lr: 0.001
sub_4:Test (Best Model) - Loss: 1.3438 - Accuracy: 0.4238 - F1: 0.4067
sub_8:Test (Best Model) - Loss: 1.1675 - Accuracy: 0.4286 - F1: 0.4290
sub_2:Test (Best Model) - Loss: 1.5437 - Accuracy: 0.4000 - F1: 0.3593
sub_9:Test (Best Model) - Loss: 1.4936 - Accuracy: 0.3333 - F1: 0.2871
sub_7:Test (Best Model) - Loss: 3.0514 - Accuracy: 0.2095 - F1: 0.0986
sub_10:Test (Best Model) - Loss: 1.3322 - Accuracy: 0.3905 - F1: 0.3358
sub_1:Test (Best Model) - Loss: 2.2348 - Accuracy: 0.4286 - F1: 0.3456
sub_6:Test (Best Model) - Loss: 1.7196 - Accuracy: 0.3476 - F1: 0.3307
sub_5:Test (Best Model) - Loss: 3.1082 - Accuracy: 0.3333 - F1: 0.2907
sub_8:Test (Best Model) - Loss: 1.2718 - Accuracy: 0.4333 - F1: 0.4040
sub_3:Test (Best Model) - Loss: 1.3696 - Accuracy: 0.3619 - F1: 0.3185
sub_4:Test (Best Model) - Loss: 2.2292 - Accuracy: 0.2952 - F1: 0.2040
sub_1:Test (Best Model) - Loss: 2.6523 - Accuracy: 0.2429 - F1: 0.1489
sub_9:Test (Best Model) - Loss: 1.4925 - Accuracy: 0.4333 - F1: 0.4115
sub_10:Test (Best Model) - Loss: 1.5319 - Accuracy: 0.3762 - F1: 0.3484
sub_5:Test (Best Model) - Loss: 1.4609 - Accuracy: 0.3524 - F1: 0.3022
sub_6:Test (Best Model) - Loss: 4.3437 - Accuracy: 0.2333 - F1: 0.1298
sub_2:Test (Best Model) - Loss: 3.9965 - Accuracy: 0.2714 - F1: 0.1793
sub_9:Test (Best Model) - Loss: 1.1829 - Accuracy: 0.4000 - F1: 0.3235
sub_8:Test (Best Model) - Loss: 1.0980 - Accuracy: 0.4476 - F1: 0.3916
sub_10:Test (Best Model) - Loss: 1.3296 - Accuracy: 0.3905 - F1: 0.3552
sub_4:Test (Best Model) - Loss: 1.9864 - Accuracy: 0.3429 - F1: 0.2421
sub_7:Test (Best Model) - Loss: 2.2997 - Accuracy: 0.2286 - F1: 0.2196
sub_6:Test (Best Model) - Loss: 1.9212 - Accuracy: 0.2000 - F1: 0.0749
sub_1:Test (Best Model) - Loss: 1.5893 - Accuracy: 0.3952 - F1: 0.3021
sub_3:Test (Best Model) - Loss: 1.7614 - Accuracy: 0.2810 - F1: 0.2603
sub_5:Test (Best Model) - Loss: 2.0056 - Accuracy: 0.4048 - F1: 0.3803
sub_9:Test (Best Model) - Loss: 1.4392 - Accuracy: 0.3952 - F1: 0.3145
sub_3:Test (Best Model) - Loss: 1.2651 - Accuracy: 0.3286 - F1: 0.3149
sub_4:Test (Best Model) - Loss: 1.9150 - Accuracy: 0.3619 - F1: 0.2856
sub_10:Test (Best Model) - Loss: 2.9061 - Accuracy: 0.2905 - F1: 0.1987
sub_2:Test (Best Model) - Loss: 1.7689 - Accuracy: 0.3619 - F1: 0.3132
sub_8:Test (Best Model) - Loss: 2.4319 - Accuracy: 0.3857 - F1: 0.3037
sub_1:Test (Best Model) - Loss: 1.8994 - Accuracy: 0.3810 - F1: 0.3450
sub_5:Test (Best Model) - Loss: 1.3708 - Accuracy: 0.4095 - F1: 0.3808
sub_9:Test (Best Model) - Loss: 1.2486 - Accuracy: 0.4238 - F1: 0.3919
sub_4:Test (Best Model) - Loss: 10.8436 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 2.4073 - Accuracy: 0.2048 - F1: 0.1538
sub_10:Test (Best Model) - Loss: 1.4134 - Accuracy: 0.4000 - F1: 0.3760
sub_6:Test (Best Model) - Loss: 2.4308 - Accuracy: 0.2286 - F1: 0.1265
sub_8:Test (Best Model) - Loss: 1.5642 - Accuracy: 0.3095 - F1: 0.2703
sub_4:Test (Best Model) - Loss: 1.3194 - Accuracy: 0.4095 - F1: 0.3567
sub_3:Test (Best Model) - Loss: 2.2240 - Accuracy: 0.3381 - F1: 0.2799
sub_1:Test (Best Model) - Loss: 1.5319 - Accuracy: 0.4476 - F1: 0.3812
sub_2:Test (Best Model) - Loss: 1.5666 - Accuracy: 0.4000 - F1: 0.3644
sub_9:Test (Best Model) - Loss: 3.3520 - Accuracy: 0.3190 - F1: 0.2750
sub_5:Test (Best Model) - Loss: 2.6861 - Accuracy: 0.3381 - F1: 0.3029
sub_4:Test (Best Model) - Loss: 1.3388 - Accuracy: 0.4429 - F1: 0.4091
sub_7:Test (Best Model) - Loss: 2.5921 - Accuracy: 0.1905 - F1: 0.0931
sub_8:Test (Best Model) - Loss: 1.1139 - Accuracy: 0.4857 - F1: 0.4642
sub_6:Test (Best Model) - Loss: 8.9434 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.1977 - Accuracy: 0.4667 - F1: 0.4670
sub_1:Test (Best Model) - Loss: 1.8680 - Accuracy: 0.3619 - F1: 0.2656
sub_3:Test (Best Model) - Loss: 1.6051 - Accuracy: 0.3476 - F1: 0.2938
sub_9:Test (Best Model) - Loss: 1.5896 - Accuracy: 0.3524 - F1: 0.3295
sub_7:Test (Best Model) - Loss: 2.9779 - Accuracy: 0.1905 - F1: 0.1128
sub_8:Test (Best Model) - Loss: 1.1517 - Accuracy: 0.4619 - F1: 0.4304
sub_5:Test (Best Model) - Loss: 1.5833 - Accuracy: 0.3524 - F1: 0.3499
sub_4:Test (Best Model) - Loss: 1.6805 - Accuracy: 0.3810 - F1: 0.3511
sub_10:Test (Best Model) - Loss: 1.8039 - Accuracy: 0.3000 - F1: 0.2579
sub_1:Test (Best Model) - Loss: 1.1273 - Accuracy: 0.4667 - F1: 0.4689
sub_6:Test (Best Model) - Loss: 10.7290 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.4950 - Accuracy: 0.4810 - F1: 0.4528
sub_7:Test (Best Model) - Loss: 1.4465 - Accuracy: 0.3143 - F1: 0.2775
sub_9:Test (Best Model) - Loss: 1.7812 - Accuracy: 0.3381 - F1: 0.3250
sub_10:Test (Best Model) - Loss: 1.2549 - Accuracy: 0.4286 - F1: 0.4095
sub_8:Test (Best Model) - Loss: 1.1630 - Accuracy: 0.4190 - F1: 0.4045
sub_3:Test (Best Model) - Loss: 1.3663 - Accuracy: 0.3667 - F1: 0.3567
sub_5:Test (Best Model) - Loss: 1.9719 - Accuracy: 0.3238 - F1: 0.3315
sub_1:Test (Best Model) - Loss: 2.2317 - Accuracy: 0.2381 - F1: 0.1465
sub_2:Test (Best Model) - Loss: 1.4007 - Accuracy: 0.4048 - F1: 0.3869
sub_6:Test (Best Model) - Loss: 2.8371 - Accuracy: 0.3095 - F1: 0.2744
sub_7:Test (Best Model) - Loss: 1.6612 - Accuracy: 0.3190 - F1: 0.3042
sub_9:Test (Best Model) - Loss: 2.0964 - Accuracy: 0.3333 - F1: 0.2944
sub_4:Test (Best Model) - Loss: 1.8127 - Accuracy: 0.3905 - F1: 0.3387
sub_10:Test (Best Model) - Loss: 1.5193 - Accuracy: 0.4238 - F1: 0.4095
sub_3:Test (Best Model) - Loss: 1.2864 - Accuracy: 0.3619 - F1: 0.3512
sub_5:Test (Best Model) - Loss: 1.8075 - Accuracy: 0.3333 - F1: 0.3297
sub_1:Test (Best Model) - Loss: 1.3610 - Accuracy: 0.4333 - F1: 0.3951
sub_7:Test (Best Model) - Loss: 1.5028 - Accuracy: 0.3476 - F1: 0.2715
sub_8:Test (Best Model) - Loss: 1.2614 - Accuracy: 0.5000 - F1: 0.4844
sub_6:Test (Best Model) - Loss: 3.5175 - Accuracy: 0.2000 - F1: 0.0706
sub_2:Test (Best Model) - Loss: 1.9174 - Accuracy: 0.3333 - F1: 0.3130
sub_3:Test (Best Model) - Loss: 1.4486 - Accuracy: 0.3048 - F1: 0.2903
sub_4:Test (Best Model) - Loss: 1.6070 - Accuracy: 0.3429 - F1: 0.2823
sub_9:Test (Best Model) - Loss: 2.2862 - Accuracy: 0.3619 - F1: 0.3364
sub_10:Test (Best Model) - Loss: 1.3557 - Accuracy: 0.4524 - F1: 0.4372
sub_8:Test (Best Model) - Loss: 1.2294 - Accuracy: 0.4762 - F1: 0.4761
sub_10:Test (Best Model) - Loss: 2.2957 - Accuracy: 0.2000 - F1: 0.0672
sub_1:Test (Best Model) - Loss: 1.7494 - Accuracy: 0.3571 - F1: 0.2591
sub_4:Test (Best Model) - Loss: 1.5193 - Accuracy: 0.3524 - F1: 0.2742
sub_7:Test (Best Model) - Loss: 1.4231 - Accuracy: 0.3619 - F1: 0.3222
sub_5:Test (Best Model) - Loss: 2.1358 - Accuracy: 0.3429 - F1: 0.3445
sub_3:Test (Best Model) - Loss: 1.2930 - Accuracy: 0.4095 - F1: 0.3712
sub_2:Test (Best Model) - Loss: 1.5412 - Accuracy: 0.3810 - F1: 0.3623
sub_9:Test (Best Model) - Loss: 1.7929 - Accuracy: 0.3095 - F1: 0.2395
sub_6:Test (Best Model) - Loss: 5.4631 - Accuracy: 0.2286 - F1: 0.1182
sub_3:Test (Best Model) - Loss: 1.5179 - Accuracy: 0.2810 - F1: 0.2560
sub_4:Test (Best Model) - Loss: 1.6262 - Accuracy: 0.2619 - F1: 0.2499
sub_10:Test (Best Model) - Loss: 5.0304 - Accuracy: 0.2000 - F1: 0.0697
sub_8:Test (Best Model) - Loss: 1.4802 - Accuracy: 0.4333 - F1: 0.3859
sub_5:Test (Best Model) - Loss: 2.0188 - Accuracy: 0.2905 - F1: 0.2938
sub_2:Test (Best Model) - Loss: 1.6315 - Accuracy: 0.3381 - F1: 0.3098
sub_6:Test (Best Model) - Loss: 1.8911 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 3.5948 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.7293 - Accuracy: 0.2238 - F1: 0.1699
sub_1:Test (Best Model) - Loss: 9.0017 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.3671 - Accuracy: 0.4000 - F1: 0.3527
sub_8:Test (Best Model) - Loss: 1.7526 - Accuracy: 0.4524 - F1: 0.3950
sub_9:Test (Best Model) - Loss: 1.5305 - Accuracy: 0.3571 - F1: 0.3245
sub_4:Test (Best Model) - Loss: 4.5009 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.1626 - Accuracy: 0.4286 - F1: 0.4234
sub_5:Test (Best Model) - Loss: 2.4260 - Accuracy: 0.2143 - F1: 0.1972
sub_1:Test (Best Model) - Loss: 1.9864 - Accuracy: 0.3810 - F1: 0.2971
sub_10:Test (Best Model) - Loss: 2.3189 - Accuracy: 0.1952 - F1: 0.1102
sub_8:Test (Best Model) - Loss: 1.3975 - Accuracy: 0.3905 - F1: 0.3252
sub_7:Test (Best Model) - Loss: 2.6715 - Accuracy: 0.2905 - F1: 0.2606
sub_5:Test (Best Model) - Loss: 5.5171 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.8353 - Accuracy: 0.3524 - F1: 0.3618
sub_2:Test (Best Model) - Loss: 1.8648 - Accuracy: 0.3238 - F1: 0.3229
sub_6:Test (Best Model) - Loss: 2.8245 - Accuracy: 0.2714 - F1: 0.2481
sub_3:Test (Best Model) - Loss: 1.2551 - Accuracy: 0.3762 - F1: 0.3033
sub_1:Test (Best Model) - Loss: 1.6843 - Accuracy: 0.3333 - F1: 0.2406
sub_8:Test (Best Model) - Loss: 1.4605 - Accuracy: 0.3810 - F1: 0.3853
sub_5:Test (Best Model) - Loss: 3.8901 - Accuracy: 0.2048 - F1: 0.1823
sub_4:Test (Best Model) - Loss: 6.6706 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.8326 - Accuracy: 0.3857 - F1: 0.3808
sub_3:Test (Best Model) - Loss: 1.5475 - Accuracy: 0.3238 - F1: 0.2657
sub_10:Test (Best Model) - Loss: 1.7137 - Accuracy: 0.3429 - F1: 0.2895
sub_2:Test (Best Model) - Loss: 1.9640 - Accuracy: 0.3429 - F1: 0.3072
sub_7:Test (Best Model) - Loss: 1.5556 - Accuracy: 0.3286 - F1: 0.2708
sub_9:Test (Best Model) - Loss: 1.4086 - Accuracy: 0.3667 - F1: 0.3381
sub_6:Test (Best Model) - Loss: 3.5415 - Accuracy: 0.2048 - F1: 0.1677
sub_8:Test (Best Model) - Loss: 1.7345 - Accuracy: 0.3762 - F1: 0.2914
sub_5:Test (Best Model) - Loss: 1.8215 - Accuracy: 0.2381 - F1: 0.1479
sub_1:Test (Best Model) - Loss: 2.0045 - Accuracy: 0.2952 - F1: 0.1736
sub_3:Test (Best Model) - Loss: 1.5732 - Accuracy: 0.2667 - F1: 0.2134
sub_7:Test (Best Model) - Loss: 1.3687 - Accuracy: 0.3571 - F1: 0.3275
sub_9:Test (Best Model) - Loss: 1.2505 - Accuracy: 0.4238 - F1: 0.3687
sub_2:Test (Best Model) - Loss: 1.4610 - Accuracy: 0.4714 - F1: 0.4341
sub_5:Test (Best Model) - Loss: 3.5116 - Accuracy: 0.2238 - F1: 0.1994
sub_6:Test (Best Model) - Loss: 2.3919 - Accuracy: 0.1810 - F1: 0.1629
sub_1:Test (Best Model) - Loss: 2.5589 - Accuracy: 0.3381 - F1: 0.2267
sub_3:Test (Best Model) - Loss: 1.4285 - Accuracy: 0.3286 - F1: 0.3223
sub_7:Test (Best Model) - Loss: 1.9471 - Accuracy: 0.3333 - F1: 0.3020
sub_6:Test (Best Model) - Loss: 2.9214 - Accuracy: 0.3095 - F1: 0.2993
sub_2:Test (Best Model) - Loss: 2.0027 - Accuracy: 0.3810 - F1: 0.3334
sub_7:Test (Best Model) - Loss: 1.8541 - Accuracy: 0.3000 - F1: 0.2700
sub_6:Test (Best Model) - Loss: 2.3999 - Accuracy: 0.2238 - F1: 0.1990
sub_2:Test (Best Model) - Loss: 1.9046 - Accuracy: 0.3619 - F1: 0.3274
sub_12:Test (Best Model) - Loss: 1.3921 - Accuracy: 0.3905 - F1: 0.3250
sub_14:Test (Best Model) - Loss: 2.0688 - Accuracy: 0.3476 - F1: 0.3443
sub_13:Test (Best Model) - Loss: 5.1659 - Accuracy: 0.2667 - F1: 0.1772
sub_12:Test (Best Model) - Loss: 2.4592 - Accuracy: 0.2952 - F1: 0.1954
sub_11:Test (Best Model) - Loss: 1.7676 - Accuracy: 0.2143 - F1: 0.2008
sub_14:Test (Best Model) - Loss: 1.8932 - Accuracy: 0.3286 - F1: 0.3153
sub_11:Test (Best Model) - Loss: 2.6412 - Accuracy: 0.3333 - F1: 0.2888
sub_13:Test (Best Model) - Loss: 1.8495 - Accuracy: 0.3571 - F1: 0.2941
sub_12:Test (Best Model) - Loss: 1.5297 - Accuracy: 0.3952 - F1: 0.3500
sub_11:Test (Best Model) - Loss: 2.0620 - Accuracy: 0.2667 - F1: 0.2406
sub_12:Test (Best Model) - Loss: 1.3102 - Accuracy: 0.3714 - F1: 0.3225
sub_13:Test (Best Model) - Loss: 1.7384 - Accuracy: 0.2952 - F1: 0.2349
sub_11:Test (Best Model) - Loss: 1.6972 - Accuracy: 0.3619 - F1: 0.3504
sub_13:Test (Best Model) - Loss: 1.3496 - Accuracy: 0.3476 - F1: 0.3424
sub_12:Test (Best Model) - Loss: 1.8280 - Accuracy: 0.3714 - F1: 0.3349
sub_11:Test (Best Model) - Loss: 1.6203 - Accuracy: 0.3905 - F1: 0.3837
sub_14:Test (Best Model) - Loss: 1.9143 - Accuracy: 0.3619 - F1: 0.3798
sub_13:Test (Best Model) - Loss: 1.4975 - Accuracy: 0.3714 - F1: 0.3370
sub_12:Test (Best Model) - Loss: 2.6318 - Accuracy: 0.2857 - F1: 0.1808
sub_11:Test (Best Model) - Loss: 2.1451 - Accuracy: 0.3000 - F1: 0.2771
sub_14:Test (Best Model) - Loss: 1.8045 - Accuracy: 0.3524 - F1: 0.3561
sub_13:Test (Best Model) - Loss: 2.7758 - Accuracy: 0.3190 - F1: 0.2309
sub_11:Test (Best Model) - Loss: 1.7174 - Accuracy: 0.3810 - F1: 0.3137
sub_12:Test (Best Model) - Loss: 1.7032 - Accuracy: 0.3952 - F1: 0.3590
sub_14:Test (Best Model) - Loss: 1.7719 - Accuracy: 0.2952 - F1: 0.2719
sub_13:Test (Best Model) - Loss: 1.4954 - Accuracy: 0.3762 - F1: 0.3558
sub_12:Test (Best Model) - Loss: 1.6392 - Accuracy: 0.3952 - F1: 0.3226
sub_14:Test (Best Model) - Loss: 2.4100 - Accuracy: 0.2238 - F1: 0.1191
sub_13:Test (Best Model) - Loss: 2.0883 - Accuracy: 0.2714 - F1: 0.1606
sub_11:Test (Best Model) - Loss: 3.0300 - Accuracy: 0.3095 - F1: 0.2942
sub_14:Test (Best Model) - Loss: 2.6828 - Accuracy: 0.2333 - F1: 0.1425
sub_13:Test (Best Model) - Loss: 1.8715 - Accuracy: 0.3810 - F1: 0.3424
sub_12:Test (Best Model) - Loss: 1.6331 - Accuracy: 0.4000 - F1: 0.3638
sub_11:Test (Best Model) - Loss: 1.4379 - Accuracy: 0.3571 - F1: 0.2877
sub_13:Test (Best Model) - Loss: 1.3394 - Accuracy: 0.3762 - F1: 0.3355
sub_11:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.4524 - F1: 0.4182
sub_12:Test (Best Model) - Loss: 1.9037 - Accuracy: 0.3667 - F1: 0.2789
sub_14:Test (Best Model) - Loss: 2.2168 - Accuracy: 0.3571 - F1: 0.3170
sub_13:Test (Best Model) - Loss: 1.9553 - Accuracy: 0.2714 - F1: 0.2052
sub_11:Test (Best Model) - Loss: 2.1607 - Accuracy: 0.3048 - F1: 0.2519
sub_12:Test (Best Model) - Loss: 2.1652 - Accuracy: 0.3095 - F1: 0.2955
sub_11:Test (Best Model) - Loss: 3.6644 - Accuracy: 0.3095 - F1: 0.2127
sub_13:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.4095 - F1: 0.3930
sub_14:Test (Best Model) - Loss: 2.3562 - Accuracy: 0.3143 - F1: 0.2530
sub_12:Test (Best Model) - Loss: 1.6473 - Accuracy: 0.2952 - F1: 0.2504
sub_11:Test (Best Model) - Loss: 1.5393 - Accuracy: 0.3333 - F1: 0.3433
sub_13:Test (Best Model) - Loss: 1.5370 - Accuracy: 0.4095 - F1: 0.3672
sub_14:Test (Best Model) - Loss: 1.4547 - Accuracy: 0.4524 - F1: 0.4341
sub_12:Test (Best Model) - Loss: 1.4109 - Accuracy: 0.4762 - F1: 0.4035
sub_13:Test (Best Model) - Loss: 1.9097 - Accuracy: 0.2952 - F1: 0.2767
sub_12:Test (Best Model) - Loss: 1.7454 - Accuracy: 0.3524 - F1: 0.3120
sub_14:Test (Best Model) - Loss: 3.1146 - Accuracy: 0.2857 - F1: 0.2305
sub_11:Test (Best Model) - Loss: 1.9936 - Accuracy: 0.4095 - F1: 0.3902
sub_13:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.3524 - F1: 0.3040
sub_12:Test (Best Model) - Loss: 1.6825 - Accuracy: 0.4333 - F1: 0.3701
sub_14:Test (Best Model) - Loss: 1.9520 - Accuracy: 0.2524 - F1: 0.2020
sub_11:Test (Best Model) - Loss: 2.7164 - Accuracy: 0.3000 - F1: 0.2575
sub_14:Test (Best Model) - Loss: 1.8974 - Accuracy: 0.4429 - F1: 0.3784
sub_14:Test (Best Model) - Loss: 4.7430 - Accuracy: 0.2333 - F1: 0.1288
sub_14:Test (Best Model) - Loss: 5.7951 - Accuracy: 0.2286 - F1: 0.1184

=== Summary Results ===

acc: 33.64 ± 4.39
F1: 28.68 ± 5.18
acc-in: 46.03 ± 3.83
F1-in: 41.89 ± 4.36
runing time: 4121.07 seconds
