lr: 0.0001
sub_4:Test (Best Model) - Loss: 1.4948 - Accuracy: 0.4048 - F1: 0.3307
sub_3:Test (Best Model) - Loss: 1.5077 - Accuracy: 0.3524 - F1: 0.3135
sub_11:Test (Best Model) - Loss: 1.4304 - Accuracy: 0.4619 - F1: 0.4246
sub_12:Test (Best Model) - Loss: 1.4664 - Accuracy: 0.4143 - F1: 0.4105
sub_6:Test (Best Model) - Loss: 1.4884 - Accuracy: 0.3762 - F1: 0.2800
sub_8:Test (Best Model) - Loss: 1.3829 - Accuracy: 0.4667 - F1: 0.4501
sub_10:Test (Best Model) - Loss: 1.4643 - Accuracy: 0.3762 - F1: 0.2842
sub_13:Test (Best Model) - Loss: 1.4859 - Accuracy: 0.3810 - F1: 0.3101
sub_14:Test (Best Model) - Loss: 1.4877 - Accuracy: 0.3619 - F1: 0.3431
sub_7:Test (Best Model) - Loss: 1.5513 - Accuracy: 0.2762 - F1: 0.2831
sub_9:Test (Best Model) - Loss: 1.3664 - Accuracy: 0.4238 - F1: 0.4021
sub_3:Test (Best Model) - Loss: 1.5027 - Accuracy: 0.3619 - F1: 0.3173
sub_2:Test (Best Model) - Loss: 1.3995 - Accuracy: 0.3952 - F1: 0.3353
sub_8:Test (Best Model) - Loss: 1.4068 - Accuracy: 0.4762 - F1: 0.4763
sub_1:Test (Best Model) - Loss: 1.4153 - Accuracy: 0.3952 - F1: 0.2823
sub_4:Test (Best Model) - Loss: 1.4360 - Accuracy: 0.4143 - F1: 0.3665
sub_11:Test (Best Model) - Loss: 1.4442 - Accuracy: 0.4095 - F1: 0.3725
sub_12:Test (Best Model) - Loss: 1.4863 - Accuracy: 0.3476 - F1: 0.3537
sub_6:Test (Best Model) - Loss: 1.4725 - Accuracy: 0.3714 - F1: 0.2978
sub_10:Test (Best Model) - Loss: 1.4270 - Accuracy: 0.4143 - F1: 0.3732
sub_5:Test (Best Model) - Loss: 1.7302 - Accuracy: 0.2667 - F1: 0.2167
sub_2:Test (Best Model) - Loss: 1.4962 - Accuracy: 0.3619 - F1: 0.2715
sub_14:Test (Best Model) - Loss: 1.4835 - Accuracy: 0.3619 - F1: 0.3426
sub_8:Test (Best Model) - Loss: 1.3542 - Accuracy: 0.4905 - F1: 0.4754
sub_4:Test (Best Model) - Loss: 1.4693 - Accuracy: 0.4048 - F1: 0.3650
sub_3:Test (Best Model) - Loss: 1.4650 - Accuracy: 0.3952 - F1: 0.3766
sub_11:Test (Best Model) - Loss: 1.4748 - Accuracy: 0.3667 - F1: 0.3294
sub_6:Test (Best Model) - Loss: 1.4861 - Accuracy: 0.4048 - F1: 0.3492
sub_10:Test (Best Model) - Loss: 1.4808 - Accuracy: 0.4190 - F1: 0.3548
sub_12:Test (Best Model) - Loss: 1.4667 - Accuracy: 0.4048 - F1: 0.3844
sub_9:Test (Best Model) - Loss: 1.3398 - Accuracy: 0.4238 - F1: 0.4141
sub_1:Test (Best Model) - Loss: 1.4507 - Accuracy: 0.3810 - F1: 0.2864
sub_7:Test (Best Model) - Loss: 1.6653 - Accuracy: 0.2333 - F1: 0.1889
sub_4:Test (Best Model) - Loss: 1.4820 - Accuracy: 0.4095 - F1: 0.3751
sub_3:Test (Best Model) - Loss: 1.5143 - Accuracy: 0.3476 - F1: 0.2975
sub_2:Test (Best Model) - Loss: 1.4271 - Accuracy: 0.4048 - F1: 0.3376
sub_8:Test (Best Model) - Loss: 1.3582 - Accuracy: 0.4762 - F1: 0.4599
sub_5:Test (Best Model) - Loss: 1.5339 - Accuracy: 0.2762 - F1: 0.2053
sub_13:Test (Best Model) - Loss: 1.4416 - Accuracy: 0.3810 - F1: 0.2949
sub_10:Test (Best Model) - Loss: 1.4683 - Accuracy: 0.4000 - F1: 0.3678
sub_8:Test (Best Model) - Loss: 1.4117 - Accuracy: 0.4476 - F1: 0.4406
sub_6:Test (Best Model) - Loss: 1.4620 - Accuracy: 0.3905 - F1: 0.3703
sub_11:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.4286 - F1: 0.3891
sub_2:Test (Best Model) - Loss: 1.5151 - Accuracy: 0.3286 - F1: 0.2636
sub_4:Test (Best Model) - Loss: 1.4742 - Accuracy: 0.3810 - F1: 0.3414
sub_12:Test (Best Model) - Loss: 1.4182 - Accuracy: 0.4048 - F1: 0.4019
sub_14:Test (Best Model) - Loss: 1.4490 - Accuracy: 0.3810 - F1: 0.3927
sub_3:Test (Best Model) - Loss: 1.5000 - Accuracy: 0.3286 - F1: 0.2564
sub_1:Test (Best Model) - Loss: 1.4434 - Accuracy: 0.4048 - F1: 0.2845
sub_7:Test (Best Model) - Loss: 1.5741 - Accuracy: 0.2524 - F1: 0.2376
sub_9:Test (Best Model) - Loss: 1.4111 - Accuracy: 0.4476 - F1: 0.4113
sub_13:Test (Best Model) - Loss: 1.4991 - Accuracy: 0.3810 - F1: 0.3236
sub_10:Test (Best Model) - Loss: 1.4911 - Accuracy: 0.3333 - F1: 0.2900
sub_8:Test (Best Model) - Loss: 1.3489 - Accuracy: 0.4952 - F1: 0.4881
sub_3:Test (Best Model) - Loss: 1.4693 - Accuracy: 0.4143 - F1: 0.3907
sub_12:Test (Best Model) - Loss: 1.4411 - Accuracy: 0.4143 - F1: 0.4205
sub_11:Test (Best Model) - Loss: 1.4030 - Accuracy: 0.4143 - F1: 0.3745
sub_1:Test (Best Model) - Loss: 1.4493 - Accuracy: 0.3905 - F1: 0.3038
sub_4:Test (Best Model) - Loss: 1.4386 - Accuracy: 0.4238 - F1: 0.3967
sub_6:Test (Best Model) - Loss: 1.4093 - Accuracy: 0.4095 - F1: 0.3478
sub_7:Test (Best Model) - Loss: 1.5605 - Accuracy: 0.2857 - F1: 0.2428
sub_5:Test (Best Model) - Loss: 1.5787 - Accuracy: 0.3000 - F1: 0.2414
sub_14:Test (Best Model) - Loss: 1.4320 - Accuracy: 0.4190 - F1: 0.4014
sub_13:Test (Best Model) - Loss: 1.4632 - Accuracy: 0.3667 - F1: 0.3077
sub_8:Test (Best Model) - Loss: 1.3568 - Accuracy: 0.4762 - F1: 0.4647
sub_9:Test (Best Model) - Loss: 1.4539 - Accuracy: 0.4238 - F1: 0.3720
sub_2:Test (Best Model) - Loss: 1.4728 - Accuracy: 0.3571 - F1: 0.2953
sub_10:Test (Best Model) - Loss: 1.3975 - Accuracy: 0.4333 - F1: 0.4010
sub_3:Test (Best Model) - Loss: 1.4671 - Accuracy: 0.4190 - F1: 0.4160
sub_12:Test (Best Model) - Loss: 1.4548 - Accuracy: 0.3762 - F1: 0.3283
sub_11:Test (Best Model) - Loss: 1.3917 - Accuracy: 0.4048 - F1: 0.3826
sub_13:Test (Best Model) - Loss: 1.5028 - Accuracy: 0.3810 - F1: 0.2669
sub_4:Test (Best Model) - Loss: 1.4724 - Accuracy: 0.3762 - F1: 0.3438
sub_5:Test (Best Model) - Loss: 1.5601 - Accuracy: 0.2571 - F1: 0.2050
sub_3:Test (Best Model) - Loss: 1.4944 - Accuracy: 0.3429 - F1: 0.3505
sub_1:Test (Best Model) - Loss: 1.4027 - Accuracy: 0.3810 - F1: 0.2823
sub_7:Test (Best Model) - Loss: 1.5636 - Accuracy: 0.2667 - F1: 0.2517
sub_8:Test (Best Model) - Loss: 1.3102 - Accuracy: 0.5000 - F1: 0.4805
sub_14:Test (Best Model) - Loss: 1.4908 - Accuracy: 0.3571 - F1: 0.3702
sub_6:Test (Best Model) - Loss: 1.4641 - Accuracy: 0.3286 - F1: 0.3056
sub_10:Test (Best Model) - Loss: 1.4233 - Accuracy: 0.4048 - F1: 0.3853
sub_9:Test (Best Model) - Loss: 1.3522 - Accuracy: 0.4667 - F1: 0.4487
sub_2:Test (Best Model) - Loss: 1.4927 - Accuracy: 0.3810 - F1: 0.3756
sub_13:Test (Best Model) - Loss: 1.4765 - Accuracy: 0.3619 - F1: 0.3531
sub_12:Test (Best Model) - Loss: 1.4905 - Accuracy: 0.3667 - F1: 0.3129
sub_4:Test (Best Model) - Loss: 1.4354 - Accuracy: 0.3810 - F1: 0.3490
sub_5:Test (Best Model) - Loss: 1.5504 - Accuracy: 0.2524 - F1: 0.2113
sub_9:Test (Best Model) - Loss: 1.5198 - Accuracy: 0.3476 - F1: 0.3035
sub_6:Test (Best Model) - Loss: 1.5135 - Accuracy: 0.3524 - F1: 0.3214
sub_3:Test (Best Model) - Loss: 1.4212 - Accuracy: 0.3905 - F1: 0.3977
sub_11:Test (Best Model) - Loss: 1.3762 - Accuracy: 0.4429 - F1: 0.4184
sub_1:Test (Best Model) - Loss: 1.4862 - Accuracy: 0.3762 - F1: 0.3679
sub_14:Test (Best Model) - Loss: 1.3859 - Accuracy: 0.4714 - F1: 0.4335
sub_7:Test (Best Model) - Loss: 1.4534 - Accuracy: 0.4333 - F1: 0.4111
sub_2:Test (Best Model) - Loss: 1.4071 - Accuracy: 0.4095 - F1: 0.3988
sub_4:Test (Best Model) - Loss: 1.4833 - Accuracy: 0.3714 - F1: 0.3398
sub_10:Test (Best Model) - Loss: 1.4130 - Accuracy: 0.3857 - F1: 0.3404
sub_8:Test (Best Model) - Loss: 1.2973 - Accuracy: 0.4905 - F1: 0.4621
sub_9:Test (Best Model) - Loss: 1.4994 - Accuracy: 0.3143 - F1: 0.2781
sub_5:Test (Best Model) - Loss: 1.4856 - Accuracy: 0.3762 - F1: 0.3662
sub_3:Test (Best Model) - Loss: 1.4733 - Accuracy: 0.3810 - F1: 0.3840
sub_13:Test (Best Model) - Loss: 1.4662 - Accuracy: 0.3952 - F1: 0.3734
sub_12:Test (Best Model) - Loss: 1.5067 - Accuracy: 0.3333 - F1: 0.2751
sub_8:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.4571 - F1: 0.4193
sub_4:Test (Best Model) - Loss: 1.4697 - Accuracy: 0.3667 - F1: 0.3235
sub_14:Test (Best Model) - Loss: 1.4158 - Accuracy: 0.4667 - F1: 0.4304
sub_9:Test (Best Model) - Loss: 1.5165 - Accuracy: 0.3048 - F1: 0.2313
sub_1:Test (Best Model) - Loss: 1.4632 - Accuracy: 0.3619 - F1: 0.3477
sub_6:Test (Best Model) - Loss: 1.5083 - Accuracy: 0.3190 - F1: 0.3216
sub_3:Test (Best Model) - Loss: 1.5434 - Accuracy: 0.3190 - F1: 0.3023
sub_13:Test (Best Model) - Loss: 1.4468 - Accuracy: 0.3762 - F1: 0.3610
sub_14:Test (Best Model) - Loss: 1.4669 - Accuracy: 0.4381 - F1: 0.4236
sub_7:Test (Best Model) - Loss: 1.5117 - Accuracy: 0.3476 - F1: 0.3186
sub_12:Test (Best Model) - Loss: 1.4892 - Accuracy: 0.3333 - F1: 0.2778
sub_10:Test (Best Model) - Loss: 1.4245 - Accuracy: 0.4238 - F1: 0.3976
sub_2:Test (Best Model) - Loss: 1.3375 - Accuracy: 0.4143 - F1: 0.4305
sub_9:Test (Best Model) - Loss: 1.5152 - Accuracy: 0.3381 - F1: 0.2912
sub_3:Test (Best Model) - Loss: 1.5673 - Accuracy: 0.2714 - F1: 0.2671
sub_8:Test (Best Model) - Loss: 1.4412 - Accuracy: 0.3905 - F1: 0.3895
sub_11:Test (Best Model) - Loss: 1.3242 - Accuracy: 0.4476 - F1: 0.3827
sub_4:Test (Best Model) - Loss: 1.4833 - Accuracy: 0.3952 - F1: 0.3598
sub_1:Test (Best Model) - Loss: 1.4081 - Accuracy: 0.4143 - F1: 0.4230
sub_5:Test (Best Model) - Loss: 1.5000 - Accuracy: 0.3857 - F1: 0.3544
sub_3:Test (Best Model) - Loss: 1.5369 - Accuracy: 0.3238 - F1: 0.3159
sub_12:Test (Best Model) - Loss: 1.4955 - Accuracy: 0.3381 - F1: 0.2818
sub_10:Test (Best Model) - Loss: 1.4309 - Accuracy: 0.3810 - F1: 0.3491
sub_14:Test (Best Model) - Loss: 1.3617 - Accuracy: 0.4476 - F1: 0.4300
sub_7:Test (Best Model) - Loss: 1.4860 - Accuracy: 0.3619 - F1: 0.3374
sub_4:Test (Best Model) - Loss: 1.4974 - Accuracy: 0.3857 - F1: 0.3750
sub_6:Test (Best Model) - Loss: 1.4708 - Accuracy: 0.3476 - F1: 0.3326
sub_8:Test (Best Model) - Loss: 1.4246 - Accuracy: 0.4286 - F1: 0.4316
sub_2:Test (Best Model) - Loss: 1.3651 - Accuracy: 0.4333 - F1: 0.4364
sub_13:Test (Best Model) - Loss: 1.4264 - Accuracy: 0.3714 - F1: 0.3197
sub_3:Test (Best Model) - Loss: 1.5236 - Accuracy: 0.3143 - F1: 0.3192
sub_1:Test (Best Model) - Loss: 1.4173 - Accuracy: 0.4429 - F1: 0.4582
sub_9:Test (Best Model) - Loss: 1.4839 - Accuracy: 0.3095 - F1: 0.2448
sub_11:Test (Best Model) - Loss: 1.3289 - Accuracy: 0.4238 - F1: 0.4013
sub_6:Test (Best Model) - Loss: 1.4778 - Accuracy: 0.3429 - F1: 0.2947
sub_5:Test (Best Model) - Loss: 1.4420 - Accuracy: 0.4095 - F1: 0.3893
sub_14:Test (Best Model) - Loss: 1.3810 - Accuracy: 0.4571 - F1: 0.4345
sub_12:Test (Best Model) - Loss: 1.5134 - Accuracy: 0.3429 - F1: 0.2851
sub_3:Test (Best Model) - Loss: 1.5457 - Accuracy: 0.3095 - F1: 0.3172
sub_10:Test (Best Model) - Loss: 1.5832 - Accuracy: 0.2667 - F1: 0.2186
sub_4:Test (Best Model) - Loss: 1.4358 - Accuracy: 0.4048 - F1: 0.3886
sub_7:Test (Best Model) - Loss: 1.4772 - Accuracy: 0.3381 - F1: 0.2950
sub_8:Test (Best Model) - Loss: 1.4340 - Accuracy: 0.4381 - F1: 0.4303
sub_1:Test (Best Model) - Loss: 1.4358 - Accuracy: 0.3857 - F1: 0.3995
sub_13:Test (Best Model) - Loss: 1.4510 - Accuracy: 0.4190 - F1: 0.3891
sub_9:Test (Best Model) - Loss: 1.5137 - Accuracy: 0.3429 - F1: 0.3094
sub_2:Test (Best Model) - Loss: 1.3130 - Accuracy: 0.4810 - F1: 0.4827
sub_4:Test (Best Model) - Loss: 1.4735 - Accuracy: 0.3857 - F1: 0.3675
sub_11:Test (Best Model) - Loss: 1.3382 - Accuracy: 0.4524 - F1: 0.4369
sub_12:Test (Best Model) - Loss: 1.4848 - Accuracy: 0.3429 - F1: 0.2775
sub_5:Test (Best Model) - Loss: 1.4576 - Accuracy: 0.3952 - F1: 0.3650
sub_6:Test (Best Model) - Loss: 1.4547 - Accuracy: 0.4476 - F1: 0.4030
sub_14:Test (Best Model) - Loss: 1.6039 - Accuracy: 0.2667 - F1: 0.1944
sub_8:Test (Best Model) - Loss: 1.4268 - Accuracy: 0.4048 - F1: 0.3787
sub_7:Test (Best Model) - Loss: 1.5243 - Accuracy: 0.3619 - F1: 0.3044
sub_9:Test (Best Model) - Loss: 1.5176 - Accuracy: 0.3238 - F1: 0.2831
sub_1:Test (Best Model) - Loss: 1.4271 - Accuracy: 0.4095 - F1: 0.4059
sub_10:Test (Best Model) - Loss: 1.5994 - Accuracy: 0.2714 - F1: 0.2165
sub_8:Test (Best Model) - Loss: 1.4954 - Accuracy: 0.4286 - F1: 0.4242
sub_14:Test (Best Model) - Loss: 1.5943 - Accuracy: 0.2857 - F1: 0.2221
sub_9:Test (Best Model) - Loss: 1.5409 - Accuracy: 0.2952 - F1: 0.2565
sub_13:Test (Best Model) - Loss: 1.4859 - Accuracy: 0.4333 - F1: 0.3731
sub_2:Test (Best Model) - Loss: 1.4978 - Accuracy: 0.2905 - F1: 0.2739
sub_4:Test (Best Model) - Loss: 1.4542 - Accuracy: 0.3714 - F1: 0.3446
sub_11:Test (Best Model) - Loss: 1.4434 - Accuracy: 0.4286 - F1: 0.4124
sub_5:Test (Best Model) - Loss: 1.4295 - Accuracy: 0.4429 - F1: 0.3922
sub_10:Test (Best Model) - Loss: 1.5661 - Accuracy: 0.2667 - F1: 0.2068
sub_6:Test (Best Model) - Loss: 1.4711 - Accuracy: 0.4095 - F1: 0.3667
sub_1:Test (Best Model) - Loss: 1.4440 - Accuracy: 0.4143 - F1: 0.4071
sub_2:Test (Best Model) - Loss: 1.4784 - Accuracy: 0.3619 - F1: 0.3736
sub_14:Test (Best Model) - Loss: 1.6071 - Accuracy: 0.2714 - F1: 0.1938
sub_12:Test (Best Model) - Loss: 1.5005 - Accuracy: 0.3095 - F1: 0.2791
sub_7:Test (Best Model) - Loss: 1.5738 - Accuracy: 0.2524 - F1: 0.2447
sub_9:Test (Best Model) - Loss: 1.4709 - Accuracy: 0.2905 - F1: 0.2302
sub_11:Test (Best Model) - Loss: 1.4328 - Accuracy: 0.4381 - F1: 0.4201
sub_13:Test (Best Model) - Loss: 1.4847 - Accuracy: 0.4429 - F1: 0.3826
sub_10:Test (Best Model) - Loss: 1.5846 - Accuracy: 0.2429 - F1: 0.1509
sub_6:Test (Best Model) - Loss: 1.4765 - Accuracy: 0.3905 - F1: 0.3480
sub_5:Test (Best Model) - Loss: 1.5161 - Accuracy: 0.2905 - F1: 0.2843
sub_14:Test (Best Model) - Loss: 1.5974 - Accuracy: 0.2238 - F1: 0.1206
sub_12:Test (Best Model) - Loss: 1.5116 - Accuracy: 0.3429 - F1: 0.2503
sub_1:Test (Best Model) - Loss: 1.3897 - Accuracy: 0.4429 - F1: 0.4339
sub_2:Test (Best Model) - Loss: 1.4453 - Accuracy: 0.3429 - F1: 0.3266
sub_10:Test (Best Model) - Loss: 1.5526 - Accuracy: 0.3571 - F1: 0.3038
sub_12:Test (Best Model) - Loss: 1.5034 - Accuracy: 0.3095 - F1: 0.2873
sub_9:Test (Best Model) - Loss: 1.4842 - Accuracy: 0.2857 - F1: 0.2568
sub_13:Test (Best Model) - Loss: 1.4258 - Accuracy: 0.4429 - F1: 0.3700
sub_11:Test (Best Model) - Loss: 1.4175 - Accuracy: 0.4429 - F1: 0.4268
sub_14:Test (Best Model) - Loss: 1.6116 - Accuracy: 0.2381 - F1: 0.1494
sub_6:Test (Best Model) - Loss: 1.3960 - Accuracy: 0.4048 - F1: 0.3888
sub_7:Test (Best Model) - Loss: 1.4954 - Accuracy: 0.3333 - F1: 0.2966
sub_5:Test (Best Model) - Loss: 1.5230 - Accuracy: 0.2857 - F1: 0.2884
sub_6:Test (Best Model) - Loss: 1.5117 - Accuracy: 0.3667 - F1: 0.3068
sub_2:Test (Best Model) - Loss: 1.4346 - Accuracy: 0.3762 - F1: 0.3634
sub_1:Test (Best Model) - Loss: 1.4226 - Accuracy: 0.4238 - F1: 0.4008
sub_2:Test (Best Model) - Loss: 1.4716 - Accuracy: 0.3429 - F1: 0.3306
sub_5:Test (Best Model) - Loss: 1.5249 - Accuracy: 0.2905 - F1: 0.3124
sub_13:Test (Best Model) - Loss: 1.3907 - Accuracy: 0.4143 - F1: 0.3532
sub_11:Test (Best Model) - Loss: 1.4118 - Accuracy: 0.4286 - F1: 0.3853
sub_7:Test (Best Model) - Loss: 1.4880 - Accuracy: 0.4048 - F1: 0.3951
sub_1:Test (Best Model) - Loss: 1.3894 - Accuracy: 0.4762 - F1: 0.4673
sub_5:Test (Best Model) - Loss: 1.4849 - Accuracy: 0.3714 - F1: 0.3841
sub_7:Test (Best Model) - Loss: 1.4849 - Accuracy: 0.3524 - F1: 0.3278
sub_13:Test (Best Model) - Loss: 1.4371 - Accuracy: 0.4381 - F1: 0.3761
sub_11:Test (Best Model) - Loss: 1.4246 - Accuracy: 0.4286 - F1: 0.4145
sub_7:Test (Best Model) - Loss: 1.5456 - Accuracy: 0.3667 - F1: 0.3210
sub_5:Test (Best Model) - Loss: 1.5034 - Accuracy: 0.3190 - F1: 0.3315

=== Summary Results ===

acc: 37.71 ± 3.57
F1: 34.36 ± 3.86
acc-in: 46.37 ± 3.64
F1-in: 44.28 ± 3.52
