lr: 0.0001
sub_10:Test (Best Model) - Loss: 1.4298 - Accuracy: 0.4476 - F1: 0.3881
sub_12:Test (Best Model) - Loss: 1.2053 - Accuracy: 0.4429 - F1: 0.4019
sub_4:Test (Best Model) - Loss: 1.6307 - Accuracy: 0.4429 - F1: 0.3868
sub_13:Test (Best Model) - Loss: 4.3414 - Accuracy: 0.2810 - F1: 0.1838
sub_9:Test (Best Model) - Loss: 1.5800 - Accuracy: 0.4333 - F1: 0.4119
sub_6:Test (Best Model) - Loss: 3.2066 - Accuracy: 0.3714 - F1: 0.2861
sub_7:Test (Best Model) - Loss: 3.3837 - Accuracy: 0.3571 - F1: 0.2769
sub_2:Test (Best Model) - Loss: 2.3379 - Accuracy: 0.4524 - F1: 0.3417
sub_1:Test (Best Model) - Loss: 4.0983 - Accuracy: 0.3381 - F1: 0.2305
sub_11:Test (Best Model) - Loss: 2.6279 - Accuracy: 0.4905 - F1: 0.4562
sub_3:Test (Best Model) - Loss: 4.1991 - Accuracy: 0.2476 - F1: 0.1328
sub_5:Test (Best Model) - Loss: 7.6228 - Accuracy: 0.2571 - F1: 0.1629
sub_14:Test (Best Model) - Loss: 2.9652 - Accuracy: 0.4429 - F1: 0.4218
sub_7:Test (Best Model) - Loss: 1.3547 - Accuracy: 0.3905 - F1: 0.3654
sub_8:Test (Best Model) - Loss: 2.7921 - Accuracy: 0.4952 - F1: 0.4814
sub_10:Test (Best Model) - Loss: 3.0987 - Accuracy: 0.4476 - F1: 0.4044
sub_12:Test (Best Model) - Loss: 2.1421 - Accuracy: 0.4381 - F1: 0.4125
sub_13:Test (Best Model) - Loss: 5.4915 - Accuracy: 0.3238 - F1: 0.2212
sub_4:Test (Best Model) - Loss: 3.1680 - Accuracy: 0.4476 - F1: 0.4227
sub_9:Test (Best Model) - Loss: 3.4726 - Accuracy: 0.4286 - F1: 0.3894
sub_10:Test (Best Model) - Loss: 1.5147 - Accuracy: 0.4476 - F1: 0.3925
sub_2:Test (Best Model) - Loss: 3.5641 - Accuracy: 0.4476 - F1: 0.3820
sub_1:Test (Best Model) - Loss: 4.0328 - Accuracy: 0.3905 - F1: 0.3421
sub_14:Test (Best Model) - Loss: 2.0288 - Accuracy: 0.5381 - F1: 0.5114
sub_5:Test (Best Model) - Loss: 5.6847 - Accuracy: 0.2905 - F1: 0.2194
sub_8:Test (Best Model) - Loss: 1.0750 - Accuracy: 0.5333 - F1: 0.5127
sub_11:Test (Best Model) - Loss: 4.1904 - Accuracy: 0.4619 - F1: 0.4100
sub_7:Test (Best Model) - Loss: 2.2866 - Accuracy: 0.3238 - F1: 0.2732
sub_6:Test (Best Model) - Loss: 4.6017 - Accuracy: 0.4095 - F1: 0.3346
sub_3:Test (Best Model) - Loss: 4.4139 - Accuracy: 0.4238 - F1: 0.3165
sub_1:Test (Best Model) - Loss: 4.3602 - Accuracy: 0.3381 - F1: 0.2338
sub_5:Test (Best Model) - Loss: 3.7726 - Accuracy: 0.3667 - F1: 0.2908
sub_4:Test (Best Model) - Loss: 2.9734 - Accuracy: 0.4524 - F1: 0.4134
sub_14:Test (Best Model) - Loss: 1.8184 - Accuracy: 0.5524 - F1: 0.5256
sub_13:Test (Best Model) - Loss: 5.6607 - Accuracy: 0.2667 - F1: 0.1440
sub_9:Test (Best Model) - Loss: 3.4079 - Accuracy: 0.4476 - F1: 0.3928
sub_12:Test (Best Model) - Loss: 2.6239 - Accuracy: 0.4857 - F1: 0.4410
sub_5:Test (Best Model) - Loss: 5.0818 - Accuracy: 0.2905 - F1: 0.2024
sub_7:Test (Best Model) - Loss: 2.7278 - Accuracy: 0.3000 - F1: 0.2896
sub_2:Test (Best Model) - Loss: 3.8212 - Accuracy: 0.4667 - F1: 0.3832
sub_10:Test (Best Model) - Loss: 1.6396 - Accuracy: 0.4619 - F1: 0.4285
sub_11:Test (Best Model) - Loss: 3.1474 - Accuracy: 0.4048 - F1: 0.3282
sub_1:Test (Best Model) - Loss: 2.9767 - Accuracy: 0.4143 - F1: 0.3169
sub_8:Test (Best Model) - Loss: 3.3135 - Accuracy: 0.4524 - F1: 0.4232
sub_13:Test (Best Model) - Loss: 2.4766 - Accuracy: 0.3810 - F1: 0.3345
sub_7:Test (Best Model) - Loss: 2.0067 - Accuracy: 0.3762 - F1: 0.3238
sub_14:Test (Best Model) - Loss: 2.1736 - Accuracy: 0.4905 - F1: 0.4773
sub_3:Test (Best Model) - Loss: 2.9680 - Accuracy: 0.3571 - F1: 0.2119
sub_12:Test (Best Model) - Loss: 1.6654 - Accuracy: 0.4238 - F1: 0.3682
sub_9:Test (Best Model) - Loss: 3.4979 - Accuracy: 0.4333 - F1: 0.4045
sub_6:Test (Best Model) - Loss: 4.2571 - Accuracy: 0.4190 - F1: 0.3200
sub_2:Test (Best Model) - Loss: 3.8125 - Accuracy: 0.4190 - F1: 0.3391
sub_5:Test (Best Model) - Loss: 4.4324 - Accuracy: 0.3762 - F1: 0.3072
sub_4:Test (Best Model) - Loss: 4.1123 - Accuracy: 0.4571 - F1: 0.4058
sub_10:Test (Best Model) - Loss: 1.3693 - Accuracy: 0.5048 - F1: 0.4592
sub_13:Test (Best Model) - Loss: 4.9521 - Accuracy: 0.2714 - F1: 0.1560
sub_1:Test (Best Model) - Loss: 3.9111 - Accuracy: 0.3905 - F1: 0.2738
sub_11:Test (Best Model) - Loss: 3.9940 - Accuracy: 0.4762 - F1: 0.4235
sub_8:Test (Best Model) - Loss: 2.2470 - Accuracy: 0.5048 - F1: 0.4813
sub_3:Test (Best Model) - Loss: 3.9078 - Accuracy: 0.2905 - F1: 0.1699
sub_14:Test (Best Model) - Loss: 3.1373 - Accuracy: 0.4333 - F1: 0.4029
sub_2:Test (Best Model) - Loss: 3.9598 - Accuracy: 0.3238 - F1: 0.2526
sub_8:Test (Best Model) - Loss: 1.1880 - Accuracy: 0.4905 - F1: 0.4671
sub_7:Test (Best Model) - Loss: 3.5911 - Accuracy: 0.4000 - F1: 0.3408
sub_9:Test (Best Model) - Loss: 4.0053 - Accuracy: 0.3952 - F1: 0.3647
sub_12:Test (Best Model) - Loss: 3.4314 - Accuracy: 0.4524 - F1: 0.4395
sub_5:Test (Best Model) - Loss: 3.6342 - Accuracy: 0.4524 - F1: 0.4028
sub_6:Test (Best Model) - Loss: 2.1578 - Accuracy: 0.3762 - F1: 0.3177
sub_13:Test (Best Model) - Loss: 2.2115 - Accuracy: 0.3952 - F1: 0.3516
sub_10:Test (Best Model) - Loss: 1.5600 - Accuracy: 0.4571 - F1: 0.4241
sub_4:Test (Best Model) - Loss: 3.1045 - Accuracy: 0.4476 - F1: 0.3594
sub_9:Test (Best Model) - Loss: 2.4582 - Accuracy: 0.3952 - F1: 0.3167
sub_1:Test (Best Model) - Loss: 1.9729 - Accuracy: 0.4381 - F1: 0.4264
sub_11:Test (Best Model) - Loss: 4.6969 - Accuracy: 0.4905 - F1: 0.4199
sub_6:Test (Best Model) - Loss: 1.3689 - Accuracy: 0.3857 - F1: 0.3002
sub_4:Test (Best Model) - Loss: 1.2672 - Accuracy: 0.4714 - F1: 0.4238
sub_2:Test (Best Model) - Loss: 1.7585 - Accuracy: 0.4810 - F1: 0.4856
sub_3:Test (Best Model) - Loss: 4.6786 - Accuracy: 0.2286 - F1: 0.1174
sub_7:Test (Best Model) - Loss: 2.1524 - Accuracy: 0.4381 - F1: 0.3866
sub_12:Test (Best Model) - Loss: 4.2346 - Accuracy: 0.3571 - F1: 0.3009
sub_13:Test (Best Model) - Loss: 1.5944 - Accuracy: 0.4238 - F1: 0.3746
sub_14:Test (Best Model) - Loss: 2.4331 - Accuracy: 0.5571 - F1: 0.5056
sub_9:Test (Best Model) - Loss: 2.9452 - Accuracy: 0.4333 - F1: 0.3784
sub_8:Test (Best Model) - Loss: 1.7100 - Accuracy: 0.5286 - F1: 0.5294
sub_5:Test (Best Model) - Loss: 3.6596 - Accuracy: 0.4857 - F1: 0.4404
sub_11:Test (Best Model) - Loss: 2.5561 - Accuracy: 0.4714 - F1: 0.4459
sub_4:Test (Best Model) - Loss: 1.3131 - Accuracy: 0.4619 - F1: 0.4597
sub_1:Test (Best Model) - Loss: 3.3470 - Accuracy: 0.4048 - F1: 0.3804
sub_3:Test (Best Model) - Loss: 1.7351 - Accuracy: 0.4429 - F1: 0.3896
sub_10:Test (Best Model) - Loss: 2.1040 - Accuracy: 0.4714 - F1: 0.4484
sub_7:Test (Best Model) - Loss: 3.3180 - Accuracy: 0.3667 - F1: 0.3190
sub_14:Test (Best Model) - Loss: 1.0991 - Accuracy: 0.5667 - F1: 0.5243
sub_2:Test (Best Model) - Loss: 1.8812 - Accuracy: 0.4952 - F1: 0.4633
sub_9:Test (Best Model) - Loss: 3.6085 - Accuracy: 0.3714 - F1: 0.3170
sub_5:Test (Best Model) - Loss: 2.9900 - Accuracy: 0.4762 - F1: 0.4309
sub_3:Test (Best Model) - Loss: 1.2168 - Accuracy: 0.3429 - F1: 0.3272
sub_8:Test (Best Model) - Loss: 1.1505 - Accuracy: 0.5000 - F1: 0.4729
sub_4:Test (Best Model) - Loss: 1.3746 - Accuracy: 0.4714 - F1: 0.4658
sub_6:Test (Best Model) - Loss: 3.9672 - Accuracy: 0.4619 - F1: 0.4620
sub_13:Test (Best Model) - Loss: 4.4937 - Accuracy: 0.4143 - F1: 0.3438
sub_12:Test (Best Model) - Loss: 3.6798 - Accuracy: 0.3762 - F1: 0.3172
sub_14:Test (Best Model) - Loss: 1.0949 - Accuracy: 0.5905 - F1: 0.5642
sub_1:Test (Best Model) - Loss: 2.0954 - Accuracy: 0.4571 - F1: 0.4395
sub_11:Test (Best Model) - Loss: 2.5729 - Accuracy: 0.5095 - F1: 0.5034
sub_5:Test (Best Model) - Loss: 3.3017 - Accuracy: 0.4333 - F1: 0.3490
sub_2:Test (Best Model) - Loss: 2.2107 - Accuracy: 0.5238 - F1: 0.5058
sub_9:Test (Best Model) - Loss: 4.2900 - Accuracy: 0.3905 - F1: 0.3178
sub_8:Test (Best Model) - Loss: 1.2559 - Accuracy: 0.5524 - F1: 0.5488
sub_7:Test (Best Model) - Loss: 4.5328 - Accuracy: 0.4238 - F1: 0.3571
sub_10:Test (Best Model) - Loss: 2.0865 - Accuracy: 0.5143 - F1: 0.5061
sub_4:Test (Best Model) - Loss: 1.9269 - Accuracy: 0.5381 - F1: 0.5497
sub_13:Test (Best Model) - Loss: 2.9427 - Accuracy: 0.4000 - F1: 0.3266
sub_3:Test (Best Model) - Loss: 1.9118 - Accuracy: 0.4429 - F1: 0.3967
sub_1:Test (Best Model) - Loss: 2.0250 - Accuracy: 0.4143 - F1: 0.3906
sub_12:Test (Best Model) - Loss: 5.0970 - Accuracy: 0.3524 - F1: 0.2936
sub_2:Test (Best Model) - Loss: 2.0339 - Accuracy: 0.4571 - F1: 0.4350
sub_11:Test (Best Model) - Loss: 2.3446 - Accuracy: 0.4905 - F1: 0.4445
sub_6:Test (Best Model) - Loss: 4.9557 - Accuracy: 0.3667 - F1: 0.3538
sub_7:Test (Best Model) - Loss: 2.5284 - Accuracy: 0.3429 - F1: 0.2306
sub_14:Test (Best Model) - Loss: 2.4784 - Accuracy: 0.6000 - F1: 0.5872
sub_13:Test (Best Model) - Loss: 2.6897 - Accuracy: 0.3762 - F1: 0.3433
sub_5:Test (Best Model) - Loss: 3.2109 - Accuracy: 0.4714 - F1: 0.3873
sub_10:Test (Best Model) - Loss: 3.3042 - Accuracy: 0.4381 - F1: 0.4008
sub_9:Test (Best Model) - Loss: 2.6767 - Accuracy: 0.4333 - F1: 0.3271
sub_4:Test (Best Model) - Loss: 1.8390 - Accuracy: 0.4571 - F1: 0.4470
sub_3:Test (Best Model) - Loss: 1.2598 - Accuracy: 0.4429 - F1: 0.3933
sub_8:Test (Best Model) - Loss: 1.6713 - Accuracy: 0.5333 - F1: 0.5293
sub_12:Test (Best Model) - Loss: 2.6369 - Accuracy: 0.4143 - F1: 0.3642
sub_1:Test (Best Model) - Loss: 2.0774 - Accuracy: 0.5048 - F1: 0.5015
sub_8:Test (Best Model) - Loss: 1.0519 - Accuracy: 0.5095 - F1: 0.4879
sub_6:Test (Best Model) - Loss: 1.5503 - Accuracy: 0.4000 - F1: 0.3684
sub_3:Test (Best Model) - Loss: 1.3106 - Accuracy: 0.3857 - F1: 0.3186
sub_9:Test (Best Model) - Loss: 2.8228 - Accuracy: 0.4381 - F1: 0.3964
sub_13:Test (Best Model) - Loss: 1.5698 - Accuracy: 0.4333 - F1: 0.3521
sub_11:Test (Best Model) - Loss: 2.2411 - Accuracy: 0.5143 - F1: 0.4490
sub_14:Test (Best Model) - Loss: 1.0863 - Accuracy: 0.5476 - F1: 0.5021
sub_10:Test (Best Model) - Loss: 3.3931 - Accuracy: 0.4238 - F1: 0.3691
sub_7:Test (Best Model) - Loss: 3.2602 - Accuracy: 0.3952 - F1: 0.3943
sub_4:Test (Best Model) - Loss: 2.4911 - Accuracy: 0.5429 - F1: 0.4977
sub_12:Test (Best Model) - Loss: 3.4985 - Accuracy: 0.4095 - F1: 0.3702
sub_2:Test (Best Model) - Loss: 2.2642 - Accuracy: 0.4571 - F1: 0.4399
sub_5:Test (Best Model) - Loss: 3.6791 - Accuracy: 0.4381 - F1: 0.4112
sub_9:Test (Best Model) - Loss: 1.2617 - Accuracy: 0.4238 - F1: 0.3816
sub_13:Test (Best Model) - Loss: 2.3257 - Accuracy: 0.4048 - F1: 0.3212
sub_6:Test (Best Model) - Loss: 3.4097 - Accuracy: 0.3571 - F1: 0.3564
sub_1:Test (Best Model) - Loss: 2.3292 - Accuracy: 0.5095 - F1: 0.5044
sub_12:Test (Best Model) - Loss: 3.3078 - Accuracy: 0.4333 - F1: 0.3564
sub_3:Test (Best Model) - Loss: 1.7532 - Accuracy: 0.3810 - F1: 0.3289
sub_10:Test (Best Model) - Loss: 3.7454 - Accuracy: 0.3524 - F1: 0.2792
sub_5:Test (Best Model) - Loss: 2.7098 - Accuracy: 0.4667 - F1: 0.4604
sub_14:Test (Best Model) - Loss: 4.9672 - Accuracy: 0.3810 - F1: 0.3193
sub_8:Test (Best Model) - Loss: 3.4381 - Accuracy: 0.4810 - F1: 0.4425
sub_11:Test (Best Model) - Loss: 2.9040 - Accuracy: 0.4667 - F1: 0.4376
sub_2:Test (Best Model) - Loss: 5.0512 - Accuracy: 0.3429 - F1: 0.3422
sub_1:Test (Best Model) - Loss: 1.5883 - Accuracy: 0.5095 - F1: 0.4818
sub_13:Test (Best Model) - Loss: 5.1197 - Accuracy: 0.3905 - F1: 0.2984
sub_6:Test (Best Model) - Loss: 1.9690 - Accuracy: 0.4238 - F1: 0.4073
sub_4:Test (Best Model) - Loss: 2.9880 - Accuracy: 0.4667 - F1: 0.4107
sub_11:Test (Best Model) - Loss: 2.1429 - Accuracy: 0.4667 - F1: 0.4296
sub_7:Test (Best Model) - Loss: 3.6202 - Accuracy: 0.3524 - F1: 0.2865
sub_10:Test (Best Model) - Loss: 3.2475 - Accuracy: 0.3571 - F1: 0.2747
sub_3:Test (Best Model) - Loss: 1.5820 - Accuracy: 0.3905 - F1: 0.3804
sub_9:Test (Best Model) - Loss: 3.7154 - Accuracy: 0.4381 - F1: 0.4385
sub_2:Test (Best Model) - Loss: 2.6456 - Accuracy: 0.4286 - F1: 0.4269
sub_8:Test (Best Model) - Loss: 2.8412 - Accuracy: 0.4619 - F1: 0.4003
sub_5:Test (Best Model) - Loss: 3.5010 - Accuracy: 0.4143 - F1: 0.4271
sub_14:Test (Best Model) - Loss: 3.9841 - Accuracy: 0.4190 - F1: 0.3573
sub_3:Test (Best Model) - Loss: 1.4930 - Accuracy: 0.3333 - F1: 0.3402
sub_1:Test (Best Model) - Loss: 1.4021 - Accuracy: 0.5524 - F1: 0.5416
sub_12:Test (Best Model) - Loss: 4.5788 - Accuracy: 0.3571 - F1: 0.2919
sub_4:Test (Best Model) - Loss: 1.7038 - Accuracy: 0.4476 - F1: 0.4005
sub_6:Test (Best Model) - Loss: 4.1644 - Accuracy: 0.3810 - F1: 0.3297
sub_13:Test (Best Model) - Loss: 1.6421 - Accuracy: 0.4429 - F1: 0.3869
sub_7:Test (Best Model) - Loss: 3.1662 - Accuracy: 0.3952 - F1: 0.3635
sub_5:Test (Best Model) - Loss: 2.1404 - Accuracy: 0.4048 - F1: 0.4077
sub_10:Test (Best Model) - Loss: 4.3672 - Accuracy: 0.3476 - F1: 0.2534
sub_11:Test (Best Model) - Loss: 3.2371 - Accuracy: 0.5190 - F1: 0.4884
sub_2:Test (Best Model) - Loss: 1.2172 - Accuracy: 0.5000 - F1: 0.5074
sub_9:Test (Best Model) - Loss: 2.4188 - Accuracy: 0.4476 - F1: 0.4298
sub_3:Test (Best Model) - Loss: 2.1051 - Accuracy: 0.3810 - F1: 0.3587
sub_1:Test (Best Model) - Loss: 1.6702 - Accuracy: 0.5095 - F1: 0.4740
sub_8:Test (Best Model) - Loss: 2.4890 - Accuracy: 0.4857 - F1: 0.3816
sub_14:Test (Best Model) - Loss: 3.8509 - Accuracy: 0.4429 - F1: 0.3681
sub_5:Test (Best Model) - Loss: 3.5207 - Accuracy: 0.4048 - F1: 0.3794
sub_6:Test (Best Model) - Loss: 3.6996 - Accuracy: 0.4143 - F1: 0.3802
sub_11:Test (Best Model) - Loss: 2.3311 - Accuracy: 0.4333 - F1: 0.4058
sub_2:Test (Best Model) - Loss: 2.5715 - Accuracy: 0.4095 - F1: 0.4297
sub_12:Test (Best Model) - Loss: 4.0683 - Accuracy: 0.3714 - F1: 0.2730
sub_7:Test (Best Model) - Loss: 1.5451 - Accuracy: 0.3810 - F1: 0.3303
sub_3:Test (Best Model) - Loss: 1.7959 - Accuracy: 0.3762 - F1: 0.3267
sub_9:Test (Best Model) - Loss: 1.9022 - Accuracy: 0.4762 - F1: 0.3984
sub_1:Test (Best Model) - Loss: 2.2272 - Accuracy: 0.4905 - F1: 0.4611
sub_13:Test (Best Model) - Loss: 4.6616 - Accuracy: 0.4048 - F1: 0.3317
sub_4:Test (Best Model) - Loss: 2.9089 - Accuracy: 0.4381 - F1: 0.4207
sub_11:Test (Best Model) - Loss: 2.2890 - Accuracy: 0.4714 - F1: 0.4349
sub_10:Test (Best Model) - Loss: 2.6412 - Accuracy: 0.3857 - F1: 0.2669
sub_2:Test (Best Model) - Loss: 2.0767 - Accuracy: 0.4190 - F1: 0.4253
sub_14:Test (Best Model) - Loss: 2.7068 - Accuracy: 0.4143 - F1: 0.3437
sub_11:Test (Best Model) - Loss: 2.0702 - Accuracy: 0.4857 - F1: 0.4359
sub_6:Test (Best Model) - Loss: 3.0791 - Accuracy: 0.4286 - F1: 0.4005
sub_8:Test (Best Model) - Loss: 2.5654 - Accuracy: 0.4524 - F1: 0.3788
sub_7:Test (Best Model) - Loss: 4.7564 - Accuracy: 0.2238 - F1: 0.1947
sub_10:Test (Best Model) - Loss: 2.8334 - Accuracy: 0.3762 - F1: 0.3038
sub_14:Test (Best Model) - Loss: 4.5344 - Accuracy: 0.3762 - F1: 0.3015
sub_4:Test (Best Model) - Loss: 2.0726 - Accuracy: 0.5000 - F1: 0.4609
sub_8:Test (Best Model) - Loss: 1.7306 - Accuracy: 0.4571 - F1: 0.4291
sub_12:Test (Best Model) - Loss: 4.9411 - Accuracy: 0.4048 - F1: 0.3210
sub_6:Test (Best Model) - Loss: 2.4592 - Accuracy: 0.4000 - F1: 0.3721
sub_12:Test (Best Model) - Loss: 4.2138 - Accuracy: 0.4143 - F1: 0.3279
sub_6:Test (Best Model) - Loss: 4.2659 - Accuracy: 0.4333 - F1: 0.4342

=== Summary Results ===

acc: 42.77 ± 4.29
F1: 38.01 ± 5.22
acc-in: 58.37 ± 4.14
F1-in: 56.06 ± 4.52
