lr: 0.0001
sub_13:Test (Best Model) - Loss: 1.9384 - Accuracy: 0.4190 - F1: 0.3551
sub_4:Test (Best Model) - Loss: 1.9184 - Accuracy: 0.4333 - F1: 0.3761
sub_9:Test (Best Model) - Loss: 1.6772 - Accuracy: 0.3571 - F1: 0.3220
sub_2:Test (Best Model) - Loss: 1.7096 - Accuracy: 0.5381 - F1: 0.4720
sub_6:Test (Best Model) - Loss: 2.8784 - Accuracy: 0.4000 - F1: 0.3336
sub_13:Test (Best Model) - Loss: 1.2227 - Accuracy: 0.4762 - F1: 0.4617
sub_10:Test (Best Model) - Loss: 2.2171 - Accuracy: 0.4476 - F1: 0.3472
sub_1:Test (Best Model) - Loss: 5.1231 - Accuracy: 0.4000 - F1: 0.2666
sub_14:Test (Best Model) - Loss: 1.4387 - Accuracy: 0.4476 - F1: 0.4484
sub_11:Test (Best Model) - Loss: 3.2846 - Accuracy: 0.4429 - F1: 0.4096
sub_12:Test (Best Model) - Loss: 1.2543 - Accuracy: 0.4238 - F1: 0.3608
sub_3:Test (Best Model) - Loss: 4.9070 - Accuracy: 0.2476 - F1: 0.1392
sub_10:Test (Best Model) - Loss: 1.5941 - Accuracy: 0.4333 - F1: 0.4088
sub_8:Test (Best Model) - Loss: 2.4618 - Accuracy: 0.5476 - F1: 0.5477
sub_5:Test (Best Model) - Loss: 4.6867 - Accuracy: 0.3619 - F1: 0.3071
sub_7:Test (Best Model) - Loss: 5.6517 - Accuracy: 0.3095 - F1: 0.2701
sub_2:Test (Best Model) - Loss: 2.1867 - Accuracy: 0.4762 - F1: 0.3982
sub_9:Test (Best Model) - Loss: 3.1624 - Accuracy: 0.4095 - F1: 0.4007
sub_4:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.4333 - F1: 0.3731
sub_11:Test (Best Model) - Loss: 3.0929 - Accuracy: 0.4619 - F1: 0.4033
sub_6:Test (Best Model) - Loss: 2.3243 - Accuracy: 0.4381 - F1: 0.3816
sub_1:Test (Best Model) - Loss: 4.5926 - Accuracy: 0.4048 - F1: 0.3391
sub_10:Test (Best Model) - Loss: 1.6916 - Accuracy: 0.4190 - F1: 0.3435
sub_13:Test (Best Model) - Loss: 5.0999 - Accuracy: 0.3524 - F1: 0.2363
sub_7:Test (Best Model) - Loss: 1.6340 - Accuracy: 0.3810 - F1: 0.3657
sub_14:Test (Best Model) - Loss: 4.8211 - Accuracy: 0.4524 - F1: 0.4015
sub_3:Test (Best Model) - Loss: 2.5827 - Accuracy: 0.4048 - F1: 0.3114
sub_5:Test (Best Model) - Loss: 4.4748 - Accuracy: 0.3619 - F1: 0.3291
sub_9:Test (Best Model) - Loss: 2.1401 - Accuracy: 0.4333 - F1: 0.3906
sub_8:Test (Best Model) - Loss: 2.8942 - Accuracy: 0.5000 - F1: 0.4918
sub_12:Test (Best Model) - Loss: 2.5795 - Accuracy: 0.4000 - F1: 0.3737
sub_4:Test (Best Model) - Loss: 2.0435 - Accuracy: 0.4381 - F1: 0.3930
sub_11:Test (Best Model) - Loss: 3.5057 - Accuracy: 0.3905 - F1: 0.3472
sub_10:Test (Best Model) - Loss: 2.7782 - Accuracy: 0.4476 - F1: 0.3794
sub_2:Test (Best Model) - Loss: 2.7153 - Accuracy: 0.4762 - F1: 0.4199
sub_3:Test (Best Model) - Loss: 2.3096 - Accuracy: 0.3524 - F1: 0.2652
sub_14:Test (Best Model) - Loss: 1.7486 - Accuracy: 0.5048 - F1: 0.4938
sub_6:Test (Best Model) - Loss: 2.4128 - Accuracy: 0.4000 - F1: 0.3112
sub_13:Test (Best Model) - Loss: 1.3131 - Accuracy: 0.4619 - F1: 0.3762
sub_1:Test (Best Model) - Loss: 4.2384 - Accuracy: 0.4286 - F1: 0.3179
sub_5:Test (Best Model) - Loss: 4.3726 - Accuracy: 0.3190 - F1: 0.2723
sub_7:Test (Best Model) - Loss: 4.1136 - Accuracy: 0.2667 - F1: 0.2612
sub_11:Test (Best Model) - Loss: 1.6117 - Accuracy: 0.4381 - F1: 0.3831
sub_9:Test (Best Model) - Loss: 3.7713 - Accuracy: 0.4476 - F1: 0.3722
sub_2:Test (Best Model) - Loss: 2.3251 - Accuracy: 0.4714 - F1: 0.3812
sub_6:Test (Best Model) - Loss: 1.5709 - Accuracy: 0.4286 - F1: 0.3802
sub_4:Test (Best Model) - Loss: 1.9529 - Accuracy: 0.4762 - F1: 0.4242
sub_3:Test (Best Model) - Loss: 3.9303 - Accuracy: 0.3571 - F1: 0.2234
sub_10:Test (Best Model) - Loss: 1.6462 - Accuracy: 0.4810 - F1: 0.4696
sub_14:Test (Best Model) - Loss: 1.9897 - Accuracy: 0.4762 - F1: 0.4621
sub_12:Test (Best Model) - Loss: 1.5825 - Accuracy: 0.4429 - F1: 0.4084
sub_13:Test (Best Model) - Loss: 5.5237 - Accuracy: 0.2429 - F1: 0.1276
sub_8:Test (Best Model) - Loss: 1.6064 - Accuracy: 0.4667 - F1: 0.4300
sub_5:Test (Best Model) - Loss: 3.5657 - Accuracy: 0.3524 - F1: 0.2740
sub_3:Test (Best Model) - Loss: 2.9410 - Accuracy: 0.2857 - F1: 0.1989
sub_7:Test (Best Model) - Loss: 2.9113 - Accuracy: 0.3333 - F1: 0.3201
sub_1:Test (Best Model) - Loss: 3.5019 - Accuracy: 0.4238 - F1: 0.3124
sub_13:Test (Best Model) - Loss: 1.3399 - Accuracy: 0.4143 - F1: 0.3943
sub_9:Test (Best Model) - Loss: 3.5128 - Accuracy: 0.4762 - F1: 0.4017
sub_11:Test (Best Model) - Loss: 4.5320 - Accuracy: 0.4190 - F1: 0.3882
sub_2:Test (Best Model) - Loss: 2.8579 - Accuracy: 0.4714 - F1: 0.4404
sub_14:Test (Best Model) - Loss: 1.4129 - Accuracy: 0.4333 - F1: 0.4323
sub_4:Test (Best Model) - Loss: 2.3003 - Accuracy: 0.4333 - F1: 0.3670
sub_6:Test (Best Model) - Loss: 3.3441 - Accuracy: 0.4095 - F1: 0.3686
sub_8:Test (Best Model) - Loss: 1.3932 - Accuracy: 0.5000 - F1: 0.4644
sub_10:Test (Best Model) - Loss: 3.3530 - Accuracy: 0.4143 - F1: 0.3563
sub_12:Test (Best Model) - Loss: 2.8658 - Accuracy: 0.4238 - F1: 0.3849
sub_3:Test (Best Model) - Loss: 1.8802 - Accuracy: 0.3762 - F1: 0.3757
sub_9:Test (Best Model) - Loss: 2.3038 - Accuracy: 0.3667 - F1: 0.2687
sub_14:Test (Best Model) - Loss: 1.1054 - Accuracy: 0.5095 - F1: 0.4445
sub_1:Test (Best Model) - Loss: 3.6682 - Accuracy: 0.4429 - F1: 0.3494
sub_8:Test (Best Model) - Loss: 1.1504 - Accuracy: 0.4810 - F1: 0.4576
sub_5:Test (Best Model) - Loss: 5.3805 - Accuracy: 0.3095 - F1: 0.2641
sub_4:Test (Best Model) - Loss: 1.4069 - Accuracy: 0.4476 - F1: 0.4206
sub_13:Test (Best Model) - Loss: 4.1468 - Accuracy: 0.4048 - F1: 0.3435
sub_11:Test (Best Model) - Loss: 2.5848 - Accuracy: 0.4714 - F1: 0.4262
sub_7:Test (Best Model) - Loss: 3.4683 - Accuracy: 0.4000 - F1: 0.3546
sub_2:Test (Best Model) - Loss: 1.9705 - Accuracy: 0.5095 - F1: 0.5165
sub_12:Test (Best Model) - Loss: 1.9584 - Accuracy: 0.4667 - F1: 0.4593
sub_3:Test (Best Model) - Loss: 1.4996 - Accuracy: 0.4429 - F1: 0.4308
sub_6:Test (Best Model) - Loss: 1.8305 - Accuracy: 0.4524 - F1: 0.4434
sub_1:Test (Best Model) - Loss: 2.5368 - Accuracy: 0.4095 - F1: 0.3731
sub_14:Test (Best Model) - Loss: 1.0426 - Accuracy: 0.5857 - F1: 0.5588
sub_5:Test (Best Model) - Loss: 2.3301 - Accuracy: 0.4714 - F1: 0.4446
sub_10:Test (Best Model) - Loss: 3.3607 - Accuracy: 0.4190 - F1: 0.3732
sub_4:Test (Best Model) - Loss: 1.9951 - Accuracy: 0.4762 - F1: 0.4449
sub_2:Test (Best Model) - Loss: 1.4351 - Accuracy: 0.5333 - F1: 0.5089
sub_9:Test (Best Model) - Loss: 4.9619 - Accuracy: 0.3000 - F1: 0.2098
sub_6:Test (Best Model) - Loss: 1.4374 - Accuracy: 0.3476 - F1: 0.3047
sub_1:Test (Best Model) - Loss: 1.2727 - Accuracy: 0.4571 - F1: 0.4615
sub_13:Test (Best Model) - Loss: 2.8333 - Accuracy: 0.4048 - F1: 0.3537
sub_11:Test (Best Model) - Loss: 2.5650 - Accuracy: 0.4810 - F1: 0.4626
sub_8:Test (Best Model) - Loss: 1.9557 - Accuracy: 0.5571 - F1: 0.5468
sub_7:Test (Best Model) - Loss: 2.8938 - Accuracy: 0.3857 - F1: 0.3654
sub_12:Test (Best Model) - Loss: 3.4741 - Accuracy: 0.4333 - F1: 0.4034
sub_5:Test (Best Model) - Loss: 2.2563 - Accuracy: 0.4857 - F1: 0.4509
sub_4:Test (Best Model) - Loss: 1.3890 - Accuracy: 0.4667 - F1: 0.4154
sub_14:Test (Best Model) - Loss: 1.5889 - Accuracy: 0.5619 - F1: 0.5369
sub_3:Test (Best Model) - Loss: 3.8243 - Accuracy: 0.4571 - F1: 0.4544
sub_8:Test (Best Model) - Loss: 1.0699 - Accuracy: 0.4667 - F1: 0.4442
sub_10:Test (Best Model) - Loss: 2.7569 - Accuracy: 0.4810 - F1: 0.4627
sub_2:Test (Best Model) - Loss: 2.1394 - Accuracy: 0.5333 - F1: 0.5322
sub_9:Test (Best Model) - Loss: 3.6055 - Accuracy: 0.2810 - F1: 0.2274
sub_1:Test (Best Model) - Loss: 3.5530 - Accuracy: 0.4048 - F1: 0.3645
sub_5:Test (Best Model) - Loss: 2.6146 - Accuracy: 0.4905 - F1: 0.4709
sub_11:Test (Best Model) - Loss: 3.7343 - Accuracy: 0.4667 - F1: 0.4266
sub_3:Test (Best Model) - Loss: 1.4770 - Accuracy: 0.4571 - F1: 0.4205
sub_4:Test (Best Model) - Loss: 1.9535 - Accuracy: 0.4524 - F1: 0.4098
sub_7:Test (Best Model) - Loss: 1.6567 - Accuracy: 0.3857 - F1: 0.3337
sub_6:Test (Best Model) - Loss: 4.8994 - Accuracy: 0.3857 - F1: 0.3548
sub_10:Test (Best Model) - Loss: 1.9083 - Accuracy: 0.4143 - F1: 0.3785
sub_12:Test (Best Model) - Loss: 1.9943 - Accuracy: 0.3905 - F1: 0.3444
sub_13:Test (Best Model) - Loss: 4.3458 - Accuracy: 0.4476 - F1: 0.4172
sub_14:Test (Best Model) - Loss: 2.1200 - Accuracy: 0.5476 - F1: 0.5151
sub_3:Test (Best Model) - Loss: 1.3081 - Accuracy: 0.3524 - F1: 0.3180
sub_5:Test (Best Model) - Loss: 2.9435 - Accuracy: 0.4476 - F1: 0.4175
sub_7:Test (Best Model) - Loss: 1.5693 - Accuracy: 0.3667 - F1: 0.3458
sub_9:Test (Best Model) - Loss: 5.1039 - Accuracy: 0.3190 - F1: 0.2508
sub_8:Test (Best Model) - Loss: 2.0757 - Accuracy: 0.5238 - F1: 0.5070
sub_2:Test (Best Model) - Loss: 1.5253 - Accuracy: 0.4524 - F1: 0.4497
sub_11:Test (Best Model) - Loss: 2.3384 - Accuracy: 0.5286 - F1: 0.4754
sub_13:Test (Best Model) - Loss: 2.3884 - Accuracy: 0.3762 - F1: 0.3465
sub_1:Test (Best Model) - Loss: 2.4817 - Accuracy: 0.4905 - F1: 0.4635
sub_10:Test (Best Model) - Loss: 2.2355 - Accuracy: 0.3952 - F1: 0.3483
sub_12:Test (Best Model) - Loss: 3.3549 - Accuracy: 0.3857 - F1: 0.3475
sub_4:Test (Best Model) - Loss: 2.9575 - Accuracy: 0.4095 - F1: 0.3823
sub_5:Test (Best Model) - Loss: 1.9497 - Accuracy: 0.4286 - F1: 0.3821
sub_6:Test (Best Model) - Loss: 2.3184 - Accuracy: 0.3429 - F1: 0.3473
sub_9:Test (Best Model) - Loss: 2.2502 - Accuracy: 0.4476 - F1: 0.3789
sub_14:Test (Best Model) - Loss: 1.5927 - Accuracy: 0.5524 - F1: 0.5154
sub_2:Test (Best Model) - Loss: 1.2972 - Accuracy: 0.4714 - F1: 0.4493
sub_3:Test (Best Model) - Loss: 1.7517 - Accuracy: 0.3238 - F1: 0.2937
sub_7:Test (Best Model) - Loss: 2.0083 - Accuracy: 0.3857 - F1: 0.3202
sub_12:Test (Best Model) - Loss: 1.9582 - Accuracy: 0.4571 - F1: 0.4197
sub_1:Test (Best Model) - Loss: 2.6601 - Accuracy: 0.4476 - F1: 0.4238
sub_5:Test (Best Model) - Loss: 2.1412 - Accuracy: 0.3905 - F1: 0.3749
sub_13:Test (Best Model) - Loss: 2.5787 - Accuracy: 0.4714 - F1: 0.3969
sub_11:Test (Best Model) - Loss: 3.4224 - Accuracy: 0.4619 - F1: 0.4217
sub_3:Test (Best Model) - Loss: 1.5302 - Accuracy: 0.3429 - F1: 0.2996
sub_8:Test (Best Model) - Loss: 3.2967 - Accuracy: 0.5000 - F1: 0.4844
sub_6:Test (Best Model) - Loss: 1.8996 - Accuracy: 0.3429 - F1: 0.3431
sub_7:Test (Best Model) - Loss: 2.0172 - Accuracy: 0.3476 - F1: 0.2719
sub_9:Test (Best Model) - Loss: 3.0035 - Accuracy: 0.3762 - F1: 0.3189
sub_10:Test (Best Model) - Loss: 4.3245 - Accuracy: 0.2762 - F1: 0.2329
sub_2:Test (Best Model) - Loss: 3.3768 - Accuracy: 0.3190 - F1: 0.2998
sub_4:Test (Best Model) - Loss: 3.6589 - Accuracy: 0.4238 - F1: 0.3878
sub_8:Test (Best Model) - Loss: 1.1286 - Accuracy: 0.4571 - F1: 0.4236
sub_13:Test (Best Model) - Loss: 2.4070 - Accuracy: 0.4048 - F1: 0.3276
sub_11:Test (Best Model) - Loss: 2.2851 - Accuracy: 0.4190 - F1: 0.3698
sub_3:Test (Best Model) - Loss: 1.5968 - Accuracy: 0.3000 - F1: 0.2798
sub_9:Test (Best Model) - Loss: 1.4284 - Accuracy: 0.3857 - F1: 0.3291
sub_12:Test (Best Model) - Loss: 3.2572 - Accuracy: 0.3857 - F1: 0.3440
sub_14:Test (Best Model) - Loss: 4.3181 - Accuracy: 0.4333 - F1: 0.3746
sub_5:Test (Best Model) - Loss: 3.7274 - Accuracy: 0.3810 - F1: 0.3679
sub_1:Test (Best Model) - Loss: 2.4237 - Accuracy: 0.4952 - F1: 0.4946
sub_10:Test (Best Model) - Loss: 5.2675 - Accuracy: 0.2762 - F1: 0.1988
sub_7:Test (Best Model) - Loss: 2.2454 - Accuracy: 0.3952 - F1: 0.3873
sub_4:Test (Best Model) - Loss: 3.0484 - Accuracy: 0.4238 - F1: 0.3976
sub_2:Test (Best Model) - Loss: 3.0860 - Accuracy: 0.4143 - F1: 0.4039
sub_3:Test (Best Model) - Loss: 2.2821 - Accuracy: 0.3333 - F1: 0.3347
sub_8:Test (Best Model) - Loss: 2.4808 - Accuracy: 0.4619 - F1: 0.4343
sub_13:Test (Best Model) - Loss: 3.8857 - Accuracy: 0.4000 - F1: 0.3205
sub_5:Test (Best Model) - Loss: 2.3829 - Accuracy: 0.3762 - F1: 0.3693
sub_9:Test (Best Model) - Loss: 2.4263 - Accuracy: 0.4286 - F1: 0.4178
sub_11:Test (Best Model) - Loss: 2.5905 - Accuracy: 0.3762 - F1: 0.3576
sub_14:Test (Best Model) - Loss: 3.1014 - Accuracy: 0.4524 - F1: 0.3892
sub_1:Test (Best Model) - Loss: 1.8860 - Accuracy: 0.4524 - F1: 0.4532
sub_6:Test (Best Model) - Loss: 3.9995 - Accuracy: 0.4238 - F1: 0.3754
sub_12:Test (Best Model) - Loss: 3.6560 - Accuracy: 0.3190 - F1: 0.2804
sub_3:Test (Best Model) - Loss: 1.4481 - Accuracy: 0.3714 - F1: 0.3281
sub_5:Test (Best Model) - Loss: 1.4632 - Accuracy: 0.4143 - F1: 0.4053
sub_7:Test (Best Model) - Loss: 1.7016 - Accuracy: 0.4333 - F1: 0.3744
sub_2:Test (Best Model) - Loss: 1.8199 - Accuracy: 0.4048 - F1: 0.4208
sub_10:Test (Best Model) - Loss: 2.6895 - Accuracy: 0.3048 - F1: 0.2193
sub_12:Test (Best Model) - Loss: 2.2665 - Accuracy: 0.3762 - F1: 0.3504
sub_11:Test (Best Model) - Loss: 2.9485 - Accuracy: 0.3952 - F1: 0.3795
sub_4:Test (Best Model) - Loss: 2.9507 - Accuracy: 0.4000 - F1: 0.4005
sub_1:Test (Best Model) - Loss: 1.4176 - Accuracy: 0.4714 - F1: 0.4651
sub_9:Test (Best Model) - Loss: 4.0900 - Accuracy: 0.3238 - F1: 0.2849
sub_13:Test (Best Model) - Loss: 2.8124 - Accuracy: 0.4524 - F1: 0.4059
sub_5:Test (Best Model) - Loss: 1.7204 - Accuracy: 0.4143 - F1: 0.3980
sub_8:Test (Best Model) - Loss: 3.7379 - Accuracy: 0.3905 - F1: 0.3615
sub_9:Test (Best Model) - Loss: 1.4676 - Accuracy: 0.4381 - F1: 0.3718
sub_7:Test (Best Model) - Loss: 3.0815 - Accuracy: 0.4048 - F1: 0.3583
sub_2:Test (Best Model) - Loss: 2.8239 - Accuracy: 0.3667 - F1: 0.3457
sub_14:Test (Best Model) - Loss: 4.1011 - Accuracy: 0.4571 - F1: 0.3816
sub_11:Test (Best Model) - Loss: 2.1972 - Accuracy: 0.4429 - F1: 0.4082
sub_13:Test (Best Model) - Loss: 3.4425 - Accuracy: 0.4381 - F1: 0.3960
sub_6:Test (Best Model) - Loss: 3.8130 - Accuracy: 0.3143 - F1: 0.2737
sub_1:Test (Best Model) - Loss: 3.6324 - Accuracy: 0.4190 - F1: 0.3944
sub_10:Test (Best Model) - Loss: 3.1432 - Accuracy: 0.2905 - F1: 0.2145
sub_12:Test (Best Model) - Loss: 4.2879 - Accuracy: 0.3381 - F1: 0.2925
sub_7:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.4190 - F1: 0.3700
sub_8:Test (Best Model) - Loss: 3.1678 - Accuracy: 0.4619 - F1: 0.4056
sub_2:Test (Best Model) - Loss: 2.8194 - Accuracy: 0.3857 - F1: 0.3900
sub_1:Test (Best Model) - Loss: 1.4319 - Accuracy: 0.4429 - F1: 0.4443
sub_4:Test (Best Model) - Loss: 2.6982 - Accuracy: 0.4762 - F1: 0.4637
sub_11:Test (Best Model) - Loss: 3.9367 - Accuracy: 0.4476 - F1: 0.3987
sub_10:Test (Best Model) - Loss: 2.6885 - Accuracy: 0.3143 - F1: 0.2208
sub_7:Test (Best Model) - Loss: 4.7189 - Accuracy: 0.2714 - F1: 0.2295
sub_12:Test (Best Model) - Loss: 3.6408 - Accuracy: 0.3714 - F1: 0.3306
sub_8:Test (Best Model) - Loss: 2.1267 - Accuracy: 0.4429 - F1: 0.4289
sub_6:Test (Best Model) - Loss: 3.4719 - Accuracy: 0.4333 - F1: 0.4370
sub_14:Test (Best Model) - Loss: 3.8418 - Accuracy: 0.4048 - F1: 0.3278
sub_4:Test (Best Model) - Loss: 2.3397 - Accuracy: 0.4333 - F1: 0.3978
sub_8:Test (Best Model) - Loss: 3.3197 - Accuracy: 0.4429 - F1: 0.3997
sub_12:Test (Best Model) - Loss: 4.4155 - Accuracy: 0.3333 - F1: 0.2450
sub_14:Test (Best Model) - Loss: 3.8347 - Accuracy: 0.3619 - F1: 0.2939
sub_6:Test (Best Model) - Loss: 1.4768 - Accuracy: 0.4524 - F1: 0.4335
sub_6:Test (Best Model) - Loss: 1.5708 - Accuracy: 0.3762 - F1: 0.3840

=== Summary Results ===

acc: 41.73 ± 3.76
F1: 37.61 ± 4.37
acc-in: 55.58 ± 3.71
F1-in: 53.02 ± 4.16
