7262 - F1: 0.7040
sub_9:Test (Best Model) - Loss: 0.6403 - Accuracy: 0.7619 - F1: 0.7504
sub_9:Test (Best Model) - Loss: 0.6568 - Accuracy: 0.7262 - F1: 0.7079
sub_9:Test (Best Model) - Loss: 0.8062 - Accuracy: 0.7262 - F1: 0.7040
sub_10:Test (Best Model) - Loss: 0.8645 - Accuracy: 0.6190 - F1: 0.6182
sub_10:Test (Best Model) - Loss: 0.8297 - Accuracy: 0.6905 - F1: 0.6816
sub_10:Test (Best Model) - Loss: 0.8026 - Accuracy: 0.6667 - F1: 0.6619
sub_10:Test (Best Model) - Loss: 1.0156 - Accuracy: 0.6190 - F1: 0.6136
sub_10:Test (Best Model) - Loss: 0.8908 - Accuracy: 0.6310 - F1: 0.6152
sub_10:Test (Best Model) - Loss: 0.8819 - Accuracy: 0.6548 - F1: 0.6547
sub_10:Test (Best Model) - Loss: 0.9311 - Accuracy: 0.6071 - F1: 0.6044
sub_10:Test (Best Model) - Loss: 0.9105 - Accuracy: 0.6667 - F1: 0.6619
sub_10:Test (Best Model) - Loss: 0.9616 - Accuracy: 0.6190 - F1: 0.6156
sub_10:Test (Best Model) - Loss: 0.9326 - Accuracy: 0.6667 - F1: 0.6667
sub_10:Test (Best Model) - Loss: 0.8627 - Accuracy: 0.6786 - F1: 0.6748
sub_10:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.6786 - F1: 0.6785
sub_10:Test (Best Model) - Loss: 0.7313 - Accuracy: 0.7500 - F1: 0.7456
sub_10:Test (Best Model) - Loss: 1.0778 - Accuracy: 0.7024 - F1: 0.6926
sub_10:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.6667 - F1: 0.6665
sub_11:Test (Best Model) - Loss: 0.9565 - Accuracy: 0.5833 - F1: 0.5804
sub_11:Test (Best Model) - Loss: 1.1864 - Accuracy: 0.6429 - F1: 0.6377
sub_11:Test (Best Model) - Loss: 0.9357 - Accuracy: 0.6190 - F1: 0.6171
sub_11:Test (Best Model) - Loss: 1.0515 - Accuracy: 0.5238 - F1: 0.5170
sub_11:Test (Best Model) - Loss: 1.0200 - Accuracy: 0.6548 - F1: 0.6523
sub_11:Test (Best Model) - Loss: 0.6292 - Accuracy: 0.6905 - F1: 0.6903
sub_11:Test (Best Model) - Loss: 0.6596 - Accuracy: 0.7143 - F1: 0.7143
sub_11:Test (Best Model) - Loss: 0.6392 - Accuracy: 0.7500 - F1: 0.7456
sub_11:Test (Best Model) - Loss: 0.6669 - Accuracy: 0.7619 - F1: 0.7614
sub_11:Test (Best Model) - Loss: 0.8187 - Accuracy: 0.6786 - F1: 0.6782
sub_11:Test (Best Model) - Loss: 0.7581 - Accuracy: 0.7024 - F1: 0.7023
sub_11:Test (Best Model) - Loss: 0.8120 - Accuracy: 0.7500 - F1: 0.7491
sub_11:Test (Best Model) - Loss: 0.8804 - Accuracy: 0.6548 - F1: 0.6543
sub_11:Test (Best Model) - Loss: 0.7411 - Accuracy: 0.7500 - F1: 0.7500
sub_11:Test (Best Model) - Loss: 0.7858 - Accuracy: 0.7381 - F1: 0.7375
sub_12:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.7262 - F1: 0.7252
sub_12:Test (Best Model) - Loss: 0.4719 - Accuracy: 0.7976 - F1: 0.7974
sub_12:Test (Best Model) - Loss: 0.3924 - Accuracy: 0.8571 - F1: 0.8571
sub_12:Test (Best Model) - Loss: 0.3825 - Accuracy: 0.8333 - F1: 0.8309
sub_12:Test (Best Model) - Loss: 0.3741 - Accuracy: 0.8095 - F1: 0.8094
sub_12:Test (Best Model) - Loss: 1.3601 - Accuracy: 0.7143 - F1: 0.7005
sub_12:Test (Best Model) - Loss: 1.0915 - Accuracy: 0.7500 - F1: 0.7365
sub_12:Test (Best Model) - Loss: 1.3591 - Accuracy: 0.7262 - F1: 0.7079
sub_12:Test (Best Model) - Loss: 1.3589 - Accuracy: 0.7500 - F1: 0.7365
sub_12:Test (Best Model) - Loss: 1.2738 - Accuracy: 0.7500 - F1: 0.7393
sub_12:Test (Best Model) - Loss: 0.7504 - Accuracy: 0.7738 - F1: 0.7712
sub_12:Test (Best Model) - Loss: 0.8352 - Accuracy: 0.7619 - F1: 0.7569
sub_12:Test (Best Model) - Loss: 0.6212 - Accuracy: 0.7500 - F1: 0.7393
sub_12:Test (Best Model) - Loss: 0.6618 - Accuracy: 0.7619 - F1: 0.7619
sub_12:Test (Best Model) - Loss: 1.1745 - Accuracy: 0.7381 - F1: 0.7326
sub_13:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.6905 - F1: 0.6876
sub_13:Test (Best Model) - Loss: 0.8050 - Accuracy: 0.7381 - F1: 0.7357
sub_13:Test (Best Model) - Loss: 0.8095 - Accuracy: 0.7143 - F1: 0.7083
sub_13:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.7857 - F1: 0.7838
sub_13:Test (Best Model) - Loss: 0.6329 - Accuracy: 0.7381 - F1: 0.7368
sub_13:Test (Best Model) - Loss: 0.9986 - Accuracy: 0.6667 - F1: 0.6636
sub_13:Test (Best Model) - Loss: 0.8130 - Accuracy: 0.7024 - F1: 0.6972
sub_13:Test (Best Model) - Loss: 0.8024 - Accuracy: 0.7500 - F1: 0.7491
sub_13:Test (Best Model) - Loss: 0.6573 - Accuracy: 0.7857 - F1: 0.7846
sub_13:Test (Best Model) - Loss: 0.6511 - Accuracy: 0.7857 - F1: 0.7846
sub_13:Test (Best Model) - Loss: 0.7353 - Accuracy: 0.7024 - F1: 0.6972
sub_13:Test (Best Model) - Loss: 0.6479 - Accuracy: 0.7976 - F1: 0.7953
sub_13:Test (Best Model) - Loss: 0.6434 - Accuracy: 0.7738 - F1: 0.7699
sub_13:Test (Best Model) - Loss: 0.5551 - Accuracy: 0.7738 - F1: 0.7699
sub_13:Test (Best Model) - Loss: 0.7374 - Accuracy: 0.7500 - F1: 0.7456
sub_14:Test (Best Model) - Loss: 0.5180 - Accuracy: 0.7857 - F1: 0.7856
sub_14:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.7738 - F1: 0.7738
sub_14:Test (Best Model) - Loss: 0.4394 - Accuracy: 0.8214 - F1: 0.8212
sub_14:Test (Best Model) - Loss: 0.8391 - Accuracy: 0.7024 - F1: 0.7003
sub_14:Test (Best Model) - Loss: 1.0635 - Accuracy: 0.7143 - F1: 0.7083
sub_14:Test (Best Model) - Loss: 0.7224 - Accuracy: 0.7143 - F1: 0.7128
sub_14:Test (Best Model) - Loss: 0.7560 - Accuracy: 0.7619 - F1: 0.7569
sub_14:Test (Best Model) - Loss: 0.6304 - Accuracy: 0.7738 - F1: 0.7730
sub_14:Test (Best Model) - Loss: 0.7765 - Accuracy: 0.7619 - F1: 0.7597
sub_14:Test (Best Model) - Loss: 0.5071 - Accuracy: 0.8214 - F1: 0.8194
sub_14:Test (Best Model) - Loss: 0.7455 - Accuracy: 0.7143 - F1: 0.7102
sub_14:Test (Best Model) - Loss: 0.5731 - Accuracy: 0.7500 - F1: 0.7418
sub_14:Test (Best Model) - Loss: 0.6466 - Accuracy: 0.7381 - F1: 0.7343
sub_14:Test (Best Model) - Loss: 0.6842 - Accuracy: 0.7381 - F1: 0.7357
sub_14:Test (Best Model) - Loss: 0.6590 - Accuracy: 0.7381 - F1: 0.7326

=== Summary Results ===

acc: 71.66 ± 6.32
F1: 70.91 ± 6.75
acc-in: 77.39 ± 7.15
F1-in: 77.06 ± 7.39
