lr: 1e-06
sub_1:Test (Best Model) - Loss: 0.5809 - Accuracy: 0.6905 - F1: 0.6840
sub_1:Test (Best Model) - Loss: 0.6186 - Accuracy: 0.6190 - F1: 0.6082
sub_1:Test (Best Model) - Loss: 0.6116 - Accuracy: 0.6905 - F1: 0.6889
sub_1:Test (Best Model) - Loss: 0.6196 - Accuracy: 0.6786 - F1: 0.6763
sub_1:Test (Best Model) - Loss: 0.6137 - Accuracy: 0.6548 - F1: 0.6543
sub_1:Test (Best Model) - Loss: 0.5543 - Accuracy: 0.7619 - F1: 0.7569
sub_1:Test (Best Model) - Loss: 0.6098 - Accuracy: 0.6905 - F1: 0.6860
sub_1:Test (Best Model) - Loss: 0.5951 - Accuracy: 0.7619 - F1: 0.7614
sub_1:Test (Best Model) - Loss: 0.5676 - Accuracy: 0.7619 - F1: 0.7607
sub_1:Test (Best Model) - Loss: 0.5697 - Accuracy: 0.7024 - F1: 0.7013
sub_1:Test (Best Model) - Loss: 0.6013 - Accuracy: 0.6548 - F1: 0.6212
sub_1:Test (Best Model) - Loss: 0.5896 - Accuracy: 0.6429 - F1: 0.5982
sub_1:Test (Best Model) - Loss: 0.6152 - Accuracy: 0.6905 - F1: 0.6788
sub_1:Test (Best Model) - Loss: 0.6049 - Accuracy: 0.6905 - F1: 0.6756
sub_1:Test (Best Model) - Loss: 0.5923 - Accuracy: 0.6310 - F1: 0.5884
sub_2:Test (Best Model) - Loss: 0.6072 - Accuracy: 0.6548 - F1: 0.6150
sub_2:Test (Best Model) - Loss: 0.6029 - Accuracy: 0.6905 - F1: 0.6577
sub_2:Test (Best Model) - Loss: 0.5981 - Accuracy: 0.7143 - F1: 0.7035
sub_2:Test (Best Model) - Loss: 0.5731 - Accuracy: 0.7381 - F1: 0.7224
sub_2:Test (Best Model) - Loss: 0.5903 - Accuracy: 0.6667 - F1: 0.6541
sub_2:Test (Best Model) - Loss: 0.5776 - Accuracy: 0.5952 - F1: 0.5159
sub_2:Test (Best Model) - Loss: 0.5613 - Accuracy: 0.6429 - F1: 0.5906
sub_2:Test (Best Model) - Loss: 0.5705 - Accuracy: 0.6071 - F1: 0.5354
sub_2:Test (Best Model) - Loss: 0.5755 - Accuracy: 0.6190 - F1: 0.5544
sub_2:Test (Best Model) - Loss: 0.5851 - Accuracy: 0.5952 - F1: 0.5159
sub_2:Test (Best Model) - Loss: 0.5422 - Accuracy: 0.7262 - F1: 0.7172
sub_2:Test (Best Model) - Loss: 0.5112 - Accuracy: 0.7262 - F1: 0.7145
sub_2:Test (Best Model) - Loss: 0.5614 - Accuracy: 0.7500 - F1: 0.7365
sub_2:Test (Best Model) - Loss: 0.5648 - Accuracy: 0.8214 - F1: 0.8155
sub_2:Test (Best Model) - Loss: 0.5422 - Accuracy: 0.7262 - F1: 0.7172
sub_3:Test (Best Model) - Loss: 0.6202 - Accuracy: 0.6310 - F1: 0.5810
sub_3:Test (Best Model) - Loss: 0.6181 - Accuracy: 0.6310 - F1: 0.5810
sub_3:Test (Best Model) - Loss: 0.6143 - Accuracy: 0.6071 - F1: 0.5452
sub_3:Test (Best Model) - Loss: 0.6413 - Accuracy: 0.5714 - F1: 0.4987
sub_3:Test (Best Model) - Loss: 0.6735 - Accuracy: 0.6071 - F1: 0.5619
sub_3:Test (Best Model) - Loss: 0.5877 - Accuracy: 0.7738 - F1: 0.7712
sub_3:Test (Best Model) - Loss: 0.6096 - Accuracy: 0.7143 - F1: 0.7141
sub_3:Test (Best Model) - Loss: 0.6560 - Accuracy: 0.6429 - F1: 0.6377
sub_3:Test (Best Model) - Loss: 0.6370 - Accuracy: 0.6667 - F1: 0.6650
sub_3:Test (Best Model) - Loss: 0.6534 - Accuracy: 0.6429 - F1: 0.6427
sub_3:Test (Best Model) - Loss: 0.6535 - Accuracy: 0.6310 - F1: 0.6245
sub_3:Test (Best Model) - Loss: 0.5957 - Accuracy: 0.6786 - F1: 0.6473
sub_3:Test (Best Model) - Loss: 0.6036 - Accuracy: 0.7262 - F1: 0.7145
sub_3:Test (Best Model) - Loss: 0.6335 - Accuracy: 0.6786 - F1: 0.6763
sub_3:Test (Best Model) - Loss: 0.6130 - Accuracy: 0.7024 - F1: 0.6863
sub_4:Test (Best Model) - Loss: 0.6021 - Accuracy: 0.7143 - F1: 0.7136
sub_4:Test (Best Model) - Loss: 0.6558 - Accuracy: 0.6190 - F1: 0.6188
sub_4:Test (Best Model) - Loss: 0.6504 - Accuracy: 0.5595 - F1: 0.5564
sub_4:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.5952 - F1: 0.5932
sub_4:Test (Best Model) - Loss: 0.6603 - Accuracy: 0.5476 - F1: 0.5382
sub_4:Test (Best Model) - Loss: 0.6269 - Accuracy: 0.5714 - F1: 0.5457
sub_4:Test (Best Model) - Loss: 0.6457 - Accuracy: 0.6190 - F1: 0.5787
sub_4:Test (Best Model) - Loss: 0.5816 - Accuracy: 0.7024 - F1: 0.6989
sub_4:Test (Best Model) - Loss: 0.6457 - Accuracy: 0.6071 - F1: 0.5904
sub_4:Test (Best Model) - Loss: 0.6326 - Accuracy: 0.6429 - F1: 0.6377
sub_4:Test (Best Model) - Loss: 0.6544 - Accuracy: 0.5595 - F1: 0.4535
sub_4:Test (Best Model) - Loss: 0.6631 - Accuracy: 0.5238 - F1: 0.4167
sub_4:Test (Best Model) - Loss: 0.6473 - Accuracy: 0.5357 - F1: 0.4382
sub_4:Test (Best Model) - Loss: 0.6643 - Accuracy: 0.5714 - F1: 0.4875
sub_4:Test (Best Model) - Loss: 0.6568 - Accuracy: 0.5476 - F1: 0.4458
sub_5:Test (Best Model) - Loss: 0.5865 - Accuracy: 0.7500 - F1: 0.7483
sub_5:Test (Best Model) - Loss: 0.5738 - Accuracy: 0.7262 - F1: 0.7040
sub_5:Test (Best Model) - Loss: 0.6150 - Accuracy: 0.7500 - F1: 0.7418
sub_5:Test (Best Model) - Loss: 0.6298 - Accuracy: 0.6310 - F1: 0.6296
sub_5:Test (Best Model) - Loss: 0.6308 - Accuracy: 0.5833 - F1: 0.5176
sub_5:Test (Best Model) - Loss: 0.6633 - Accuracy: 0.5595 - F1: 0.4999
sub_5:Test (Best Model) - Loss: 0.6474 - Accuracy: 0.5833 - F1: 0.5073
sub_5:Test (Best Model) - Loss: 0.6049 - Accuracy: 0.6429 - F1: 0.6327
sub_5:Test (Best Model) - Loss: 0.5794 - Accuracy: 0.7143 - F1: 0.6889
sub_5:Test (Best Model) - Loss: 0.6270 - Accuracy: 0.5833 - F1: 0.5073
sub_5:Test (Best Model) - Loss: 0.6253 - Accuracy: 0.6429 - F1: 0.5982
sub_5:Test (Best Model) - Loss: 0.6113 - Accuracy: 0.6429 - F1: 0.5982
sub_5:Test (Best Model) - Loss: 0.6142 - Accuracy: 0.6310 - F1: 0.5951
sub_5:Test (Best Model) - Loss: 0.6031 - Accuracy: 0.6786 - F1: 0.6473
sub_5:Test (Best Model) - Loss: 0.5818 - Accuracy: 0.7262 - F1: 0.7114
sub_6:Test (Best Model) - Loss: 0.6526 - Accuracy: 0.5476 - F1: 0.5382
sub_6:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5000 - F1: 0.4954
sub_6:Test (Best Model) - Loss: 0.7002 - Accuracy: 0.5952 - F1: 0.5952
sub_6:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5238 - F1: 0.5235
sub_6:Test (Best Model) - Loss: 0.6583 - Accuracy: 0.5714 - F1: 0.5714
sub_6:Test (Best Model) - Loss: 0.6422 - Accuracy: 0.5952 - F1: 0.5915
sub_6:Test (Best Model) - Loss: 0.6679 - Accuracy: 0.6071 - F1: 0.6044
sub_6:Test (Best Model) - Loss: 0.6699 - Accuracy: 0.6071 - F1: 0.6057
sub_6:Test (Best Model) - Loss: 0.6612 - Accuracy: 0.5714 - F1: 0.5553
sub_6:Test (Best Model) - Loss: 0.6375 - Accuracy: 0.6786 - F1: 0.6763
sub_6:Test (Best Model) - Loss: 0.6807 - Accuracy: 0.5238 - F1: 0.5195
sub_6:Test (Best Model) - Loss: 0.6482 - Accuracy: 0.6667 - F1: 0.6619
sub_6:Test (Best Model) - Loss: 0.6686 - Accuracy: 0.6071 - F1: 0.6071
sub_6:Test (Best Model) - Loss: 0.6756 - Accuracy: 0.5833 - F1: 0.5828
sub_6:Test (Best Model) - Loss: 0.6571 - Accuracy: 0.6071 - F1: 0.5904
sub_7:Test (Best Model) - Loss: 0.6687 - Accuracy: 0.5952 - F1: 0.5894
sub_7:Test (Best Model) - Loss: 0.6675 - Accuracy: 0.5238 - F1: 0.4952
sub_7:Test (Best Model) - Loss: 0.6719 - Accuracy: 0.5833 - F1: 0.5828
sub_7:Test (Best Model) - Loss: 0.6581 - Accuracy: 0.6548 - F1: 0.6535
sub_7:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.5833 - F1: 0.5609
sub_7:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.4881 - F1: 0.4712
sub_7:Test (Best Model) - Loss: 0.6658 - Accuracy: 0.5833 - F1: 0.5556
sub_7:Test (Best Model) - Loss: 0.6596 - Accuracy: 0.5595 - F1: 0.5302
sub_7:Test (Best Model) - Loss: 0.6621 - Accuracy: 0.5714 - F1: 0.5457
sub_7:Test (Best Model) - Loss: 0.6723 - Accuracy: 0.6190 - F1: 0.5714
sub_7:Test (Best Model) - Loss: 0.6691 - Accuracy: 0.5952 - F1: 0.5654
sub_7:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5357 - F1: 0.5341
sub_7:Test (Best Model) - Loss: 0.6693 - Accuracy: 0.6190 - F1: 0.5910
sub_7:Test (Best Model) - Loss: 0.6734 - Accuracy: 0.6429 - F1: 0.6354
sub_7:Test (Best Model) - Loss: 0.6794 - Accuracy: 0.5595 - F1: 0.5238
sub_8:Test (Best Model) - Loss: 0.5538 - Accuracy: 0.6905 - F1: 0.6756
sub_8:Test (Best Model) - Loss: 0.4665 - Accuracy: 0.8214 - F1: 0.8208
sub_8:Test (Best Model) - Loss: 0.5879 - Accuracy: 0.7143 - F1: 0.7035
sub_8:Test (Best Model) - Loss: 0.4502 - Accuracy: 0.8214 - F1: 0.8214
sub_8:Test (Best Model) - Loss: 0.5600 - Accuracy: 0.7619 - F1: 0.7551
sub_8:Test (Best Model) - Loss: 0.5025 - Accuracy: 0.7976 - F1: 0.7953
sub_8:Test (Best Model) - Loss: 0.5774 - Accuracy: 0.7381 - F1: 0.7188
sub_8:Test (Best Model) - Loss: 0.5424 - Accuracy: 0.7976 - F1: 0.7953
sub_8:Test (Best Model) - Loss: 0.5926 - Accuracy: 0.7500 - F1: 0.7439
sub_8:Test (Best Model) - Loss: 0.5694 - Accuracy: 0.7619 - F1: 0.7529
sub_8:Test (Best Model) - Loss: 0.5876 - Accuracy: 0.5833 - F1: 0.5073
sub_8:Test (Best Model) - Loss: 0.5203 - Accuracy: 0.7143 - F1: 0.7005
sub_8:Test (Best Model) - Loss: 0.5022 - Accuracy: 0.7500 - F1: 0.7393
sub_8:Test (Best Model) - Loss: 0.5625 - Accuracy: 0.7143 - F1: 0.6932
sub_8:Test (Best Model) - Loss: 0.4859 - Accuracy: 0.7976 - F1: 0.7941
sub_9:Test (Best Model) - Loss: 0.5689 - Accuracy: 0.7619 - F1: 0.7614
sub_9:Test (Best Model) - Loss: 0.5643 - Accuracy: 0.7619 - F1: 0.7619
sub_9:Test (Best Model) - Loss: 0.5401 - Accuracy: 0.8095 - F1: 0.8094
sub_9:Test (Best Model) - Loss: 0.5704 - Accuracy: 0.7381 - F1: 0.7379
sub_9:Test (Best Model) - Loss: 0.5640 - Accuracy: 0.7500 - F1: 0.7491
sub_9:Test (Best Model) - Loss: 0.6701 - Accuracy: 0.5714 - F1: 0.5592
sub_9:Test (Best Model) - Loss: 0.6326 - Accuracy: 0.6548 - F1: 0.6523
sub_9:Test (Best Model) - Loss: 0.6302 - Accuracy: 0.6190 - F1: 0.6111
sub_9:Test (Best Model) - Loss: 0.6544 - Accuracy: 0.6429 - F1: 0.6294
sub_9:Test (Best Model) - Loss: 0.6719 - Accuracy: 0.5714 - F1: 0.5653
sub_9:Test (Best Model) - Loss: 0.6466 - Accuracy: 0.6310 - F1: 0.5884
sub_9:Test (Best Model) - Loss: 0.6252 - Accuracy: 0.7024 - F1: 0.6735
sub_9:Test (Best Model) - Loss: 0.6365 - Accuracy: 0.6548 - F1: 0.6361
sub_9:Test (Best Model) - Loss: 0.6267 - Accuracy: 0.7262 - F1: 0.7145
sub_9:Test (Best Model) - Loss: 0.5767 - Accuracy: 0.7024 - F1: 0.6735
sub_10:Test (Best Model) - Loss: 0.6726 - Accuracy: 0.5714 - F1: 0.5705
sub_10:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.5357 - F1: 0.5351
sub_10:Test (Best Model) - Loss: 0.6773 - Accuracy: 0.5238 - F1: 0.5227
sub_10:Test (Best Model) - Loss: 0.6617 - Accuracy: 0.6190 - F1: 0.6156
sub_10:Test (Best Model) - Loss: 0.6795 - Accuracy: 0.6071 - F1: 0.6066
sub_10:Test (Best Model) - Loss: 0.6746 - Accuracy: 0.5357 - F1: 0.5048
sub_10:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5119 - F1: 0.5118
sub_10:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5357 - F1: 0.5159
sub_10:Test (Best Model) - Loss: 0.6678 - Accuracy: 0.6071 - F1: 0.5860
sub_10:Test (Best Model) - Loss: 0.6463 - Accuracy: 0.6786 - F1: 0.6774
sub_10:Test (Best Model) - Loss: 0.6653 - Accuracy: 0.5952 - F1: 0.5950
sub_10:Test (Best Model) - Loss: 0.6712 - Accuracy: 0.5476 - F1: 0.5258
sub_10:Test (Best Model) - Loss: 0.6515 - Accuracy: 0.6429 - F1: 0.6429
sub_10:Test (Best Model) - Loss: 0.6769 - Accuracy: 0.5833 - F1: 0.5696
sub_10:Test (Best Model) - Loss: 0.6648 - Accuracy: 0.5952 - F1: 0.5943
sub_11:Test (Best Model) - Loss: 0.6653 - Accuracy: 0.6548 - F1: 0.6400
sub_11:Test (Best Model) - Loss: 0.7022 - Accuracy: 0.4762 - F1: 0.4510
sub_11:Test (Best Model) - Loss: 0.6854 - Accuracy: 0.5238 - F1: 0.5170
sub_11:Test (Best Model) - Loss: 0.6761 - Accuracy: 0.5714 - F1: 0.5653
sub_11:Test (Best Model) - Loss: 0.6511 - Accuracy: 0.6071 - F1: 0.5975
sub_11:Test (Best Model) - Loss: 0.6475 - Accuracy: 0.5833 - F1: 0.5353
sub_11:Test (Best Model) - Loss: 0.6565 - Accuracy: 0.6548 - F1: 0.6268
sub_11:Test (Best Model) - Loss: 0.6311 - Accuracy: 0.6071 - F1: 0.5904
sub_11:Test (Best Model) - Loss: 0.6196 - Accuracy: 0.6667 - F1: 0.6466
sub_11:Test (Best Model) - Loss: 0.6245 - Accuracy: 0.6667 - F1: 0.6597
sub_11:Test (Best Model) - Loss: 0.6652 - Accuracy: 0.6071 - F1: 0.5810
sub_11:Test (Best Model) - Loss: 0.6715 - Accuracy: 0.5595 - F1: 0.5450
sub_11:Test (Best Model) - Loss: 0.6412 - Accuracy: 0.6667 - F1: 0.6597
sub_11:Test (Best Model) - Loss: 0.6526 - Accuracy: 0.6071 - F1: 0.5975
sub_11:Test (Best Model) - Loss: 0.6354 - Accuracy: 0.6429 - F1: 0.6396
sub_12:Test (Best Model) - Loss: 0.6228 - Accuracy: 0.6905 - F1: 0.6903
sub_12:Test (Best Model) - Loss: 0.6388 - Accuracy: 0.6190 - F1: 0.6156
sub_12:Test (Best Model) - Loss: 0.5976 - Accuracy: 0.7024 - F1: 0.6989
sub_12:Test (Best Model) - Loss: 0.5934 - Accuracy: 0.8095 - F1: 0.8094
sub_12:Test (Best Model) - Loss: 0.6067 - Accuracy: 0.6548 - F1: 0.6547
sub_12:Test (Best Model) - Loss: 0.5674 - Accuracy: 0.7381 - F1: 0.7306
sub_12:Test (Best Model) - Loss: 0.6104 - Accuracy: 0.7024 - F1: 0.6972
sub_12:Test (Best Model) - Loss: 0.5792 - Accuracy: 0.7381 - F1: 0.7282
sub_12:Test (Best Model) - Loss: 0.6516 - Accuracy: 0.6786 - F1: 0.6730
sub_12:Test (Best Model) - Loss: 0.5786 - Accuracy: 0.7738 - F1: 0.7699
sub_12:Test (Best Model) - Loss: 0.6175 - Accuracy: 0.6667 - F1: 0.6421
sub_12:Test (Best Model) - Loss: 0.5806 - Accuracy: 0.7143 - F1: 0.6932
sub_12:Test (Best Model) - Loss: 0.5410 - Accuracy: 0.7262 - F1: 0.7079
sub_12:Test (Best Model) - Loss: 0.5932 - Accuracy: 0.7738 - F1: 0.7699
sub_12:Test (Best Model) - Loss: 0.6058 - Accuracy: 0.6786 - F1: 0.6648
sub_13:Test (Best Model) - Loss: 0.6552 - Accuracy: 0.6548 - F1: 0.6487
sub_13:Test (Best Model) - Loss: 0.6447 - Accuracy: 0.6548 - F1: 0.6547
sub_13:Test (Best Model) - Loss: 0.6513 - Accuracy: 0.6905 - F1: 0.6788
sub_13:Test (Best Model) - Loss: 0.6135 - Accuracy: 0.7381 - F1: 0.7368
sub_13:Test (Best Model) - Loss: 0.6706 - Accuracy: 0.5952 - F1: 0.5915
sub_13:Test (Best Model) - Loss: 0.6563 - Accuracy: 0.5952 - F1: 0.5952
sub_13:Test (Best Model) - Loss: 0.6380 - Accuracy: 0.6548 - F1: 0.6547
sub_13:Test (Best Model) - Loss: 0.6154 - Accuracy: 0.7262 - F1: 0.7252
sub_13:Test (Best Model) - Loss: 0.6452 - Accuracy: 0.6786 - F1: 0.6763
sub_13:Test (Best Model) - Loss: 0.6553 - Accuracy: 0.6548 - F1: 0.6535
sub_13:Test (Best Model) - Loss: 0.6232 - Accuracy: 0.7500 - F1: 0.7471
sub_13:Test (Best Model) - Loss: 0.6137 - Accuracy: 0.6667 - F1: 0.6636
sub_13:Test (Best Model) - Loss: 0.6209 - Accuracy: 0.7500 - F1: 0.7456
sub_13:Test (Best Model) - Loss: 0.6089 - Accuracy: 0.7738 - F1: 0.7664
sub_13:Test (Best Model) - Loss: 0.6402 - Accuracy: 0.6310 - F1: 0.6219
sub_14:Test (Best Model) - Loss: 0.5906 - Accuracy: 0.5952 - F1: 0.5524
sub_14:Test (Best Model) - Loss: 0.5473 - Accuracy: 0.7024 - F1: 0.6951
sub_14:Test (Best Model) - Loss: 0.5888 - Accuracy: 0.6548 - F1: 0.6268
sub_14:Test (Best Model) - Loss: 0.5536 - Accuracy: 0.7143 - F1: 0.7136
sub_14:Test (Best Model) - Loss: 0.5692 - Accuracy: 0.7024 - F1: 0.6972
sub_14:Test (Best Model) - Loss: 0.5106 - Accuracy: 0.7500 - F1: 0.7393
sub_14:Test (Best Model) - Loss: 0.6007 - Accuracy: 0.5952 - F1: 0.5361
sub_14:Test (Best Model) - Loss: 0.5940 - Accuracy: 0.6310 - F1: 0.5810
sub_14:Test (Best Model) - Loss: 0.5540 - Accuracy: 0.6786 - F1: 0.6612
sub_14:Test (Best Model) - Loss: 0.5251 - Accuracy: 0.7024 - F1: 0.6825
sub_14:Test (Best Model) - Loss: 0.5900 - Accuracy: 0.7024 - F1: 0.6926
sub_14:Test (Best Model) - Loss: 0.5850 - Accuracy: 0.6667 - F1: 0.6466
sub_14:Test (Best Model) - Loss: 0.6323 - Accuracy: 0.6310 - F1: 0.5884
sub_14:Test (Best Model) - Loss: 0.6066 - Accuracy: 0.7143 - F1: 0.7061
sub_14:Test (Best Model) - Loss: 0.5309 - Accuracy: 0.7500 - F1: 0.7491

=== Summary Results ===

acc: 65.30 ± 5.21
F1: 63.50 ± 5.45
acc-in: 68.69 ± 6.05
F1-in: 67.50 ± 6.30
