lr: 1e-05
sub_12:Test (Best Model) - Loss: 1.4028 - Accuracy: 0.3667 - F1: 0.3208
sub_4:Test (Best Model) - Loss: 1.7095 - Accuracy: 0.3571 - F1: 0.2667
sub_11:Test (Best Model) - Loss: 1.3619 - Accuracy: 0.4190 - F1: 0.3540
sub_8:Test (Best Model) - Loss: 1.2034 - Accuracy: 0.4381 - F1: 0.3953
sub_10:Test (Best Model) - Loss: 1.5556 - Accuracy: 0.3429 - F1: 0.2752
sub_3:Test (Best Model) - Loss: 1.6853 - Accuracy: 0.2952 - F1: 0.1994
sub_12:Test (Best Model) - Loss: 1.4216 - Accuracy: 0.3524 - F1: 0.3224
sub_5:Test (Best Model) - Loss: 1.8146 - Accuracy: 0.2333 - F1: 0.1562
sub_6:Test (Best Model) - Loss: 1.4714 - Accuracy: 0.3857 - F1: 0.3232
sub_14:Test (Best Model) - Loss: 1.2685 - Accuracy: 0.4667 - F1: 0.4400
sub_9:Test (Best Model) - Loss: 1.2714 - Accuracy: 0.4143 - F1: 0.3465
sub_1:Test (Best Model) - Loss: 1.9549 - Accuracy: 0.3286 - F1: 0.2572
sub_13:Test (Best Model) - Loss: 1.3648 - Accuracy: 0.3810 - F1: 0.3444
sub_2:Test (Best Model) - Loss: 2.6891 - Accuracy: 0.3810 - F1: 0.2703
sub_8:Test (Best Model) - Loss: 1.2667 - Accuracy: 0.4619 - F1: 0.4383
sub_10:Test (Best Model) - Loss: 1.4786 - Accuracy: 0.4000 - F1: 0.3249
sub_4:Test (Best Model) - Loss: 1.4278 - Accuracy: 0.3762 - F1: 0.3334
sub_7:Test (Best Model) - Loss: 1.4032 - Accuracy: 0.3381 - F1: 0.3340
sub_8:Test (Best Model) - Loss: 1.3024 - Accuracy: 0.4524 - F1: 0.4169
sub_3:Test (Best Model) - Loss: 1.2982 - Accuracy: 0.3952 - F1: 0.3496
sub_14:Test (Best Model) - Loss: 1.4909 - Accuracy: 0.4571 - F1: 0.4196
sub_2:Test (Best Model) - Loss: 1.8020 - Accuracy: 0.3238 - F1: 0.1968
sub_4:Test (Best Model) - Loss: 1.4121 - Accuracy: 0.4286 - F1: 0.3456
sub_6:Test (Best Model) - Loss: 1.4181 - Accuracy: 0.3952 - F1: 0.3439
sub_12:Test (Best Model) - Loss: 1.2120 - Accuracy: 0.4429 - F1: 0.3556
sub_10:Test (Best Model) - Loss: 1.5675 - Accuracy: 0.3333 - F1: 0.2325
sub_13:Test (Best Model) - Loss: 1.4634 - Accuracy: 0.3714 - F1: 0.2609
sub_5:Test (Best Model) - Loss: 1.5815 - Accuracy: 0.3095 - F1: 0.2406
sub_11:Test (Best Model) - Loss: 1.2865 - Accuracy: 0.4429 - F1: 0.4208
sub_7:Test (Best Model) - Loss: 1.5516 - Accuracy: 0.2762 - F1: 0.2380
sub_6:Test (Best Model) - Loss: 1.6080 - Accuracy: 0.3000 - F1: 0.2028
sub_8:Test (Best Model) - Loss: 1.1682 - Accuracy: 0.4619 - F1: 0.4119
sub_14:Test (Best Model) - Loss: 1.5256 - Accuracy: 0.3762 - F1: 0.2948
sub_2:Test (Best Model) - Loss: 1.9417 - Accuracy: 0.3143 - F1: 0.2002
sub_1:Test (Best Model) - Loss: 1.7916 - Accuracy: 0.3286 - F1: 0.2671
sub_4:Test (Best Model) - Loss: 1.3659 - Accuracy: 0.4667 - F1: 0.4129
sub_12:Test (Best Model) - Loss: 1.2792 - Accuracy: 0.3762 - F1: 0.3613
sub_10:Test (Best Model) - Loss: 1.5237 - Accuracy: 0.3524 - F1: 0.3012
sub_9:Test (Best Model) - Loss: 1.1733 - Accuracy: 0.4000 - F1: 0.3434
sub_3:Test (Best Model) - Loss: 1.4354 - Accuracy: 0.3381 - F1: 0.2404
sub_13:Test (Best Model) - Loss: 1.6572 - Accuracy: 0.2476 - F1: 0.1985
sub_2:Test (Best Model) - Loss: 1.6428 - Accuracy: 0.3429 - F1: 0.2758
sub_8:Test (Best Model) - Loss: 1.2139 - Accuracy: 0.4476 - F1: 0.3928
sub_4:Test (Best Model) - Loss: 1.3717 - Accuracy: 0.4143 - F1: 0.3359
sub_5:Test (Best Model) - Loss: 1.8067 - Accuracy: 0.2333 - F1: 0.1414
sub_7:Test (Best Model) - Loss: 1.6066 - Accuracy: 0.2857 - F1: 0.2127
sub_11:Test (Best Model) - Loss: 1.4845 - Accuracy: 0.4143 - F1: 0.3380
sub_6:Test (Best Model) - Loss: 1.3003 - Accuracy: 0.3429 - F1: 0.2952
sub_12:Test (Best Model) - Loss: 1.2655 - Accuracy: 0.4667 - F1: 0.4180
sub_2:Test (Best Model) - Loss: 1.8886 - Accuracy: 0.2952 - F1: 0.2018
sub_8:Test (Best Model) - Loss: 1.2000 - Accuracy: 0.4619 - F1: 0.4257
sub_14:Test (Best Model) - Loss: 1.2889 - Accuracy: 0.4714 - F1: 0.4237
sub_10:Test (Best Model) - Loss: 1.4503 - Accuracy: 0.3762 - F1: 0.2915
sub_1:Test (Best Model) - Loss: 2.0350 - Accuracy: 0.2667 - F1: 0.1608
sub_4:Test (Best Model) - Loss: 1.3103 - Accuracy: 0.4524 - F1: 0.3898
sub_2:Test (Best Model) - Loss: 1.4487 - Accuracy: 0.3381 - F1: 0.3148
sub_9:Test (Best Model) - Loss: 1.4343 - Accuracy: 0.4000 - F1: 0.2499
sub_12:Test (Best Model) - Loss: 1.6349 - Accuracy: 0.3048 - F1: 0.2220
sub_3:Test (Best Model) - Loss: 1.7638 - Accuracy: 0.3619 - F1: 0.2172
sub_8:Test (Best Model) - Loss: 1.1414 - Accuracy: 0.4476 - F1: 0.4109
sub_6:Test (Best Model) - Loss: 1.4017 - Accuracy: 0.4048 - F1: 0.3116
sub_10:Test (Best Model) - Loss: 1.3161 - Accuracy: 0.4476 - F1: 0.3727
sub_7:Test (Best Model) - Loss: 1.5087 - Accuracy: 0.3286 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 1.4641 - Accuracy: 0.4048 - F1: 0.3491
sub_11:Test (Best Model) - Loss: 1.3219 - Accuracy: 0.4476 - F1: 0.4141
sub_6:Test (Best Model) - Loss: 1.6271 - Accuracy: 0.3286 - F1: 0.3059
sub_14:Test (Best Model) - Loss: 1.3314 - Accuracy: 0.4333 - F1: 0.4034
sub_2:Test (Best Model) - Loss: 1.2344 - Accuracy: 0.4333 - F1: 0.4128
sub_12:Test (Best Model) - Loss: 1.5437 - Accuracy: 0.3238 - F1: 0.2294
sub_8:Test (Best Model) - Loss: 1.2406 - Accuracy: 0.4476 - F1: 0.4036
sub_5:Test (Best Model) - Loss: 2.7460 - Accuracy: 0.3286 - F1: 0.2420
sub_13:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.4238 - F1: 0.3346
sub_9:Test (Best Model) - Loss: 1.3269 - Accuracy: 0.3810 - F1: 0.2938
sub_12:Test (Best Model) - Loss: 1.4938 - Accuracy: 0.3667 - F1: 0.3108
sub_6:Test (Best Model) - Loss: 1.4746 - Accuracy: 0.3476 - F1: 0.3052
sub_8:Test (Best Model) - Loss: 1.2233 - Accuracy: 0.4143 - F1: 0.3898
sub_4:Test (Best Model) - Loss: 1.3938 - Accuracy: 0.4333 - F1: 0.3924
sub_10:Test (Best Model) - Loss: 1.2957 - Accuracy: 0.4048 - F1: 0.3175
sub_14:Test (Best Model) - Loss: 1.4641 - Accuracy: 0.3476 - F1: 0.3271
sub_3:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2190 - F1: 0.1033
sub_2:Test (Best Model) - Loss: 1.2513 - Accuracy: 0.4429 - F1: 0.4125
sub_7:Test (Best Model) - Loss: 1.4480 - Accuracy: 0.3476 - F1: 0.3137
sub_11:Test (Best Model) - Loss: 1.6036 - Accuracy: 0.3476 - F1: 0.2306
sub_1:Test (Best Model) - Loss: 2.1796 - Accuracy: 0.3667 - F1: 0.2753
sub_13:Test (Best Model) - Loss: 1.4724 - Accuracy: 0.3667 - F1: 0.2397
sub_8:Test (Best Model) - Loss: 1.2570 - Accuracy: 0.4429 - F1: 0.3743
sub_6:Test (Best Model) - Loss: 1.4033 - Accuracy: 0.4238 - F1: 0.3675
sub_10:Test (Best Model) - Loss: 1.2726 - Accuracy: 0.4190 - F1: 0.3922
sub_14:Test (Best Model) - Loss: 1.2892 - Accuracy: 0.4857 - F1: 0.4370
sub_12:Test (Best Model) - Loss: 1.6025 - Accuracy: 0.3048 - F1: 0.2260
sub_9:Test (Best Model) - Loss: 1.2780 - Accuracy: 0.4286 - F1: 0.3405
sub_5:Test (Best Model) - Loss: 2.0498 - Accuracy: 0.2667 - F1: 0.1587
sub_3:Test (Best Model) - Loss: 1.4175 - Accuracy: 0.3286 - F1: 0.2916
sub_4:Test (Best Model) - Loss: 1.4313 - Accuracy: 0.3857 - F1: 0.3615
sub_1:Test (Best Model) - Loss: 1.6632 - Accuracy: 0.2952 - F1: 0.1866
sub_2:Test (Best Model) - Loss: 1.4260 - Accuracy: 0.3524 - F1: 0.3267
sub_11:Test (Best Model) - Loss: 1.3554 - Accuracy: 0.4286 - F1: 0.3580
sub_12:Test (Best Model) - Loss: 1.3685 - Accuracy: 0.3667 - F1: 0.2937
sub_7:Test (Best Model) - Loss: 1.5622 - Accuracy: 0.3000 - F1: 0.2671
sub_10:Test (Best Model) - Loss: 1.2980 - Accuracy: 0.4143 - F1: 0.3940
sub_8:Test (Best Model) - Loss: 1.2446 - Accuracy: 0.4190 - F1: 0.3701
sub_13:Test (Best Model) - Loss: 1.4305 - Accuracy: 0.3810 - F1: 0.3650
sub_9:Test (Best Model) - Loss: 1.6899 - Accuracy: 0.3429 - F1: 0.2583
sub_5:Test (Best Model) - Loss: 1.4022 - Accuracy: 0.3571 - F1: 0.2820
sub_8:Test (Best Model) - Loss: 1.2551 - Accuracy: 0.4143 - F1: 0.3839
sub_3:Test (Best Model) - Loss: 1.3119 - Accuracy: 0.3333 - F1: 0.3228
sub_2:Test (Best Model) - Loss: 1.2894 - Accuracy: 0.3905 - F1: 0.3172
sub_6:Test (Best Model) - Loss: 1.4235 - Accuracy: 0.3524 - F1: 0.3455
sub_14:Test (Best Model) - Loss: 1.1362 - Accuracy: 0.5286 - F1: 0.4544
sub_4:Test (Best Model) - Loss: 1.2704 - Accuracy: 0.4143 - F1: 0.3951
sub_1:Test (Best Model) - Loss: 1.4701 - Accuracy: 0.3714 - F1: 0.2797
sub_11:Test (Best Model) - Loss: 1.1839 - Accuracy: 0.4667 - F1: 0.4109
sub_10:Test (Best Model) - Loss: 1.2758 - Accuracy: 0.4238 - F1: 0.3946
sub_9:Test (Best Model) - Loss: 1.5109 - Accuracy: 0.3571 - F1: 0.2930
sub_6:Test (Best Model) - Loss: 1.4556 - Accuracy: 0.3857 - F1: 0.3521
sub_12:Test (Best Model) - Loss: 1.3434 - Accuracy: 0.4143 - F1: 0.3796
sub_4:Test (Best Model) - Loss: 1.3629 - Accuracy: 0.4524 - F1: 0.4184
sub_8:Test (Best Model) - Loss: 1.2350 - Accuracy: 0.4333 - F1: 0.4091
sub_7:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.3476 - F1: 0.2890
sub_2:Test (Best Model) - Loss: 1.3140 - Accuracy: 0.4286 - F1: 0.3797
sub_14:Test (Best Model) - Loss: 1.2309 - Accuracy: 0.4857 - F1: 0.4522
sub_13:Test (Best Model) - Loss: 1.4410 - Accuracy: 0.3333 - F1: 0.2485
sub_11:Test (Best Model) - Loss: 1.2705 - Accuracy: 0.4571 - F1: 0.3708
sub_10:Test (Best Model) - Loss: 1.4955 - Accuracy: 0.3429 - F1: 0.2441
sub_8:Test (Best Model) - Loss: 1.3724 - Accuracy: 0.4048 - F1: 0.3842
sub_5:Test (Best Model) - Loss: 1.4537 - Accuracy: 0.3810 - F1: 0.2916
sub_3:Test (Best Model) - Loss: 1.2424 - Accuracy: 0.4048 - F1: 0.3771
sub_9:Test (Best Model) - Loss: 1.5815 - Accuracy: 0.3714 - F1: 0.3296
sub_4:Test (Best Model) - Loss: 1.4019 - Accuracy: 0.4333 - F1: 0.4251
sub_6:Test (Best Model) - Loss: 1.4259 - Accuracy: 0.3762 - F1: 0.3072
sub_2:Test (Best Model) - Loss: 1.3467 - Accuracy: 0.4095 - F1: 0.3727
sub_12:Test (Best Model) - Loss: 1.2775 - Accuracy: 0.4333 - F1: 0.3958
sub_1:Test (Best Model) - Loss: 1.3747 - Accuracy: 0.4190 - F1: 0.3624
sub_14:Test (Best Model) - Loss: 1.3462 - Accuracy: 0.4476 - F1: 0.3451
sub_10:Test (Best Model) - Loss: 1.5897 - Accuracy: 0.2857 - F1: 0.2431
sub_13:Test (Best Model) - Loss: 1.3968 - Accuracy: 0.3857 - F1: 0.3457
sub_12:Test (Best Model) - Loss: 1.3722 - Accuracy: 0.3429 - F1: 0.3075
sub_2:Test (Best Model) - Loss: 1.2414 - Accuracy: 0.3952 - F1: 0.3905
sub_10:Test (Best Model) - Loss: 1.6563 - Accuracy: 0.2571 - F1: 0.2354
sub_8:Test (Best Model) - Loss: 1.2874 - Accuracy: 0.4571 - F1: 0.4583
sub_4:Test (Best Model) - Loss: 1.2805 - Accuracy: 0.4667 - F1: 0.4323
sub_5:Test (Best Model) - Loss: 1.4154 - Accuracy: 0.3952 - F1: 0.3199
sub_9:Test (Best Model) - Loss: 1.4440 - Accuracy: 0.3857 - F1: 0.2956
sub_6:Test (Best Model) - Loss: 1.4318 - Accuracy: 0.2952 - F1: 0.2641
sub_14:Test (Best Model) - Loss: 2.8148 - Accuracy: 0.2429 - F1: 0.1396
sub_2:Test (Best Model) - Loss: 1.3425 - Accuracy: 0.4095 - F1: 0.3629
sub_13:Test (Best Model) - Loss: 1.4059 - Accuracy: 0.3762 - F1: 0.3539
sub_3:Test (Best Model) - Loss: 1.3900 - Accuracy: 0.4095 - F1: 0.3693
sub_7:Test (Best Model) - Loss: 1.3306 - Accuracy: 0.3429 - F1: 0.2937
sub_1:Test (Best Model) - Loss: 1.3310 - Accuracy: 0.3810 - F1: 0.3511
sub_4:Test (Best Model) - Loss: 1.3662 - Accuracy: 0.4238 - F1: 0.3969
sub_6:Test (Best Model) - Loss: 1.5202 - Accuracy: 0.4000 - F1: 0.3011
sub_12:Test (Best Model) - Loss: 1.3546 - Accuracy: 0.4048 - F1: 0.3293
sub_11:Test (Best Model) - Loss: 1.2047 - Accuracy: 0.4667 - F1: 0.4611
sub_5:Test (Best Model) - Loss: 1.4361 - Accuracy: 0.3619 - F1: 0.3140
sub_14:Test (Best Model) - Loss: 2.3499 - Accuracy: 0.2524 - F1: 0.1573
sub_2:Test (Best Model) - Loss: 1.2196 - Accuracy: 0.4714 - F1: 0.4549
sub_3:Test (Best Model) - Loss: 1.2829 - Accuracy: 0.4333 - F1: 0.4019
sub_13:Test (Best Model) - Loss: 1.4445 - Accuracy: 0.3524 - F1: 0.2814
sub_10:Test (Best Model) - Loss: 1.4423 - Accuracy: 0.3714 - F1: 0.3491
sub_6:Test (Best Model) - Loss: 1.5526 - Accuracy: 0.2667 - F1: 0.1900
sub_9:Test (Best Model) - Loss: 1.6487 - Accuracy: 0.3667 - F1: 0.2245
sub_4:Test (Best Model) - Loss: 1.2841 - Accuracy: 0.4619 - F1: 0.4141
sub_7:Test (Best Model) - Loss: 1.5063 - Accuracy: 0.3762 - F1: 0.3104
sub_3:Test (Best Model) - Loss: 1.5831 - Accuracy: 0.3000 - F1: 0.2605
sub_12:Test (Best Model) - Loss: 1.4089 - Accuracy: 0.3714 - F1: 0.3598
sub_6:Test (Best Model) - Loss: 1.5436 - Accuracy: 0.3524 - F1: 0.3039
sub_10:Test (Best Model) - Loss: 1.5171 - Accuracy: 0.3429 - F1: 0.2706
sub_14:Test (Best Model) - Loss: 2.8657 - Accuracy: 0.2476 - F1: 0.1565
sub_14:Test (Best Model) - Loss: 1.6732 - Accuracy: 0.2857 - F1: 0.2152
sub_5:Test (Best Model) - Loss: 1.4006 - Accuracy: 0.4238 - F1: 0.3626
sub_11:Test (Best Model) - Loss: 1.3233 - Accuracy: 0.3857 - F1: 0.3301
sub_1:Test (Best Model) - Loss: 1.3294 - Accuracy: 0.3810 - F1: 0.3882
sub_14:Test (Best Model) - Loss: 1.8002 - Accuracy: 0.2524 - F1: 0.1513
sub_7:Test (Best Model) - Loss: 1.5514 - Accuracy: 0.3619 - F1: 0.2730
sub_3:Test (Best Model) - Loss: 1.4756 - Accuracy: 0.3000 - F1: 0.2718
sub_13:Test (Best Model) - Loss: 1.3269 - Accuracy: 0.4476 - F1: 0.3391
sub_5:Test (Best Model) - Loss: 1.5294 - Accuracy: 0.3238 - F1: 0.2617
sub_9:Test (Best Model) - Loss: 1.2404 - Accuracy: 0.4619 - F1: 0.4065
sub_7:Test (Best Model) - Loss: 1.5439 - Accuracy: 0.2667 - F1: 0.2631
sub_11:Test (Best Model) - Loss: 1.3260 - Accuracy: 0.4095 - F1: 0.3408
sub_1:Test (Best Model) - Loss: 1.1720 - Accuracy: 0.4810 - F1: 0.4779
sub_5:Test (Best Model) - Loss: 1.4394 - Accuracy: 0.3286 - F1: 0.3154
sub_13:Test (Best Model) - Loss: 1.4528 - Accuracy: 0.4095 - F1: 0.3070
sub_3:Test (Best Model) - Loss: 1.4988 - Accuracy: 0.2714 - F1: 0.2420
sub_7:Test (Best Model) - Loss: 1.5289 - Accuracy: 0.3143 - F1: 0.2263
sub_9:Test (Best Model) - Loss: 1.3124 - Accuracy: 0.3667 - F1: 0.3135
sub_1:Test (Best Model) - Loss: 1.2519 - Accuracy: 0.4857 - F1: 0.4735
sub_11:Test (Best Model) - Loss: 1.3587 - Accuracy: 0.4190 - F1: 0.3796
sub_3:Test (Best Model) - Loss: 1.5174 - Accuracy: 0.2952 - F1: 0.2635
sub_7:Test (Best Model) - Loss: 1.5458 - Accuracy: 0.2810 - F1: 0.2252
sub_13:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.4095 - F1: 0.3057
sub_9:Test (Best Model) - Loss: 1.2625 - Accuracy: 0.3714 - F1: 0.3561
sub_5:Test (Best Model) - Loss: 1.3397 - Accuracy: 0.3810 - F1: 0.3666
sub_3:Test (Best Model) - Loss: 1.4231 - Accuracy: 0.3524 - F1: 0.3288
sub_1:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.4000 - F1: 0.3920
sub_9:Test (Best Model) - Loss: 1.2555 - Accuracy: 0.4619 - F1: 0.4287
sub_7:Test (Best Model) - Loss: 1.5147 - Accuracy: 0.3048 - F1: 0.2902
sub_11:Test (Best Model) - Loss: 1.3799 - Accuracy: 0.4286 - F1: 0.4184
sub_13:Test (Best Model) - Loss: 1.2818 - Accuracy: 0.4429 - F1: 0.3504
sub_5:Test (Best Model) - Loss: 1.3896 - Accuracy: 0.3762 - F1: 0.3745
sub_1:Test (Best Model) - Loss: 1.2725 - Accuracy: 0.4333 - F1: 0.4154
sub_9:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.3476 - F1: 0.3296
sub_13:Test (Best Model) - Loss: 1.3666 - Accuracy: 0.3667 - F1: 0.3095
sub_7:Test (Best Model) - Loss: 1.4856 - Accuracy: 0.3286 - F1: 0.2996
sub_5:Test (Best Model) - Loss: 1.4220 - Accuracy: 0.4333 - F1: 0.4255
sub_1:Test (Best Model) - Loss: 1.2894 - Accuracy: 0.4048 - F1: 0.3507
sub_11:Test (Best Model) - Loss: 1.3300 - Accuracy: 0.4571 - F1: 0.4023
sub_1:Test (Best Model) - Loss: 1.2116 - Accuracy: 0.4810 - F1: 0.4453
sub_11:Test (Best Model) - Loss: 1.2744 - Accuracy: 0.4619 - F1: 0.3977

=== Summary Results ===

acc: 38.00 ± 3.38
F1: 32.46 ± 3.68
acc-in: 46.62 ± 3.36
F1-in: 42.41 ± 3.00
