lr: 0.001
sub_1:Test (Best Model) - Loss: 1.7546 - Accuracy: 0.4286 - F1: 0.3326
sub_12:Test (Best Model) - Loss: 1.8839 - Accuracy: 0.4190 - F1: 0.4035
sub_8:Test (Best Model) - Loss: 1.5267 - Accuracy: 0.4667 - F1: 0.4433
sub_14:Test (Best Model) - Loss: 1.7010 - Accuracy: 0.4810 - F1: 0.4914
sub_9:Test (Best Model) - Loss: 1.9083 - Accuracy: 0.3905 - F1: 0.3733
sub_6:Test (Best Model) - Loss: 2.5392 - Accuracy: 0.3429 - F1: 0.2887
sub_11:Test (Best Model) - Loss: 2.0332 - Accuracy: 0.4905 - F1: 0.4500
sub_13:Test (Best Model) - Loss: 2.3149 - Accuracy: 0.3238 - F1: 0.2317
sub_3:Test (Best Model) - Loss: 2.7459 - Accuracy: 0.2905 - F1: 0.1778
sub_7:Test (Best Model) - Loss: 2.4683 - Accuracy: 0.2857 - F1: 0.2471
sub_5:Test (Best Model) - Loss: 3.4095 - Accuracy: 0.2667 - F1: 0.1769
sub_2:Test (Best Model) - Loss: 2.0747 - Accuracy: 0.4476 - F1: 0.3904
sub_12:Test (Best Model) - Loss: 1.3411 - Accuracy: 0.4619 - F1: 0.4496
sub_10:Test (Best Model) - Loss: 2.1047 - Accuracy: 0.4476 - F1: 0.3886
sub_4:Test (Best Model) - Loss: 1.8002 - Accuracy: 0.4762 - F1: 0.4317
sub_14:Test (Best Model) - Loss: 1.6259 - Accuracy: 0.4714 - F1: 0.4687
sub_3:Test (Best Model) - Loss: 2.3491 - Accuracy: 0.2857 - F1: 0.1668
sub_9:Test (Best Model) - Loss: 1.7762 - Accuracy: 0.4429 - F1: 0.4293
sub_8:Test (Best Model) - Loss: 1.9506 - Accuracy: 0.4762 - F1: 0.4602
sub_2:Test (Best Model) - Loss: 1.4332 - Accuracy: 0.4381 - F1: 0.3708
sub_5:Test (Best Model) - Loss: 2.5386 - Accuracy: 0.3048 - F1: 0.2210
sub_7:Test (Best Model) - Loss: 2.6296 - Accuracy: 0.2381 - F1: 0.1933
sub_11:Test (Best Model) - Loss: 1.8815 - Accuracy: 0.5190 - F1: 0.4834
sub_6:Test (Best Model) - Loss: 2.0096 - Accuracy: 0.3952 - F1: 0.3275
sub_1:Test (Best Model) - Loss: 2.4483 - Accuracy: 0.3667 - F1: 0.3033
sub_10:Test (Best Model) - Loss: 2.0294 - Accuracy: 0.4667 - F1: 0.4121
sub_12:Test (Best Model) - Loss: 1.6452 - Accuracy: 0.4333 - F1: 0.4083
sub_14:Test (Best Model) - Loss: 1.3951 - Accuracy: 0.4952 - F1: 0.4830
sub_13:Test (Best Model) - Loss: 2.3923 - Accuracy: 0.3429 - F1: 0.2567
sub_5:Test (Best Model) - Loss: 2.1356 - Accuracy: 0.3000 - F1: 0.2260
sub_2:Test (Best Model) - Loss: 1.8019 - Accuracy: 0.4143 - F1: 0.3259
sub_4:Test (Best Model) - Loss: 1.7439 - Accuracy: 0.4571 - F1: 0.4186
sub_8:Test (Best Model) - Loss: 1.6547 - Accuracy: 0.5095 - F1: 0.5196
sub_3:Test (Best Model) - Loss: 2.8347 - Accuracy: 0.3000 - F1: 0.2044
sub_7:Test (Best Model) - Loss: 2.4808 - Accuracy: 0.2714 - F1: 0.2731
sub_10:Test (Best Model) - Loss: 1.5304 - Accuracy: 0.4905 - F1: 0.4442
sub_9:Test (Best Model) - Loss: 1.7771 - Accuracy: 0.4286 - F1: 0.4160
sub_6:Test (Best Model) - Loss: 2.1644 - Accuracy: 0.4048 - F1: 0.3381
sub_1:Test (Best Model) - Loss: 2.0829 - Accuracy: 0.4143 - F1: 0.3232
sub_5:Test (Best Model) - Loss: 2.0490 - Accuracy: 0.2810 - F1: 0.1846
sub_13:Test (Best Model) - Loss: 2.2194 - Accuracy: 0.3048 - F1: 0.2226
sub_14:Test (Best Model) - Loss: 1.8353 - Accuracy: 0.4619 - F1: 0.4426
sub_3:Test (Best Model) - Loss: 2.1627 - Accuracy: 0.3000 - F1: 0.1908
sub_12:Test (Best Model) - Loss: 2.0460 - Accuracy: 0.4095 - F1: 0.3576
sub_2:Test (Best Model) - Loss: 1.7925 - Accuracy: 0.4476 - F1: 0.3733
sub_7:Test (Best Model) - Loss: 1.7859 - Accuracy: 0.3000 - F1: 0.2550
sub_8:Test (Best Model) - Loss: 1.7285 - Accuracy: 0.5190 - F1: 0.5217
sub_11:Test (Best Model) - Loss: 2.1394 - Accuracy: 0.4857 - F1: 0.4665
sub_5:Test (Best Model) - Loss: 2.4724 - Accuracy: 0.2905 - F1: 0.2233
sub_10:Test (Best Model) - Loss: 2.0123 - Accuracy: 0.4524 - F1: 0.4090
sub_6:Test (Best Model) - Loss: 2.1185 - Accuracy: 0.4286 - F1: 0.3915
sub_4:Test (Best Model) - Loss: 1.6383 - Accuracy: 0.4762 - F1: 0.4355
sub_14:Test (Best Model) - Loss: 1.4505 - Accuracy: 0.4429 - F1: 0.4468
sub_9:Test (Best Model) - Loss: 2.0403 - Accuracy: 0.4524 - F1: 0.4036
sub_7:Test (Best Model) - Loss: 2.1589 - Accuracy: 0.2619 - F1: 0.2537
sub_2:Test (Best Model) - Loss: 1.9734 - Accuracy: 0.4143 - F1: 0.3638
sub_12:Test (Best Model) - Loss: 2.0146 - Accuracy: 0.4095 - F1: 0.3967
sub_3:Test (Best Model) - Loss: 3.3953 - Accuracy: 0.2476 - F1: 0.1395
sub_1:Test (Best Model) - Loss: 2.0459 - Accuracy: 0.4286 - F1: 0.3273
sub_6:Test (Best Model) - Loss: 1.7489 - Accuracy: 0.4190 - F1: 0.3374
sub_8:Test (Best Model) - Loss: 1.8930 - Accuracy: 0.4762 - F1: 0.4540
sub_11:Test (Best Model) - Loss: 1.5653 - Accuracy: 0.5000 - F1: 0.4416
sub_14:Test (Best Model) - Loss: 1.2105 - Accuracy: 0.5190 - F1: 0.5160
sub_10:Test (Best Model) - Loss: 1.7949 - Accuracy: 0.4524 - F1: 0.4277
sub_12:Test (Best Model) - Loss: 1.6243 - Accuracy: 0.3810 - F1: 0.3275
sub_13:Test (Best Model) - Loss: 2.0184 - Accuracy: 0.3429 - F1: 0.2661
sub_2:Test (Best Model) - Loss: 1.7409 - Accuracy: 0.4429 - F1: 0.4604
sub_7:Test (Best Model) - Loss: 1.9064 - Accuracy: 0.4429 - F1: 0.4136
sub_1:Test (Best Model) - Loss: 1.8856 - Accuracy: 0.3762 - F1: 0.3012
sub_11:Test (Best Model) - Loss: 1.3275 - Accuracy: 0.5143 - F1: 0.4572
sub_8:Test (Best Model) - Loss: 1.2786 - Accuracy: 0.4810 - F1: 0.4783
sub_4:Test (Best Model) - Loss: 2.2893 - Accuracy: 0.4524 - F1: 0.4013
sub_5:Test (Best Model) - Loss: 2.1036 - Accuracy: 0.4476 - F1: 0.4171
sub_9:Test (Best Model) - Loss: 2.3876 - Accuracy: 0.4381 - F1: 0.4068
sub_12:Test (Best Model) - Loss: 2.2067 - Accuracy: 0.3667 - F1: 0.3022
sub_6:Test (Best Model) - Loss: 2.1306 - Accuracy: 0.3762 - F1: 0.3887
sub_14:Test (Best Model) - Loss: 1.4366 - Accuracy: 0.5905 - F1: 0.5582
sub_3:Test (Best Model) - Loss: 2.2631 - Accuracy: 0.4000 - F1: 0.3691
sub_10:Test (Best Model) - Loss: 2.2884 - Accuracy: 0.4429 - F1: 0.4255
sub_4:Test (Best Model) - Loss: 1.6257 - Accuracy: 0.4238 - F1: 0.3731
sub_13:Test (Best Model) - Loss: 3.0758 - Accuracy: 0.2667 - F1: 0.1736
sub_8:Test (Best Model) - Loss: 1.8307 - Accuracy: 0.4952 - F1: 0.4935
sub_7:Test (Best Model) - Loss: 2.0740 - Accuracy: 0.4095 - F1: 0.3863
sub_9:Test (Best Model) - Loss: 1.5468 - Accuracy: 0.4190 - F1: 0.3561
sub_2:Test (Best Model) - Loss: 1.7545 - Accuracy: 0.3857 - F1: 0.3711
sub_1:Test (Best Model) - Loss: 1.8667 - Accuracy: 0.3810 - F1: 0.3273
sub_12:Test (Best Model) - Loss: 2.2382 - Accuracy: 0.3286 - F1: 0.2675
sub_10:Test (Best Model) - Loss: 1.5916 - Accuracy: 0.4714 - F1: 0.4539
sub_11:Test (Best Model) - Loss: 1.9334 - Accuracy: 0.4810 - F1: 0.4604
sub_6:Test (Best Model) - Loss: 2.3945 - Accuracy: 0.3905 - F1: 0.3989
sub_4:Test (Best Model) - Loss: 1.7069 - Accuracy: 0.4571 - F1: 0.4614
sub_5:Test (Best Model) - Loss: 1.8065 - Accuracy: 0.4619 - F1: 0.4353
sub_14:Test (Best Model) - Loss: 1.6705 - Accuracy: 0.5667 - F1: 0.5434
sub_12:Test (Best Model) - Loss: 1.7389 - Accuracy: 0.3762 - F1: 0.3277
sub_8:Test (Best Model) - Loss: 1.6231 - Accuracy: 0.5190 - F1: 0.5117
sub_9:Test (Best Model) - Loss: 1.7529 - Accuracy: 0.4238 - F1: 0.3896
sub_7:Test (Best Model) - Loss: 2.2418 - Accuracy: 0.3952 - F1: 0.3385
sub_2:Test (Best Model) - Loss: 1.8178 - Accuracy: 0.4905 - F1: 0.4635
sub_10:Test (Best Model) - Loss: 1.5970 - Accuracy: 0.4667 - F1: 0.4661
sub_1:Test (Best Model) - Loss: 2.7155 - Accuracy: 0.3381 - F1: 0.2855
sub_5:Test (Best Model) - Loss: 1.5672 - Accuracy: 0.4762 - F1: 0.4575
sub_3:Test (Best Model) - Loss: 1.9716 - Accuracy: 0.3952 - F1: 0.3721
sub_4:Test (Best Model) - Loss: 2.3744 - Accuracy: 0.3905 - F1: 0.3646
sub_12:Test (Best Model) - Loss: 1.8584 - Accuracy: 0.4000 - F1: 0.3525
sub_13:Test (Best Model) - Loss: 2.5224 - Accuracy: 0.3667 - F1: 0.3541
sub_14:Test (Best Model) - Loss: 1.4202 - Accuracy: 0.5952 - F1: 0.5822
sub_9:Test (Best Model) - Loss: 1.4980 - Accuracy: 0.4286 - F1: 0.3877
sub_10:Test (Best Model) - Loss: 1.7113 - Accuracy: 0.4286 - F1: 0.3909
sub_8:Test (Best Model) - Loss: 1.6636 - Accuracy: 0.5000 - F1: 0.5008
sub_6:Test (Best Model) - Loss: 2.5043 - Accuracy: 0.4190 - F1: 0.4214
sub_11:Test (Best Model) - Loss: 1.8014 - Accuracy: 0.5000 - F1: 0.4863
sub_5:Test (Best Model) - Loss: 1.4090 - Accuracy: 0.4714 - F1: 0.4471
sub_4:Test (Best Model) - Loss: 1.4292 - Accuracy: 0.4714 - F1: 0.4623
sub_12:Test (Best Model) - Loss: 2.1326 - Accuracy: 0.3429 - F1: 0.2681
sub_14:Test (Best Model) - Loss: 1.1847 - Accuracy: 0.5286 - F1: 0.5054
sub_8:Test (Best Model) - Loss: 1.1213 - Accuracy: 0.5286 - F1: 0.4989
sub_2:Test (Best Model) - Loss: 2.4151 - Accuracy: 0.3810 - F1: 0.3859
sub_13:Test (Best Model) - Loss: 1.8224 - Accuracy: 0.4095 - F1: 0.3851
sub_6:Test (Best Model) - Loss: 1.8490 - Accuracy: 0.4095 - F1: 0.4252
sub_10:Test (Best Model) - Loss: 1.8701 - Accuracy: 0.4095 - F1: 0.4045
sub_7:Test (Best Model) - Loss: 2.3755 - Accuracy: 0.3952 - F1: 0.3346
sub_3:Test (Best Model) - Loss: 2.4298 - Accuracy: 0.3571 - F1: 0.3391
sub_12:Test (Best Model) - Loss: 1.7328 - Accuracy: 0.3524 - F1: 0.2815
sub_1:Test (Best Model) - Loss: 1.8897 - Accuracy: 0.4286 - F1: 0.4202
sub_4:Test (Best Model) - Loss: 1.4462 - Accuracy: 0.4333 - F1: 0.4299
sub_8:Test (Best Model) - Loss: 1.4073 - Accuracy: 0.4429 - F1: 0.4416
sub_5:Test (Best Model) - Loss: 1.8035 - Accuracy: 0.5333 - F1: 0.4662
sub_2:Test (Best Model) - Loss: 1.4251 - Accuracy: 0.4000 - F1: 0.4124
sub_14:Test (Best Model) - Loss: 2.5194 - Accuracy: 0.3286 - F1: 0.2666
sub_13:Test (Best Model) - Loss: 1.5614 - Accuracy: 0.4143 - F1: 0.3735
sub_9:Test (Best Model) - Loss: 2.2845 - Accuracy: 0.4190 - F1: 0.3754
sub_1:Test (Best Model) - Loss: 1.9053 - Accuracy: 0.3952 - F1: 0.3483
sub_6:Test (Best Model) - Loss: 2.3474 - Accuracy: 0.3476 - F1: 0.3560
sub_7:Test (Best Model) - Loss: 2.4313 - Accuracy: 0.3333 - F1: 0.2600
sub_14:Test (Best Model) - Loss: 1.9196 - Accuracy: 0.2905 - F1: 0.2193
sub_4:Test (Best Model) - Loss: 1.5948 - Accuracy: 0.4381 - F1: 0.4260
sub_10:Test (Best Model) - Loss: 2.3425 - Accuracy: 0.3762 - F1: 0.3386
sub_12:Test (Best Model) - Loss: 2.2828 - Accuracy: 0.3476 - F1: 0.2683
sub_8:Test (Best Model) - Loss: 1.7481 - Accuracy: 0.4905 - F1: 0.4900
sub_9:Test (Best Model) - Loss: 2.1030 - Accuracy: 0.3286 - F1: 0.2675
sub_11:Test (Best Model) - Loss: 2.0543 - Accuracy: 0.5095 - F1: 0.4764
sub_2:Test (Best Model) - Loss: 2.3346 - Accuracy: 0.3190 - F1: 0.3117
sub_3:Test (Best Model) - Loss: 2.1794 - Accuracy: 0.3810 - F1: 0.3100
sub_1:Test (Best Model) - Loss: 1.6315 - Accuracy: 0.3905 - F1: 0.3506
sub_10:Test (Best Model) - Loss: 1.9589 - Accuracy: 0.3476 - F1: 0.2957
sub_5:Test (Best Model) - Loss: 2.0554 - Accuracy: 0.3333 - F1: 0.3416
sub_13:Test (Best Model) - Loss: 2.5244 - Accuracy: 0.3476 - F1: 0.2993
sub_6:Test (Best Model) - Loss: 1.8359 - Accuracy: 0.4619 - F1: 0.4620
sub_12:Test (Best Model) - Loss: 2.2708 - Accuracy: 0.3381 - F1: 0.2443
sub_11:Test (Best Model) - Loss: 1.2710 - Accuracy: 0.4762 - F1: 0.4465
sub_14:Test (Best Model) - Loss: 2.3598 - Accuracy: 0.3190 - F1: 0.2654
sub_8:Test (Best Model) - Loss: 1.6492 - Accuracy: 0.4857 - F1: 0.4626
sub_9:Test (Best Model) - Loss: 1.7216 - Accuracy: 0.3429 - F1: 0.3050
sub_7:Test (Best Model) - Loss: 2.5696 - Accuracy: 0.2667 - F1: 0.2496
sub_4:Test (Best Model) - Loss: 1.8415 - Accuracy: 0.4619 - F1: 0.4269
sub_2:Test (Best Model) - Loss: 2.0365 - Accuracy: 0.3619 - F1: 0.3766
sub_10:Test (Best Model) - Loss: 2.0079 - Accuracy: 0.3714 - F1: 0.3162
sub_5:Test (Best Model) - Loss: 1.6002 - Accuracy: 0.3762 - F1: 0.3885
sub_14:Test (Best Model) - Loss: 1.8507 - Accuracy: 0.3143 - F1: 0.2551
sub_13:Test (Best Model) - Loss: 2.1204 - Accuracy: 0.3810 - F1: 0.3552
sub_11:Test (Best Model) - Loss: 1.2759 - Accuracy: 0.5000 - F1: 0.4835
sub_12:Test (Best Model) - Loss: 2.2217 - Accuracy: 0.3286 - F1: 0.2571
sub_8:Test (Best Model) - Loss: 1.5272 - Accuracy: 0.4762 - F1: 0.4643
sub_1:Test (Best Model) - Loss: 1.6396 - Accuracy: 0.4524 - F1: 0.4502
sub_6:Test (Best Model) - Loss: 2.2399 - Accuracy: 0.3571 - F1: 0.3279
sub_2:Test (Best Model) - Loss: 1.5194 - Accuracy: 0.4429 - F1: 0.4548
sub_3:Test (Best Model) - Loss: 2.0076 - Accuracy: 0.4333 - F1: 0.4185
sub_9:Test (Best Model) - Loss: 1.7234 - Accuracy: 0.4381 - F1: 0.4027
sub_4:Test (Best Model) - Loss: 1.7058 - Accuracy: 0.4571 - F1: 0.4247
sub_7:Test (Best Model) - Loss: 2.2593 - Accuracy: 0.3667 - F1: 0.3041
sub_10:Test (Best Model) - Loss: 2.0791 - Accuracy: 0.3333 - F1: 0.2847
sub_14:Test (Best Model) - Loss: 2.4901 - Accuracy: 0.2810 - F1: 0.2101
sub_13:Test (Best Model) - Loss: 1.9426 - Accuracy: 0.3857 - F1: 0.3072
sub_11:Test (Best Model) - Loss: 1.5591 - Accuracy: 0.4048 - F1: 0.3765
sub_2:Test (Best Model) - Loss: 1.4217 - Accuracy: 0.3619 - F1: 0.3794
sub_3:Test (Best Model) - Loss: 2.3093 - Accuracy: 0.3000 - F1: 0.2867
sub_8:Test (Best Model) - Loss: 1.8465 - Accuracy: 0.4667 - F1: 0.4585
sub_6:Test (Best Model) - Loss: 2.1040 - Accuracy: 0.4190 - F1: 0.3655
sub_4:Test (Best Model) - Loss: 1.5239 - Accuracy: 0.4857 - F1: 0.4592
sub_5:Test (Best Model) - Loss: 2.6956 - Accuracy: 0.3333 - F1: 0.3046
sub_1:Test (Best Model) - Loss: 1.9536 - Accuracy: 0.4381 - F1: 0.4461
sub_2:Test (Best Model) - Loss: 1.8263 - Accuracy: 0.3762 - F1: 0.3992
sub_10:Test (Best Model) - Loss: 2.0300 - Accuracy: 0.3810 - F1: 0.3255
sub_7:Test (Best Model) - Loss: 2.0710 - Accuracy: 0.3190 - F1: 0.3206
sub_9:Test (Best Model) - Loss: 2.4447 - Accuracy: 0.3714 - F1: 0.3221
sub_13:Test (Best Model) - Loss: 2.4890 - Accuracy: 0.4286 - F1: 0.3378
sub_3:Test (Best Model) - Loss: 2.1603 - Accuracy: 0.3333 - F1: 0.3121
sub_11:Test (Best Model) - Loss: 2.2824 - Accuracy: 0.4333 - F1: 0.4082
sub_4:Test (Best Model) - Loss: 1.7926 - Accuracy: 0.4381 - F1: 0.4238
sub_6:Test (Best Model) - Loss: 2.0122 - Accuracy: 0.4571 - F1: 0.4407
sub_5:Test (Best Model) - Loss: 2.3107 - Accuracy: 0.3381 - F1: 0.3431
sub_7:Test (Best Model) - Loss: 2.2207 - Accuracy: 0.3286 - F1: 0.3217
sub_1:Test (Best Model) - Loss: 1.9942 - Accuracy: 0.4000 - F1: 0.3978
sub_13:Test (Best Model) - Loss: 2.6400 - Accuracy: 0.3905 - F1: 0.2924
sub_4:Test (Best Model) - Loss: 1.5533 - Accuracy: 0.4714 - F1: 0.4602
sub_7:Test (Best Model) - Loss: 2.2858 - Accuracy: 0.2333 - F1: 0.1693
sub_9:Test (Best Model) - Loss: 2.3605 - Accuracy: 0.4714 - F1: 0.4170
sub_3:Test (Best Model) - Loss: 2.4853 - Accuracy: 0.3095 - F1: 0.2395
sub_11:Test (Best Model) - Loss: 2.2823 - Accuracy: 0.4286 - F1: 0.4072
sub_5:Test (Best Model) - Loss: 1.9409 - Accuracy: 0.3429 - F1: 0.3579
sub_6:Test (Best Model) - Loss: 2.4905 - Accuracy: 0.4238 - F1: 0.4025
sub_1:Test (Best Model) - Loss: 1.7752 - Accuracy: 0.4238 - F1: 0.3608
sub_3:Test (Best Model) - Loss: 1.6137 - Accuracy: 0.3429 - F1: 0.2892
sub_13:Test (Best Model) - Loss: 1.7953 - Accuracy: 0.4190 - F1: 0.3608
sub_9:Test (Best Model) - Loss: 2.1314 - Accuracy: 0.3810 - F1: 0.3208
sub_3:Test (Best Model) - Loss: 1.5553 - Accuracy: 0.4048 - F1: 0.3665
sub_1:Test (Best Model) - Loss: 1.9107 - Accuracy: 0.4381 - F1: 0.4286
sub_11:Test (Best Model) - Loss: 2.0987 - Accuracy: 0.4000 - F1: 0.3720
sub_13:Test (Best Model) - Loss: 2.2263 - Accuracy: 0.4143 - F1: 0.3339
sub_11:Test (Best Model) - Loss: 1.9641 - Accuracy: 0.4429 - F1: 0.4051

=== Summary Results ===

acc: 40.67 ± 4.63
F1: 37.00 ± 5.73
acc-in: 56.09 ± 3.46
F1-in: 54.57 ± 3.48
