lr: 0.001
sub_12:Test (Best Model) - Loss: 1.5945 - Accuracy: 0.3476 - F1: 0.3410
sub_7:Test (Best Model) - Loss: 1.9281 - Accuracy: 0.2238 - F1: 0.2198
sub_8:Test (Best Model) - Loss: 1.7885 - Accuracy: 0.4476 - F1: 0.4545
sub_1:Test (Best Model) - Loss: 2.3576 - Accuracy: 0.3857 - F1: 0.2801
sub_6:Test (Best Model) - Loss: 2.3401 - Accuracy: 0.3714 - F1: 0.3402
sub_4:Test (Best Model) - Loss: 1.8249 - Accuracy: 0.4095 - F1: 0.3605
sub_9:Test (Best Model) - Loss: 2.0540 - Accuracy: 0.3952 - F1: 0.3570
sub_5:Test (Best Model) - Loss: 2.4245 - Accuracy: 0.2714 - F1: 0.2181
sub_11:Test (Best Model) - Loss: 2.0547 - Accuracy: 0.4190 - F1: 0.3923
sub_3:Test (Best Model) - Loss: 2.2646 - Accuracy: 0.3667 - F1: 0.3063
sub_14:Test (Best Model) - Loss: 2.4381 - Accuracy: 0.4048 - F1: 0.4280
sub_13:Test (Best Model) - Loss: 2.2332 - Accuracy: 0.3667 - F1: 0.2799
sub_10:Test (Best Model) - Loss: 2.5470 - Accuracy: 0.4095 - F1: 0.3226
sub_2:Test (Best Model) - Loss: 1.7688 - Accuracy: 0.4238 - F1: 0.3697
sub_12:Test (Best Model) - Loss: 2.0751 - Accuracy: 0.3190 - F1: 0.3294
sub_5:Test (Best Model) - Loss: 1.8412 - Accuracy: 0.3286 - F1: 0.2957
sub_7:Test (Best Model) - Loss: 2.2272 - Accuracy: 0.2190 - F1: 0.2061
sub_9:Test (Best Model) - Loss: 1.5640 - Accuracy: 0.4143 - F1: 0.4010
sub_8:Test (Best Model) - Loss: 1.9065 - Accuracy: 0.4476 - F1: 0.4425
sub_6:Test (Best Model) - Loss: 2.0502 - Accuracy: 0.4095 - F1: 0.3708
sub_13:Test (Best Model) - Loss: 1.8699 - Accuracy: 0.3952 - F1: 0.2887
sub_1:Test (Best Model) - Loss: 1.8687 - Accuracy: 0.4000 - F1: 0.3096
sub_4:Test (Best Model) - Loss: 2.2827 - Accuracy: 0.3857 - F1: 0.3294
sub_10:Test (Best Model) - Loss: 1.5930 - Accuracy: 0.4238 - F1: 0.3563
sub_14:Test (Best Model) - Loss: 2.0219 - Accuracy: 0.3810 - F1: 0.3825
sub_2:Test (Best Model) - Loss: 1.8083 - Accuracy: 0.4143 - F1: 0.3325
sub_11:Test (Best Model) - Loss: 2.2647 - Accuracy: 0.4190 - F1: 0.3902
sub_12:Test (Best Model) - Loss: 1.9422 - Accuracy: 0.4000 - F1: 0.3760
sub_3:Test (Best Model) - Loss: 2.2580 - Accuracy: 0.3762 - F1: 0.3713
sub_5:Test (Best Model) - Loss: 2.2340 - Accuracy: 0.2857 - F1: 0.2473
sub_7:Test (Best Model) - Loss: 2.5833 - Accuracy: 0.2429 - F1: 0.2302
sub_13:Test (Best Model) - Loss: 1.7790 - Accuracy: 0.3524 - F1: 0.2585
sub_4:Test (Best Model) - Loss: 1.8410 - Accuracy: 0.3905 - F1: 0.3630
sub_6:Test (Best Model) - Loss: 2.2035 - Accuracy: 0.4143 - F1: 0.3792
sub_10:Test (Best Model) - Loss: 2.2710 - Accuracy: 0.4238 - F1: 0.3538
sub_14:Test (Best Model) - Loss: 2.1904 - Accuracy: 0.3857 - F1: 0.3980
sub_1:Test (Best Model) - Loss: 2.0280 - Accuracy: 0.4238 - F1: 0.3279
sub_2:Test (Best Model) - Loss: 1.9444 - Accuracy: 0.4667 - F1: 0.4200
sub_3:Test (Best Model) - Loss: 1.5648 - Accuracy: 0.3952 - F1: 0.3608
sub_12:Test (Best Model) - Loss: 2.1290 - Accuracy: 0.3667 - F1: 0.3258
sub_11:Test (Best Model) - Loss: 1.7768 - Accuracy: 0.4619 - F1: 0.4432
sub_7:Test (Best Model) - Loss: 1.8111 - Accuracy: 0.2952 - F1: 0.2823
sub_5:Test (Best Model) - Loss: 2.3328 - Accuracy: 0.2667 - F1: 0.2194
sub_8:Test (Best Model) - Loss: 2.0320 - Accuracy: 0.5000 - F1: 0.4977
sub_4:Test (Best Model) - Loss: 1.5094 - Accuracy: 0.4095 - F1: 0.3678
sub_13:Test (Best Model) - Loss: 1.7415 - Accuracy: 0.3571 - F1: 0.2818
sub_9:Test (Best Model) - Loss: 1.7749 - Accuracy: 0.4429 - F1: 0.4177
sub_2:Test (Best Model) - Loss: 1.3775 - Accuracy: 0.4667 - F1: 0.4086
sub_12:Test (Best Model) - Loss: 1.6964 - Accuracy: 0.4286 - F1: 0.4329
sub_1:Test (Best Model) - Loss: 2.1118 - Accuracy: 0.3857 - F1: 0.3011
sub_4:Test (Best Model) - Loss: 1.5519 - Accuracy: 0.3857 - F1: 0.3431
sub_8:Test (Best Model) - Loss: 1.4496 - Accuracy: 0.4857 - F1: 0.4601
sub_10:Test (Best Model) - Loss: 2.1044 - Accuracy: 0.4286 - F1: 0.4046
sub_7:Test (Best Model) - Loss: 2.1876 - Accuracy: 0.2286 - F1: 0.2302
sub_5:Test (Best Model) - Loss: 2.0184 - Accuracy: 0.2762 - F1: 0.2335
sub_6:Test (Best Model) - Loss: 2.4487 - Accuracy: 0.4000 - F1: 0.3811
sub_13:Test (Best Model) - Loss: 1.7738 - Accuracy: 0.3238 - F1: 0.2300
sub_11:Test (Best Model) - Loss: 1.8608 - Accuracy: 0.4333 - F1: 0.3903
sub_9:Test (Best Model) - Loss: 1.7332 - Accuracy: 0.4238 - F1: 0.3826
sub_12:Test (Best Model) - Loss: 2.0518 - Accuracy: 0.3524 - F1: 0.3109
sub_3:Test (Best Model) - Loss: 2.4707 - Accuracy: 0.3857 - F1: 0.3377
sub_14:Test (Best Model) - Loss: 1.8000 - Accuracy: 0.3905 - F1: 0.3809
sub_8:Test (Best Model) - Loss: 1.3425 - Accuracy: 0.4714 - F1: 0.4474
sub_1:Test (Best Model) - Loss: 1.8954 - Accuracy: 0.3952 - F1: 0.3109
sub_10:Test (Best Model) - Loss: 1.5578 - Accuracy: 0.3952 - F1: 0.3569
sub_4:Test (Best Model) - Loss: 2.0475 - Accuracy: 0.3810 - F1: 0.3379
sub_2:Test (Best Model) - Loss: 1.8230 - Accuracy: 0.3905 - F1: 0.3470
sub_6:Test (Best Model) - Loss: 2.4570 - Accuracy: 0.4000 - F1: 0.3517
sub_12:Test (Best Model) - Loss: 2.3255 - Accuracy: 0.3762 - F1: 0.3332
sub_7:Test (Best Model) - Loss: 1.8133 - Accuracy: 0.4476 - F1: 0.4106
sub_14:Test (Best Model) - Loss: 1.8396 - Accuracy: 0.3619 - F1: 0.3679
sub_8:Test (Best Model) - Loss: 1.6390 - Accuracy: 0.4905 - F1: 0.4820
sub_11:Test (Best Model) - Loss: 1.5604 - Accuracy: 0.4571 - F1: 0.4057
sub_5:Test (Best Model) - Loss: 1.9561 - Accuracy: 0.3762 - F1: 0.3515
sub_4:Test (Best Model) - Loss: 2.2405 - Accuracy: 0.3905 - F1: 0.3699
sub_10:Test (Best Model) - Loss: 2.1697 - Accuracy: 0.4381 - F1: 0.3976
sub_12:Test (Best Model) - Loss: 1.9664 - Accuracy: 0.3667 - F1: 0.3276
sub_2:Test (Best Model) - Loss: 1.5082 - Accuracy: 0.4429 - F1: 0.4485
sub_6:Test (Best Model) - Loss: 2.1960 - Accuracy: 0.3286 - F1: 0.3186
sub_8:Test (Best Model) - Loss: 1.5123 - Accuracy: 0.5333 - F1: 0.5284
sub_4:Test (Best Model) - Loss: 1.7053 - Accuracy: 0.3619 - F1: 0.3325
sub_14:Test (Best Model) - Loss: 1.4348 - Accuracy: 0.4571 - F1: 0.4380
sub_1:Test (Best Model) - Loss: 2.3937 - Accuracy: 0.3476 - F1: 0.3213
sub_13:Test (Best Model) - Loss: 2.4068 - Accuracy: 0.3667 - F1: 0.3737
sub_10:Test (Best Model) - Loss: 2.0802 - Accuracy: 0.4429 - F1: 0.4261
sub_8:Test (Best Model) - Loss: 1.4141 - Accuracy: 0.4810 - F1: 0.4680
sub_2:Test (Best Model) - Loss: 1.7662 - Accuracy: 0.3952 - F1: 0.3800
sub_9:Test (Best Model) - Loss: 2.2792 - Accuracy: 0.4571 - F1: 0.3949
sub_12:Test (Best Model) - Loss: 2.7495 - Accuracy: 0.3286 - F1: 0.2840
sub_14:Test (Best Model) - Loss: 1.9635 - Accuracy: 0.4429 - F1: 0.4267
sub_7:Test (Best Model) - Loss: 1.9835 - Accuracy: 0.4000 - F1: 0.3616
sub_6:Test (Best Model) - Loss: 2.0297 - Accuracy: 0.3524 - F1: 0.3476
sub_10:Test (Best Model) - Loss: 1.7747 - Accuracy: 0.3762 - F1: 0.3529
sub_8:Test (Best Model) - Loss: 1.8687 - Accuracy: 0.4571 - F1: 0.4479
sub_3:Test (Best Model) - Loss: 2.6512 - Accuracy: 0.4095 - F1: 0.3807
sub_5:Test (Best Model) - Loss: 2.5045 - Accuracy: 0.3619 - F1: 0.3343
sub_2:Test (Best Model) - Loss: 1.8081 - Accuracy: 0.4619 - F1: 0.4677
sub_12:Test (Best Model) - Loss: 2.0830 - Accuracy: 0.3333 - F1: 0.2823
sub_4:Test (Best Model) - Loss: 2.4176 - Accuracy: 0.3476 - F1: 0.3156
sub_9:Test (Best Model) - Loss: 1.9446 - Accuracy: 0.3952 - F1: 0.3420
sub_10:Test (Best Model) - Loss: 1.7108 - Accuracy: 0.3905 - F1: 0.3601
sub_14:Test (Best Model) - Loss: 1.8699 - Accuracy: 0.4333 - F1: 0.4299
sub_8:Test (Best Model) - Loss: 1.5496 - Accuracy: 0.4667 - F1: 0.4433
sub_7:Test (Best Model) - Loss: 1.6475 - Accuracy: 0.3667 - F1: 0.3551
sub_6:Test (Best Model) - Loss: 2.2347 - Accuracy: 0.3286 - F1: 0.3265
sub_11:Test (Best Model) - Loss: 1.7843 - Accuracy: 0.4333 - F1: 0.4053
sub_12:Test (Best Model) - Loss: 1.8261 - Accuracy: 0.3286 - F1: 0.2828
sub_13:Test (Best Model) - Loss: 2.3134 - Accuracy: 0.3810 - F1: 0.3430
sub_3:Test (Best Model) - Loss: 1.4949 - Accuracy: 0.3714 - F1: 0.3519
sub_4:Test (Best Model) - Loss: 1.7134 - Accuracy: 0.3333 - F1: 0.3175
sub_5:Test (Best Model) - Loss: 1.6312 - Accuracy: 0.3857 - F1: 0.3773
sub_2:Test (Best Model) - Loss: 1.5854 - Accuracy: 0.4048 - F1: 0.4166
sub_1:Test (Best Model) - Loss: 2.4924 - Accuracy: 0.3286 - F1: 0.2911
sub_8:Test (Best Model) - Loss: 1.7301 - Accuracy: 0.3571 - F1: 0.3533
sub_12:Test (Best Model) - Loss: 1.6864 - Accuracy: 0.3429 - F1: 0.2912
sub_10:Test (Best Model) - Loss: 2.4350 - Accuracy: 0.3476 - F1: 0.3421
sub_9:Test (Best Model) - Loss: 1.7960 - Accuracy: 0.3857 - F1: 0.3316
sub_13:Test (Best Model) - Loss: 1.6451 - Accuracy: 0.3714 - F1: 0.3628
sub_6:Test (Best Model) - Loss: 2.3080 - Accuracy: 0.3857 - F1: 0.3748
sub_7:Test (Best Model) - Loss: 1.8723 - Accuracy: 0.3619 - F1: 0.3430
sub_4:Test (Best Model) - Loss: 2.0508 - Accuracy: 0.3667 - F1: 0.3366
sub_5:Test (Best Model) - Loss: 2.0148 - Accuracy: 0.3952 - F1: 0.3813
sub_14:Test (Best Model) - Loss: 1.9126 - Accuracy: 0.4333 - F1: 0.4321
sub_2:Test (Best Model) - Loss: 1.7615 - Accuracy: 0.4190 - F1: 0.4388
sub_11:Test (Best Model) - Loss: 1.9840 - Accuracy: 0.4476 - F1: 0.4084
sub_3:Test (Best Model) - Loss: 2.1626 - Accuracy: 0.4190 - F1: 0.4094
sub_10:Test (Best Model) - Loss: 1.8028 - Accuracy: 0.2810 - F1: 0.2400
sub_8:Test (Best Model) - Loss: 1.9029 - Accuracy: 0.3905 - F1: 0.3985
sub_1:Test (Best Model) - Loss: 2.4727 - Accuracy: 0.3286 - F1: 0.3187
sub_5:Test (Best Model) - Loss: 1.6025 - Accuracy: 0.3619 - F1: 0.3090
sub_9:Test (Best Model) - Loss: 2.1149 - Accuracy: 0.3286 - F1: 0.2491
sub_12:Test (Best Model) - Loss: 2.3574 - Accuracy: 0.3190 - F1: 0.3044
sub_7:Test (Best Model) - Loss: 2.4067 - Accuracy: 0.3667 - F1: 0.3234
sub_2:Test (Best Model) - Loss: 2.1250 - Accuracy: 0.3048 - F1: 0.2850
sub_14:Test (Best Model) - Loss: 1.7756 - Accuracy: 0.4476 - F1: 0.4470
sub_6:Test (Best Model) - Loss: 2.4259 - Accuracy: 0.3524 - F1: 0.3341
sub_1:Test (Best Model) - Loss: 1.4859 - Accuracy: 0.3571 - F1: 0.3425
sub_8:Test (Best Model) - Loss: 1.7915 - Accuracy: 0.3905 - F1: 0.3946
sub_13:Test (Best Model) - Loss: 2.2614 - Accuracy: 0.4000 - F1: 0.3730
sub_9:Test (Best Model) - Loss: 1.6732 - Accuracy: 0.3286 - F1: 0.2796
sub_11:Test (Best Model) - Loss: 1.8349 - Accuracy: 0.4524 - F1: 0.4317
sub_3:Test (Best Model) - Loss: 2.2441 - Accuracy: 0.3476 - F1: 0.3465
sub_5:Test (Best Model) - Loss: 1.9953 - Accuracy: 0.2810 - F1: 0.2899
sub_12:Test (Best Model) - Loss: 1.9314 - Accuracy: 0.3048 - F1: 0.2762
sub_4:Test (Best Model) - Loss: 1.9205 - Accuracy: 0.3810 - F1: 0.3761
sub_10:Test (Best Model) - Loss: 2.4657 - Accuracy: 0.2429 - F1: 0.1788
sub_8:Test (Best Model) - Loss: 1.5499 - Accuracy: 0.3905 - F1: 0.4042
sub_9:Test (Best Model) - Loss: 1.8110 - Accuracy: 0.3952 - F1: 0.3429
sub_7:Test (Best Model) - Loss: 2.8234 - Accuracy: 0.2524 - F1: 0.2633
sub_1:Test (Best Model) - Loss: 2.0198 - Accuracy: 0.3095 - F1: 0.2851
sub_2:Test (Best Model) - Loss: 2.6335 - Accuracy: 0.3095 - F1: 0.2914
sub_14:Test (Best Model) - Loss: 2.8442 - Accuracy: 0.2857 - F1: 0.2193
sub_12:Test (Best Model) - Loss: 1.7679 - Accuracy: 0.3238 - F1: 0.2816
sub_13:Test (Best Model) - Loss: 2.2039 - Accuracy: 0.4000 - F1: 0.3764
sub_3:Test (Best Model) - Loss: 2.2233 - Accuracy: 0.3905 - F1: 0.3579
sub_10:Test (Best Model) - Loss: 2.2271 - Accuracy: 0.2619 - F1: 0.2066
sub_4:Test (Best Model) - Loss: 1.9893 - Accuracy: 0.3571 - F1: 0.3422
sub_9:Test (Best Model) - Loss: 2.0709 - Accuracy: 0.3000 - F1: 0.2520
sub_11:Test (Best Model) - Loss: 2.0704 - Accuracy: 0.4524 - F1: 0.4238
sub_1:Test (Best Model) - Loss: 1.9013 - Accuracy: 0.4095 - F1: 0.4103
sub_5:Test (Best Model) - Loss: 2.9595 - Accuracy: 0.2429 - F1: 0.2509
sub_6:Test (Best Model) - Loss: 2.5968 - Accuracy: 0.3857 - F1: 0.3808
sub_10:Test (Best Model) - Loss: 2.0593 - Accuracy: 0.2667 - F1: 0.2145
sub_14:Test (Best Model) - Loss: 2.8886 - Accuracy: 0.2667 - F1: 0.1898
sub_8:Test (Best Model) - Loss: 2.4152 - Accuracy: 0.4000 - F1: 0.4004
sub_7:Test (Best Model) - Loss: 1.9665 - Accuracy: 0.3333 - F1: 0.3059
sub_4:Test (Best Model) - Loss: 1.5798 - Accuracy: 0.3905 - F1: 0.3664
sub_2:Test (Best Model) - Loss: 1.9203 - Accuracy: 0.3048 - F1: 0.3161
sub_3:Test (Best Model) - Loss: 2.3807 - Accuracy: 0.3238 - F1: 0.3212
sub_13:Test (Best Model) - Loss: 2.4026 - Accuracy: 0.3857 - F1: 0.3404
sub_11:Test (Best Model) - Loss: 1.7737 - Accuracy: 0.4619 - F1: 0.4500
sub_1:Test (Best Model) - Loss: 1.6562 - Accuracy: 0.4571 - F1: 0.4449
sub_10:Test (Best Model) - Loss: 1.9275 - Accuracy: 0.2905 - F1: 0.2421
sub_14:Test (Best Model) - Loss: 2.5263 - Accuracy: 0.2857 - F1: 0.2188
sub_3:Test (Best Model) - Loss: 2.0922 - Accuracy: 0.2714 - F1: 0.2799
sub_6:Test (Best Model) - Loss: 2.2751 - Accuracy: 0.3857 - F1: 0.3793
sub_4:Test (Best Model) - Loss: 1.8720 - Accuracy: 0.3714 - F1: 0.3555
sub_7:Test (Best Model) - Loss: 2.1058 - Accuracy: 0.3238 - F1: 0.3127
sub_9:Test (Best Model) - Loss: 2.0632 - Accuracy: 0.3381 - F1: 0.2828
sub_2:Test (Best Model) - Loss: 2.0181 - Accuracy: 0.3095 - F1: 0.3032
sub_11:Test (Best Model) - Loss: 1.5743 - Accuracy: 0.4095 - F1: 0.4008
sub_5:Test (Best Model) - Loss: 2.5251 - Accuracy: 0.3095 - F1: 0.3167
sub_14:Test (Best Model) - Loss: 2.1873 - Accuracy: 0.2714 - F1: 0.2053
sub_13:Test (Best Model) - Loss: 2.1439 - Accuracy: 0.4143 - F1: 0.3608
sub_2:Test (Best Model) - Loss: 2.0090 - Accuracy: 0.2190 - F1: 0.2370
sub_1:Test (Best Model) - Loss: 1.9190 - Accuracy: 0.4048 - F1: 0.4132
sub_5:Test (Best Model) - Loss: 2.0070 - Accuracy: 0.3286 - F1: 0.3456
sub_7:Test (Best Model) - Loss: 2.5587 - Accuracy: 0.2952 - F1: 0.2841
sub_3:Test (Best Model) - Loss: 2.6775 - Accuracy: 0.2905 - F1: 0.2911
sub_6:Test (Best Model) - Loss: 2.5614 - Accuracy: 0.3905 - F1: 0.3620
sub_14:Test (Best Model) - Loss: 2.1861 - Accuracy: 0.2476 - F1: 0.1594
sub_13:Test (Best Model) - Loss: 2.0379 - Accuracy: 0.4143 - F1: 0.3562
sub_1:Test (Best Model) - Loss: 1.4157 - Accuracy: 0.3667 - F1: 0.3569
sub_9:Test (Best Model) - Loss: 2.9058 - Accuracy: 0.3286 - F1: 0.2954
sub_5:Test (Best Model) - Loss: 2.2631 - Accuracy: 0.2762 - F1: 0.2769
sub_11:Test (Best Model) - Loss: 2.5723 - Accuracy: 0.4143 - F1: 0.3948
sub_7:Test (Best Model) - Loss: 2.3105 - Accuracy: 0.2857 - F1: 0.2687
sub_13:Test (Best Model) - Loss: 2.1272 - Accuracy: 0.4095 - F1: 0.3674
sub_6:Test (Best Model) - Loss: 2.2388 - Accuracy: 0.4095 - F1: 0.4082
sub_1:Test (Best Model) - Loss: 1.8725 - Accuracy: 0.4762 - F1: 0.4635
sub_9:Test (Best Model) - Loss: 2.6234 - Accuracy: 0.3238 - F1: 0.2721
sub_11:Test (Best Model) - Loss: 2.1513 - Accuracy: 0.3857 - F1: 0.3751
sub_3:Test (Best Model) - Loss: 2.5918 - Accuracy: 0.3095 - F1: 0.3049
sub_13:Test (Best Model) - Loss: 1.6487 - Accuracy: 0.4286 - F1: 0.3691
sub_6:Test (Best Model) - Loss: 2.3673 - Accuracy: 0.3429 - F1: 0.3328
sub_9:Test (Best Model) - Loss: 2.7129 - Accuracy: 0.2762 - F1: 0.2203
sub_3:Test (Best Model) - Loss: 2.3390 - Accuracy: 0.3190 - F1: 0.2973
sub_11:Test (Best Model) - Loss: 2.0238 - Accuracy: 0.4048 - F1: 0.3819
sub_3:Test (Best Model) - Loss: 2.1051 - Accuracy: 0.3190 - F1: 0.3098
sub_11:Test (Best Model) - Loss: 2.3757 - Accuracy: 0.4286 - F1: 0.4175

=== Summary Results ===

acc: 37.22 ± 3.56
F1: 34.42 ± 3.89
acc-in: 50.55 ± 3.78
F1-in: 49.11 ± 4.05
