lr: 0.0001
sub_8:Test (Best Model) - Loss: 1.1528 - Accuracy: 0.4857 - F1: 0.4291
sub_12:Test (Best Model) - Loss: 1.4073 - Accuracy: 0.3857 - F1: 0.3383
sub_11:Test (Best Model) - Loss: 1.3058 - Accuracy: 0.4714 - F1: 0.4430
sub_9:Test (Best Model) - Loss: 1.1598 - Accuracy: 0.4143 - F1: 0.3480
sub_2:Test (Best Model) - Loss: 3.1650 - Accuracy: 0.4333 - F1: 0.3823
sub_14:Test (Best Model) - Loss: 1.6235 - Accuracy: 0.4571 - F1: 0.4609
sub_8:Test (Best Model) - Loss: 1.1122 - Accuracy: 0.5048 - F1: 0.4658
sub_10:Test (Best Model) - Loss: 1.9252 - Accuracy: 0.4095 - F1: 0.3197
sub_4:Test (Best Model) - Loss: 3.8732 - Accuracy: 0.3905 - F1: 0.3057
sub_8:Test (Best Model) - Loss: 1.2592 - Accuracy: 0.4619 - F1: 0.4150
sub_12:Test (Best Model) - Loss: 2.9201 - Accuracy: 0.4524 - F1: 0.3855
sub_6:Test (Best Model) - Loss: 4.2476 - Accuracy: 0.3857 - F1: 0.3206
sub_7:Test (Best Model) - Loss: 3.2710 - Accuracy: 0.2714 - F1: 0.2250
sub_2:Test (Best Model) - Loss: 3.0663 - Accuracy: 0.4333 - F1: 0.3451
sub_5:Test (Best Model) - Loss: 5.5705 - Accuracy: 0.3000 - F1: 0.2121
sub_14:Test (Best Model) - Loss: 2.0329 - Accuracy: 0.4667 - F1: 0.4078
sub_10:Test (Best Model) - Loss: 2.8537 - Accuracy: 0.4667 - F1: 0.4107
sub_13:Test (Best Model) - Loss: 3.4074 - Accuracy: 0.3143 - F1: 0.1956
sub_1:Test (Best Model) - Loss: 4.4569 - Accuracy: 0.4095 - F1: 0.2692
sub_12:Test (Best Model) - Loss: 1.4627 - Accuracy: 0.4571 - F1: 0.3876
sub_4:Test (Best Model) - Loss: 3.0958 - Accuracy: 0.4381 - F1: 0.3864
sub_3:Test (Best Model) - Loss: 6.9567 - Accuracy: 0.2048 - F1: 0.0765
sub_8:Test (Best Model) - Loss: 1.8974 - Accuracy: 0.5000 - F1: 0.4578
sub_9:Test (Best Model) - Loss: 4.3364 - Accuracy: 0.3762 - F1: 0.3262
sub_5:Test (Best Model) - Loss: 4.7350 - Accuracy: 0.3143 - F1: 0.2377
sub_4:Test (Best Model) - Loss: 1.9115 - Accuracy: 0.4381 - F1: 0.3749
sub_10:Test (Best Model) - Loss: 1.9017 - Accuracy: 0.4714 - F1: 0.3835
sub_8:Test (Best Model) - Loss: 1.2547 - Accuracy: 0.4571 - F1: 0.4142
sub_12:Test (Best Model) - Loss: 1.5501 - Accuracy: 0.4762 - F1: 0.4216
sub_14:Test (Best Model) - Loss: 1.6441 - Accuracy: 0.5286 - F1: 0.5196
sub_11:Test (Best Model) - Loss: 1.4381 - Accuracy: 0.5714 - F1: 0.5595
sub_6:Test (Best Model) - Loss: 4.4929 - Accuracy: 0.3905 - F1: 0.2934
sub_2:Test (Best Model) - Loss: 5.2839 - Accuracy: 0.3667 - F1: 0.2794
sub_8:Test (Best Model) - Loss: 1.1151 - Accuracy: 0.4810 - F1: 0.4546
sub_1:Test (Best Model) - Loss: 3.7977 - Accuracy: 0.3286 - F1: 0.2587
sub_13:Test (Best Model) - Loss: 4.6590 - Accuracy: 0.2762 - F1: 0.1577
sub_10:Test (Best Model) - Loss: 1.9039 - Accuracy: 0.5048 - F1: 0.4290
sub_12:Test (Best Model) - Loss: 2.3657 - Accuracy: 0.4381 - F1: 0.4210
sub_14:Test (Best Model) - Loss: 2.0228 - Accuracy: 0.4619 - F1: 0.4553
sub_4:Test (Best Model) - Loss: 2.3456 - Accuracy: 0.4667 - F1: 0.4121
sub_5:Test (Best Model) - Loss: 4.9289 - Accuracy: 0.3095 - F1: 0.2369
sub_7:Test (Best Model) - Loss: 3.1233 - Accuracy: 0.2810 - F1: 0.2563
sub_2:Test (Best Model) - Loss: 6.1034 - Accuracy: 0.3333 - F1: 0.2429
sub_3:Test (Best Model) - Loss: 2.2733 - Accuracy: 0.3714 - F1: 0.2772
sub_8:Test (Best Model) - Loss: 1.7445 - Accuracy: 0.4952 - F1: 0.4622
sub_11:Test (Best Model) - Loss: 2.0649 - Accuracy: 0.4524 - F1: 0.3730
sub_14:Test (Best Model) - Loss: 1.5116 - Accuracy: 0.4000 - F1: 0.4120
sub_9:Test (Best Model) - Loss: 3.7127 - Accuracy: 0.4524 - F1: 0.3536
sub_6:Test (Best Model) - Loss: 5.2082 - Accuracy: 0.4095 - F1: 0.3392
sub_10:Test (Best Model) - Loss: 1.8471 - Accuracy: 0.4810 - F1: 0.4266
sub_12:Test (Best Model) - Loss: 3.9550 - Accuracy: 0.3952 - F1: 0.3316
sub_1:Test (Best Model) - Loss: 3.6169 - Accuracy: 0.4048 - F1: 0.3003
sub_4:Test (Best Model) - Loss: 3.4781 - Accuracy: 0.4238 - F1: 0.3302
sub_5:Test (Best Model) - Loss: 5.5851 - Accuracy: 0.3143 - F1: 0.2125
sub_2:Test (Best Model) - Loss: 4.3296 - Accuracy: 0.3619 - F1: 0.2682
sub_3:Test (Best Model) - Loss: 2.3983 - Accuracy: 0.2952 - F1: 0.2241
sub_8:Test (Best Model) - Loss: 2.7667 - Accuracy: 0.5000 - F1: 0.4777
sub_10:Test (Best Model) - Loss: 2.0297 - Accuracy: 0.4667 - F1: 0.4455
sub_13:Test (Best Model) - Loss: 6.0491 - Accuracy: 0.3333 - F1: 0.2026
sub_4:Test (Best Model) - Loss: 2.1125 - Accuracy: 0.4238 - F1: 0.3571
sub_14:Test (Best Model) - Loss: 1.5065 - Accuracy: 0.5476 - F1: 0.5359
sub_12:Test (Best Model) - Loss: 5.1971 - Accuracy: 0.3667 - F1: 0.3065
sub_11:Test (Best Model) - Loss: 1.8804 - Accuracy: 0.4810 - F1: 0.4362
sub_9:Test (Best Model) - Loss: 2.5496 - Accuracy: 0.4000 - F1: 0.3420
sub_7:Test (Best Model) - Loss: 3.6524 - Accuracy: 0.2810 - F1: 0.2235
sub_1:Test (Best Model) - Loss: 4.3665 - Accuracy: 0.3952 - F1: 0.2783
sub_6:Test (Best Model) - Loss: 2.3102 - Accuracy: 0.4000 - F1: 0.3272
sub_2:Test (Best Model) - Loss: 1.7004 - Accuracy: 0.5048 - F1: 0.4990
sub_3:Test (Best Model) - Loss: 4.5533 - Accuracy: 0.2190 - F1: 0.0985
sub_5:Test (Best Model) - Loss: 6.3099 - Accuracy: 0.2762 - F1: 0.1908
sub_8:Test (Best Model) - Loss: 1.5667 - Accuracy: 0.5000 - F1: 0.4736
sub_6:Test (Best Model) - Loss: 1.4131 - Accuracy: 0.3857 - F1: 0.3091
sub_11:Test (Best Model) - Loss: 2.3062 - Accuracy: 0.4524 - F1: 0.3861
sub_3:Test (Best Model) - Loss: 4.0941 - Accuracy: 0.2333 - F1: 0.1161
sub_14:Test (Best Model) - Loss: 2.1108 - Accuracy: 0.5667 - F1: 0.4846
sub_8:Test (Best Model) - Loss: 1.1485 - Accuracy: 0.5048 - F1: 0.4432
sub_4:Test (Best Model) - Loss: 1.3338 - Accuracy: 0.4905 - F1: 0.4971
sub_10:Test (Best Model) - Loss: 1.7718 - Accuracy: 0.4524 - F1: 0.4221
sub_7:Test (Best Model) - Loss: 1.9146 - Accuracy: 0.3286 - F1: 0.3274
sub_12:Test (Best Model) - Loss: 6.2223 - Accuracy: 0.3476 - F1: 0.2850
sub_1:Test (Best Model) - Loss: 3.6473 - Accuracy: 0.3190 - F1: 0.2171
sub_2:Test (Best Model) - Loss: 1.8894 - Accuracy: 0.4857 - F1: 0.4424
sub_6:Test (Best Model) - Loss: 2.4094 - Accuracy: 0.4238 - F1: 0.4339
sub_10:Test (Best Model) - Loss: 1.4124 - Accuracy: 0.4714 - F1: 0.4367
sub_9:Test (Best Model) - Loss: 1.9319 - Accuracy: 0.5000 - F1: 0.4979
sub_13:Test (Best Model) - Loss: 3.2466 - Accuracy: 0.3619 - F1: 0.2932
sub_4:Test (Best Model) - Loss: 1.7564 - Accuracy: 0.4524 - F1: 0.4396
sub_8:Test (Best Model) - Loss: 1.7981 - Accuracy: 0.4286 - F1: 0.4039
sub_14:Test (Best Model) - Loss: 1.5550 - Accuracy: 0.5571 - F1: 0.4666
sub_3:Test (Best Model) - Loss: 1.1870 - Accuracy: 0.4429 - F1: 0.3945
sub_12:Test (Best Model) - Loss: 4.4440 - Accuracy: 0.3524 - F1: 0.3004
sub_11:Test (Best Model) - Loss: 2.7626 - Accuracy: 0.4762 - F1: 0.4351
sub_5:Test (Best Model) - Loss: 3.2601 - Accuracy: 0.4619 - F1: 0.3912
sub_10:Test (Best Model) - Loss: 1.5797 - Accuracy: 0.4524 - F1: 0.4303
sub_2:Test (Best Model) - Loss: 1.5614 - Accuracy: 0.5381 - F1: 0.5444
sub_6:Test (Best Model) - Loss: 1.4171 - Accuracy: 0.4238 - F1: 0.4265
sub_4:Test (Best Model) - Loss: 2.5186 - Accuracy: 0.4905 - F1: 0.4910
sub_12:Test (Best Model) - Loss: 4.3886 - Accuracy: 0.3476 - F1: 0.2943
sub_14:Test (Best Model) - Loss: 2.2748 - Accuracy: 0.5905 - F1: 0.5321
sub_8:Test (Best Model) - Loss: 1.8065 - Accuracy: 0.4619 - F1: 0.4441
sub_9:Test (Best Model) - Loss: 4.6333 - Accuracy: 0.3095 - F1: 0.2340
sub_7:Test (Best Model) - Loss: 3.4904 - Accuracy: 0.2952 - F1: 0.2897
sub_2:Test (Best Model) - Loss: 2.4051 - Accuracy: 0.4190 - F1: 0.3918
sub_13:Test (Best Model) - Loss: 5.5077 - Accuracy: 0.2857 - F1: 0.1577
sub_10:Test (Best Model) - Loss: 1.8638 - Accuracy: 0.4524 - F1: 0.4206
sub_1:Test (Best Model) - Loss: 2.8411 - Accuracy: 0.4095 - F1: 0.3614
sub_5:Test (Best Model) - Loss: 2.4890 - Accuracy: 0.4952 - F1: 0.4641
sub_4:Test (Best Model) - Loss: 1.3420 - Accuracy: 0.4619 - F1: 0.4644
sub_12:Test (Best Model) - Loss: 2.4308 - Accuracy: 0.3667 - F1: 0.3296
sub_3:Test (Best Model) - Loss: 1.2141 - Accuracy: 0.3857 - F1: 0.3716
sub_8:Test (Best Model) - Loss: 3.5108 - Accuracy: 0.4429 - F1: 0.4200
sub_14:Test (Best Model) - Loss: 1.3755 - Accuracy: 0.5571 - F1: 0.5073
sub_11:Test (Best Model) - Loss: 2.1434 - Accuracy: 0.4952 - F1: 0.4645
sub_6:Test (Best Model) - Loss: 4.5458 - Accuracy: 0.3667 - F1: 0.3604
sub_2:Test (Best Model) - Loss: 1.9362 - Accuracy: 0.4571 - F1: 0.4495
sub_9:Test (Best Model) - Loss: 3.2844 - Accuracy: 0.3714 - F1: 0.3205
sub_10:Test (Best Model) - Loss: 4.6423 - Accuracy: 0.3095 - F1: 0.2176
sub_4:Test (Best Model) - Loss: 2.9393 - Accuracy: 0.4571 - F1: 0.3716
sub_12:Test (Best Model) - Loss: 3.5479 - Accuracy: 0.3619 - F1: 0.3021
sub_14:Test (Best Model) - Loss: 5.0819 - Accuracy: 0.2810 - F1: 0.2059
sub_5:Test (Best Model) - Loss: 2.9455 - Accuracy: 0.4429 - F1: 0.3739
sub_13:Test (Best Model) - Loss: 3.2757 - Accuracy: 0.4095 - F1: 0.3570
sub_2:Test (Best Model) - Loss: 3.8097 - Accuracy: 0.3714 - F1: 0.3685
sub_6:Test (Best Model) - Loss: 1.4211 - Accuracy: 0.3714 - F1: 0.3676
sub_7:Test (Best Model) - Loss: 4.0352 - Accuracy: 0.3762 - F1: 0.2592
sub_8:Test (Best Model) - Loss: 3.1425 - Accuracy: 0.4905 - F1: 0.4547
sub_4:Test (Best Model) - Loss: 1.5932 - Accuracy: 0.4667 - F1: 0.4230
sub_10:Test (Best Model) - Loss: 4.0091 - Accuracy: 0.3190 - F1: 0.2435
sub_3:Test (Best Model) - Loss: 1.2260 - Accuracy: 0.3524 - F1: 0.3290
sub_14:Test (Best Model) - Loss: 4.6272 - Accuracy: 0.3286 - F1: 0.2678
sub_11:Test (Best Model) - Loss: 3.1652 - Accuracy: 0.4619 - F1: 0.4040
sub_8:Test (Best Model) - Loss: 1.7271 - Accuracy: 0.4048 - F1: 0.3737
sub_1:Test (Best Model) - Loss: 4.2173 - Accuracy: 0.3714 - F1: 0.3476
sub_4:Test (Best Model) - Loss: 1.4525 - Accuracy: 0.4762 - F1: 0.4241
sub_6:Test (Best Model) - Loss: 1.7859 - Accuracy: 0.3952 - F1: 0.3813
sub_12:Test (Best Model) - Loss: 5.9738 - Accuracy: 0.3143 - F1: 0.2305
sub_2:Test (Best Model) - Loss: 3.3631 - Accuracy: 0.3333 - F1: 0.3463
sub_10:Test (Best Model) - Loss: 3.5748 - Accuracy: 0.3000 - F1: 0.2094
sub_9:Test (Best Model) - Loss: 2.7603 - Accuracy: 0.3952 - F1: 0.3331
sub_13:Test (Best Model) - Loss: 2.0695 - Accuracy: 0.3762 - F1: 0.2950
sub_4:Test (Best Model) - Loss: 1.3719 - Accuracy: 0.4857 - F1: 0.4545
sub_5:Test (Best Model) - Loss: 3.6248 - Accuracy: 0.4238 - F1: 0.3907
sub_14:Test (Best Model) - Loss: 4.1208 - Accuracy: 0.4190 - F1: 0.3499
sub_3:Test (Best Model) - Loss: 1.9656 - Accuracy: 0.4238 - F1: 0.3451
sub_7:Test (Best Model) - Loss: 1.6416 - Accuracy: 0.3381 - F1: 0.3154
sub_12:Test (Best Model) - Loss: 2.3493 - Accuracy: 0.4429 - F1: 0.4005
sub_10:Test (Best Model) - Loss: 3.6087 - Accuracy: 0.3619 - F1: 0.2612
sub_4:Test (Best Model) - Loss: 1.5282 - Accuracy: 0.5000 - F1: 0.4862
sub_9:Test (Best Model) - Loss: 3.9257 - Accuracy: 0.3571 - F1: 0.3039
sub_6:Test (Best Model) - Loss: 4.0839 - Accuracy: 0.4429 - F1: 0.4256
sub_11:Test (Best Model) - Loss: 2.6369 - Accuracy: 0.4857 - F1: 0.4157
sub_1:Test (Best Model) - Loss: 2.4390 - Accuracy: 0.3857 - F1: 0.3515
sub_10:Test (Best Model) - Loss: 1.8978 - Accuracy: 0.3952 - F1: 0.2897
sub_2:Test (Best Model) - Loss: 1.7663 - Accuracy: 0.4619 - F1: 0.4692
sub_3:Test (Best Model) - Loss: 1.6221 - Accuracy: 0.4095 - F1: 0.3433
sub_13:Test (Best Model) - Loss: 3.3243 - Accuracy: 0.4048 - F1: 0.3476
sub_5:Test (Best Model) - Loss: 3.0737 - Accuracy: 0.4619 - F1: 0.3419
sub_11:Test (Best Model) - Loss: 1.3279 - Accuracy: 0.4333 - F1: 0.3970
sub_12:Test (Best Model) - Loss: 4.7363 - Accuracy: 0.3476 - F1: 0.2695
sub_14:Test (Best Model) - Loss: 5.3336 - Accuracy: 0.3000 - F1: 0.2350
sub_2:Test (Best Model) - Loss: 2.5435 - Accuracy: 0.3333 - F1: 0.3434
sub_1:Test (Best Model) - Loss: 1.5770 - Accuracy: 0.4667 - F1: 0.4768
sub_7:Test (Best Model) - Loss: 3.5200 - Accuracy: 0.3048 - F1: 0.2482
sub_9:Test (Best Model) - Loss: 3.5511 - Accuracy: 0.4095 - F1: 0.3133
sub_11:Test (Best Model) - Loss: 2.0458 - Accuracy: 0.4714 - F1: 0.4228
sub_6:Test (Best Model) - Loss: 3.8758 - Accuracy: 0.4571 - F1: 0.4221
sub_14:Test (Best Model) - Loss: 5.9572 - Accuracy: 0.2905 - F1: 0.2219
sub_1:Test (Best Model) - Loss: 1.0770 - Accuracy: 0.4762 - F1: 0.4843
sub_3:Test (Best Model) - Loss: 1.5954 - Accuracy: 0.3524 - F1: 0.3190
sub_13:Test (Best Model) - Loss: 1.8528 - Accuracy: 0.4048 - F1: 0.3454
sub_2:Test (Best Model) - Loss: 3.2607 - Accuracy: 0.3619 - F1: 0.3800
sub_6:Test (Best Model) - Loss: 2.7918 - Accuracy: 0.4190 - F1: 0.3856
sub_5:Test (Best Model) - Loss: 3.3440 - Accuracy: 0.3381 - F1: 0.3290
sub_3:Test (Best Model) - Loss: 1.5462 - Accuracy: 0.3333 - F1: 0.3473
sub_9:Test (Best Model) - Loss: 2.3881 - Accuracy: 0.4429 - F1: 0.3930
sub_7:Test (Best Model) - Loss: 2.8306 - Accuracy: 0.4095 - F1: 0.3442
sub_6:Test (Best Model) - Loss: 2.6041 - Accuracy: 0.4714 - F1: 0.4632
sub_13:Test (Best Model) - Loss: 2.7649 - Accuracy: 0.4000 - F1: 0.3365
sub_6:Test (Best Model) - Loss: 1.5824 - Accuracy: 0.4429 - F1: 0.4085
sub_11:Test (Best Model) - Loss: 3.7795 - Accuracy: 0.4381 - F1: 0.4174
sub_3:Test (Best Model) - Loss: 1.7931 - Accuracy: 0.3238 - F1: 0.3072
sub_13:Test (Best Model) - Loss: 2.4926 - Accuracy: 0.4000 - F1: 0.3258
sub_1:Test (Best Model) - Loss: 3.0495 - Accuracy: 0.5048 - F1: 0.4698
sub_5:Test (Best Model) - Loss: 3.1624 - Accuracy: 0.3905 - F1: 0.3903
sub_9:Test (Best Model) - Loss: 3.3346 - Accuracy: 0.3333 - F1: 0.2812
sub_7:Test (Best Model) - Loss: 4.8367 - Accuracy: 0.3143 - F1: 0.2157
sub_11:Test (Best Model) - Loss: 2.4228 - Accuracy: 0.3857 - F1: 0.3632
sub_9:Test (Best Model) - Loss: 1.2321 - Accuracy: 0.3762 - F1: 0.3005
sub_13:Test (Best Model) - Loss: 3.5785 - Accuracy: 0.3857 - F1: 0.3147
sub_1:Test (Best Model) - Loss: 2.7757 - Accuracy: 0.3905 - F1: 0.3677
sub_3:Test (Best Model) - Loss: 1.7164 - Accuracy: 0.3810 - F1: 0.3508
sub_5:Test (Best Model) - Loss: 4.5788 - Accuracy: 0.3429 - F1: 0.3207
sub_3:Test (Best Model) - Loss: 1.4437 - Accuracy: 0.3143 - F1: 0.2871
sub_7:Test (Best Model) - Loss: 3.9188 - Accuracy: 0.3333 - F1: 0.3085
sub_13:Test (Best Model) - Loss: 3.4317 - Accuracy: 0.4238 - F1: 0.3413
sub_5:Test (Best Model) - Loss: 2.5112 - Accuracy: 0.3429 - F1: 0.3621
sub_9:Test (Best Model) - Loss: 2.7752 - Accuracy: 0.4333 - F1: 0.3728
sub_1:Test (Best Model) - Loss: 4.7112 - Accuracy: 0.4095 - F1: 0.3642
sub_11:Test (Best Model) - Loss: 3.6222 - Accuracy: 0.4952 - F1: 0.4483
sub_1:Test (Best Model) - Loss: 2.1601 - Accuracy: 0.4667 - F1: 0.4106
sub_13:Test (Best Model) - Loss: 3.2335 - Accuracy: 0.4238 - F1: 0.3708
sub_7:Test (Best Model) - Loss: 4.6535 - Accuracy: 0.3571 - F1: 0.2749
sub_9:Test (Best Model) - Loss: 3.9185 - Accuracy: 0.3952 - F1: 0.3219
sub_5:Test (Best Model) - Loss: 3.2200 - Accuracy: 0.3810 - F1: 0.3668
sub_11:Test (Best Model) - Loss: 3.7819 - Accuracy: 0.4333 - F1: 0.3823
sub_13:Test (Best Model) - Loss: 2.1894 - Accuracy: 0.4048 - F1: 0.3607
sub_1:Test (Best Model) - Loss: 2.8342 - Accuracy: 0.4286 - F1: 0.3811
sub_7:Test (Best Model) - Loss: 3.3520 - Accuracy: 0.3810 - F1: 0.3058
sub_7:Test (Best Model) - Loss: 3.5891 - Accuracy: 0.2952 - F1: 0.2648
sub_7:Test (Best Model) - Loss: 1.3301 - Accuracy: 0.4143 - F1: 0.3916

=== Summary Results ===

acc: 40.78 ± 4.32
F1: 35.73 ± 5.04
acc-in: 58.06 ± 3.81
F1-in: 55.48 ± 4.09
