lr: 0.001
sub_1:Test (Best Model) - Loss: 19.3252 - Accuracy: 0.3524 - F1: 0.2657
sub_2:Test (Best Model) - Loss: 2.4448 - Accuracy: 0.3857 - F1: 0.3214
sub_3:Test (Best Model) - Loss: 11.0182 - Accuracy: 0.2238 - F1: 0.1060
sub_1:Test (Best Model) - Loss: 18.8712 - Accuracy: 0.3286 - F1: 0.2578
sub_3:Test (Best Model) - Loss: 10.8597 - Accuracy: 0.2238 - F1: 0.1095
sub_2:Test (Best Model) - Loss: 2.8591 - Accuracy: 0.4619 - F1: 0.4127
sub_3:Test (Best Model) - Loss: 9.4934 - Accuracy: 0.3000 - F1: 0.2152
sub_2:Test (Best Model) - Loss: 2.1758 - Accuracy: 0.4190 - F1: 0.3460
sub_1:Test (Best Model) - Loss: 12.6398 - Accuracy: 0.3190 - F1: 0.2462
sub_1:Test (Best Model) - Loss: 11.8952 - Accuracy: 0.3143 - F1: 0.2440
sub_3:Test (Best Model) - Loss: 20.3171 - Accuracy: 0.3476 - F1: 0.2330
sub_2:Test (Best Model) - Loss: 2.5117 - Accuracy: 0.4286 - F1: 0.3652
sub_3:Test (Best Model) - Loss: 5.5008 - Accuracy: 0.2190 - F1: 0.0992
sub_1:Test (Best Model) - Loss: 10.2228 - Accuracy: 0.3762 - F1: 0.3131
sub_3:Test (Best Model) - Loss: 1.8519 - Accuracy: 0.3952 - F1: 0.3348
sub_2:Test (Best Model) - Loss: 5.4964 - Accuracy: 0.3952 - F1: 0.3596
sub_1:Test (Best Model) - Loss: 4.4074 - Accuracy: 0.3476 - F1: 0.3516
sub_3:Test (Best Model) - Loss: 3.5145 - Accuracy: 0.3857 - F1: 0.3592
sub_2:Test (Best Model) - Loss: 4.6673 - Accuracy: 0.4190 - F1: 0.3877
sub_1:Test (Best Model) - Loss: 5.1266 - Accuracy: 0.3524 - F1: 0.3428
sub_3:Test (Best Model) - Loss: 1.7831 - Accuracy: 0.3905 - F1: 0.3896
sub_2:Test (Best Model) - Loss: 4.3690 - Accuracy: 0.4286 - F1: 0.3926
sub_3:Test (Best Model) - Loss: 1.8835 - Accuracy: 0.3905 - F1: 0.3550
sub_1:Test (Best Model) - Loss: 6.2253 - Accuracy: 0.4048 - F1: 0.4198
sub_3:Test (Best Model) - Loss: 2.3829 - Accuracy: 0.3476 - F1: 0.2993
sub_2:Test (Best Model) - Loss: 3.3121 - Accuracy: 0.4714 - F1: 0.4592
sub_3:Test (Best Model) - Loss: 8.0543 - Accuracy: 0.2952 - F1: 0.2875
sub_1:Test (Best Model) - Loss: 4.6756 - Accuracy: 0.3333 - F1: 0.3459
sub_3:Test (Best Model) - Loss: 12.5311 - Accuracy: 0.3190 - F1: 0.3173
sub_2:Test (Best Model) - Loss: 3.8144 - Accuracy: 0.3714 - F1: 0.3661
sub_1:Test (Best Model) - Loss: 3.6461 - Accuracy: 0.3619 - F1: 0.3789
sub_3:Test (Best Model) - Loss: 19.1453 - Accuracy: 0.3238 - F1: 0.3279
sub_2:Test (Best Model) - Loss: 4.6182 - Accuracy: 0.4000 - F1: 0.3766
sub_1:Test (Best Model) - Loss: 11.1979 - Accuracy: 0.3286 - F1: 0.2989
sub_3:Test (Best Model) - Loss: 5.1075 - Accuracy: 0.3190 - F1: 0.2901
sub_3:Test (Best Model) - Loss: 10.6286 - Accuracy: 0.2810 - F1: 0.2917
sub_2:Test (Best Model) - Loss: 29.5720 - Accuracy: 0.2667 - F1: 0.1829
sub_1:Test (Best Model) - Loss: 8.2184 - Accuracy: 0.3381 - F1: 0.2948
sub_2:Test (Best Model) - Loss: 15.2697 - Accuracy: 0.2952 - F1: 0.2361
sub_1:Test (Best Model) - Loss: 8.1969 - Accuracy: 0.3333 - F1: 0.2745
sub_2:Test (Best Model) - Loss: 15.0434 - Accuracy: 0.3048 - F1: 0.2537
sub_1:Test (Best Model) - Loss: 6.6875 - Accuracy: 0.3333 - F1: 0.2960
sub_2:Test (Best Model) - Loss: 26.6740 - Accuracy: 0.3095 - F1: 0.2663
sub_1:Test (Best Model) - Loss: 7.6656 - Accuracy: 0.3619 - F1: 0.3111
sub_2:Test (Best Model) - Loss: 14.9877 - Accuracy: 0.3000 - F1: 0.2817
sub_4:Test (Best Model) - Loss: 4.7758 - Accuracy: 0.3429 - F1: 0.2923
sub_5:Test (Best Model) - Loss: 44.8742 - Accuracy: 0.2571 - F1: 0.2054
sub_6:Test (Best Model) - Loss: 10.5610 - Accuracy: 0.3333 - F1: 0.2523
sub_5:Test (Best Model) - Loss: 29.4546 - Accuracy: 0.2381 - F1: 0.1532
sub_6:Test (Best Model) - Loss: 9.2583 - Accuracy: 0.3619 - F1: 0.3100
sub_4:Test (Best Model) - Loss: 3.4338 - Accuracy: 0.3952 - F1: 0.3590
sub_6:Test (Best Model) - Loss: 7.9151 - Accuracy: 0.3952 - F1: 0.3268
sub_4:Test (Best Model) - Loss: 2.2962 - Accuracy: 0.3571 - F1: 0.3015
sub_5:Test (Best Model) - Loss: 29.2962 - Accuracy: 0.2476 - F1: 0.1792
sub_6:Test (Best Model) - Loss: 5.8225 - Accuracy: 0.3619 - F1: 0.3148
sub_5:Test (Best Model) - Loss: 22.5508 - Accuracy: 0.2381 - F1: 0.1944
sub_4:Test (Best Model) - Loss: 3.7346 - Accuracy: 0.3714 - F1: 0.3107
sub_5:Test (Best Model) - Loss: 18.3961 - Accuracy: 0.2238 - F1: 0.1679
sub_6:Test (Best Model) - Loss: 5.5212 - Accuracy: 0.3381 - F1: 0.3310
sub_4:Test (Best Model) - Loss: 2.3919 - Accuracy: 0.4190 - F1: 0.3721
sub_4:Test (Best Model) - Loss: 8.7686 - Accuracy: 0.3857 - F1: 0.3478
sub_5:Test (Best Model) - Loss: 24.7423 - Accuracy: 0.3286 - F1: 0.2783
sub_6:Test (Best Model) - Loss: 9.6171 - Accuracy: 0.3571 - F1: 0.3454
sub_4:Test (Best Model) - Loss: 2.9905 - Accuracy: 0.3857 - F1: 0.3468
sub_5:Test (Best Model) - Loss: 22.2652 - Accuracy: 0.3619 - F1: 0.3110
sub_6:Test (Best Model) - Loss: 7.9686 - Accuracy: 0.3667 - F1: 0.3497
sub_4:Test (Best Model) - Loss: 3.3565 - Accuracy: 0.4524 - F1: 0.4386
sub_4:Test (Best Model) - Loss: 3.3087 - Accuracy: 0.3810 - F1: 0.3731
sub_5:Test (Best Model) - Loss: 19.1061 - Accuracy: 0.4095 - F1: 0.3784
sub_6:Test (Best Model) - Loss: 8.3138 - Accuracy: 0.3286 - F1: 0.3398
sub_5:Test (Best Model) - Loss: 9.5123 - Accuracy: 0.3524 - F1: 0.3449
sub_6:Test (Best Model) - Loss: 8.7071 - Accuracy: 0.3000 - F1: 0.3008
sub_4:Test (Best Model) - Loss: 6.2469 - Accuracy: 0.4286 - F1: 0.3833
sub_5:Test (Best Model) - Loss: 16.7263 - Accuracy: 0.4000 - F1: 0.3476
sub_6:Test (Best Model) - Loss: 8.2453 - Accuracy: 0.2857 - F1: 0.2926
sub_4:Test (Best Model) - Loss: 3.7558 - Accuracy: 0.3571 - F1: 0.3611
sub_5:Test (Best Model) - Loss: 11.2176 - Accuracy: 0.2476 - F1: 0.2661
sub_6:Test (Best Model) - Loss: 82.2852 - Accuracy: 0.2952 - F1: 0.2065
sub_4:Test (Best Model) - Loss: 3.1421 - Accuracy: 0.3095 - F1: 0.3144
sub_4:Test (Best Model) - Loss: 2.2889 - Accuracy: 0.4238 - F1: 0.4269
sub_6:Test (Best Model) - Loss: 99.1778 - Accuracy: 0.2810 - F1: 0.2450
sub_5:Test (Best Model) - Loss: 8.1254 - Accuracy: 0.2762 - F1: 0.2723
sub_4:Test (Best Model) - Loss: 2.6405 - Accuracy: 0.3571 - F1: 0.3602
sub_5:Test (Best Model) - Loss: 5.9001 - Accuracy: 0.3000 - F1: 0.3067
sub_6:Test (Best Model) - Loss: 8.1848 - Accuracy: 0.3476 - F1: 0.2951
sub_4:Test (Best Model) - Loss: 3.8611 - Accuracy: 0.3762 - F1: 0.3861
sub_6:Test (Best Model) - Loss: 48.1775 - Accuracy: 0.3238 - F1: 0.2435
sub_5:Test (Best Model) - Loss: 4.9147 - Accuracy: 0.3048 - F1: 0.3000
sub_5:Test (Best Model) - Loss: 4.3083 - Accuracy: 0.3571 - F1: 0.3643
sub_6:Test (Best Model) - Loss: 19.7967 - Accuracy: 0.3238 - F1: 0.2862
sub_9:Test (Best Model) - Loss: 4.2808 - Accuracy: 0.3667 - F1: 0.2973
sub_7:Test (Best Model) - Loss: 4.6121 - Accuracy: 0.3476 - F1: 0.3349
sub_8:Test (Best Model) - Loss: 3.7656 - Accuracy: 0.4571 - F1: 0.4618
sub_9:Test (Best Model) - Loss: 9.6048 - Accuracy: 0.3857 - F1: 0.3177
sub_8:Test (Best Model) - Loss: 3.9198 - Accuracy: 0.4238 - F1: 0.3974
sub_7:Test (Best Model) - Loss: 6.0543 - Accuracy: 0.3667 - F1: 0.3607
sub_9:Test (Best Model) - Loss: 6.3426 - Accuracy: 0.4000 - F1: 0.3330
sub_8:Test (Best Model) - Loss: 3.6323 - Accuracy: 0.4429 - F1: 0.4136
sub_8:Test (Best Model) - Loss: 3.8493 - Accuracy: 0.4286 - F1: 0.3954
sub_7:Test (Best Model) - Loss: 4.3763 - Accuracy: 0.3238 - F1: 0.2942
sub_9:Test (Best Model) - Loss: 7.3065 - Accuracy: 0.4143 - F1: 0.3530
sub_8:Test (Best Model) - Loss: 4.2848 - Accuracy: 0.4429 - F1: 0.4117
sub_7:Test (Best Model) - Loss: 4.5816 - Accuracy: 0.3143 - F1: 0.2877
sub_9:Test (Best Model) - Loss: 5.8934 - Accuracy: 0.4286 - F1: 0.3642
sub_7:Test (Best Model) - Loss: 3.2804 - Accuracy: 0.3667 - F1: 0.3027
sub_8:Test (Best Model) - Loss: 3.4112 - Accuracy: 0.4905 - F1: 0.4896
sub_8:Test (Best Model) - Loss: 1.9827 - Accuracy: 0.4762 - F1: 0.4600
sub_7:Test (Best Model) - Loss: 4.6697 - Accuracy: 0.3286 - F1: 0.3295
sub_8:Test (Best Model) - Loss: 1.3692 - Accuracy: 0.4857 - F1: 0.4841
sub_9:Test (Best Model) - Loss: 12.3246 - Accuracy: 0.3571 - F1: 0.2857
sub_7:Test (Best Model) - Loss: 5.1465 - Accuracy: 0.3857 - F1: 0.3564
sub_9:Test (Best Model) - Loss: 10.6457 - Accuracy: 0.3333 - F1: 0.2650
sub_8:Test (Best Model) - Loss: 2.1521 - Accuracy: 0.4381 - F1: 0.4043
sub_7:Test (Best Model) - Loss: 4.6493 - Accuracy: 0.3381 - F1: 0.3288
sub_8:Test (Best Model) - Loss: 1.3567 - Accuracy: 0.4524 - F1: 0.4416
sub_9:Test (Best Model) - Loss: 15.6993 - Accuracy: 0.3286 - F1: 0.2866
sub_8:Test (Best Model) - Loss: 10.8446 - Accuracy: 0.3619 - F1: 0.3400
sub_9:Test (Best Model) - Loss: 6.8311 - Accuracy: 0.3238 - F1: 0.2476
sub_7:Test (Best Model) - Loss: 5.0089 - Accuracy: 0.3476 - F1: 0.3389
sub_9:Test (Best Model) - Loss: 10.3074 - Accuracy: 0.4000 - F1: 0.3700
sub_8:Test (Best Model) - Loss: 7.9968 - Accuracy: 0.3619 - F1: 0.3568
sub_7:Test (Best Model) - Loss: 10.5122 - Accuracy: 0.3476 - F1: 0.2768
sub_9:Test (Best Model) - Loss: 14.0494 - Accuracy: 0.2571 - F1: 0.2563
sub_7:Test (Best Model) - Loss: 11.2211 - Accuracy: 0.3095 - F1: 0.3266
sub_8:Test (Best Model) - Loss: 11.9419 - Accuracy: 0.3238 - F1: 0.2872
sub_7:Test (Best Model) - Loss: 8.7670 - Accuracy: 0.3095 - F1: 0.2837
sub_8:Test (Best Model) - Loss: 12.7369 - Accuracy: 0.4143 - F1: 0.4209
sub_9:Test (Best Model) - Loss: 25.4579 - Accuracy: 0.3095 - F1: 0.2904
sub_8:Test (Best Model) - Loss: 8.5562 - Accuracy: 0.3619 - F1: 0.3335
sub_7:Test (Best Model) - Loss: 11.1362 - Accuracy: 0.3667 - F1: 0.3676
sub_9:Test (Best Model) - Loss: 14.7595 - Accuracy: 0.3238 - F1: 0.3210
sub_7:Test (Best Model) - Loss: 5.6934 - Accuracy: 0.3857 - F1: 0.3807
sub_9:Test (Best Model) - Loss: 7.7647 - Accuracy: 0.3571 - F1: 0.3408
sub_7:Test (Best Model) - Loss: 4.7598 - Accuracy: 0.3619 - F1: 0.3494
sub_9:Test (Best Model) - Loss: 7.9887 - Accuracy: 0.3333 - F1: 0.2584
sub_12:Test (Best Model) - Loss: 3.2554 - Accuracy: 0.3048 - F1: 0.2765
sub_10:Test (Best Model) - Loss: 6.6444 - Accuracy: 0.4238 - F1: 0.3659
sub_11:Test (Best Model) - Loss: 7.1277 - Accuracy: 0.4476 - F1: 0.3935
sub_12:Test (Best Model) - Loss: 3.1743 - Accuracy: 0.3762 - F1: 0.3678
sub_10:Test (Best Model) - Loss: 4.3791 - Accuracy: 0.4333 - F1: 0.3956
sub_10:Test (Best Model) - Loss: 6.0868 - Accuracy: 0.3905 - F1: 0.3518
sub_12:Test (Best Model) - Loss: 3.5317 - Accuracy: 0.3667 - F1: 0.3552
sub_11:Test (Best Model) - Loss: 5.9624 - Accuracy: 0.4476 - F1: 0.4413
sub_10:Test (Best Model) - Loss: 4.3481 - Accuracy: 0.3905 - F1: 0.3773
sub_12:Test (Best Model) - Loss: 2.1247 - Accuracy: 0.4286 - F1: 0.3964
sub_11:Test (Best Model) - Loss: 3.4505 - Accuracy: 0.4571 - F1: 0.4186
sub_12:Test (Best Model) - Loss: 3.9697 - Accuracy: 0.3571 - F1: 0.3178
sub_10:Test (Best Model) - Loss: 9.0191 - Accuracy: 0.4143 - F1: 0.3850
sub_12:Test (Best Model) - Loss: 4.4708 - Accuracy: 0.3619 - F1: 0.3213
sub_11:Test (Best Model) - Loss: 6.8371 - Accuracy: 0.4333 - F1: 0.3735
sub_10:Test (Best Model) - Loss: 3.8341 - Accuracy: 0.4238 - F1: 0.4003
sub_11:Test (Best Model) - Loss: 9.4051 - Accuracy: 0.4429 - F1: 0.4064
sub_12:Test (Best Model) - Loss: 7.8567 - Accuracy: 0.3381 - F1: 0.2886
sub_10:Test (Best Model) - Loss: 3.5957 - Accuracy: 0.4333 - F1: 0.3886
sub_11:Test (Best Model) - Loss: 3.5395 - Accuracy: 0.4476 - F1: 0.4196
sub_12:Test (Best Model) - Loss: 6.8412 - Accuracy: 0.3143 - F1: 0.2789
sub_10:Test (Best Model) - Loss: 4.7641 - Accuracy: 0.4000 - F1: 0.3710
sub_12:Test (Best Model) - Loss: 4.2184 - Accuracy: 0.3429 - F1: 0.3179
sub_11:Test (Best Model) - Loss: 5.9896 - Accuracy: 0.4286 - F1: 0.4282
sub_12:Test (Best Model) - Loss: 3.5156 - Accuracy: 0.3048 - F1: 0.2709
sub_10:Test (Best Model) - Loss: 3.2030 - Accuracy: 0.4000 - F1: 0.3446
sub_12:Test (Best Model) - Loss: 13.3610 - Accuracy: 0.3143 - F1: 0.3024
sub_10:Test (Best Model) - Loss: 2.8032 - Accuracy: 0.3762 - F1: 0.3475
sub_11:Test (Best Model) - Loss: 7.8975 - Accuracy: 0.4524 - F1: 0.4113
sub_12:Test (Best Model) - Loss: 8.7222 - Accuracy: 0.3286 - F1: 0.3124
sub_10:Test (Best Model) - Loss: 16.5988 - Accuracy: 0.3000 - F1: 0.2280
sub_11:Test (Best Model) - Loss: 6.6502 - Accuracy: 0.4571 - F1: 0.4356
sub_12:Test (Best Model) - Loss: 13.6773 - Accuracy: 0.2571 - F1: 0.2427
sub_10:Test (Best Model) - Loss: 6.1128 - Accuracy: 0.2238 - F1: 0.1990
sub_12:Test (Best Model) - Loss: 6.9661 - Accuracy: 0.2857 - F1: 0.2764
sub_11:Test (Best Model) - Loss: 6.0574 - Accuracy: 0.3952 - F1: 0.3559
sub_10:Test (Best Model) - Loss: 11.2041 - Accuracy: 0.2810 - F1: 0.2060
sub_12:Test (Best Model) - Loss: 14.4678 - Accuracy: 0.3190 - F1: 0.2681
sub_10:Test (Best Model) - Loss: 9.4275 - Accuracy: 0.2429 - F1: 0.2069
sub_11:Test (Best Model) - Loss: 3.9962 - Accuracy: 0.3714 - F1: 0.3755
sub_11:Test (Best Model) - Loss: 5.6223 - Accuracy: 0.3952 - F1: 0.3937
sub_10:Test (Best Model) - Loss: 10.5593 - Accuracy: 0.2952 - F1: 0.2311
sub_11:Test (Best Model) - Loss: 3.7465 - Accuracy: 0.3714 - F1: 0.3756
sub_11:Test (Best Model) - Loss: 3.3967 - Accuracy: 0.4000 - F1: 0.3953
sub_11:Test (Best Model) - Loss: 2.6995 - Accuracy: 0.3619 - F1: 0.3666
sub_13:Test (Best Model) - Loss: 12.5689 - Accuracy: 0.2619 - F1: 0.1745
sub_14:Test (Best Model) - Loss: 5.1025 - Accuracy: 0.3857 - F1: 0.3922
sub_14:Test (Best Model) - Loss: 6.2777 - Accuracy: 0.3905 - F1: 0.3757
sub_13:Test (Best Model) - Loss: 6.2865 - Accuracy: 0.3571 - F1: 0.2791
sub_13:Test (Best Model) - Loss: 9.5003 - Accuracy: 0.2952 - F1: 0.2229
sub_14:Test (Best Model) - Loss: 7.4277 - Accuracy: 0.3762 - F1: 0.3887
sub_14:Test (Best Model) - Loss: 5.7381 - Accuracy: 0.3429 - F1: 0.3356
sub_13:Test (Best Model) - Loss: 5.6120 - Accuracy: 0.3048 - F1: 0.2293
sub_14:Test (Best Model) - Loss: 5.4170 - Accuracy: 0.3333 - F1: 0.3085
sub_13:Test (Best Model) - Loss: 10.0165 - Accuracy: 0.2905 - F1: 0.2201
sub_14:Test (Best Model) - Loss: 1.5492 - Accuracy: 0.4476 - F1: 0.4132
sub_13:Test (Best Model) - Loss: 5.5742 - Accuracy: 0.3571 - F1: 0.3126
sub_14:Test (Best Model) - Loss: 2.8167 - Accuracy: 0.4810 - F1: 0.4646
sub_13:Test (Best Model) - Loss: 3.7949 - Accuracy: 0.3143 - F1: 0.2994
sub_14:Test (Best Model) - Loss: 3.8647 - Accuracy: 0.4429 - F1: 0.3868
sub_14:Test (Best Model) - Loss: 3.9040 - Accuracy: 0.4810 - F1: 0.4309
sub_13:Test (Best Model) - Loss: 3.5268 - Accuracy: 0.4048 - F1: 0.3741
sub_14:Test (Best Model) - Loss: 1.2537 - Accuracy: 0.5095 - F1: 0.4462
sub_14:Test (Best Model) - Loss: 5.4180 - Accuracy: 0.2810 - F1: 0.2069
sub_13:Test (Best Model) - Loss: 3.8074 - Accuracy: 0.4095 - F1: 0.3742
sub_14:Test (Best Model) - Loss: 3.7067 - Accuracy: 0.2429 - F1: 0.1525
sub_13:Test (Best Model) - Loss: 3.1163 - Accuracy: 0.3762 - F1: 0.3674
sub_14:Test (Best Model) - Loss: 4.8258 - Accuracy: 0.2429 - F1: 0.1611
sub_14:Test (Best Model) - Loss: 4.8689 - Accuracy: 0.2571 - F1: 0.1740
sub_13:Test (Best Model) - Loss: 8.2754 - Accuracy: 0.3476 - F1: 0.3018
sub_14:Test (Best Model) - Loss: 8.0637 - Accuracy: 0.2524 - F1: 0.1603
sub_13:Test (Best Model) - Loss: 4.5862 - Accuracy: 0.3810 - F1: 0.3443
sub_13:Test (Best Model) - Loss: 4.4892 - Accuracy: 0.3714 - F1: 0.2909
sub_13:Test (Best Model) - Loss: 4.9390 - Accuracy: 0.3381 - F1: 0.3039
sub_13:Test (Best Model) - Loss: 4.8814 - Accuracy: 0.4190 - F1: 0.3355

=== Summary Results ===

acc: 35.81 ± 3.34
F1: 32.27 ± 3.98
acc-in: 51.52 ± 4.41
F1-in: 49.36 ± 4.92
runing time: 2666.25 seconds
