lr: 1e-05
sub_1:Test (Best Model) - Loss: 0.5929 - Accuracy: 0.7381 - F1: 0.7224
sub_1:Test (Best Model) - Loss: 0.6572 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 0.5891 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 0.5937 - Accuracy: 0.7381 - F1: 0.7188
sub_1:Test (Best Model) - Loss: 0.6492 - Accuracy: 0.7143 - F1: 0.6932
sub_1:Test (Best Model) - Loss: 0.4318 - Accuracy: 0.8690 - F1: 0.8675
sub_1:Test (Best Model) - Loss: 0.4160 - Accuracy: 0.8452 - F1: 0.8425
sub_1:Test (Best Model) - Loss: 0.4134 - Accuracy: 0.8690 - F1: 0.8686
sub_1:Test (Best Model) - Loss: 0.4327 - Accuracy: 0.7976 - F1: 0.7969
sub_1:Test (Best Model) - Loss: 0.4050 - Accuracy: 0.8452 - F1: 0.8447
sub_1:Test (Best Model) - Loss: 0.6027 - Accuracy: 0.6905 - F1: 0.6577
sub_1:Test (Best Model) - Loss: 0.5530 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 0.5063 - Accuracy: 0.7143 - F1: 0.6889
sub_1:Test (Best Model) - Loss: 0.5499 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 0.5709 - Accuracy: 0.7262 - F1: 0.7040
sub_2:Test (Best Model) - Loss: 0.4184 - Accuracy: 0.8333 - F1: 0.8333
sub_2:Test (Best Model) - Loss: 0.4158 - Accuracy: 0.8690 - F1: 0.8690
sub_2:Test (Best Model) - Loss: 0.3765 - Accuracy: 0.9286 - F1: 0.9285
sub_2:Test (Best Model) - Loss: 0.4051 - Accuracy: 0.8929 - F1: 0.8925
sub_2:Test (Best Model) - Loss: 0.4456 - Accuracy: 0.8214 - F1: 0.8194
sub_2:Test (Best Model) - Loss: 0.4115 - Accuracy: 0.7976 - F1: 0.7890
sub_2:Test (Best Model) - Loss: 0.3779 - Accuracy: 0.7857 - F1: 0.7754
sub_2:Test (Best Model) - Loss: 0.3637 - Accuracy: 0.8333 - F1: 0.8286
sub_2:Test (Best Model) - Loss: 0.3729 - Accuracy: 0.7619 - F1: 0.7476
sub_2:Test (Best Model) - Loss: 0.4047 - Accuracy: 0.8095 - F1: 0.8024
sub_2:Test (Best Model) - Loss: 0.3570 - Accuracy: 0.8571 - F1: 0.8558
sub_2:Test (Best Model) - Loss: 0.3423 - Accuracy: 0.8810 - F1: 0.8799
sub_2:Test (Best Model) - Loss: 0.3669 - Accuracy: 0.8690 - F1: 0.8681
sub_2:Test (Best Model) - Loss: 0.2891 - Accuracy: 0.8810 - F1: 0.8799
sub_2:Test (Best Model) - Loss: 0.3805 - Accuracy: 0.8214 - F1: 0.8208
sub_3:Test (Best Model) - Loss: 0.6861 - Accuracy: 0.6190 - F1: 0.5634
sub_3:Test (Best Model) - Loss: 0.7736 - Accuracy: 0.5595 - F1: 0.4670
sub_3:Test (Best Model) - Loss: 0.6321 - Accuracy: 0.6190 - F1: 0.5634
sub_3:Test (Best Model) - Loss: 0.7703 - Accuracy: 0.5595 - F1: 0.4670
sub_3:Test (Best Model) - Loss: 0.8819 - Accuracy: 0.5833 - F1: 0.4958
sub_3:Test (Best Model) - Loss: 0.4230 - Accuracy: 0.7500 - F1: 0.7500
sub_3:Test (Best Model) - Loss: 0.4816 - Accuracy: 0.7738 - F1: 0.7735
sub_3:Test (Best Model) - Loss: 0.5465 - Accuracy: 0.6667 - F1: 0.6665
sub_3:Test (Best Model) - Loss: 0.5254 - Accuracy: 0.7143 - F1: 0.7117
sub_3:Test (Best Model) - Loss: 0.4731 - Accuracy: 0.7500 - F1: 0.7500
sub_3:Test (Best Model) - Loss: 0.6482 - Accuracy: 0.7262 - F1: 0.7040
sub_3:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.6548 - F1: 0.6080
sub_3:Test (Best Model) - Loss: 0.6553 - Accuracy: 0.7024 - F1: 0.6735
sub_3:Test (Best Model) - Loss: 0.5920 - Accuracy: 0.7024 - F1: 0.6735
sub_3:Test (Best Model) - Loss: 0.6719 - Accuracy: 0.6548 - F1: 0.6080
sub_4:Test (Best Model) - Loss: 0.4843 - Accuracy: 0.7381 - F1: 0.7379
sub_4:Test (Best Model) - Loss: 0.4780 - Accuracy: 0.7500 - F1: 0.7483
sub_4:Test (Best Model) - Loss: 0.5369 - Accuracy: 0.7262 - F1: 0.7243
sub_4:Test (Best Model) - Loss: 0.5492 - Accuracy: 0.7024 - F1: 0.7023
sub_4:Test (Best Model) - Loss: 0.5042 - Accuracy: 0.7976 - F1: 0.7962
sub_4:Test (Best Model) - Loss: 0.5215 - Accuracy: 0.7381 - F1: 0.7368
sub_4:Test (Best Model) - Loss: 0.4826 - Accuracy: 0.7500 - F1: 0.7439
sub_4:Test (Best Model) - Loss: 0.4201 - Accuracy: 0.8333 - F1: 0.8332
sub_4:Test (Best Model) - Loss: 0.3988 - Accuracy: 0.8452 - F1: 0.8450
sub_4:Test (Best Model) - Loss: 0.4596 - Accuracy: 0.7738 - F1: 0.7722
sub_4:Test (Best Model) - Loss: 0.4375 - Accuracy: 0.7619 - F1: 0.7529
sub_4:Test (Best Model) - Loss: 0.4367 - Accuracy: 0.7857 - F1: 0.7776
sub_4:Test (Best Model) - Loss: 0.4732 - Accuracy: 0.7857 - F1: 0.7776
sub_4:Test (Best Model) - Loss: 0.5360 - Accuracy: 0.7619 - F1: 0.7504
sub_4:Test (Best Model) - Loss: 0.4630 - Accuracy: 0.7738 - F1: 0.7664
sub_5:Test (Best Model) - Loss: 0.3700 - Accuracy: 0.8333 - F1: 0.8332
sub_5:Test (Best Model) - Loss: 0.3794 - Accuracy: 0.8452 - F1: 0.8450
sub_5:Test (Best Model) - Loss: 0.2984 - Accuracy: 0.9167 - F1: 0.9166
sub_5:Test (Best Model) - Loss: 0.3966 - Accuracy: 0.8095 - F1: 0.8091
sub_5:Test (Best Model) - Loss: 0.3594 - Accuracy: 0.8571 - F1: 0.8568
sub_5:Test (Best Model) - Loss: 0.4466 - Accuracy: 0.8333 - F1: 0.8286
sub_5:Test (Best Model) - Loss: 0.4239 - Accuracy: 0.7857 - F1: 0.7812
sub_5:Test (Best Model) - Loss: 0.4346 - Accuracy: 0.7619 - F1: 0.7569
sub_5:Test (Best Model) - Loss: 0.3911 - Accuracy: 0.8452 - F1: 0.8425
sub_5:Test (Best Model) - Loss: 0.4173 - Accuracy: 0.8214 - F1: 0.8194
sub_5:Test (Best Model) - Loss: 0.3770 - Accuracy: 0.7857 - F1: 0.7812
sub_5:Test (Best Model) - Loss: 0.3661 - Accuracy: 0.8333 - F1: 0.8318
sub_5:Test (Best Model) - Loss: 0.3753 - Accuracy: 0.7976 - F1: 0.7953
sub_5:Test (Best Model) - Loss: 0.3843 - Accuracy: 0.8333 - F1: 0.8309
sub_5:Test (Best Model) - Loss: 0.3429 - Accuracy: 0.9286 - F1: 0.9285
sub_6:Test (Best Model) - Loss: 0.6320 - Accuracy: 0.6786 - F1: 0.6782
sub_6:Test (Best Model) - Loss: 0.5733 - Accuracy: 0.7024 - F1: 0.7013
sub_6:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.6429 - F1: 0.6427
sub_6:Test (Best Model) - Loss: 0.6193 - Accuracy: 0.6667 - F1: 0.6659
sub_6:Test (Best Model) - Loss: 0.6206 - Accuracy: 0.6786 - F1: 0.6785
sub_6:Test (Best Model) - Loss: 0.6048 - Accuracy: 0.6190 - F1: 0.6190
sub_6:Test (Best Model) - Loss: 0.6137 - Accuracy: 0.6667 - F1: 0.6650
sub_6:Test (Best Model) - Loss: 0.5605 - Accuracy: 0.7143 - F1: 0.7143
sub_6:Test (Best Model) - Loss: 0.6063 - Accuracy: 0.6190 - F1: 0.6156
sub_6:Test (Best Model) - Loss: 0.5232 - Accuracy: 0.7738 - F1: 0.7712
sub_6:Test (Best Model) - Loss: 0.5944 - Accuracy: 0.6548 - F1: 0.6547
sub_6:Test (Best Model) - Loss: 0.5810 - Accuracy: 0.7143 - F1: 0.7136
sub_6:Test (Best Model) - Loss: 0.5377 - Accuracy: 0.7619 - F1: 0.7618
sub_6:Test (Best Model) - Loss: 0.6400 - Accuracy: 0.6905 - F1: 0.6876
sub_6:Test (Best Model) - Loss: 0.5985 - Accuracy: 0.6310 - F1: 0.6305
sub_7:Test (Best Model) - Loss: 0.6593 - Accuracy: 0.6071 - F1: 0.5975
sub_7:Test (Best Model) - Loss: 0.7322 - Accuracy: 0.5238 - F1: 0.5214
sub_7:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.6190 - F1: 0.6156
sub_7:Test (Best Model) - Loss: 0.7110 - Accuracy: 0.6429 - F1: 0.6354
sub_7:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.5833 - F1: 0.5785
sub_7:Test (Best Model) - Loss: 0.6434 - Accuracy: 0.6310 - F1: 0.6010
sub_7:Test (Best Model) - Loss: 0.5663 - Accuracy: 0.6071 - F1: 0.5753
sub_7:Test (Best Model) - Loss: 0.6196 - Accuracy: 0.6310 - F1: 0.6111
sub_7:Test (Best Model) - Loss: 0.6544 - Accuracy: 0.5476 - F1: 0.5435
sub_7:Test (Best Model) - Loss: 0.6280 - Accuracy: 0.6310 - F1: 0.6010
sub_7:Test (Best Model) - Loss: 0.6167 - Accuracy: 0.5952 - F1: 0.5932
sub_7:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.5595 - F1: 0.5595
sub_7:Test (Best Model) - Loss: 0.6111 - Accuracy: 0.6429 - F1: 0.6427
sub_7:Test (Best Model) - Loss: 0.6417 - Accuracy: 0.6190 - F1: 0.6171
sub_7:Test (Best Model) - Loss: 0.6703 - Accuracy: 0.5833 - F1: 0.5655
sub_8:Test (Best Model) - Loss: 0.3782 - Accuracy: 0.8452 - F1: 0.8450
sub_8:Test (Best Model) - Loss: 0.3602 - Accuracy: 0.8333 - F1: 0.8330
sub_8:Test (Best Model) - Loss: 0.3574 - Accuracy: 0.8690 - F1: 0.8686
sub_8:Test (Best Model) - Loss: 0.3587 - Accuracy: 0.8214 - F1: 0.8212
sub_8:Test (Best Model) - Loss: 0.3567 - Accuracy: 0.8333 - F1: 0.8332
sub_8:Test (Best Model) - Loss: 0.3024 - Accuracy: 0.9167 - F1: 0.9166
sub_8:Test (Best Model) - Loss: 0.2888 - Accuracy: 0.8810 - F1: 0.8792
sub_8:Test (Best Model) - Loss: 0.2944 - Accuracy: 0.8929 - F1: 0.8928
sub_8:Test (Best Model) - Loss: 0.2812 - Accuracy: 0.8810 - F1: 0.8803
sub_8:Test (Best Model) - Loss: 0.2921 - Accuracy: 0.9048 - F1: 0.9043
sub_8:Test (Best Model) - Loss: 0.2640 - Accuracy: 0.8810 - F1: 0.8799
sub_8:Test (Best Model) - Loss: 0.2977 - Accuracy: 0.8690 - F1: 0.8668
sub_8:Test (Best Model) - Loss: 0.2758 - Accuracy: 0.8810 - F1: 0.8799
sub_8:Test (Best Model) - Loss: 0.2583 - Accuracy: 0.9167 - F1: 0.9161
sub_8:Test (Best Model) - Loss: 0.2835 - Accuracy: 0.8571 - F1: 0.8558
sub_9:Test (Best Model) - Loss: 0.3990 - Accuracy: 0.8452 - F1: 0.8450
sub_9:Test (Best Model) - Loss: 0.3847 - Accuracy: 0.8571 - F1: 0.8564
sub_9:Test (Best Model) - Loss: 0.4095 - Accuracy: 0.8214 - F1: 0.8194
sub_9:Test (Best Model) - Loss: 0.4702 - Accuracy: 0.7500 - F1: 0.7439
sub_9:Test (Best Model) - Loss: 0.4698 - Accuracy: 0.7738 - F1: 0.7683
sub_9:Test (Best Model) - Loss: 0.4318 - Accuracy: 0.8214 - F1: 0.8194
sub_9:Test (Best Model) - Loss: 0.5094 - Accuracy: 0.7619 - F1: 0.7585
sub_9:Test (Best Model) - Loss: 0.4835 - Accuracy: 0.7619 - F1: 0.7614
sub_9:Test (Best Model) - Loss: 0.4223 - Accuracy: 0.8571 - F1: 0.8558
sub_9:Test (Best Model) - Loss: 0.4485 - Accuracy: 0.7976 - F1: 0.7962
sub_9:Test (Best Model) - Loss: 0.5686 - Accuracy: 0.6905 - F1: 0.6577
sub_9:Test (Best Model) - Loss: 0.5233 - Accuracy: 0.7381 - F1: 0.7188
sub_9:Test (Best Model) - Loss: 0.4924 - Accuracy: 0.7262 - F1: 0.7079
sub_9:Test (Best Model) - Loss: 0.4865 - Accuracy: 0.7024 - F1: 0.6783
sub_9:Test (Best Model) - Loss: 0.4876 - Accuracy: 0.7262 - F1: 0.7040
sub_10:Test (Best Model) - Loss: 0.5783 - Accuracy: 0.7024 - F1: 0.7023
sub_10:Test (Best Model) - Loss: 0.5887 - Accuracy: 0.6667 - F1: 0.6665
sub_10:Test (Best Model) - Loss: 0.6118 - Accuracy: 0.6905 - F1: 0.6840
sub_10:Test (Best Model) - Loss: 0.6112 - Accuracy: 0.6905 - F1: 0.6860
sub_10:Test (Best Model) - Loss: 0.6009 - Accuracy: 0.6786 - F1: 0.6763
sub_10:Test (Best Model) - Loss: 0.5945 - Accuracy: 0.6905 - F1: 0.6889
sub_10:Test (Best Model) - Loss: 0.5682 - Accuracy: 0.6667 - F1: 0.6619
sub_10:Test (Best Model) - Loss: 0.6403 - Accuracy: 0.6190 - F1: 0.6171
sub_10:Test (Best Model) - Loss: 0.6143 - Accuracy: 0.6667 - F1: 0.6636
sub_10:Test (Best Model) - Loss: 0.5899 - Accuracy: 0.6905 - F1: 0.6903
sub_10:Test (Best Model) - Loss: 0.6321 - Accuracy: 0.6667 - F1: 0.6665
sub_10:Test (Best Model) - Loss: 0.5263 - Accuracy: 0.7143 - F1: 0.7128
sub_10:Test (Best Model) - Loss: 0.4830 - Accuracy: 0.8095 - F1: 0.8094
sub_10:Test (Best Model) - Loss: 0.5619 - Accuracy: 0.7024 - F1: 0.6972
sub_10:Test (Best Model) - Loss: 0.5536 - Accuracy: 0.7143 - F1: 0.7141
sub_11:Test (Best Model) - Loss: 0.5471 - Accuracy: 0.7024 - F1: 0.7023
sub_11:Test (Best Model) - Loss: 0.5897 - Accuracy: 0.6548 - F1: 0.6547
sub_11:Test (Best Model) - Loss: 0.5931 - Accuracy: 0.7143 - F1: 0.7143
sub_11:Test (Best Model) - Loss: 0.6254 - Accuracy: 0.6548 - F1: 0.6547
sub_11:Test (Best Model) - Loss: 0.5080 - Accuracy: 0.7024 - F1: 0.7013
sub_11:Test (Best Model) - Loss: 0.4341 - Accuracy: 0.7976 - F1: 0.7941
sub_11:Test (Best Model) - Loss: 0.4834 - Accuracy: 0.7738 - F1: 0.7722
sub_11:Test (Best Model) - Loss: 0.4267 - Accuracy: 0.8333 - F1: 0.8325
sub_11:Test (Best Model) - Loss: 0.4733 - Accuracy: 0.7619 - F1: 0.7614
sub_11:Test (Best Model) - Loss: 0.4648 - Accuracy: 0.7262 - F1: 0.7262
sub_11:Test (Best Model) - Loss: 0.4799 - Accuracy: 0.7857 - F1: 0.7826
sub_11:Test (Best Model) - Loss: 0.5732 - Accuracy: 0.6786 - F1: 0.6707
sub_11:Test (Best Model) - Loss: 0.4867 - Accuracy: 0.7857 - F1: 0.7838
sub_11:Test (Best Model) - Loss: 0.4492 - Accuracy: 0.7857 - F1: 0.7812
sub_11:Test (Best Model) - Loss: 0.5057 - Accuracy: 0.7381 - F1: 0.7368
sub_12:Test (Best Model) - Loss: 0.4250 - Accuracy: 0.8214 - F1: 0.8208
sub_12:Test (Best Model) - Loss: 0.3530 - Accuracy: 0.8571 - F1: 0.8568
sub_12:Test (Best Model) - Loss: 0.3969 - Accuracy: 0.8452 - F1: 0.8442
sub_12:Test (Best Model) - Loss: 0.3458 - Accuracy: 0.9048 - F1: 0.9048
sub_12:Test (Best Model) - Loss: 0.3955 - Accuracy: 0.8452 - F1: 0.8450
sub_12:Test (Best Model) - Loss: 0.5301 - Accuracy: 0.7381 - F1: 0.7255
sub_12:Test (Best Model) - Loss: 0.4870 - Accuracy: 0.7262 - F1: 0.7114
sub_12:Test (Best Model) - Loss: 0.5144 - Accuracy: 0.7381 - F1: 0.7282
sub_12:Test (Best Model) - Loss: 0.4850 - Accuracy: 0.7619 - F1: 0.7504
sub_12:Test (Best Model) - Loss: 0.5274 - Accuracy: 0.7500 - F1: 0.7439
sub_12:Test (Best Model) - Loss: 0.4969 - Accuracy: 0.7738 - F1: 0.7641
sub_12:Test (Best Model) - Loss: 0.4206 - Accuracy: 0.8214 - F1: 0.8170
sub_12:Test (Best Model) - Loss: 0.3821 - Accuracy: 0.8452 - F1: 0.8425
sub_12:Test (Best Model) - Loss: 0.3770 - Accuracy: 0.8214 - F1: 0.8183
sub_12:Test (Best Model) - Loss: 0.5088 - Accuracy: 0.7500 - F1: 0.7365
sub_13:Test (Best Model) - Loss: 0.5708 - Accuracy: 0.6786 - F1: 0.6774
sub_13:Test (Best Model) - Loss: 0.5635 - Accuracy: 0.7262 - F1: 0.7262
sub_13:Test (Best Model) - Loss: 0.5438 - Accuracy: 0.7024 - F1: 0.6972
sub_13:Test (Best Model) - Loss: 0.5247 - Accuracy: 0.7857 - F1: 0.7838
sub_13:Test (Best Model) - Loss: 0.5452 - Accuracy: 0.7857 - F1: 0.7856
sub_13:Test (Best Model) - Loss: 0.5281 - Accuracy: 0.6905 - F1: 0.6860
sub_13:Test (Best Model) - Loss: 0.5145 - Accuracy: 0.7024 - F1: 0.6972
sub_13:Test (Best Model) - Loss: 0.5227 - Accuracy: 0.7262 - F1: 0.7214
sub_13:Test (Best Model) - Loss: 0.4672 - Accuracy: 0.7857 - F1: 0.7846
sub_13:Test (Best Model) - Loss: 0.4747 - Accuracy: 0.7500 - F1: 0.7483
sub_13:Test (Best Model) - Loss: 0.5074 - Accuracy: 0.7738 - F1: 0.7712
sub_13:Test (Best Model) - Loss: 0.5560 - Accuracy: 0.7500 - F1: 0.7471
sub_13:Test (Best Model) - Loss: 0.4895 - Accuracy: 0.8214 - F1: 0.8202
sub_13:Test (Best Model) - Loss: 0.4772 - Accuracy: 0.8214 - F1: 0.8208
sub_13:Test (Best Model) - Loss: 0.5152 - Accuracy: 0.7738 - F1: 0.7722
sub_14:Test (Best Model) - Loss: 0.3259 - Accuracy: 0.8690 - F1: 0.8681
sub_14:Test (Best Model) - Loss: 0.3456 - Accuracy: 0.8333 - F1: 0.8330
sub_14:Test (Best Model) - Loss: 0.2936 - Accuracy: 0.9048 - F1: 0.9047
sub_14:Test (Best Model) - Loss: 0.3385 - Accuracy: 0.8571 - F1: 0.8571
sub_14:Test (Best Model) - Loss: 0.3394 - Accuracy: 0.8929 - F1: 0.8928
sub_14:Test (Best Model) - Loss: 0.3103 - Accuracy: 0.8571 - F1: 0.8551
sub_14:Test (Best Model) - Loss: 0.4501 - Accuracy: 0.7619 - F1: 0.7569
sub_14:Test (Best Model) - Loss: 0.3521 - Accuracy: 0.8214 - F1: 0.8170
sub_14:Test (Best Model) - Loss: 0.3590 - Accuracy: 0.8095 - F1: 0.8068
sub_14:Test (Best Model) - Loss: 0.2974 - Accuracy: 0.8571 - F1: 0.8551
sub_14:Test (Best Model) - Loss: 0.3968 - Accuracy: 0.8214 - F1: 0.8194
sub_14:Test (Best Model) - Loss: 0.3440 - Accuracy: 0.9048 - F1: 0.9045
sub_14:Test (Best Model) - Loss: 0.3828 - Accuracy: 0.8214 - F1: 0.8212
sub_14:Test (Best Model) - Loss: 0.3592 - Accuracy: 0.8810 - F1: 0.8809
sub_14:Test (Best Model) - Loss: 0.4179 - Accuracy: 0.8333 - F1: 0.8333

=== Summary Results ===

acc: 75.98 ± 7.53
F1: 75.28 ± 7.98
acc-in: 81.47 ± 6.95
F1-in: 81.16 ± 7.17
