lr: 1e-06
sub_6:Test (Best Model) - Loss: 1.2313 - Accuracy: 0.4881 - F1: 0.3280
sub_4:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.6548 - F1: 0.6361
sub_7:Test (Best Model) - Loss: 0.8498 - Accuracy: 0.4405 - F1: 0.3384
sub_9:Test (Best Model) - Loss: 0.8267 - Accuracy: 0.5119 - F1: 0.3944
sub_1:Test (Best Model) - Loss: 0.7816 - Accuracy: 0.5357 - F1: 0.4239
sub_5:Test (Best Model) - Loss: 0.9980 - Accuracy: 0.5000 - F1: 0.4556
sub_11:Test (Best Model) - Loss: 1.0624 - Accuracy: 0.5238 - F1: 0.3842
sub_10:Test (Best Model) - Loss: 0.5618 - Accuracy: 0.7024 - F1: 0.6825
sub_6:Test (Best Model) - Loss: 0.8358 - Accuracy: 0.5000 - F1: 0.4020
sub_8:Test (Best Model) - Loss: 0.1997 - Accuracy: 0.9524 - F1: 0.9523
sub_2:Test (Best Model) - Loss: 0.2813 - Accuracy: 0.9048 - F1: 0.9045
sub_12:Test (Best Model) - Loss: 0.3824 - Accuracy: 0.8214 - F1: 0.8170
sub_6:Test (Best Model) - Loss: 0.7227 - Accuracy: 0.5238 - F1: 0.4430
sub_14:Test (Best Model) - Loss: 0.4104 - Accuracy: 0.8095 - F1: 0.8041
sub_10:Test (Best Model) - Loss: 0.5339 - Accuracy: 0.6548 - F1: 0.6361
sub_4:Test (Best Model) - Loss: 0.5710 - Accuracy: 0.7262 - F1: 0.7172
sub_7:Test (Best Model) - Loss: 0.6296 - Accuracy: 0.6310 - F1: 0.6309
sub_3:Test (Best Model) - Loss: 0.6633 - Accuracy: 0.6190 - F1: 0.5544
sub_11:Test (Best Model) - Loss: 0.3655 - Accuracy: 0.8452 - F1: 0.8442
sub_8:Test (Best Model) - Loss: 0.2423 - Accuracy: 0.9286 - F1: 0.9286
sub_12:Test (Best Model) - Loss: 0.4440 - Accuracy: 0.8214 - F1: 0.8170
sub_5:Test (Best Model) - Loss: 0.8434 - Accuracy: 0.4167 - F1: 0.4065
sub_13:Test (Best Model) - Loss: 0.4438 - Accuracy: 0.7500 - F1: 0.7393
sub_10:Test (Best Model) - Loss: 0.4946 - Accuracy: 0.7857 - F1: 0.7826
sub_9:Test (Best Model) - Loss: 0.2593 - Accuracy: 0.9881 - F1: 0.9881
sub_2:Test (Best Model) - Loss: 0.3731 - Accuracy: 0.8929 - F1: 0.8927
sub_14:Test (Best Model) - Loss: 0.5208 - Accuracy: 0.7500 - F1: 0.7471
sub_6:Test (Best Model) - Loss: 0.3265 - Accuracy: 0.8810 - F1: 0.8807
sub_4:Test (Best Model) - Loss: 0.3708 - Accuracy: 0.8333 - F1: 0.8325
sub_13:Test (Best Model) - Loss: 0.5536 - Accuracy: 0.7619 - F1: 0.7614
sub_7:Test (Best Model) - Loss: 0.6493 - Accuracy: 0.5833 - F1: 0.5353
sub_8:Test (Best Model) - Loss: 0.2816 - Accuracy: 0.8690 - F1: 0.8668
sub_10:Test (Best Model) - Loss: 0.8044 - Accuracy: 0.6071 - F1: 0.5354
sub_1:Test (Best Model) - Loss: 0.3828 - Accuracy: 0.8571 - F1: 0.8558
sub_6:Test (Best Model) - Loss: 0.5490 - Accuracy: 0.7262 - F1: 0.7230
sub_7:Test (Best Model) - Loss: 0.7691 - Accuracy: 0.5357 - F1: 0.4382
sub_2:Test (Best Model) - Loss: 0.3631 - Accuracy: 0.8452 - F1: 0.8414
sub_12:Test (Best Model) - Loss: 0.2401 - Accuracy: 0.9524 - F1: 0.9523
sub_14:Test (Best Model) - Loss: 0.5372 - Accuracy: 0.7976 - F1: 0.7969
sub_10:Test (Best Model) - Loss: 0.2770 - Accuracy: 0.8690 - F1: 0.8675
sub_5:Test (Best Model) - Loss: 0.5416 - Accuracy: 0.7500 - F1: 0.7456
sub_4:Test (Best Model) - Loss: 0.2701 - Accuracy: 0.9167 - F1: 0.9167
sub_3:Test (Best Model) - Loss: 0.4042 - Accuracy: 0.8690 - F1: 0.8686
sub_8:Test (Best Model) - Loss: 0.2065 - Accuracy: 0.9286 - F1: 0.9282
sub_6:Test (Best Model) - Loss: 0.8177 - Accuracy: 0.3810 - F1: 0.3810
sub_4:Test (Best Model) - Loss: 0.3981 - Accuracy: 0.8333 - F1: 0.8286
sub_8:Test (Best Model) - Loss: 0.1554 - Accuracy: 0.9762 - F1: 0.9762
sub_11:Test (Best Model) - Loss: 0.2986 - Accuracy: 0.8452 - F1: 0.8414
sub_14:Test (Best Model) - Loss: 0.5250 - Accuracy: 0.7024 - F1: 0.6825
sub_13:Test (Best Model) - Loss: 0.7058 - Accuracy: 0.5714 - F1: 0.5088
sub_12:Test (Best Model) - Loss: 0.7580 - Accuracy: 0.5714 - F1: 0.4750
sub_7:Test (Best Model) - Loss: 0.5819 - Accuracy: 0.6667 - F1: 0.6619
sub_10:Test (Best Model) - Loss: 0.4168 - Accuracy: 0.8095 - F1: 0.8091
sub_5:Test (Best Model) - Loss: 0.6524 - Accuracy: 0.5833 - F1: 0.5655
sub_9:Test (Best Model) - Loss: 0.1631 - Accuracy: 0.9881 - F1: 0.9881
sub_2:Test (Best Model) - Loss: 0.3170 - Accuracy: 0.8810 - F1: 0.8799
sub_7:Test (Best Model) - Loss: 0.6303 - Accuracy: 0.6429 - F1: 0.5982
sub_6:Test (Best Model) - Loss: 0.9497 - Accuracy: 0.4405 - F1: 0.3861
sub_12:Test (Best Model) - Loss: 0.3925 - Accuracy: 0.8333 - F1: 0.8309
sub_8:Test (Best Model) - Loss: 0.1770 - Accuracy: 0.9762 - F1: 0.9762
sub_4:Test (Best Model) - Loss: 0.2989 - Accuracy: 0.9048 - F1: 0.9048
sub_14:Test (Best Model) - Loss: 0.3917 - Accuracy: 0.8214 - F1: 0.8194
sub_1:Test (Best Model) - Loss: 0.5631 - Accuracy: 0.6667 - F1: 0.6466
sub_3:Test (Best Model) - Loss: 0.7077 - Accuracy: 0.5119 - F1: 0.4794
sub_11:Test (Best Model) - Loss: 0.4807 - Accuracy: 0.6905 - F1: 0.6840
sub_12:Test (Best Model) - Loss: 0.5579 - Accuracy: 0.6786 - F1: 0.6415
sub_4:Test (Best Model) - Loss: 0.2501 - Accuracy: 0.9405 - F1: 0.9405
sub_14:Test (Best Model) - Loss: 0.4871 - Accuracy: 0.7500 - F1: 0.7333
sub_2:Test (Best Model) - Loss: 0.1812 - Accuracy: 0.9643 - F1: 0.9643
sub_8:Test (Best Model) - Loss: 0.2170 - Accuracy: 0.9762 - F1: 0.9762
sub_6:Test (Best Model) - Loss: 0.5263 - Accuracy: 0.7976 - F1: 0.7890
sub_1:Test (Best Model) - Loss: 0.5369 - Accuracy: 0.7976 - F1: 0.7941
sub_10:Test (Best Model) - Loss: 0.2948 - Accuracy: 0.8810 - F1: 0.8799
sub_5:Test (Best Model) - Loss: 0.7362 - Accuracy: 0.6310 - F1: 0.6219
sub_13:Test (Best Model) - Loss: 0.3493 - Accuracy: 0.8810 - F1: 0.8799
sub_3:Test (Best Model) - Loss: 0.4928 - Accuracy: 0.7738 - F1: 0.7699
sub_9:Test (Best Model) - Loss: 0.2934 - Accuracy: 0.9762 - F1: 0.9762
sub_14:Test (Best Model) - Loss: 0.3633 - Accuracy: 0.8452 - F1: 0.8425
sub_4:Test (Best Model) - Loss: 0.3328 - Accuracy: 0.9286 - F1: 0.9286
sub_11:Test (Best Model) - Loss: 0.3126 - Accuracy: 0.8810 - F1: 0.8792
sub_7:Test (Best Model) - Loss: 0.4121 - Accuracy: 0.8333 - F1: 0.8318
sub_6:Test (Best Model) - Loss: 0.7491 - Accuracy: 0.6190 - F1: 0.5714
sub_2:Test (Best Model) - Loss: 0.5440 - Accuracy: 0.7738 - F1: 0.7616
sub_12:Test (Best Model) - Loss: 0.2227 - Accuracy: 0.9405 - F1: 0.9405
sub_10:Test (Best Model) - Loss: 0.2958 - Accuracy: 0.8810 - F1: 0.8792
sub_13:Test (Best Model) - Loss: 0.9420 - Accuracy: 0.5119 - F1: 0.3593
sub_8:Test (Best Model) - Loss: 0.0589 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 0.3990 - Accuracy: 0.8095 - F1: 0.8056
sub_7:Test (Best Model) - Loss: 0.5761 - Accuracy: 0.6667 - F1: 0.6541
sub_6:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.6786 - F1: 0.6785
sub_14:Test (Best Model) - Loss: 0.5509 - Accuracy: 0.7381 - F1: 0.7188
sub_4:Test (Best Model) - Loss: 0.4055 - Accuracy: 0.8095 - F1: 0.8056
sub_9:Test (Best Model) - Loss: 0.1080 - Accuracy: 0.9762 - F1: 0.9762
sub_5:Test (Best Model) - Loss: 0.4354 - Accuracy: 0.8333 - F1: 0.8330
sub_2:Test (Best Model) - Loss: 0.3128 - Accuracy: 0.8690 - F1: 0.8668
sub_12:Test (Best Model) - Loss: 0.3796 - Accuracy: 0.8571 - F1: 0.8564
sub_11:Test (Best Model) - Loss: 0.4006 - Accuracy: 0.8690 - F1: 0.8681
sub_3:Test (Best Model) - Loss: 0.6557 - Accuracy: 0.6071 - F1: 0.5810
sub_10:Test (Best Model) - Loss: 0.2805 - Accuracy: 0.9048 - F1: 0.9039
sub_8:Test (Best Model) - Loss: 0.2019 - Accuracy: 0.9643 - F1: 0.9642
sub_5:Test (Best Model) - Loss: 0.7082 - Accuracy: 0.4881 - F1: 0.4712
sub_4:Test (Best Model) - Loss: 0.6123 - Accuracy: 0.5833 - F1: 0.5176
sub_13:Test (Best Model) - Loss: 0.4532 - Accuracy: 0.8571 - F1: 0.8558
sub_6:Test (Best Model) - Loss: 0.7013 - Accuracy: 0.5952 - F1: 0.5894
sub_2:Test (Best Model) - Loss: 0.3667 - Accuracy: 0.8214 - F1: 0.8155
sub_5:Test (Best Model) - Loss: 0.4443 - Accuracy: 0.8810 - F1: 0.8807
sub_12:Test (Best Model) - Loss: 0.4486 - Accuracy: 0.8333 - F1: 0.8330
sub_6:Test (Best Model) - Loss: 0.8956 - Accuracy: 0.5714 - F1: 0.5088
sub_7:Test (Best Model) - Loss: 0.4317 - Accuracy: 0.8214 - F1: 0.8202
sub_1:Test (Best Model) - Loss: 0.4708 - Accuracy: 0.7738 - F1: 0.7735
sub_14:Test (Best Model) - Loss: 0.5411 - Accuracy: 0.7143 - F1: 0.6889
sub_9:Test (Best Model) - Loss: 0.3139 - Accuracy: 0.9048 - F1: 0.9048
sub_8:Test (Best Model) - Loss: 0.2631 - Accuracy: 0.9405 - F1: 0.9403
sub_10:Test (Best Model) - Loss: 0.3759 - Accuracy: 0.8452 - F1: 0.8414
sub_11:Test (Best Model) - Loss: 0.1799 - Accuracy: 0.9405 - F1: 0.9404
sub_2:Test (Best Model) - Loss: 0.5963 - Accuracy: 0.7619 - F1: 0.7476
sub_4:Test (Best Model) - Loss: 0.3584 - Accuracy: 0.8810 - F1: 0.8803
sub_3:Test (Best Model) - Loss: 0.3037 - Accuracy: 0.8810 - F1: 0.8803
sub_13:Test (Best Model) - Loss: 0.5796 - Accuracy: 0.7262 - F1: 0.7262
sub_5:Test (Best Model) - Loss: 0.5728 - Accuracy: 0.7381 - F1: 0.7379
sub_6:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.6310 - F1: 0.6152
sub_12:Test (Best Model) - Loss: 0.3817 - Accuracy: 0.8214 - F1: 0.8214
sub_8:Test (Best Model) - Loss: 0.4284 - Accuracy: 0.8095 - F1: 0.8024
sub_14:Test (Best Model) - Loss: 0.2276 - Accuracy: 0.9762 - F1: 0.9762
sub_7:Test (Best Model) - Loss: 0.5220 - Accuracy: 0.7024 - F1: 0.7013
sub_8:Test (Best Model) - Loss: 0.7534 - Accuracy: 0.5000 - F1: 0.4269
sub_10:Test (Best Model) - Loss: 0.9842 - Accuracy: 0.5833 - F1: 0.4958
sub_2:Test (Best Model) - Loss: 0.2994 - Accuracy: 0.8929 - F1: 0.8916
sub_9:Test (Best Model) - Loss: 0.3823 - Accuracy: 0.8333 - F1: 0.8299
sub_4:Test (Best Model) - Loss: 0.5127 - Accuracy: 0.7262 - F1: 0.7243
sub_1:Test (Best Model) - Loss: 0.3981 - Accuracy: 0.7381 - F1: 0.7188
sub_5:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.6548 - F1: 0.6080
sub_6:Test (Best Model) - Loss: 0.7867 - Accuracy: 0.5714 - F1: 0.5088
sub_13:Test (Best Model) - Loss: 0.3836 - Accuracy: 0.8571 - F1: 0.8568
sub_14:Test (Best Model) - Loss: 1.0079 - Accuracy: 0.5714 - F1: 0.4750
sub_12:Test (Best Model) - Loss: 0.2988 - Accuracy: 0.8929 - F1: 0.8927
sub_8:Test (Best Model) - Loss: 0.6278 - Accuracy: 0.6905 - F1: 0.6756
sub_7:Test (Best Model) - Loss: 0.7289 - Accuracy: 0.5357 - F1: 0.4729
sub_3:Test (Best Model) - Loss: 0.5896 - Accuracy: 0.6310 - F1: 0.5728
sub_10:Test (Best Model) - Loss: 1.0225 - Accuracy: 0.4881 - F1: 0.3947
sub_11:Test (Best Model) - Loss: 0.1405 - Accuracy: 0.9643 - F1: 0.9643
sub_2:Test (Best Model) - Loss: 0.4647 - Accuracy: 0.7619 - F1: 0.7529
sub_4:Test (Best Model) - Loss: 0.5099 - Accuracy: 0.7381 - F1: 0.7306
sub_7:Test (Best Model) - Loss: 1.0017 - Accuracy: 0.5357 - F1: 0.4625
sub_12:Test (Best Model) - Loss: 0.5174 - Accuracy: 0.6429 - F1: 0.5906
sub_14:Test (Best Model) - Loss: 0.8218 - Accuracy: 0.6071 - F1: 0.5354
sub_9:Test (Best Model) - Loss: 0.2721 - Accuracy: 0.9405 - F1: 0.9404
sub_10:Test (Best Model) - Loss: 0.4720 - Accuracy: 0.7500 - F1: 0.7491
sub_6:Test (Best Model) - Loss: 0.8094 - Accuracy: 0.5714 - F1: 0.5675
sub_5:Test (Best Model) - Loss: 0.5482 - Accuracy: 0.7024 - F1: 0.7023
sub_13:Test (Best Model) - Loss: 0.3549 - Accuracy: 0.7976 - F1: 0.7890
sub_1:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.8452 - F1: 0.8450
sub_8:Test (Best Model) - Loss: 0.5465 - Accuracy: 0.7500 - F1: 0.7365
sub_12:Test (Best Model) - Loss: 0.2921 - Accuracy: 0.9048 - F1: 0.9039
sub_5:Test (Best Model) - Loss: 1.0079 - Accuracy: 0.4881 - F1: 0.3474
sub_7:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.6786 - F1: 0.6415
sub_4:Test (Best Model) - Loss: 0.4854 - Accuracy: 0.7500 - F1: 0.7497
sub_3:Test (Best Model) - Loss: 0.5815 - Accuracy: 0.7143 - F1: 0.7128
sub_14:Test (Best Model) - Loss: 0.7222 - Accuracy: 0.5833 - F1: 0.5270
sub_11:Test (Best Model) - Loss: 0.3752 - Accuracy: 0.8690 - F1: 0.8668
sub_2:Test (Best Model) - Loss: 0.3273 - Accuracy: 0.8571 - F1: 0.8571
sub_8:Test (Best Model) - Loss: 0.2953 - Accuracy: 0.9048 - F1: 0.9047
sub_10:Test (Best Model) - Loss: 0.6513 - Accuracy: 0.6429 - F1: 0.6257
sub_1:Test (Best Model) - Loss: 0.4808 - Accuracy: 0.7500 - F1: 0.7483
sub_9:Test (Best Model) - Loss: 0.3953 - Accuracy: 0.8214 - F1: 0.8212
sub_4:Test (Best Model) - Loss: 0.6794 - Accuracy: 0.6190 - F1: 0.5634
sub_10:Test (Best Model) - Loss: 0.5082 - Accuracy: 0.7500 - F1: 0.7500
sub_14:Test (Best Model) - Loss: 0.8691 - Accuracy: 0.5595 - F1: 0.4535
sub_2:Test (Best Model) - Loss: 0.2570 - Accuracy: 0.8810 - F1: 0.8792
sub_7:Test (Best Model) - Loss: 0.8298 - Accuracy: 0.5595 - F1: 0.4535
sub_13:Test (Best Model) - Loss: 0.4119 - Accuracy: 0.7738 - F1: 0.7712
sub_12:Test (Best Model) - Loss: 0.4248 - Accuracy: 0.8095 - F1: 0.8068
sub_5:Test (Best Model) - Loss: 0.5975 - Accuracy: 0.7024 - F1: 0.6972
sub_3:Test (Best Model) - Loss: 0.7108 - Accuracy: 0.5952 - F1: 0.5800
sub_12:Test (Best Model) - Loss: 0.4973 - Accuracy: 0.7738 - F1: 0.7722
sub_2:Test (Best Model) - Loss: 0.2931 - Accuracy: 0.9405 - F1: 0.9403
sub_14:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.6905 - F1: 0.6577
sub_11:Test (Best Model) - Loss: 0.1623 - Accuracy: 0.9286 - F1: 0.9284
sub_1:Test (Best Model) - Loss: 0.5743 - Accuracy: 0.6667 - F1: 0.6313
sub_7:Test (Best Model) - Loss: 0.8514 - Accuracy: 0.4881 - F1: 0.4712
sub_9:Test (Best Model) - Loss: 0.3209 - Accuracy: 0.8214 - F1: 0.8155
sub_13:Test (Best Model) - Loss: 0.3517 - Accuracy: 0.8333 - F1: 0.8286
sub_3:Test (Best Model) - Loss: 0.5400 - Accuracy: 0.7143 - F1: 0.7128
sub_2:Test (Best Model) - Loss: 0.2575 - Accuracy: 0.9048 - F1: 0.9039
sub_9:Test (Best Model) - Loss: 0.5443 - Accuracy: 0.7262 - F1: 0.7262
sub_11:Test (Best Model) - Loss: 0.2745 - Accuracy: 0.8929 - F1: 0.8921
sub_5:Test (Best Model) - Loss: 0.5324 - Accuracy: 0.7500 - F1: 0.7471
sub_1:Test (Best Model) - Loss: 0.3162 - Accuracy: 0.9286 - F1: 0.9282
sub_13:Test (Best Model) - Loss: 0.3709 - Accuracy: 0.8929 - F1: 0.8925
sub_9:Test (Best Model) - Loss: 0.2990 - Accuracy: 0.8333 - F1: 0.8286
sub_1:Test (Best Model) - Loss: 0.9342 - Accuracy: 0.4405 - F1: 0.3760
sub_3:Test (Best Model) - Loss: 0.6108 - Accuracy: 0.6786 - F1: 0.6473
sub_11:Test (Best Model) - Loss: 0.2092 - Accuracy: 0.9405 - F1: 0.9405
sub_5:Test (Best Model) - Loss: 0.5509 - Accuracy: 0.7143 - F1: 0.7005
sub_13:Test (Best Model) - Loss: 0.3379 - Accuracy: 0.8810 - F1: 0.8809
sub_1:Test (Best Model) - Loss: 0.8295 - Accuracy: 0.5833 - F1: 0.5073
sub_9:Test (Best Model) - Loss: 0.4003 - Accuracy: 0.8571 - F1: 0.8542
sub_3:Test (Best Model) - Loss: 0.7101 - Accuracy: 0.5357 - F1: 0.5159
sub_11:Test (Best Model) - Loss: 0.3030 - Accuracy: 0.9048 - F1: 0.9039
sub_13:Test (Best Model) - Loss: 0.8307 - Accuracy: 0.4405 - F1: 0.4398
sub_9:Test (Best Model) - Loss: 0.6119 - Accuracy: 0.7619 - F1: 0.7529
sub_1:Test (Best Model) - Loss: 0.5751 - Accuracy: 0.6905 - F1: 0.6876
sub_3:Test (Best Model) - Loss: 0.7093 - Accuracy: 0.5952 - F1: 0.5361
sub_11:Test (Best Model) - Loss: 0.2903 - Accuracy: 0.9286 - F1: 0.9285
sub_13:Test (Best Model) - Loss: 0.2718 - Accuracy: 0.9048 - F1: 0.9039
sub_9:Test (Best Model) - Loss: 0.3794 - Accuracy: 0.7976 - F1: 0.7969
sub_1:Test (Best Model) - Loss: 0.5374 - Accuracy: 0.6786 - F1: 0.6612
sub_11:Test (Best Model) - Loss: 0.1411 - Accuracy: 0.9762 - F1: 0.9762
sub_3:Test (Best Model) - Loss: 0.6541 - Accuracy: 0.6548 - F1: 0.6080
sub_3:Test (Best Model) - Loss: 0.7832 - Accuracy: 0.5595 - F1: 0.4535

=== Summary Results ===

acc: 75.33 ± 9.08
F1: 73.33 ± 10.16
acc-in: 84.58 ± 9.35
F1-in: 83.16 ± 10.30
