lr: 1e-05
sub_9:Test (Best Model) - Loss: 1.5365 - Accuracy: 0.3571 - F1: 0.2196
sub_13:Test (Best Model) - Loss: 1.4597 - Accuracy: 0.3667 - F1: 0.3068
sub_11:Test (Best Model) - Loss: 1.3934 - Accuracy: 0.4333 - F1: 0.3766
sub_5:Test (Best Model) - Loss: 1.9266 - Accuracy: 0.2619 - F1: 0.1909
sub_6:Test (Best Model) - Loss: 1.5319 - Accuracy: 0.3238 - F1: 0.2700
sub_10:Test (Best Model) - Loss: 1.5535 - Accuracy: 0.3429 - F1: 0.2667
sub_3:Test (Best Model) - Loss: 1.5814 - Accuracy: 0.2762 - F1: 0.1810
sub_7:Test (Best Model) - Loss: 1.5787 - Accuracy: 0.3048 - F1: 0.2269
sub_2:Test (Best Model) - Loss: 1.6111 - Accuracy: 0.4000 - F1: 0.3069
sub_4:Test (Best Model) - Loss: 1.4826 - Accuracy: 0.4238 - F1: 0.3243
sub_8:Test (Best Model) - Loss: 1.1865 - Accuracy: 0.4095 - F1: 0.3629
sub_12:Test (Best Model) - Loss: 1.3155 - Accuracy: 0.3619 - F1: 0.3430
sub_10:Test (Best Model) - Loss: 1.4925 - Accuracy: 0.3143 - F1: 0.2318
sub_5:Test (Best Model) - Loss: 1.7266 - Accuracy: 0.3190 - F1: 0.2514
sub_3:Test (Best Model) - Loss: 1.3472 - Accuracy: 0.3762 - F1: 0.3618
sub_1:Test (Best Model) - Loss: 3.2532 - Accuracy: 0.3238 - F1: 0.2391
sub_4:Test (Best Model) - Loss: 1.4483 - Accuracy: 0.3571 - F1: 0.3452
sub_6:Test (Best Model) - Loss: 1.3648 - Accuracy: 0.3667 - F1: 0.3296
sub_14:Test (Best Model) - Loss: 1.2958 - Accuracy: 0.4524 - F1: 0.4188
sub_13:Test (Best Model) - Loss: 1.5937 - Accuracy: 0.3095 - F1: 0.2454
sub_7:Test (Best Model) - Loss: 1.4649 - Accuracy: 0.2905 - F1: 0.2096
sub_8:Test (Best Model) - Loss: 1.2497 - Accuracy: 0.4429 - F1: 0.4057
sub_2:Test (Best Model) - Loss: 1.6591 - Accuracy: 0.3714 - F1: 0.2433
sub_9:Test (Best Model) - Loss: 1.2237 - Accuracy: 0.4333 - F1: 0.3998
sub_12:Test (Best Model) - Loss: 1.3307 - Accuracy: 0.3619 - F1: 0.3410
sub_11:Test (Best Model) - Loss: 1.4292 - Accuracy: 0.4381 - F1: 0.3990
sub_5:Test (Best Model) - Loss: 1.5871 - Accuracy: 0.3286 - F1: 0.2298
sub_7:Test (Best Model) - Loss: 1.5490 - Accuracy: 0.3048 - F1: 0.2404
sub_6:Test (Best Model) - Loss: 1.5239 - Accuracy: 0.3190 - F1: 0.2293
sub_10:Test (Best Model) - Loss: 1.6748 - Accuracy: 0.3286 - F1: 0.2387
sub_2:Test (Best Model) - Loss: 1.8510 - Accuracy: 0.3048 - F1: 0.1938
sub_1:Test (Best Model) - Loss: 1.5686 - Accuracy: 0.2905 - F1: 0.2147
sub_13:Test (Best Model) - Loss: 1.5992 - Accuracy: 0.3095 - F1: 0.2100
sub_3:Test (Best Model) - Loss: 1.3793 - Accuracy: 0.3286 - F1: 0.2519
sub_8:Test (Best Model) - Loss: 1.2919 - Accuracy: 0.4381 - F1: 0.3958
sub_11:Test (Best Model) - Loss: 1.3942 - Accuracy: 0.4143 - F1: 0.3556
sub_14:Test (Best Model) - Loss: 1.5037 - Accuracy: 0.3810 - F1: 0.3843
sub_4:Test (Best Model) - Loss: 1.4157 - Accuracy: 0.4095 - F1: 0.3181
sub_12:Test (Best Model) - Loss: 1.3259 - Accuracy: 0.4095 - F1: 0.3549
sub_9:Test (Best Model) - Loss: 1.5059 - Accuracy: 0.3857 - F1: 0.2706
sub_3:Test (Best Model) - Loss: 1.5416 - Accuracy: 0.3810 - F1: 0.2466
sub_6:Test (Best Model) - Loss: 1.4163 - Accuracy: 0.3286 - F1: 0.2807
sub_11:Test (Best Model) - Loss: 1.4276 - Accuracy: 0.3905 - F1: 0.3313
sub_10:Test (Best Model) - Loss: 1.5051 - Accuracy: 0.3857 - F1: 0.3427
sub_13:Test (Best Model) - Loss: 1.3571 - Accuracy: 0.4190 - F1: 0.3492
sub_7:Test (Best Model) - Loss: 1.4384 - Accuracy: 0.3476 - F1: 0.3112
sub_12:Test (Best Model) - Loss: 1.4065 - Accuracy: 0.3762 - F1: 0.3433
sub_14:Test (Best Model) - Loss: 1.5215 - Accuracy: 0.3857 - F1: 0.3040
sub_5:Test (Best Model) - Loss: 2.8153 - Accuracy: 0.3238 - F1: 0.2418
sub_1:Test (Best Model) - Loss: 2.1112 - Accuracy: 0.2857 - F1: 0.1801
sub_9:Test (Best Model) - Loss: 1.2716 - Accuracy: 0.4143 - F1: 0.3309
sub_2:Test (Best Model) - Loss: 1.9615 - Accuracy: 0.4095 - F1: 0.3487
sub_6:Test (Best Model) - Loss: 1.4335 - Accuracy: 0.3810 - F1: 0.2725
sub_3:Test (Best Model) - Loss: 1.7847 - Accuracy: 0.2143 - F1: 0.0968
sub_8:Test (Best Model) - Loss: 1.1806 - Accuracy: 0.4905 - F1: 0.4562
sub_10:Test (Best Model) - Loss: 1.4036 - Accuracy: 0.3810 - F1: 0.3011
sub_11:Test (Best Model) - Loss: 1.5242 - Accuracy: 0.3667 - F1: 0.2810
sub_14:Test (Best Model) - Loss: 1.3503 - Accuracy: 0.4524 - F1: 0.3996
sub_12:Test (Best Model) - Loss: 1.3729 - Accuracy: 0.4095 - F1: 0.3463
sub_13:Test (Best Model) - Loss: 1.6203 - Accuracy: 0.2952 - F1: 0.1783
sub_4:Test (Best Model) - Loss: 1.4976 - Accuracy: 0.5000 - F1: 0.4285
sub_3:Test (Best Model) - Loss: 1.4211 - Accuracy: 0.3905 - F1: 0.3308
sub_5:Test (Best Model) - Loss: 1.6042 - Accuracy: 0.3286 - F1: 0.2025
sub_2:Test (Best Model) - Loss: 1.6249 - Accuracy: 0.2810 - F1: 0.1966
sub_9:Test (Best Model) - Loss: 1.3202 - Accuracy: 0.3810 - F1: 0.2602
sub_7:Test (Best Model) - Loss: 1.3426 - Accuracy: 0.4333 - F1: 0.3864
sub_10:Test (Best Model) - Loss: 1.3656 - Accuracy: 0.3810 - F1: 0.3298
sub_11:Test (Best Model) - Loss: 1.4079 - Accuracy: 0.4000 - F1: 0.3394
sub_13:Test (Best Model) - Loss: 1.4671 - Accuracy: 0.3381 - F1: 0.3360
sub_4:Test (Best Model) - Loss: 1.3180 - Accuracy: 0.4238 - F1: 0.3344
sub_8:Test (Best Model) - Loss: 1.2525 - Accuracy: 0.4429 - F1: 0.4039
sub_7:Test (Best Model) - Loss: 1.5108 - Accuracy: 0.3333 - F1: 0.3285
sub_2:Test (Best Model) - Loss: 1.4046 - Accuracy: 0.3762 - F1: 0.3246
sub_1:Test (Best Model) - Loss: 2.2959 - Accuracy: 0.3810 - F1: 0.2853
sub_6:Test (Best Model) - Loss: 1.3762 - Accuracy: 0.3857 - F1: 0.3199
sub_3:Test (Best Model) - Loss: 1.3561 - Accuracy: 0.4000 - F1: 0.3641
sub_5:Test (Best Model) - Loss: 1.3983 - Accuracy: 0.3095 - F1: 0.2277
sub_14:Test (Best Model) - Loss: 1.3082 - Accuracy: 0.4143 - F1: 0.3817
sub_12:Test (Best Model) - Loss: 1.7095 - Accuracy: 0.3286 - F1: 0.2342
sub_8:Test (Best Model) - Loss: 1.2760 - Accuracy: 0.4000 - F1: 0.3389
sub_2:Test (Best Model) - Loss: 1.2431 - Accuracy: 0.4476 - F1: 0.4559
sub_11:Test (Best Model) - Loss: 1.2068 - Accuracy: 0.4762 - F1: 0.4180
sub_9:Test (Best Model) - Loss: 1.7092 - Accuracy: 0.4000 - F1: 0.3264
sub_3:Test (Best Model) - Loss: 1.3627 - Accuracy: 0.4190 - F1: 0.3318
sub_6:Test (Best Model) - Loss: 1.4413 - Accuracy: 0.3714 - F1: 0.3258
sub_7:Test (Best Model) - Loss: 1.3975 - Accuracy: 0.3333 - F1: 0.2481
sub_10:Test (Best Model) - Loss: 1.2150 - Accuracy: 0.4476 - F1: 0.3878
sub_13:Test (Best Model) - Loss: 1.3355 - Accuracy: 0.4048 - F1: 0.3250
sub_8:Test (Best Model) - Loss: 1.2309 - Accuracy: 0.4238 - F1: 0.3671
sub_1:Test (Best Model) - Loss: 1.9221 - Accuracy: 0.2905 - F1: 0.1634
sub_3:Test (Best Model) - Loss: 1.4240 - Accuracy: 0.3619 - F1: 0.3376
sub_14:Test (Best Model) - Loss: 1.2626 - Accuracy: 0.4619 - F1: 0.4213
sub_4:Test (Best Model) - Loss: 1.1786 - Accuracy: 0.4762 - F1: 0.4442
sub_9:Test (Best Model) - Loss: 1.4368 - Accuracy: 0.3810 - F1: 0.3096
sub_6:Test (Best Model) - Loss: 1.5014 - Accuracy: 0.3667 - F1: 0.2955
sub_2:Test (Best Model) - Loss: 1.2170 - Accuracy: 0.4571 - F1: 0.3971
sub_5:Test (Best Model) - Loss: 1.4104 - Accuracy: 0.4190 - F1: 0.3596
sub_12:Test (Best Model) - Loss: 1.6715 - Accuracy: 0.3190 - F1: 0.2540
sub_7:Test (Best Model) - Loss: 1.4301 - Accuracy: 0.3571 - F1: 0.2900
sub_11:Test (Best Model) - Loss: 1.2272 - Accuracy: 0.4429 - F1: 0.3964
sub_8:Test (Best Model) - Loss: 1.2023 - Accuracy: 0.4238 - F1: 0.3970
sub_3:Test (Best Model) - Loss: 1.3481 - Accuracy: 0.3810 - F1: 0.3205
sub_1:Test (Best Model) - Loss: 1.3793 - Accuracy: 0.4190 - F1: 0.3572
sub_10:Test (Best Model) - Loss: 1.2654 - Accuracy: 0.4714 - F1: 0.4523
sub_4:Test (Best Model) - Loss: 1.4053 - Accuracy: 0.4238 - F1: 0.3810
sub_6:Test (Best Model) - Loss: 1.4670 - Accuracy: 0.2857 - F1: 0.3024
sub_12:Test (Best Model) - Loss: 1.7852 - Accuracy: 0.3143 - F1: 0.2469
sub_2:Test (Best Model) - Loss: 1.2223 - Accuracy: 0.4381 - F1: 0.4092
sub_8:Test (Best Model) - Loss: 1.3086 - Accuracy: 0.4476 - F1: 0.4100
sub_9:Test (Best Model) - Loss: 1.4505 - Accuracy: 0.3810 - F1: 0.3178
sub_13:Test (Best Model) - Loss: 1.2921 - Accuracy: 0.4429 - F1: 0.3809
sub_14:Test (Best Model) - Loss: 1.1867 - Accuracy: 0.5000 - F1: 0.4388
sub_3:Test (Best Model) - Loss: 1.5810 - Accuracy: 0.2476 - F1: 0.2026
sub_7:Test (Best Model) - Loss: 1.4273 - Accuracy: 0.3762 - F1: 0.3131
sub_10:Test (Best Model) - Loss: 1.3918 - Accuracy: 0.3714 - F1: 0.3251
sub_11:Test (Best Model) - Loss: 1.1824 - Accuracy: 0.4476 - F1: 0.4392
sub_4:Test (Best Model) - Loss: 1.3434 - Accuracy: 0.4048 - F1: 0.3425
sub_12:Test (Best Model) - Loss: 1.5366 - Accuracy: 0.3667 - F1: 0.3125
sub_13:Test (Best Model) - Loss: 1.4566 - Accuracy: 0.3619 - F1: 0.2891
sub_5:Test (Best Model) - Loss: 1.3306 - Accuracy: 0.4667 - F1: 0.4091
sub_1:Test (Best Model) - Loss: 1.2560 - Accuracy: 0.4143 - F1: 0.3402
sub_9:Test (Best Model) - Loss: 1.3473 - Accuracy: 0.4095 - F1: 0.3067
sub_8:Test (Best Model) - Loss: 1.2420 - Accuracy: 0.4619 - F1: 0.4127
sub_6:Test (Best Model) - Loss: 1.3527 - Accuracy: 0.3667 - F1: 0.3243
sub_11:Test (Best Model) - Loss: 1.3048 - Accuracy: 0.4619 - F1: 0.4040
sub_10:Test (Best Model) - Loss: 1.3907 - Accuracy: 0.4048 - F1: 0.3380
sub_14:Test (Best Model) - Loss: 1.3665 - Accuracy: 0.4429 - F1: 0.3632
sub_7:Test (Best Model) - Loss: 1.5734 - Accuracy: 0.3190 - F1: 0.2846
sub_3:Test (Best Model) - Loss: 1.4746 - Accuracy: 0.3143 - F1: 0.2930
sub_2:Test (Best Model) - Loss: 1.2150 - Accuracy: 0.4333 - F1: 0.3691
sub_12:Test (Best Model) - Loss: 1.4348 - Accuracy: 0.4000 - F1: 0.3038
sub_13:Test (Best Model) - Loss: 1.4848 - Accuracy: 0.3429 - F1: 0.2777
sub_4:Test (Best Model) - Loss: 1.2914 - Accuracy: 0.4619 - F1: 0.4616
sub_1:Test (Best Model) - Loss: 1.2508 - Accuracy: 0.3952 - F1: 0.3710
sub_11:Test (Best Model) - Loss: 1.2795 - Accuracy: 0.4810 - F1: 0.4165
sub_9:Test (Best Model) - Loss: 1.4449 - Accuracy: 0.4190 - F1: 0.3104
sub_6:Test (Best Model) - Loss: 1.5008 - Accuracy: 0.3381 - F1: 0.2433
sub_5:Test (Best Model) - Loss: 1.3157 - Accuracy: 0.4571 - F1: 0.3782
sub_14:Test (Best Model) - Loss: 1.1400 - Accuracy: 0.5333 - F1: 0.4802
sub_8:Test (Best Model) - Loss: 1.2610 - Accuracy: 0.4048 - F1: 0.3762
sub_10:Test (Best Model) - Loss: 1.3270 - Accuracy: 0.3857 - F1: 0.2977
sub_7:Test (Best Model) - Loss: 1.5242 - Accuracy: 0.3095 - F1: 0.2802
sub_3:Test (Best Model) - Loss: 1.4910 - Accuracy: 0.3095 - F1: 0.2864
sub_9:Test (Best Model) - Loss: 1.4334 - Accuracy: 0.3571 - F1: 0.2905
sub_1:Test (Best Model) - Loss: 1.3029 - Accuracy: 0.4286 - F1: 0.4128
sub_13:Test (Best Model) - Loss: 1.3458 - Accuracy: 0.4571 - F1: 0.3849
sub_11:Test (Best Model) - Loss: 1.3464 - Accuracy: 0.4286 - F1: 0.3919
sub_2:Test (Best Model) - Loss: 1.3010 - Accuracy: 0.4476 - F1: 0.3955
sub_6:Test (Best Model) - Loss: 1.4514 - Accuracy: 0.3571 - F1: 0.3273
sub_12:Test (Best Model) - Loss: 1.3335 - Accuracy: 0.4048 - F1: 0.3776
sub_7:Test (Best Model) - Loss: 1.5352 - Accuracy: 0.3286 - F1: 0.2379
sub_9:Test (Best Model) - Loss: 1.3743 - Accuracy: 0.3571 - F1: 0.3736
sub_10:Test (Best Model) - Loss: 1.5607 - Accuracy: 0.3238 - F1: 0.2590
sub_11:Test (Best Model) - Loss: 1.3639 - Accuracy: 0.3905 - F1: 0.3485
sub_4:Test (Best Model) - Loss: 1.2037 - Accuracy: 0.4333 - F1: 0.3996
sub_5:Test (Best Model) - Loss: 1.3759 - Accuracy: 0.4667 - F1: 0.3759
sub_8:Test (Best Model) - Loss: 1.2031 - Accuracy: 0.3952 - F1: 0.3104
sub_2:Test (Best Model) - Loss: 1.2465 - Accuracy: 0.4143 - F1: 0.3865
sub_3:Test (Best Model) - Loss: 1.4588 - Accuracy: 0.3524 - F1: 0.3231
sub_1:Test (Best Model) - Loss: 1.1975 - Accuracy: 0.5000 - F1: 0.4684
sub_13:Test (Best Model) - Loss: 1.4654 - Accuracy: 0.4286 - F1: 0.3343
sub_6:Test (Best Model) - Loss: 1.5202 - Accuracy: 0.3952 - F1: 0.3216
sub_12:Test (Best Model) - Loss: 1.2932 - Accuracy: 0.4429 - F1: 0.4019
sub_10:Test (Best Model) - Loss: 1.5275 - Accuracy: 0.3429 - F1: 0.2964
sub_4:Test (Best Model) - Loss: 1.3973 - Accuracy: 0.4238 - F1: 0.3667
sub_14:Test (Best Model) - Loss: 1.1426 - Accuracy: 0.5190 - F1: 0.4575
sub_8:Test (Best Model) - Loss: 1.3006 - Accuracy: 0.4095 - F1: 0.4078
sub_5:Test (Best Model) - Loss: 1.4481 - Accuracy: 0.3619 - F1: 0.3022
sub_11:Test (Best Model) - Loss: 1.2793 - Accuracy: 0.4190 - F1: 0.3978
sub_3:Test (Best Model) - Loss: 1.4151 - Accuracy: 0.4095 - F1: 0.3777
sub_13:Test (Best Model) - Loss: 1.4206 - Accuracy: 0.3905 - F1: 0.3190
sub_6:Test (Best Model) - Loss: 1.5161 - Accuracy: 0.3048 - F1: 0.2279
sub_9:Test (Best Model) - Loss: 1.2976 - Accuracy: 0.4048 - F1: 0.3776
sub_7:Test (Best Model) - Loss: 1.4297 - Accuracy: 0.3714 - F1: 0.3083
sub_12:Test (Best Model) - Loss: 1.3274 - Accuracy: 0.3571 - F1: 0.3262
sub_1:Test (Best Model) - Loss: 1.2229 - Accuracy: 0.4619 - F1: 0.4264
sub_13:Test (Best Model) - Loss: 1.3270 - Accuracy: 0.4095 - F1: 0.3356
sub_8:Test (Best Model) - Loss: 1.3519 - Accuracy: 0.4238 - F1: 0.3780
sub_11:Test (Best Model) - Loss: 1.2846 - Accuracy: 0.5238 - F1: 0.4675
sub_14:Test (Best Model) - Loss: 1.8954 - Accuracy: 0.2619 - F1: 0.1628
sub_4:Test (Best Model) - Loss: 1.4273 - Accuracy: 0.4238 - F1: 0.4081
sub_2:Test (Best Model) - Loss: 1.0553 - Accuracy: 0.4667 - F1: 0.4702
sub_5:Test (Best Model) - Loss: 1.5119 - Accuracy: 0.2905 - F1: 0.2548
sub_10:Test (Best Model) - Loss: 1.4141 - Accuracy: 0.3476 - F1: 0.2910
sub_9:Test (Best Model) - Loss: 1.3042 - Accuracy: 0.4381 - F1: 0.3994
sub_12:Test (Best Model) - Loss: 1.4386 - Accuracy: 0.3762 - F1: 0.2807
sub_1:Test (Best Model) - Loss: 1.2558 - Accuracy: 0.4762 - F1: 0.4670
sub_8:Test (Best Model) - Loss: 1.3193 - Accuracy: 0.4333 - F1: 0.4316
sub_7:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.3429 - F1: 0.3124
sub_9:Test (Best Model) - Loss: 1.3312 - Accuracy: 0.4381 - F1: 0.4259
sub_6:Test (Best Model) - Loss: 1.3687 - Accuracy: 0.4238 - F1: 0.4115
sub_5:Test (Best Model) - Loss: 1.4420 - Accuracy: 0.3190 - F1: 0.2922
sub_14:Test (Best Model) - Loss: 1.7665 - Accuracy: 0.3095 - F1: 0.2379
sub_1:Test (Best Model) - Loss: 1.3264 - Accuracy: 0.4333 - F1: 0.3970
sub_13:Test (Best Model) - Loss: 1.2979 - Accuracy: 0.4381 - F1: 0.3549
sub_10:Test (Best Model) - Loss: 1.5953 - Accuracy: 0.3619 - F1: 0.2834
sub_4:Test (Best Model) - Loss: 1.3383 - Accuracy: 0.4905 - F1: 0.4766
sub_2:Test (Best Model) - Loss: 1.1801 - Accuracy: 0.4381 - F1: 0.4191
sub_12:Test (Best Model) - Loss: 1.3355 - Accuracy: 0.3810 - F1: 0.2924
sub_7:Test (Best Model) - Loss: 1.3735 - Accuracy: 0.3857 - F1: 0.3818
sub_5:Test (Best Model) - Loss: 1.2452 - Accuracy: 0.4429 - F1: 0.4514
sub_14:Test (Best Model) - Loss: 2.4560 - Accuracy: 0.2952 - F1: 0.2310
sub_2:Test (Best Model) - Loss: 1.3151 - Accuracy: 0.4524 - F1: 0.4245
sub_4:Test (Best Model) - Loss: 1.3709 - Accuracy: 0.3667 - F1: 0.3565
sub_1:Test (Best Model) - Loss: 1.2477 - Accuracy: 0.5048 - F1: 0.4578
sub_5:Test (Best Model) - Loss: 1.3337 - Accuracy: 0.4381 - F1: 0.4253
sub_1:Test (Best Model) - Loss: 1.2887 - Accuracy: 0.4714 - F1: 0.4600
sub_4:Test (Best Model) - Loss: 1.3573 - Accuracy: 0.4048 - F1: 0.3322
sub_14:Test (Best Model) - Loss: 2.0288 - Accuracy: 0.3000 - F1: 0.2293
sub_14:Test (Best Model) - Loss: 1.7073 - Accuracy: 0.2905 - F1: 0.2077

=== Summary Results ===

acc: 38.87 ± 2.98
F1: 33.20 ± 3.41
acc-in: 47.05 ± 3.62
F1-in: 42.76 ± 3.75
