lr: 1e-06
sub_1:Test (Best Model) - Loss: 0.6280 - Accuracy: 0.5714 - F1: 0.5675
sub_1:Test (Best Model) - Loss: 0.6384 - Accuracy: 0.6667 - F1: 0.6650
sub_1:Test (Best Model) - Loss: 0.5928 - Accuracy: 0.6667 - F1: 0.6597
sub_1:Test (Best Model) - Loss: 0.6084 - Accuracy: 0.7262 - F1: 0.7243
sub_1:Test (Best Model) - Loss: 0.6559 - Accuracy: 0.5714 - F1: 0.5714
sub_1:Test (Best Model) - Loss: 0.6207 - Accuracy: 0.7143 - F1: 0.7102
sub_1:Test (Best Model) - Loss: 0.6214 - Accuracy: 0.7024 - F1: 0.6863
sub_1:Test (Best Model) - Loss: 0.6009 - Accuracy: 0.7024 - F1: 0.7013
sub_1:Test (Best Model) - Loss: 0.6117 - Accuracy: 0.6548 - F1: 0.6535
sub_1:Test (Best Model) - Loss: 0.5513 - Accuracy: 0.7262 - F1: 0.7230
sub_1:Test (Best Model) - Loss: 0.6275 - Accuracy: 0.6786 - F1: 0.6612
sub_1:Test (Best Model) - Loss: 0.5637 - Accuracy: 0.6786 - F1: 0.6525
sub_1:Test (Best Model) - Loss: 0.5564 - Accuracy: 0.7619 - F1: 0.7476
sub_1:Test (Best Model) - Loss: 0.6105 - Accuracy: 0.7619 - F1: 0.7529
sub_1:Test (Best Model) - Loss: 0.5964 - Accuracy: 0.6429 - F1: 0.5982
sub_2:Test (Best Model) - Loss: 0.6169 - Accuracy: 0.7143 - F1: 0.7005
sub_2:Test (Best Model) - Loss: 0.6181 - Accuracy: 0.5833 - F1: 0.5176
sub_2:Test (Best Model) - Loss: 0.6131 - Accuracy: 0.6190 - F1: 0.5714
sub_2:Test (Best Model) - Loss: 0.6093 - Accuracy: 0.6190 - F1: 0.5787
sub_2:Test (Best Model) - Loss: 0.6306 - Accuracy: 0.6310 - F1: 0.6063
sub_2:Test (Best Model) - Loss: 0.5793 - Accuracy: 0.5952 - F1: 0.5265
sub_2:Test (Best Model) - Loss: 0.5552 - Accuracy: 0.6071 - F1: 0.5354
sub_2:Test (Best Model) - Loss: 0.5785 - Accuracy: 0.6190 - F1: 0.5544
sub_2:Test (Best Model) - Loss: 0.5669 - Accuracy: 0.7024 - F1: 0.6735
sub_2:Test (Best Model) - Loss: 0.5899 - Accuracy: 0.6071 - F1: 0.5452
sub_2:Test (Best Model) - Loss: 0.5906 - Accuracy: 0.7143 - F1: 0.7061
sub_2:Test (Best Model) - Loss: 0.5768 - Accuracy: 0.7619 - F1: 0.7551
sub_2:Test (Best Model) - Loss: 0.5943 - Accuracy: 0.7381 - F1: 0.7306
sub_2:Test (Best Model) - Loss: 0.5802 - Accuracy: 0.7857 - F1: 0.7796
sub_2:Test (Best Model) - Loss: 0.5598 - Accuracy: 0.7024 - F1: 0.6951
sub_3:Test (Best Model) - Loss: 0.6315 - Accuracy: 0.6071 - F1: 0.5540
sub_3:Test (Best Model) - Loss: 0.6355 - Accuracy: 0.6429 - F1: 0.6111
sub_3:Test (Best Model) - Loss: 0.6456 - Accuracy: 0.5833 - F1: 0.5176
sub_3:Test (Best Model) - Loss: 0.6432 - Accuracy: 0.6071 - F1: 0.5619
sub_3:Test (Best Model) - Loss: 0.6489 - Accuracy: 0.6071 - F1: 0.5619
sub_3:Test (Best Model) - Loss: 0.6152 - Accuracy: 0.7500 - F1: 0.7491
sub_3:Test (Best Model) - Loss: 0.6526 - Accuracy: 0.5714 - F1: 0.5714
sub_3:Test (Best Model) - Loss: 0.6638 - Accuracy: 0.6190 - F1: 0.6171
sub_3:Test (Best Model) - Loss: 0.6329 - Accuracy: 0.7262 - F1: 0.7195
sub_3:Test (Best Model) - Loss: 0.6184 - Accuracy: 0.7024 - F1: 0.7023
sub_3:Test (Best Model) - Loss: 0.6570 - Accuracy: 0.6310 - F1: 0.6188
sub_3:Test (Best Model) - Loss: 0.6322 - Accuracy: 0.6429 - F1: 0.6410
sub_3:Test (Best Model) - Loss: 0.6402 - Accuracy: 0.7143 - F1: 0.7117
sub_3:Test (Best Model) - Loss: 0.6584 - Accuracy: 0.5952 - F1: 0.5952
sub_3:Test (Best Model) - Loss: 0.5782 - Accuracy: 0.7262 - F1: 0.7079
sub_4:Test (Best Model) - Loss: 0.6723 - Accuracy: 0.5952 - F1: 0.5837
sub_4:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.5595 - F1: 0.5518
sub_4:Test (Best Model) - Loss: 0.6798 - Accuracy: 0.5357 - F1: 0.5351
sub_4:Test (Best Model) - Loss: 0.6719 - Accuracy: 0.5595 - F1: 0.5564
sub_4:Test (Best Model) - Loss: 0.6795 - Accuracy: 0.5595 - F1: 0.5595
sub_4:Test (Best Model) - Loss: 0.6593 - Accuracy: 0.5357 - F1: 0.5048
sub_4:Test (Best Model) - Loss: 0.6576 - Accuracy: 0.5714 - F1: 0.5333
sub_4:Test (Best Model) - Loss: 0.6364 - Accuracy: 0.6667 - F1: 0.6619
sub_4:Test (Best Model) - Loss: 0.6460 - Accuracy: 0.6429 - F1: 0.6396
sub_4:Test (Best Model) - Loss: 0.6444 - Accuracy: 0.6190 - F1: 0.6082
sub_4:Test (Best Model) - Loss: 0.6603 - Accuracy: 0.5238 - F1: 0.4167
sub_4:Test (Best Model) - Loss: 0.6698 - Accuracy: 0.5476 - F1: 0.4708
sub_4:Test (Best Model) - Loss: 0.6733 - Accuracy: 0.5238 - F1: 0.4013
sub_4:Test (Best Model) - Loss: 0.6713 - Accuracy: 0.5238 - F1: 0.3842
sub_4:Test (Best Model) - Loss: 0.6564 - Accuracy: 0.6071 - F1: 0.5354
sub_5:Test (Best Model) - Loss: 0.6320 - Accuracy: 0.6548 - F1: 0.6508
sub_5:Test (Best Model) - Loss: 0.6421 - Accuracy: 0.5952 - F1: 0.5159
sub_5:Test (Best Model) - Loss: 0.6437 - Accuracy: 0.6786 - F1: 0.6648
sub_5:Test (Best Model) - Loss: 0.6268 - Accuracy: 0.7143 - F1: 0.7128
sub_5:Test (Best Model) - Loss: 0.6304 - Accuracy: 0.5952 - F1: 0.5361
sub_5:Test (Best Model) - Loss: 0.6353 - Accuracy: 0.5238 - F1: 0.4542
sub_5:Test (Best Model) - Loss: 0.6225 - Accuracy: 0.5952 - F1: 0.5159
sub_5:Test (Best Model) - Loss: 0.6324 - Accuracy: 0.6548 - F1: 0.6361
sub_5:Test (Best Model) - Loss: 0.6182 - Accuracy: 0.6429 - F1: 0.5982
sub_5:Test (Best Model) - Loss: 0.6630 - Accuracy: 0.5714 - F1: 0.5088
sub_5:Test (Best Model) - Loss: 0.6288 - Accuracy: 0.6667 - F1: 0.6421
sub_5:Test (Best Model) - Loss: 0.6343 - Accuracy: 0.6786 - F1: 0.6415
sub_5:Test (Best Model) - Loss: 0.6095 - Accuracy: 0.6905 - F1: 0.6788
sub_5:Test (Best Model) - Loss: 0.6448 - Accuracy: 0.6548 - F1: 0.6150
sub_5:Test (Best Model) - Loss: 0.6324 - Accuracy: 0.6786 - F1: 0.6648
sub_6:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.4759
sub_6:Test (Best Model) - Loss: 0.6839 - Accuracy: 0.5595 - F1: 0.5544
sub_6:Test (Best Model) - Loss: 0.7038 - Accuracy: 0.4643 - F1: 0.4511
sub_6:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5952 - F1: 0.5932
sub_6:Test (Best Model) - Loss: 0.6669 - Accuracy: 0.5833 - F1: 0.5819
sub_6:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.5476 - F1: 0.5382
sub_6:Test (Best Model) - Loss: 0.6773 - Accuracy: 0.5119 - F1: 0.4911
sub_6:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.5357 - F1: 0.5048
sub_6:Test (Best Model) - Loss: 0.6732 - Accuracy: 0.5714 - F1: 0.5653
sub_6:Test (Best Model) - Loss: 0.6703 - Accuracy: 0.6310 - F1: 0.6188
sub_6:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5238 - F1: 0.5170
sub_6:Test (Best Model) - Loss: 0.6642 - Accuracy: 0.6786 - F1: 0.6782
sub_6:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.5952 - F1: 0.5952
sub_6:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.5595 - F1: 0.5595
sub_6:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5476 - F1: 0.5435
sub_7:Test (Best Model) - Loss: 0.6638 - Accuracy: 0.5952 - F1: 0.5800
sub_7:Test (Best Model) - Loss: 0.6789 - Accuracy: 0.5357 - F1: 0.4981
sub_7:Test (Best Model) - Loss: 0.6752 - Accuracy: 0.5595 - F1: 0.5450
sub_7:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5238 - F1: 0.5214
sub_7:Test (Best Model) - Loss: 0.6759 - Accuracy: 0.5595 - F1: 0.5358
sub_7:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.4881 - F1: 0.4662
sub_7:Test (Best Model) - Loss: 0.6561 - Accuracy: 0.5119 - F1: 0.4557
sub_7:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.5238 - F1: 0.5009
sub_7:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.4881 - F1: 0.4755
sub_7:Test (Best Model) - Loss: 0.6669 - Accuracy: 0.6190 - F1: 0.5852
sub_7:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.4524 - F1: 0.4121
sub_7:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.5119 - F1: 0.4958
sub_7:Test (Best Model) - Loss: 0.6799 - Accuracy: 0.5357 - F1: 0.5243
sub_7:Test (Best Model) - Loss: 0.6811 - Accuracy: 0.5714 - F1: 0.5692
sub_7:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.5595 - F1: 0.5167
sub_8:Test (Best Model) - Loss: 0.5237 - Accuracy: 0.7738 - F1: 0.7722
sub_8:Test (Best Model) - Loss: 0.6179 - Accuracy: 0.6190 - F1: 0.5852
sub_8:Test (Best Model) - Loss: 0.5329 - Accuracy: 0.8095 - F1: 0.8068
sub_8:Test (Best Model) - Loss: 0.5031 - Accuracy: 0.7857 - F1: 0.7856
sub_8:Test (Best Model) - Loss: 0.5315 - Accuracy: 0.7738 - F1: 0.7683
sub_8:Test (Best Model) - Loss: 0.5903 - Accuracy: 0.7619 - F1: 0.7569
sub_8:Test (Best Model) - Loss: 0.5849 - Accuracy: 0.6905 - F1: 0.6577
sub_8:Test (Best Model) - Loss: 0.6015 - Accuracy: 0.6905 - F1: 0.6756
sub_8:Test (Best Model) - Loss: 0.5590 - Accuracy: 0.7619 - F1: 0.7585
sub_8:Test (Best Model) - Loss: 0.4665 - Accuracy: 0.8333 - F1: 0.8309
sub_8:Test (Best Model) - Loss: 0.6011 - Accuracy: 0.5595 - F1: 0.4535
sub_8:Test (Best Model) - Loss: 0.6147 - Accuracy: 0.6071 - F1: 0.5354
sub_8:Test (Best Model) - Loss: 0.5948 - Accuracy: 0.6190 - F1: 0.5634
sub_8:Test (Best Model) - Loss: 0.5369 - Accuracy: 0.7500 - F1: 0.7333
sub_8:Test (Best Model) - Loss: 0.6269 - Accuracy: 0.6429 - F1: 0.6166
sub_9:Test (Best Model) - Loss: 0.5748 - Accuracy: 0.7738 - F1: 0.7730
sub_9:Test (Best Model) - Loss: 0.6221 - Accuracy: 0.7143 - F1: 0.7061
sub_9:Test (Best Model) - Loss: 0.6085 - Accuracy: 0.7738 - F1: 0.7712
sub_9:Test (Best Model) - Loss: 0.6375 - Accuracy: 0.6667 - F1: 0.6619
sub_9:Test (Best Model) - Loss: 0.6138 - Accuracy: 0.7500 - F1: 0.7497
sub_9:Test (Best Model) - Loss: 0.6585 - Accuracy: 0.6190 - F1: 0.6047
sub_9:Test (Best Model) - Loss: 0.6523 - Accuracy: 0.6190 - F1: 0.6111
sub_9:Test (Best Model) - Loss: 0.6740 - Accuracy: 0.5833 - F1: 0.5761
sub_9:Test (Best Model) - Loss: 0.6592 - Accuracy: 0.6310 - F1: 0.6219
sub_9:Test (Best Model) - Loss: 0.6555 - Accuracy: 0.6667 - F1: 0.6619
sub_9:Test (Best Model) - Loss: 0.6163 - Accuracy: 0.6548 - F1: 0.6268
sub_9:Test (Best Model) - Loss: 0.6424 - Accuracy: 0.6548 - F1: 0.6434
sub_9:Test (Best Model) - Loss: 0.6228 - Accuracy: 0.6190 - F1: 0.5910
sub_9:Test (Best Model) - Loss: 0.6291 - Accuracy: 0.6786 - F1: 0.6571
sub_9:Test (Best Model) - Loss: 0.5773 - Accuracy: 0.6786 - F1: 0.6415
sub_10:Test (Best Model) - Loss: 0.6695 - Accuracy: 0.6071 - F1: 0.6066
sub_10:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.5476 - F1: 0.5474
sub_10:Test (Best Model) - Loss: 0.6755 - Accuracy: 0.5357 - F1: 0.5341
sub_10:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.5833 - F1: 0.5833
sub_10:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5595 - F1: 0.5595
sub_10:Test (Best Model) - Loss: 0.6599 - Accuracy: 0.6071 - F1: 0.6003
sub_10:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5357 - F1: 0.5341
sub_10:Test (Best Model) - Loss: 0.6738 - Accuracy: 0.5595 - F1: 0.5564
sub_10:Test (Best Model) - Loss: 0.6546 - Accuracy: 0.6190 - F1: 0.6190
sub_10:Test (Best Model) - Loss: 0.6784 - Accuracy: 0.5476 - F1: 0.5347
sub_10:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.5952 - F1: 0.5943
sub_10:Test (Best Model) - Loss: 0.6678 - Accuracy: 0.5952 - F1: 0.5837
sub_10:Test (Best Model) - Loss: 0.6520 - Accuracy: 0.6429 - F1: 0.6396
sub_10:Test (Best Model) - Loss: 0.6724 - Accuracy: 0.6190 - F1: 0.6136
sub_10:Test (Best Model) - Loss: 0.6644 - Accuracy: 0.6310 - F1: 0.6296
sub_11:Test (Best Model) - Loss: 0.6745 - Accuracy: 0.5595 - F1: 0.5302
sub_11:Test (Best Model) - Loss: 0.6761 - Accuracy: 0.5476 - F1: 0.5258
sub_11:Test (Best Model) - Loss: 0.6954 - Accuracy: 0.5357 - F1: 0.5204
sub_11:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.5476 - F1: 0.5382
sub_11:Test (Best Model) - Loss: 0.6533 - Accuracy: 0.6786 - F1: 0.6680
sub_11:Test (Best Model) - Loss: 0.6672 - Accuracy: 0.6071 - F1: 0.5619
sub_11:Test (Best Model) - Loss: 0.6536 - Accuracy: 0.5595 - F1: 0.5088
sub_11:Test (Best Model) - Loss: 0.6629 - Accuracy: 0.5595 - F1: 0.5518
sub_11:Test (Best Model) - Loss: 0.6578 - Accuracy: 0.6429 - F1: 0.6257
sub_11:Test (Best Model) - Loss: 0.6220 - Accuracy: 0.6905 - F1: 0.6756
sub_11:Test (Best Model) - Loss: 0.6799 - Accuracy: 0.5357 - F1: 0.5159
sub_11:Test (Best Model) - Loss: 0.6684 - Accuracy: 0.6071 - F1: 0.5904
sub_11:Test (Best Model) - Loss: 0.6652 - Accuracy: 0.5952 - F1: 0.5709
sub_11:Test (Best Model) - Loss: 0.6697 - Accuracy: 0.5952 - F1: 0.5758
sub_11:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.5357 - F1: 0.5159
sub_12:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.4881 - F1: 0.4880
sub_12:Test (Best Model) - Loss: 0.6581 - Accuracy: 0.6190 - F1: 0.6047
sub_12:Test (Best Model) - Loss: 0.6361 - Accuracy: 0.6310 - F1: 0.6284
sub_12:Test (Best Model) - Loss: 0.5900 - Accuracy: 0.8452 - F1: 0.8447
sub_12:Test (Best Model) - Loss: 0.6157 - Accuracy: 0.7262 - F1: 0.7243
sub_12:Test (Best Model) - Loss: 0.6488 - Accuracy: 0.7143 - F1: 0.7136
sub_12:Test (Best Model) - Loss: 0.6213 - Accuracy: 0.7857 - F1: 0.7846
sub_12:Test (Best Model) - Loss: 0.6407 - Accuracy: 0.6905 - F1: 0.6816
sub_12:Test (Best Model) - Loss: 0.6630 - Accuracy: 0.6310 - F1: 0.6188
sub_12:Test (Best Model) - Loss: 0.6226 - Accuracy: 0.6786 - F1: 0.6730
sub_12:Test (Best Model) - Loss: 0.6244 - Accuracy: 0.6548 - F1: 0.6317
sub_12:Test (Best Model) - Loss: 0.6240 - Accuracy: 0.6310 - F1: 0.6111
sub_12:Test (Best Model) - Loss: 0.6051 - Accuracy: 0.7024 - F1: 0.6951
sub_12:Test (Best Model) - Loss: 0.6221 - Accuracy: 0.7143 - F1: 0.7128
sub_12:Test (Best Model) - Loss: 0.6034 - Accuracy: 0.7024 - F1: 0.6897
sub_13:Test (Best Model) - Loss: 0.6425 - Accuracy: 0.6786 - F1: 0.6774
sub_13:Test (Best Model) - Loss: 0.6556 - Accuracy: 0.7024 - F1: 0.7023
sub_13:Test (Best Model) - Loss: 0.6403 - Accuracy: 0.7143 - F1: 0.7083
sub_13:Test (Best Model) - Loss: 0.6578 - Accuracy: 0.6429 - F1: 0.6294
sub_13:Test (Best Model) - Loss: 0.6525 - Accuracy: 0.6905 - F1: 0.6903
sub_13:Test (Best Model) - Loss: 0.6353 - Accuracy: 0.6905 - F1: 0.6876
sub_13:Test (Best Model) - Loss: 0.6407 - Accuracy: 0.6905 - F1: 0.6903
sub_13:Test (Best Model) - Loss: 0.6331 - Accuracy: 0.6786 - F1: 0.6763
sub_13:Test (Best Model) - Loss: 0.6242 - Accuracy: 0.6786 - F1: 0.6774
sub_13:Test (Best Model) - Loss: 0.6587 - Accuracy: 0.6310 - F1: 0.6296
sub_13:Test (Best Model) - Loss: 0.6503 - Accuracy: 0.6667 - F1: 0.6597
sub_13:Test (Best Model) - Loss: 0.6383 - Accuracy: 0.6905 - F1: 0.6840
sub_13:Test (Best Model) - Loss: 0.6344 - Accuracy: 0.7143 - F1: 0.7102
sub_13:Test (Best Model) - Loss: 0.6066 - Accuracy: 0.7262 - F1: 0.7172
sub_13:Test (Best Model) - Loss: 0.6128 - Accuracy: 0.7024 - F1: 0.6989
sub_14:Test (Best Model) - Loss: 0.6218 - Accuracy: 0.6310 - F1: 0.6111
sub_14:Test (Best Model) - Loss: 0.5633 - Accuracy: 0.7143 - F1: 0.7083
sub_14:Test (Best Model) - Loss: 0.6308 - Accuracy: 0.5952 - F1: 0.5524
sub_14:Test (Best Model) - Loss: 0.5451 - Accuracy: 0.7262 - F1: 0.7252
sub_14:Test (Best Model) - Loss: 0.6420 - Accuracy: 0.5714 - F1: 0.5553
sub_14:Test (Best Model) - Loss: 0.6141 - Accuracy: 0.5833 - F1: 0.5270
sub_14:Test (Best Model) - Loss: 0.6096 - Accuracy: 0.5833 - F1: 0.5270
sub_14:Test (Best Model) - Loss: 0.6269 - Accuracy: 0.5833 - F1: 0.5270
sub_14:Test (Best Model) - Loss: 0.6048 - Accuracy: 0.6667 - F1: 0.6506
sub_14:Test (Best Model) - Loss: 0.6034 - Accuracy: 0.6071 - F1: 0.5540
sub_14:Test (Best Model) - Loss: 0.6209 - Accuracy: 0.6786 - F1: 0.6707
sub_14:Test (Best Model) - Loss: 0.6236 - Accuracy: 0.6548 - F1: 0.6268
sub_14:Test (Best Model) - Loss: 0.6434 - Accuracy: 0.5952 - F1: 0.5446
sub_14:Test (Best Model) - Loss: 0.6343 - Accuracy: 0.5833 - F1: 0.5609
sub_14:Test (Best Model) - Loss: 0.6419 - Accuracy: 0.5952 - F1: 0.5654

=== Summary Results ===

acc: 63.23 ± 5.33
F1: 61.23 ± 5.66
acc-in: 68.27 ± 4.94
F1-in: 67.00 ± 5.30
