lr: 0.0001
sub_1:Test (Best Model) - Loss: 2.2429 - Accuracy: 0.7262 - F1: 0.7079
sub_1:Test (Best Model) - Loss: 2.2766 - Accuracy: 0.7143 - F1: 0.6889
sub_1:Test (Best Model) - Loss: 1.9639 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 1.7542 - Accuracy: 0.7143 - F1: 0.6889
sub_1:Test (Best Model) - Loss: 1.9464 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 1.4517 - Accuracy: 0.7381 - F1: 0.7343
sub_1:Test (Best Model) - Loss: 0.5966 - Accuracy: 0.8571 - F1: 0.8571
sub_1:Test (Best Model) - Loss: 1.0978 - Accuracy: 0.7976 - F1: 0.7976
sub_1:Test (Best Model) - Loss: 0.7015 - Accuracy: 0.7738 - F1: 0.7738
sub_1:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.8214 - F1: 0.8214
sub_1:Test (Best Model) - Loss: 1.3709 - Accuracy: 0.7024 - F1: 0.6735
sub_1:Test (Best Model) - Loss: 0.9946 - Accuracy: 0.7381 - F1: 0.7224
sub_1:Test (Best Model) - Loss: 1.0481 - Accuracy: 0.7500 - F1: 0.7333
sub_1:Test (Best Model) - Loss: 1.1550 - Accuracy: 0.7738 - F1: 0.7616
sub_1:Test (Best Model) - Loss: 1.1631 - Accuracy: 0.7381 - F1: 0.7188
sub_2:Test (Best Model) - Loss: 1.1724 - Accuracy: 0.7024 - F1: 0.6897
sub_2:Test (Best Model) - Loss: 0.7574 - Accuracy: 0.7619 - F1: 0.7597
sub_2:Test (Best Model) - Loss: 0.6698 - Accuracy: 0.7857 - F1: 0.7796
sub_2:Test (Best Model) - Loss: 0.8582 - Accuracy: 0.7381 - F1: 0.7357
sub_2:Test (Best Model) - Loss: 0.8369 - Accuracy: 0.6310 - F1: 0.5884
sub_2:Test (Best Model) - Loss: 0.6168 - Accuracy: 0.7976 - F1: 0.7941
sub_2:Test (Best Model) - Loss: 0.4659 - Accuracy: 0.7619 - F1: 0.7569
sub_2:Test (Best Model) - Loss: 0.4567 - Accuracy: 0.8095 - F1: 0.8068
sub_2:Test (Best Model) - Loss: 0.5187 - Accuracy: 0.7381 - F1: 0.7255
sub_2:Test (Best Model) - Loss: 0.3966 - Accuracy: 0.8333 - F1: 0.8309
sub_2:Test (Best Model) - Loss: 0.6177 - Accuracy: 0.7976 - F1: 0.7976
sub_2:Test (Best Model) - Loss: 0.5570 - Accuracy: 0.8095 - F1: 0.8095
sub_2:Test (Best Model) - Loss: 0.7220 - Accuracy: 0.7619 - F1: 0.7614
sub_2:Test (Best Model) - Loss: 0.3674 - Accuracy: 0.8810 - F1: 0.8807
sub_2:Test (Best Model) - Loss: 0.6256 - Accuracy: 0.7857 - F1: 0.7857
sub_3:Test (Best Model) - Loss: 2.6417 - Accuracy: 0.5476 - F1: 0.4590
sub_3:Test (Best Model) - Loss: 2.0657 - Accuracy: 0.5595 - F1: 0.4999
sub_3:Test (Best Model) - Loss: 1.5808 - Accuracy: 0.5476 - F1: 0.4708
sub_3:Test (Best Model) - Loss: 1.3583 - Accuracy: 0.5714 - F1: 0.5333
sub_3:Test (Best Model) - Loss: 2.3621 - Accuracy: 0.5952 - F1: 0.5159
sub_3:Test (Best Model) - Loss: 0.9827 - Accuracy: 0.6548 - F1: 0.6547
sub_3:Test (Best Model) - Loss: 0.8786 - Accuracy: 0.6786 - F1: 0.6763
sub_3:Test (Best Model) - Loss: 0.9459 - Accuracy: 0.6786 - F1: 0.6782
sub_3:Test (Best Model) - Loss: 1.0750 - Accuracy: 0.7143 - F1: 0.7128
sub_3:Test (Best Model) - Loss: 0.8896 - Accuracy: 0.7262 - F1: 0.7262
sub_3:Test (Best Model) - Loss: 1.9000 - Accuracy: 0.6667 - F1: 0.6250
sub_3:Test (Best Model) - Loss: 1.2981 - Accuracy: 0.6905 - F1: 0.6577
sub_3:Test (Best Model) - Loss: 1.2416 - Accuracy: 0.7143 - F1: 0.6932
sub_3:Test (Best Model) - Loss: 1.2364 - Accuracy: 0.7024 - F1: 0.6783
sub_3:Test (Best Model) - Loss: 1.2451 - Accuracy: 0.6905 - F1: 0.6630
sub_4:Test (Best Model) - Loss: 1.1170 - Accuracy: 0.6905 - F1: 0.6905
sub_4:Test (Best Model) - Loss: 1.2487 - Accuracy: 0.6190 - F1: 0.6171
sub_4:Test (Best Model) - Loss: 1.0264 - Accuracy: 0.6905 - F1: 0.6905
sub_4:Test (Best Model) - Loss: 0.9604 - Accuracy: 0.7024 - F1: 0.7003
sub_4:Test (Best Model) - Loss: 0.9628 - Accuracy: 0.7024 - F1: 0.7020
sub_4:Test (Best Model) - Loss: 0.9423 - Accuracy: 0.7143 - F1: 0.7128
sub_4:Test (Best Model) - Loss: 0.8076 - Accuracy: 0.7381 - F1: 0.7368
sub_4:Test (Best Model) - Loss: 0.8133 - Accuracy: 0.7262 - F1: 0.7214
sub_4:Test (Best Model) - Loss: 0.6387 - Accuracy: 0.7619 - F1: 0.7569
sub_4:Test (Best Model) - Loss: 0.6543 - Accuracy: 0.7738 - F1: 0.7722
sub_4:Test (Best Model) - Loss: 0.5937 - Accuracy: 0.7857 - F1: 0.7846
sub_4:Test (Best Model) - Loss: 0.6130 - Accuracy: 0.7857 - F1: 0.7838
sub_4:Test (Best Model) - Loss: 0.5689 - Accuracy: 0.7857 - F1: 0.7856
sub_4:Test (Best Model) - Loss: 1.2305 - Accuracy: 0.6429 - F1: 0.6214
sub_4:Test (Best Model) - Loss: 0.4631 - Accuracy: 0.8214 - F1: 0.8208
sub_5:Test (Best Model) - Loss: 0.4950 - Accuracy: 0.8333 - F1: 0.8330
sub_5:Test (Best Model) - Loss: 0.5057 - Accuracy: 0.8095 - F1: 0.8091
sub_5:Test (Best Model) - Loss: 0.4948 - Accuracy: 0.8095 - F1: 0.8094
sub_5:Test (Best Model) - Loss: 0.7845 - Accuracy: 0.7262 - F1: 0.7230
sub_5:Test (Best Model) - Loss: 0.6183 - Accuracy: 0.7500 - F1: 0.7456
sub_5:Test (Best Model) - Loss: 0.6345 - Accuracy: 0.7857 - F1: 0.7812
sub_5:Test (Best Model) - Loss: 0.5480 - Accuracy: 0.8095 - F1: 0.8068
sub_5:Test (Best Model) - Loss: 0.3722 - Accuracy: 0.8571 - F1: 0.8568
sub_5:Test (Best Model) - Loss: 0.4573 - Accuracy: 0.8333 - F1: 0.8286
sub_5:Test (Best Model) - Loss: 0.5214 - Accuracy: 0.8214 - F1: 0.8212
sub_5:Test (Best Model) - Loss: 0.5463 - Accuracy: 0.8214 - F1: 0.8194
sub_5:Test (Best Model) - Loss: 0.5237 - Accuracy: 0.7976 - F1: 0.7969
sub_5:Test (Best Model) - Loss: 0.5795 - Accuracy: 0.7738 - F1: 0.7699
sub_5:Test (Best Model) - Loss: 0.4781 - Accuracy: 0.8095 - F1: 0.8078
sub_5:Test (Best Model) - Loss: 0.4884 - Accuracy: 0.7857 - F1: 0.7852
sub_6:Test (Best Model) - Loss: 1.4404 - Accuracy: 0.5833 - F1: 0.5828
sub_6:Test (Best Model) - Loss: 1.2776 - Accuracy: 0.5952 - F1: 0.5952
sub_6:Test (Best Model) - Loss: 1.2733 - Accuracy: 0.5833 - F1: 0.5804
sub_6:Test (Best Model) - Loss: 1.4902 - Accuracy: 0.5476 - F1: 0.5474
sub_6:Test (Best Model) - Loss: 1.1524 - Accuracy: 0.5952 - F1: 0.5952
sub_6:Test (Best Model) - Loss: 1.0718 - Accuracy: 0.7024 - F1: 0.6989
sub_6:Test (Best Model) - Loss: 1.3628 - Accuracy: 0.6429 - F1: 0.6427
sub_6:Test (Best Model) - Loss: 1.1762 - Accuracy: 0.6905 - F1: 0.6876
sub_6:Test (Best Model) - Loss: 1.3172 - Accuracy: 0.6190 - F1: 0.6182
sub_6:Test (Best Model) - Loss: 1.0251 - Accuracy: 0.6905 - F1: 0.6876
sub_6:Test (Best Model) - Loss: 0.9623 - Accuracy: 0.6310 - F1: 0.6305
sub_6:Test (Best Model) - Loss: 0.9695 - Accuracy: 0.6905 - F1: 0.6898
sub_6:Test (Best Model) - Loss: 0.7829 - Accuracy: 0.6905 - F1: 0.6876
sub_6:Test (Best Model) - Loss: 1.1719 - Accuracy: 0.6071 - F1: 0.6044
sub_6:Test (Best Model) - Loss: 1.0370 - Accuracy: 0.6071 - F1: 0.6066
sub_7:Test (Best Model) - Loss: 1.2411 - Accuracy: 0.6667 - F1: 0.6541
sub_7:Test (Best Model) - Loss: 1.3563 - Accuracy: 0.6071 - F1: 0.6026
sub_7:Test (Best Model) - Loss: 1.5011 - Accuracy: 0.5952 - F1: 0.5758
sub_7:Test (Best Model) - Loss: 1.5512 - Accuracy: 0.5833 - F1: 0.5609
sub_7:Test (Best Model) - Loss: 1.4206 - Accuracy: 0.5714 - F1: 0.5508
sub_7:Test (Best Model) - Loss: 1.0733 - Accuracy: 0.6310 - F1: 0.6152
sub_7:Test (Best Model) - Loss: 1.1180 - Accuracy: 0.6071 - F1: 0.5810
sub_7:Test (Best Model) - Loss: 1.3583 - Accuracy: 0.5119 - F1: 0.4911
sub_7:Test (Best Model) - Loss: 1.2822 - Accuracy: 0.5714 - F1: 0.5675
sub_7:Test (Best Model) - Loss: 1.0708 - Accuracy: 0.5833 - F1: 0.5696
sub_7:Test (Best Model) - Loss: 1.1522 - Accuracy: 0.5952 - F1: 0.5950
sub_7:Test (Best Model) - Loss: 1.0282 - Accuracy: 0.6786 - F1: 0.6763
sub_7:Test (Best Model) - Loss: 0.9952 - Accuracy: 0.5952 - F1: 0.5950
sub_7:Test (Best Model) - Loss: 1.0300 - Accuracy: 0.5714 - F1: 0.5692
sub_7:Test (Best Model) - Loss: 1.0054 - Accuracy: 0.5833 - F1: 0.5804
sub_8:Test (Best Model) - Loss: 0.7176 - Accuracy: 0.8214 - F1: 0.8212
sub_8:Test (Best Model) - Loss: 0.7181 - Accuracy: 0.8095 - F1: 0.8085
sub_8:Test (Best Model) - Loss: 0.7184 - Accuracy: 0.8333 - F1: 0.8332
sub_8:Test (Best Model) - Loss: 0.9870 - Accuracy: 0.8214 - F1: 0.8202
sub_8:Test (Best Model) - Loss: 0.5903 - Accuracy: 0.8571 - F1: 0.8568
sub_8:Test (Best Model) - Loss: 0.4993 - Accuracy: 0.7976 - F1: 0.7976
sub_8:Test (Best Model) - Loss: 0.6059 - Accuracy: 0.8095 - F1: 0.8068
sub_8:Test (Best Model) - Loss: 0.5096 - Accuracy: 0.8333 - F1: 0.8333
sub_8:Test (Best Model) - Loss: 0.4546 - Accuracy: 0.8690 - F1: 0.8675
sub_8:Test (Best Model) - Loss: 0.7533 - Accuracy: 0.8452 - F1: 0.8425
sub_8:Test (Best Model) - Loss: 0.3016 - Accuracy: 0.8810 - F1: 0.8809
sub_8:Test (Best Model) - Loss: 0.3982 - Accuracy: 0.8452 - F1: 0.8447
sub_8:Test (Best Model) - Loss: 0.2896 - Accuracy: 0.8929 - F1: 0.8925
sub_8:Test (Best Model) - Loss: 0.2682 - Accuracy: 0.9048 - F1: 0.9047
sub_8:Test (Best Model) - Loss: 0.3812 - Accuracy: 0.8571 - F1: 0.8571
sub_9:Test (Best Model) - Loss: 0.8019 - Accuracy: 0.7381 - F1: 0.7282
sub_9:Test (Best Model) - Loss: 0.8994 - Accuracy: 0.7381 - F1: 0.7282
sub_9:Test (Best Model) - Loss: 0.6287 - Accuracy: 0.7619 - F1: 0.7614
sub_9:Test (Best Model) - Loss: 1.1468 - Accuracy: 0.6905 - F1: 0.6719
sub_9:Test (Best Model) - Loss: 1.3556 - Accuracy: 0.6548 - F1: 0.6400
sub_9:Test (Best Model) - Loss: 0.7386 - Accuracy: 0.7857 - F1: 0.7857
sub_9:Test (Best Model) - Loss: 0.9146 - Accuracy: 0.7143 - F1: 0.7128
sub_9:Test (Best Model) - Loss: 0.8743 - Accuracy: 0.6667 - F1: 0.6665
sub_9:Test (Best Model) - Loss: 0.6573 - Accuracy: 0.7738 - F1: 0.7735
sub_9:Test (Best Model) - Loss: 0.7322 - Accuracy: 0.7262 - F1: 0.7230
sub_9:Test (Best Model) - Loss: 0.9915 - Accuracy: 0.6905 - F1: 0.6577
sub_9:Test (Best Model) - Loss: 0.7255 - Accuracy: 0.7143 - F1: 0.6889
sub_9:Test (Best Model) - Loss: 0.7763 - Accuracy: 0.7381 - F1: 0.7188
sub_9:Test (Best Model) - Loss: 0.8239 - Accuracy: 0.6905 - F1: 0.6577
sub_9:Test (Best Model) - Loss: 0.9217 - Accuracy: 0.7143 - F1: 0.6889
sub_10:Test (Best Model) - Loss: 0.9157 - Accuracy: 0.6310 - F1: 0.6305
sub_10:Test (Best Model) - Loss: 0.8557 - Accuracy: 0.6905 - F1: 0.6860
sub_10:Test (Best Model) - Loss: 0.9965 - Accuracy: 0.6667 - F1: 0.6650
sub_10:Test (Best Model) - Loss: 1.1716 - Accuracy: 0.6548 - F1: 0.6547
sub_10:Test (Best Model) - Loss: 0.7802 - Accuracy: 0.7024 - F1: 0.7013
sub_10:Test (Best Model) - Loss: 0.9110 - Accuracy: 0.6190 - F1: 0.6190
sub_10:Test (Best Model) - Loss: 0.9618 - Accuracy: 0.5952 - F1: 0.5868
sub_10:Test (Best Model) - Loss: 1.1439 - Accuracy: 0.6071 - F1: 0.6066
sub_10:Test (Best Model) - Loss: 1.1080 - Accuracy: 0.5714 - F1: 0.5692
sub_10:Test (Best Model) - Loss: 1.0811 - Accuracy: 0.6667 - F1: 0.6665
sub_10:Test (Best Model) - Loss: 0.8359 - Accuracy: 0.7619 - F1: 0.7619
sub_10:Test (Best Model) - Loss: 0.7498 - Accuracy: 0.7024 - F1: 0.7023
sub_10:Test (Best Model) - Loss: 0.8071 - Accuracy: 0.7381 - F1: 0.7379
sub_10:Test (Best Model) - Loss: 1.1561 - Accuracy: 0.7024 - F1: 0.6951
sub_10:Test (Best Model) - Loss: 0.9111 - Accuracy: 0.6429 - F1: 0.6410
sub_11:Test (Best Model) - Loss: 1.0649 - Accuracy: 0.6071 - F1: 0.6057
sub_11:Test (Best Model) - Loss: 1.0571 - Accuracy: 0.6071 - F1: 0.6026
sub_11:Test (Best Model) - Loss: 1.2311 - Accuracy: 0.5952 - F1: 0.5943
sub_11:Test (Best Model) - Loss: 1.0798 - Accuracy: 0.6310 - F1: 0.6219
sub_11:Test (Best Model) - Loss: 1.0893 - Accuracy: 0.7024 - F1: 0.6926
sub_11:Test (Best Model) - Loss: 0.5457 - Accuracy: 0.7738 - F1: 0.7735
sub_11:Test (Best Model) - Loss: 0.5814 - Accuracy: 0.7500 - F1: 0.7497
sub_11:Test (Best Model) - Loss: 0.6175 - Accuracy: 0.7738 - F1: 0.7722
sub_11:Test (Best Model) - Loss: 0.7319 - Accuracy: 0.7143 - F1: 0.7141
sub_11:Test (Best Model) - Loss: 0.9031 - Accuracy: 0.7024 - F1: 0.7020
sub_11:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.7024 - F1: 0.7003
sub_11:Test (Best Model) - Loss: 0.9702 - Accuracy: 0.6786 - F1: 0.6782
sub_11:Test (Best Model) - Loss: 0.8561 - Accuracy: 0.6905 - F1: 0.6898
sub_11:Test (Best Model) - Loss: 0.7194 - Accuracy: 0.7381 - F1: 0.7381
sub_11:Test (Best Model) - Loss: 0.8098 - Accuracy: 0.7500 - F1: 0.7500
sub_12:Test (Best Model) - Loss: 0.7397 - Accuracy: 0.7500 - F1: 0.7500
sub_12:Test (Best Model) - Loss: 0.5241 - Accuracy: 0.8333 - F1: 0.8332
sub_12:Test (Best Model) - Loss: 0.4502 - Accuracy: 0.8095 - F1: 0.8094
sub_12:Test (Best Model) - Loss: 0.4607 - Accuracy: 0.8452 - F1: 0.8425
sub_12:Test (Best Model) - Loss: 0.3531 - Accuracy: 0.8452 - F1: 0.8452
sub_12:Test (Best Model) - Loss: 1.5656 - Accuracy: 0.7381 - F1: 0.7255
sub_12:Test (Best Model) - Loss: 1.4102 - Accuracy: 0.7024 - F1: 0.6783
sub_12:Test (Best Model) - Loss: 1.8592 - Accuracy: 0.6905 - F1: 0.6630
sub_12:Test (Best Model) - Loss: 1.6492 - Accuracy: 0.7381 - F1: 0.7255
sub_12:Test (Best Model) - Loss: 1.3459 - Accuracy: 0.7024 - F1: 0.6825
sub_12:Test (Best Model) - Loss: 0.8248 - Accuracy: 0.7500 - F1: 0.7439
sub_12:Test (Best Model) - Loss: 0.6399 - Accuracy: 0.7857 - F1: 0.7852
sub_12:Test (Best Model) - Loss: 0.7227 - Accuracy: 0.7738 - F1: 0.7722
sub_12:Test (Best Model) - Loss: 0.6497 - Accuracy: 0.7738 - F1: 0.7712
sub_12:Test (Best Model) - Loss: 0.8125 - Accuracy: 0.7619 - F1: 0.7614
sub_13:Test (Best Model) - Loss: 0.6635 - Accuracy: 0.7024 - F1: 0.7020
sub_13:Test (Best Model) - Loss: 0.8372 - Accuracy: 0.7143 - F1: 0.7117
sub_13:Test (Best Model) - Loss: 1.1549 - Accuracy: 0.7024 - F1: 0.6897
sub_13:Test (Best Model) - Loss: 0.5689 - Accuracy: 0.7738 - F1: 0.7735
sub_13:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.7619 - F1: 0.7597
sub_13:Test (Best Model) - Loss: 0.8803 - Accuracy: 0.7262 - F1: 0.7243
sub_13:Test (Best Model) - Loss: 0.7634 - Accuracy: 0.7143 - F1: 0.7117
sub_13:Test (Best Model) - Loss: 0.7480 - Accuracy: 0.7262 - F1: 0.7243
sub_13:Test (Best Model) - Loss: 0.7119 - Accuracy: 0.7262 - F1: 0.7258
sub_13:Test (Best Model) - Loss: 0.6634 - Accuracy: 0.7738 - F1: 0.7735
sub_13:Test (Best Model) - Loss: 0.7103 - Accuracy: 0.7857 - F1: 0.7826
sub_13:Test (Best Model) - Loss: 0.8737 - Accuracy: 0.7619 - F1: 0.7597
sub_13:Test (Best Model) - Loss: 0.6556 - Accuracy: 0.7381 - F1: 0.7306
sub_13:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.8095 - F1: 0.8041
sub_13:Test (Best Model) - Loss: 0.7323 - Accuracy: 0.7857 - F1: 0.7826
sub_14:Test (Best Model) - Loss: 0.6031 - Accuracy: 0.7381 - F1: 0.7375
sub_14:Test (Best Model) - Loss: 0.8371 - Accuracy: 0.7381 - F1: 0.7381
sub_14:Test (Best Model) - Loss: 0.5579 - Accuracy: 0.7857 - F1: 0.7857
sub_14:Test (Best Model) - Loss: 0.7328 - Accuracy: 0.7619 - F1: 0.7614
sub_14:Test (Best Model) - Loss: 1.1232 - Accuracy: 0.7381 - F1: 0.7375
sub_14:Test (Best Model) - Loss: 0.5592 - Accuracy: 0.8214 - F1: 0.8208
sub_14:Test (Best Model) - Loss: 0.6315 - Accuracy: 0.8333 - F1: 0.8318
sub_14:Test (Best Model) - Loss: 0.6444 - Accuracy: 0.7976 - F1: 0.7962
sub_14:Test (Best Model) - Loss: 0.9404 - Accuracy: 0.7738 - F1: 0.7722
sub_14:Test (Best Model) - Loss: 0.4841 - Accuracy: 0.8214 - F1: 0.8202
sub_14:Test (Best Model) - Loss: 0.8870 - Accuracy: 0.6905 - F1: 0.6860
sub_14:Test (Best Model) - Loss: 0.6502 - Accuracy: 0.7500 - F1: 0.7418
sub_14:Test (Best Model) - Loss: 0.5884 - Accuracy: 0.7619 - F1: 0.7618
sub_14:Test (Best Model) - Loss: 0.5874 - Accuracy: 0.8333 - F1: 0.8330
sub_14:Test (Best Model) - Loss: 0.5953 - Accuracy: 0.7738 - F1: 0.7730

=== Summary Results ===

acc: 72.47 ± 6.75
F1: 71.76 ± 7.10
acc-in: 78.65 ± 5.98
F1-in: 78.39 ± 6.08
