lr: 0.001
sub_1:Test (Best Model) - Loss: 7.7795 - Accuracy: 0.2353 - F1: 0.2317
sub_1:Test (Best Model) - Loss: 5.7532 - Accuracy: 0.3676 - F1: 0.3610
sub_1:Test (Best Model) - Loss: 5.7591 - Accuracy: 0.2941 - F1: 0.3042
sub_1:Test (Best Model) - Loss: 6.2079 - Accuracy: 0.3382 - F1: 0.2695
sub_1:Test (Best Model) - Loss: 5.8412 - Accuracy: 0.3676 - F1: 0.3658
sub_1:Test (Best Model) - Loss: 5.6917 - Accuracy: 0.2899 - F1: 0.2419
sub_1:Test (Best Model) - Loss: 6.6551 - Accuracy: 0.3188 - F1: 0.3098
sub_1:Test (Best Model) - Loss: 6.5057 - Accuracy: 0.3623 - F1: 0.3208
sub_1:Test (Best Model) - Loss: 7.8274 - Accuracy: 0.4348 - F1: 0.4068
sub_1:Test (Best Model) - Loss: 5.7423 - Accuracy: 0.4203 - F1: 0.4007
sub_1:Test (Best Model) - Loss: 6.8023 - Accuracy: 0.3676 - F1: 0.3469
sub_1:Test (Best Model) - Loss: 4.7362 - Accuracy: 0.3676 - F1: 0.3509
sub_1:Test (Best Model) - Loss: 4.3126 - Accuracy: 0.5294 - F1: 0.5304
sub_1:Test (Best Model) - Loss: 6.5179 - Accuracy: 0.3971 - F1: 0.3932
sub_1:Test (Best Model) - Loss: 6.4677 - Accuracy: 0.3529 - F1: 0.3517
sub_2:Test (Best Model) - Loss: 9.5652 - Accuracy: 0.2319 - F1: 0.2149
sub_2:Test (Best Model) - Loss: 6.2135 - Accuracy: 0.2464 - F1: 0.2626
sub_2:Test (Best Model) - Loss: 6.0949 - Accuracy: 0.2899 - F1: 0.2934
sub_2:Test (Best Model) - Loss: 6.8186 - Accuracy: 0.2609 - F1: 0.2682
sub_2:Test (Best Model) - Loss: 9.9024 - Accuracy: 0.1739 - F1: 0.1803
sub_2:Test (Best Model) - Loss: 5.4138 - Accuracy: 0.2059 - F1: 0.2228
sub_2:Test (Best Model) - Loss: 5.8721 - Accuracy: 0.2794 - F1: 0.2637
sub_2:Test (Best Model) - Loss: 4.3839 - Accuracy: 0.3676 - F1: 0.3858
sub_2:Test (Best Model) - Loss: 4.8307 - Accuracy: 0.3676 - F1: 0.3540
sub_2:Test (Best Model) - Loss: 5.3025 - Accuracy: 0.3382 - F1: 0.3461
sub_2:Test (Best Model) - Loss: 6.3498 - Accuracy: 0.3188 - F1: 0.2666
sub_2:Test (Best Model) - Loss: 5.3507 - Accuracy: 0.3623 - F1: 0.3350
sub_2:Test (Best Model) - Loss: 4.9488 - Accuracy: 0.3913 - F1: 0.3810
sub_2:Test (Best Model) - Loss: 6.4208 - Accuracy: 0.3623 - F1: 0.3351
sub_2:Test (Best Model) - Loss: 7.6509 - Accuracy: 0.3333 - F1: 0.3118
sub_3:Test (Best Model) - Loss: 8.0265 - Accuracy: 0.3529 - F1: 0.3534
sub_3:Test (Best Model) - Loss: 7.0508 - Accuracy: 0.2794 - F1: 0.2663
sub_3:Test (Best Model) - Loss: 7.3824 - Accuracy: 0.2059 - F1: 0.1941
sub_3:Test (Best Model) - Loss: 8.1752 - Accuracy: 0.2647 - F1: 0.2473
sub_3:Test (Best Model) - Loss: 7.4576 - Accuracy: 0.2206 - F1: 0.2118
sub_3:Test (Best Model) - Loss: 7.0038 - Accuracy: 0.2899 - F1: 0.2370
sub_3:Test (Best Model) - Loss: 8.0073 - Accuracy: 0.2609 - F1: 0.2387
sub_3:Test (Best Model) - Loss: 6.3283 - Accuracy: 0.2174 - F1: 0.2023
sub_3:Test (Best Model) - Loss: 6.6586 - Accuracy: 0.2754 - F1: 0.2587
sub_3:Test (Best Model) - Loss: 6.4474 - Accuracy: 0.2609 - F1: 0.2517
sub_3:Test (Best Model) - Loss: 8.9990 - Accuracy: 0.2754 - F1: 0.2588
sub_3:Test (Best Model) - Loss: 8.4365 - Accuracy: 0.2609 - F1: 0.2384
sub_3:Test (Best Model) - Loss: 7.7308 - Accuracy: 0.2319 - F1: 0.2275
sub_3:Test (Best Model) - Loss: 7.1875 - Accuracy: 0.3043 - F1: 0.2895
sub_3:Test (Best Model) - Loss: 9.1497 - Accuracy: 0.2754 - F1: 0.2611
sub_4:Test (Best Model) - Loss: 7.1466 - Accuracy: 0.3333 - F1: 0.3281
sub_4:Test (Best Model) - Loss: 6.2395 - Accuracy: 0.3188 - F1: 0.3334
sub_4:Test (Best Model) - Loss: 6.4726 - Accuracy: 0.3043 - F1: 0.2880
sub_4:Test (Best Model) - Loss: 5.3205 - Accuracy: 0.3913 - F1: 0.3920
sub_4:Test (Best Model) - Loss: 6.1915 - Accuracy: 0.3768 - F1: 0.3812
sub_4:Test (Best Model) - Loss: 5.0852 - Accuracy: 0.4058 - F1: 0.4151
sub_4:Test (Best Model) - Loss: 6.0686 - Accuracy: 0.3768 - F1: 0.3803
sub_4:Test (Best Model) - Loss: 5.3549 - Accuracy: 0.3768 - F1: 0.3781
sub_4:Test (Best Model) - Loss: 5.1371 - Accuracy: 0.4058 - F1: 0.4127
sub_4:Test (Best Model) - Loss: 5.8707 - Accuracy: 0.2899 - F1: 0.2985
sub_4:Test (Best Model) - Loss: 7.5756 - Accuracy: 0.4058 - F1: 0.3582
sub_4:Test (Best Model) - Loss: 5.5143 - Accuracy: 0.3913 - F1: 0.3876
sub_4:Test (Best Model) - Loss: 6.1010 - Accuracy: 0.2319 - F1: 0.2385
sub_4:Test (Best Model) - Loss: 5.7718 - Accuracy: 0.4638 - F1: 0.4751
sub_4:Test (Best Model) - Loss: 7.5124 - Accuracy: 0.3913 - F1: 0.3731
sub_5:Test (Best Model) - Loss: 13.2659 - Accuracy: 0.2353 - F1: 0.2112
sub_5:Test (Best Model) - Loss: 9.8522 - Accuracy: 0.3676 - F1: 0.3551
sub_5:Test (Best Model) - Loss: 12.6943 - Accuracy: 0.3235 - F1: 0.3304
sub_5:Test (Best Model) - Loss: 8.0547 - Accuracy: 0.4265 - F1: 0.4257
sub_5:Test (Best Model) - Loss: 8.4219 - Accuracy: 0.3382 - F1: 0.3535
sub_5:Test (Best Model) - Loss: 6.7863 - Accuracy: 0.4412 - F1: 0.4341
sub_5:Test (Best Model) - Loss: 5.3870 - Accuracy: 0.4706 - F1: 0.4203
sub_5:Test (Best Model) - Loss: 4.6273 - Accuracy: 0.4118 - F1: 0.4220
sub_5:Test (Best Model) - Loss: 2.8303 - Accuracy: 0.4706 - F1: 0.4695
sub_5:Test (Best Model) - Loss: 4.9208 - Accuracy: 0.4412 - F1: 0.4308
sub_5:Test (Best Model) - Loss: 6.9468 - Accuracy: 0.2941 - F1: 0.2959
sub_5:Test (Best Model) - Loss: 6.7093 - Accuracy: 0.3676 - F1: 0.3500
sub_5:Test (Best Model) - Loss: 7.2427 - Accuracy: 0.3971 - F1: 0.3734
sub_5:Test (Best Model) - Loss: 5.5429 - Accuracy: 0.2794 - F1: 0.2780
sub_5:Test (Best Model) - Loss: 4.6724 - Accuracy: 0.4706 - F1: 0.4792
sub_6:Test (Best Model) - Loss: 4.0565 - Accuracy: 0.3529 - F1: 0.3297
sub_6:Test (Best Model) - Loss: 4.3300 - Accuracy: 0.3235 - F1: 0.3263
sub_6:Test (Best Model) - Loss: 4.8152 - Accuracy: 0.3235 - F1: 0.2809
sub_6:Test (Best Model) - Loss: 4.5611 - Accuracy: 0.3529 - F1: 0.3649
sub_6:Test (Best Model) - Loss: 3.9167 - Accuracy: 0.4118 - F1: 0.4276
sub_6:Test (Best Model) - Loss: 5.8088 - Accuracy: 0.2174 - F1: 0.1919
sub_6:Test (Best Model) - Loss: 6.0403 - Accuracy: 0.3478 - F1: 0.2642
sub_6:Test (Best Model) - Loss: 5.1728 - Accuracy: 0.3333 - F1: 0.2726
sub_6:Test (Best Model) - Loss: 7.0271 - Accuracy: 0.3188 - F1: 0.2911
sub_6:Test (Best Model) - Loss: 7.2611 - Accuracy: 0.3623 - F1: 0.3098
sub_6:Test (Best Model) - Loss: 5.6743 - Accuracy: 0.2464 - F1: 0.2156
sub_6:Test (Best Model) - Loss: 7.1089 - Accuracy: 0.2464 - F1: 0.2474
sub_6:Test (Best Model) - Loss: 10.0894 - Accuracy: 0.2899 - F1: 0.2845
sub_6:Test (Best Model) - Loss: 6.0642 - Accuracy: 0.3188 - F1: 0.3205
sub_6:Test (Best Model) - Loss: 4.1165 - Accuracy: 0.4783 - F1: 0.4832
sub_7:Test (Best Model) - Loss: 4.8461 - Accuracy: 0.3971 - F1: 0.3798
sub_7:Test (Best Model) - Loss: 7.6161 - Accuracy: 0.3088 - F1: 0.3030
sub_7:Test (Best Model) - Loss: 5.9310 - Accuracy: 0.3676 - F1: 0.3538
sub_7:Test (Best Model) - Loss: 6.3851 - Accuracy: 0.3971 - F1: 0.3925
sub_7:Test (Best Model) - Loss: 7.4537 - Accuracy: 0.2059 - F1: 0.1961
sub_7:Test (Best Model) - Loss: 7.0782 - Accuracy: 0.3088 - F1: 0.2916
sub_7:Test (Best Model) - Loss: 7.8340 - Accuracy: 0.2500 - F1: 0.2535
sub_7:Test (Best Model) - Loss: 6.6750 - Accuracy: 0.3235 - F1: 0.3351
sub_7:Test (Best Model) - Loss: 6.2453 - Accuracy: 0.3676 - F1: 0.3612
sub_7:Test (Best Model) - Loss: 6.1864 - Accuracy: 0.3824 - F1: 0.3776
sub_7:Test (Best Model) - Loss: 5.3476 - Accuracy: 0.3382 - F1: 0.3091
sub_7:Test (Best Model) - Loss: 6.6811 - Accuracy: 0.2794 - F1: 0.2662
sub_7:Test (Best Model) - Loss: 7.8989 - Accuracy: 0.3088 - F1: 0.2776
sub_7:Test (Best Model) - Loss: 8.6219 - Accuracy: 0.3971 - F1: 0.3632
sub_7:Test (Best Model) - Loss: 6.5835 - Accuracy: 0.3235 - F1: 0.3170
sub_8:Test (Best Model) - Loss: 7.4627 - Accuracy: 0.2206 - F1: 0.2217
sub_8:Test (Best Model) - Loss: 7.3701 - Accuracy: 0.3088 - F1: 0.3158
sub_8:Test (Best Model) - Loss: 7.9188 - Accuracy: 0.2941 - F1: 0.2983
sub_8:Test (Best Model) - Loss: 8.3883 - Accuracy: 0.3088 - F1: 0.3105
sub_8:Test (Best Model) - Loss: 7.4089 - Accuracy: 0.2500 - F1: 0.2432
sub_8:Test (Best Model) - Loss: 5.3503 - Accuracy: 0.3382 - F1: 0.3335
sub_8:Test (Best Model) - Loss: 7.7289 - Accuracy: 0.2647 - F1: 0.2534
sub_8:Test (Best Model) - Loss: 7.0069 - Accuracy: 0.3088 - F1: 0.3062
sub_8:Test (Best Model) - Loss: 7.5732 - Accuracy: 0.2353 - F1: 0.2165
sub_8:Test (Best Model) - Loss: 6.5324 - Accuracy: 0.2500 - F1: 0.2462
sub_8:Test (Best Model) - Loss: 9.8991 - Accuracy: 0.2059 - F1: 0.1885
sub_8:Test (Best Model) - Loss: 8.0666 - Accuracy: 0.2353 - F1: 0.2369
sub_8:Test (Best Model) - Loss: 8.0167 - Accuracy: 0.3088 - F1: 0.2974
sub_8:Test (Best Model) - Loss: 8.8674 - Accuracy: 0.3235 - F1: 0.3361
sub_8:Test (Best Model) - Loss: 7.5846 - Accuracy: 0.2206 - F1: 0.1995
sub_9:Test (Best Model) - Loss: 4.8859 - Accuracy: 0.3676 - F1: 0.3871
sub_9:Test (Best Model) - Loss: 4.1596 - Accuracy: 0.3529 - F1: 0.3680
sub_9:Test (Best Model) - Loss: 4.4706 - Accuracy: 0.3824 - F1: 0.4013
sub_9:Test (Best Model) - Loss: 4.1642 - Accuracy: 0.5000 - F1: 0.5251
sub_9:Test (Best Model) - Loss: 3.6910 - Accuracy: 0.5441 - F1: 0.5615
sub_9:Test (Best Model) - Loss: 9.1603 - Accuracy: 0.2794 - F1: 0.2847
sub_9:Test (Best Model) - Loss: 9.6518 - Accuracy: 0.2500 - F1: 0.2717
sub_9:Test (Best Model) - Loss: 7.1511 - Accuracy: 0.2647 - F1: 0.2758
sub_9:Test (Best Model) - Loss: 7.0148 - Accuracy: 0.3088 - F1: 0.3397
sub_9:Test (Best Model) - Loss: 7.2827 - Accuracy: 0.2941 - F1: 0.3254
sub_9:Test (Best Model) - Loss: 6.2832 - Accuracy: 0.3235 - F1: 0.3219
sub_9:Test (Best Model) - Loss: 9.3887 - Accuracy: 0.3235 - F1: 0.3433
sub_9:Test (Best Model) - Loss: 6.2270 - Accuracy: 0.3382 - F1: 0.3808
sub_9:Test (Best Model) - Loss: 9.0052 - Accuracy: 0.3235 - F1: 0.3449
sub_9:Test (Best Model) - Loss: 6.9350 - Accuracy: 0.4265 - F1: 0.4517
sub_10:Test (Best Model) - Loss: 7.6288 - Accuracy: 0.1912 - F1: 0.1723
sub_10:Test (Best Model) - Loss: 7.4082 - Accuracy: 0.2794 - F1: 0.2670
sub_10:Test (Best Model) - Loss: 5.5493 - Accuracy: 0.2353 - F1: 0.2226
sub_10:Test (Best Model) - Loss: 7.5429 - Accuracy: 0.3971 - F1: 0.3902
sub_10:Test (Best Model) - Loss: 6.4919 - Accuracy: 0.3235 - F1: 0.3284
sub_10:Test (Best Model) - Loss: 8.1128 - Accuracy: 0.2353 - F1: 0.2338
sub_10:Test (Best Model) - Loss: 8.8543 - Accuracy: 0.1912 - F1: 0.1912
sub_10:Test (Best Model) - Loss: 7.4189 - Accuracy: 0.3088 - F1: 0.2989
sub_10:Test (Best Model) - Loss: 6.8228 - Accuracy: 0.2941 - F1: 0.2800
sub_10:Test (Best Model) - Loss: 6.5900 - Accuracy: 0.3235 - F1: 0.3182
sub_10:Test (Best Model) - Loss: 8.7864 - Accuracy: 0.2754 - F1: 0.2643
sub_10:Test (Best Model) - Loss: 7.9932 - Accuracy: 0.3333 - F1: 0.3296
sub_10:Test (Best Model) - Loss: 8.4294 - Accuracy: 0.2029 - F1: 0.1911
sub_10:Test (Best Model) - Loss: 7.3938 - Accuracy: 0.3043 - F1: 0.2986
sub_10:Test (Best Model) - Loss: 7.2331 - Accuracy: 0.2029 - F1: 0.1941
sub_11:Test (Best Model) - Loss: 9.0659 - Accuracy: 0.3333 - F1: 0.3071
sub_11:Test (Best Model) - Loss: 6.9522 - Accuracy: 0.2899 - F1: 0.2678
sub_11:Test (Best Model) - Loss: 8.7223 - Accuracy: 0.2899 - F1: 0.2824
sub_11:Test (Best Model) - Loss: 6.7864 - Accuracy: 0.3188 - F1: 0.3204
sub_11:Test (Best Model) - Loss: 8.8251 - Accuracy: 0.2609 - F1: 0.2441
sub_11:Test (Best Model) - Loss: 6.2655 - Accuracy: 0.3913 - F1: 0.3407
sub_11:Test (Best Model) - Loss: 6.9474 - Accuracy: 0.4348 - F1: 0.4047
sub_11:Test (Best Model) - Loss: 7.0016 - Accuracy: 0.4348 - F1: 0.4155
sub_11:Test (Best Model) - Loss: 7.5395 - Accuracy: 0.3623 - F1: 0.3056
sub_11:Test (Best Model) - Loss: 5.4664 - Accuracy: 0.3623 - F1: 0.3489
sub_11:Test (Best Model) - Loss: 4.8090 - Accuracy: 0.2754 - F1: 0.2197
sub_11:Test (Best Model) - Loss: 6.7485 - Accuracy: 0.3188 - F1: 0.3064
sub_11:Test (Best Model) - Loss: 7.0806 - Accuracy: 0.3623 - F1: 0.3077
sub_11:Test (Best Model) - Loss: 4.6251 - Accuracy: 0.3913 - F1: 0.3614
sub_11:Test (Best Model) - Loss: 6.5546 - Accuracy: 0.3043 - F1: 0.2437
sub_12:Test (Best Model) - Loss: 4.3424 - Accuracy: 0.4412 - F1: 0.4180
sub_12:Test (Best Model) - Loss: 6.0678 - Accuracy: 0.3382 - F1: 0.3232
sub_12:Test (Best Model) - Loss: 5.5453 - Accuracy: 0.3382 - F1: 0.3332
sub_12:Test (Best Model) - Loss: 4.7964 - Accuracy: 0.4118 - F1: 0.4092
sub_12:Test (Best Model) - Loss: 4.3223 - Accuracy: 0.4265 - F1: 0.4106
sub_12:Test (Best Model) - Loss: 6.9758 - Accuracy: 0.2754 - F1: 0.2657
sub_12:Test (Best Model) - Loss: 4.8681 - Accuracy: 0.3768 - F1: 0.3650
sub_12:Test (Best Model) - Loss: 5.9251 - Accuracy: 0.3768 - F1: 0.3325
sub_12:Test (Best Model) - Loss: 5.3436 - Accuracy: 0.4058 - F1: 0.3914
sub_12:Test (Best Model) - Loss: 5.1662 - Accuracy: 0.3768 - F1: 0.3693
sub_12:Test (Best Model) - Loss: 6.1191 - Accuracy: 0.4118 - F1: 0.3773
sub_12:Test (Best Model) - Loss: 6.6450 - Accuracy: 0.3971 - F1: 0.3775
sub_12:Test (Best Model) - Loss: 7.1860 - Accuracy: 0.2794 - F1: 0.2619
sub_12:Test (Best Model) - Loss: 7.1242 - Accuracy: 0.3529 - F1: 0.3412
sub_12:Test (Best Model) - Loss: 5.0859 - Accuracy: 0.3824 - F1: 0.3748
sub_13:Test (Best Model) - Loss: 7.3482 - Accuracy: 0.3235 - F1: 0.2890
sub_13:Test (Best Model) - Loss: 8.2177 - Accuracy: 0.3382 - F1: 0.3158
sub_13:Test (Best Model) - Loss: 8.1301 - Accuracy: 0.3235 - F1: 0.3356
sub_13:Test (Best Model) - Loss: 7.9357 - Accuracy: 0.3529 - F1: 0.3759
sub_13:Test (Best Model) - Loss: 6.8365 - Accuracy: 0.4118 - F1: 0.4239
sub_13:Test (Best Model) - Loss: 6.5964 - Accuracy: 0.3333 - F1: 0.3271
sub_13:Test (Best Model) - Loss: 6.1460 - Accuracy: 0.2899 - F1: 0.2680
sub_13:Test (Best Model) - Loss: 7.4672 - Accuracy: 0.2609 - F1: 0.2476
sub_13:Test (Best Model) - Loss: 7.4030 - Accuracy: 0.3478 - F1: 0.3462
sub_13:Test (Best Model) - Loss: 9.1489 - Accuracy: 0.2754 - F1: 0.2510
sub_13:Test (Best Model) - Loss: 8.0463 - Accuracy: 0.2647 - F1: 0.2217
sub_13:Test (Best Model) - Loss: 6.7941 - Accuracy: 0.2794 - F1: 0.2900
sub_13:Test (Best Model) - Loss: 5.3977 - Accuracy: 0.2500 - F1: 0.2595
sub_13:Test (Best Model) - Loss: 5.7305 - Accuracy: 0.2647 - F1: 0.2672
sub_13:Test (Best Model) - Loss: 5.1352 - Accuracy: 0.3235 - F1: 0.3278
sub_14:Test (Best Model) - Loss: 7.1094 - Accuracy: 0.2206 - F1: 0.2246
sub_14:Test (Best Model) - Loss: 6.7227 - Accuracy: 0.1912 - F1: 0.1856
sub_14:Test (Best Model) - Loss: 6.5292 - Accuracy: 0.2647 - F1: 0.2817
sub_14:Test (Best Model) - Loss: 5.1015 - Accuracy: 0.3235 - F1: 0.3408
sub_14:Test (Best Model) - Loss: 6.3997 - Accuracy: 0.2647 - F1: 0.2561
sub_14:Test (Best Model) - Loss: 8.5573 - Accuracy: 0.2500 - F1: 0.2276
sub_14:Test (Best Model) - Loss: 8.3116 - Accuracy: 0.4412 - F1: 0.4548
sub_14:Test (Best Model) - Loss: 7.1926 - Accuracy: 0.2941 - F1: 0.2874
sub_14:Test (Best Model) - Loss: 7.2211 - Accuracy: 0.2941 - F1: 0.2823
sub_14:Test (Best Model) - Loss: 7.9957 - Accuracy: 0.3088 - F1: 0.2634
sub_14:Test (Best Model) - Loss: 6.4986 - Accuracy: 0.3382 - F1: 0.3272
sub_14:Test (Best Model) - Loss: 6.7895 - Accuracy: 0.3382 - F1: 0.3193
sub_14:Test (Best Model) - Loss: 6.9103 - Accuracy: 0.2941 - F1: 0.3088
sub_14:Test (Best Model) - Loss: 5.5548 - Accuracy: 0.3971 - F1: 0.4089
sub_14:Test (Best Model) - Loss: 5.4136 - Accuracy: 0.2794 - F1: 0.2762
sub_15:Test (Best Model) - Loss: 7.8093 - Accuracy: 0.3824 - F1: 0.3666
sub_15:Test (Best Model) - Loss: 11.9465 - Accuracy: 0.2647 - F1: 0.2599
sub_15:Test (Best Model) - Loss: 8.4413 - Accuracy: 0.3824 - F1: 0.3911
sub_15:Test (Best Model) - Loss: 7.6786 - Accuracy: 0.3824 - F1: 0.3919
sub_15:Test (Best Model) - Loss: 8.5769 - Accuracy: 0.3088 - F1: 0.3093
sub_15:Test (Best Model) - Loss: 4.7841 - Accuracy: 0.3824 - F1: 0.4021
sub_15:Test (Best Model) - Loss: 10.7492 - Accuracy: 0.3529 - F1: 0.3389
sub_15:Test (Best Model) - Loss: 5.8345 - Accuracy: 0.4706 - F1: 0.4627
sub_15:Test (Best Model) - Loss: 5.5942 - Accuracy: 0.4706 - F1: 0.4583
sub_15:Test (Best Model) - Loss: 5.0271 - Accuracy: 0.4559 - F1: 0.4351
sub_15:Test (Best Model) - Loss: 7.9181 - Accuracy: 0.3676 - F1: 0.3392
sub_15:Test (Best Model) - Loss: 5.3436 - Accuracy: 0.3971 - F1: 0.4001
sub_15:Test (Best Model) - Loss: 5.6431 - Accuracy: 0.3824 - F1: 0.3873
sub_15:Test (Best Model) - Loss: 6.8098 - Accuracy: 0.3824 - F1: 0.4028
sub_15:Test (Best Model) - Loss: 9.5894 - Accuracy: 0.3529 - F1: 0.3161
sub_16:Test (Best Model) - Loss: 5.8728 - Accuracy: 0.3824 - F1: 0.3550
sub_16:Test (Best Model) - Loss: 4.6209 - Accuracy: 0.3971 - F1: 0.3707
sub_16:Test (Best Model) - Loss: 5.1836 - Accuracy: 0.3529 - F1: 0.3468
sub_16:Test (Best Model) - Loss: 4.3557 - Accuracy: 0.3382 - F1: 0.3380
sub_16:Test (Best Model) - Loss: 3.9012 - Accuracy: 0.4412 - F1: 0.4250
sub_16:Test (Best Model) - Loss: 7.2101 - Accuracy: 0.4265 - F1: 0.4049
sub_16:Test (Best Model) - Loss: 7.4738 - Accuracy: 0.3088 - F1: 0.2920
sub_16:Test (Best Model) - Loss: 7.6410 - Accuracy: 0.2941 - F1: 0.2911
sub_16:Test (Best Model) - Loss: 5.3838 - Accuracy: 0.3676 - F1: 0.3498
sub_16:Test (Best Model) - Loss: 9.8031 - Accuracy: 0.2794 - F1: 0.2728
sub_16:Test (Best Model) - Loss: 5.2230 - Accuracy: 0.4265 - F1: 0.3774
sub_16:Test (Best Model) - Loss: 4.7383 - Accuracy: 0.3824 - F1: 0.3516
sub_16:Test (Best Model) - Loss: 5.3147 - Accuracy: 0.3676 - F1: 0.3377
sub_16:Test (Best Model) - Loss: 8.0832 - Accuracy: 0.3382 - F1: 0.2800
sub_16:Test (Best Model) - Loss: 5.3587 - Accuracy: 0.3382 - F1: 0.3401
sub_17:Test (Best Model) - Loss: 6.0544 - Accuracy: 0.3623 - F1: 0.3553
sub_17:Test (Best Model) - Loss: 3.8916 - Accuracy: 0.3768 - F1: 0.3614
sub_17:Test (Best Model) - Loss: 6.1982 - Accuracy: 0.3478 - F1: 0.3252
sub_17:Test (Best Model) - Loss: 4.0859 - Accuracy: 0.4203 - F1: 0.4269
sub_17:Test (Best Model) - Loss: 4.5851 - Accuracy: 0.3913 - F1: 0.3895
sub_17:Test (Best Model) - Loss: 8.3113 - Accuracy: 0.3043 - F1: 0.2234
sub_17:Test (Best Model) - Loss: 7.9427 - Accuracy: 0.3478 - F1: 0.2864
sub_17:Test (Best Model) - Loss: 5.8351 - Accuracy: 0.3768 - F1: 0.3268
sub_17:Test (Best Model) - Loss: 7.8277 - Accuracy: 0.3623 - F1: 0.3145
sub_17:Test (Best Model) - Loss: 8.0677 - Accuracy: 0.3188 - F1: 0.2828
sub_17:Test (Best Model) - Loss: 5.7916 - Accuracy: 0.4118 - F1: 0.4168
sub_17:Test (Best Model) - Loss: 5.9615 - Accuracy: 0.3529 - F1: 0.3522
sub_17:Test (Best Model) - Loss: 7.1823 - Accuracy: 0.3382 - F1: 0.3357
sub_17:Test (Best Model) - Loss: 6.5580 - Accuracy: 0.3824 - F1: 0.3826
sub_17:Test (Best Model) - Loss: 7.3973 - Accuracy: 0.3382 - F1: 0.3378
sub_18:Test (Best Model) - Loss: 5.4270 - Accuracy: 0.3333 - F1: 0.3184
sub_18:Test (Best Model) - Loss: 5.6375 - Accuracy: 0.2754 - F1: 0.2993
sub_18:Test (Best Model) - Loss: 5.2716 - Accuracy: 0.2609 - F1: 0.2708
sub_18:Test (Best Model) - Loss: 6.0586 - Accuracy: 0.2899 - F1: 0.3139
sub_18:Test (Best Model) - Loss: 5.2115 - Accuracy: 0.2754 - F1: 0.2487
sub_18:Test (Best Model) - Loss: 5.6302 - Accuracy: 0.3088 - F1: 0.3188
sub_18:Test (Best Model) - Loss: 5.4674 - Accuracy: 0.3088 - F1: 0.3084
sub_18:Test (Best Model) - Loss: 6.0151 - Accuracy: 0.3676 - F1: 0.3576
sub_18:Test (Best Model) - Loss: 7.6716 - Accuracy: 0.3088 - F1: 0.3074
sub_18:Test (Best Model) - Loss: 6.1338 - Accuracy: 0.3971 - F1: 0.4160
sub_18:Test (Best Model) - Loss: 6.1286 - Accuracy: 0.2794 - F1: 0.2817
sub_18:Test (Best Model) - Loss: 7.7546 - Accuracy: 0.2794 - F1: 0.2806
sub_18:Test (Best Model) - Loss: 5.9324 - Accuracy: 0.2353 - F1: 0.2522
sub_18:Test (Best Model) - Loss: 6.4057 - Accuracy: 0.3088 - F1: 0.2846
sub_18:Test (Best Model) - Loss: 5.9073 - Accuracy: 0.2941 - F1: 0.2908
sub_19:Test (Best Model) - Loss: 7.5883 - Accuracy: 0.2206 - F1: 0.1959
sub_19:Test (Best Model) - Loss: 7.0373 - Accuracy: 0.2941 - F1: 0.2253
sub_19:Test (Best Model) - Loss: 7.5015 - Accuracy: 0.3088 - F1: 0.2579
sub_19:Test (Best Model) - Loss: 4.7160 - Accuracy: 0.2647 - F1: 0.2377
sub_19:Test (Best Model) - Loss: 7.9461 - Accuracy: 0.3529 - F1: 0.2781
sub_19:Test (Best Model) - Loss: 9.0364 - Accuracy: 0.3088 - F1: 0.3054
sub_19:Test (Best Model) - Loss: 8.2771 - Accuracy: 0.2059 - F1: 0.1973
sub_19:Test (Best Model) - Loss: 8.0990 - Accuracy: 0.2500 - F1: 0.2298
sub_19:Test (Best Model) - Loss: 7.1230 - Accuracy: 0.2941 - F1: 0.2918
sub_19:Test (Best Model) - Loss: 8.5343 - Accuracy: 0.2647 - F1: 0.2544
sub_19:Test (Best Model) - Loss: 6.9899 - Accuracy: 0.2941 - F1: 0.3010
sub_19:Test (Best Model) - Loss: 9.7741 - Accuracy: 0.2500 - F1: 0.2238
sub_19:Test (Best Model) - Loss: 5.4690 - Accuracy: 0.3676 - F1: 0.3292
sub_19:Test (Best Model) - Loss: 8.8752 - Accuracy: 0.2794 - F1: 0.2758
sub_19:Test (Best Model) - Loss: 7.1913 - Accuracy: 0.2941 - F1: 0.3056
sub_20:Test (Best Model) - Loss: 6.2251 - Accuracy: 0.3824 - F1: 0.3788
sub_20:Test (Best Model) - Loss: 5.3983 - Accuracy: 0.4412 - F1: 0.4322
sub_20:Test (Best Model) - Loss: 6.5036 - Accuracy: 0.3676 - F1: 0.3624
sub_20:Test (Best Model) - Loss: 6.5628 - Accuracy: 0.3971 - F1: 0.3906
sub_20:Test (Best Model) - Loss: 5.2502 - Accuracy: 0.4853 - F1: 0.4703
sub_20:Test (Best Model) - Loss: 5.8540 - Accuracy: 0.3235 - F1: 0.3311
sub_20:Test (Best Model) - Loss: 6.6761 - Accuracy: 0.3824 - F1: 0.3881
sub_20:Test (Best Model) - Loss: 7.6984 - Accuracy: 0.4265 - F1: 0.4392
sub_20:Test (Best Model) - Loss: 6.7416 - Accuracy: 0.3088 - F1: 0.3037
sub_20:Test (Best Model) - Loss: 6.2718 - Accuracy: 0.3088 - F1: 0.3189
sub_20:Test (Best Model) - Loss: 7.0846 - Accuracy: 0.3623 - F1: 0.3541
sub_20:Test (Best Model) - Loss: 7.0619 - Accuracy: 0.3478 - F1: 0.3494
sub_20:Test (Best Model) - Loss: 6.1796 - Accuracy: 0.4638 - F1: 0.4664
sub_20:Test (Best Model) - Loss: 5.9662 - Accuracy: 0.4348 - F1: 0.4297
sub_20:Test (Best Model) - Loss: 5.9422 - Accuracy: 0.3768 - F1: 0.3838
sub_21:Test (Best Model) - Loss: 6.9564 - Accuracy: 0.3235 - F1: 0.3065
sub_21:Test (Best Model) - Loss: 8.1903 - Accuracy: 0.3529 - F1: 0.3364
sub_21:Test (Best Model) - Loss: 9.1119 - Accuracy: 0.3971 - F1: 0.3609
sub_21:Test (Best Model) - Loss: 6.5191 - Accuracy: 0.3676 - F1: 0.3345
sub_21:Test (Best Model) - Loss: 9.7655 - Accuracy: 0.3235 - F1: 0.3175
sub_21:Test (Best Model) - Loss: 5.9053 - Accuracy: 0.3824 - F1: 0.3812
sub_21:Test (Best Model) - Loss: 7.8290 - Accuracy: 0.2794 - F1: 0.2780
sub_21:Test (Best Model) - Loss: 5.7739 - Accuracy: 0.2941 - F1: 0.2646
sub_21:Test (Best Model) - Loss: 5.3184 - Accuracy: 0.3529 - F1: 0.3175
sub_21:Test (Best Model) - Loss: 5.7507 - Accuracy: 0.3529 - F1: 0.3170
sub_21:Test (Best Model) - Loss: 5.5051 - Accuracy: 0.2941 - F1: 0.3001
sub_21:Test (Best Model) - Loss: 6.3907 - Accuracy: 0.3382 - F1: 0.2786
sub_21:Test (Best Model) - Loss: 7.2593 - Accuracy: 0.3382 - F1: 0.3170
sub_21:Test (Best Model) - Loss: 6.0449 - Accuracy: 0.4265 - F1: 0.3673
sub_21:Test (Best Model) - Loss: 4.7341 - Accuracy: 0.2794 - F1: 0.2605
sub_22:Test (Best Model) - Loss: 8.7098 - Accuracy: 0.3235 - F1: 0.3241
sub_22:Test (Best Model) - Loss: 7.0144 - Accuracy: 0.3824 - F1: 0.3916
sub_22:Test (Best Model) - Loss: 6.7408 - Accuracy: 0.3088 - F1: 0.3068
sub_22:Test (Best Model) - Loss: 5.9774 - Accuracy: 0.3382 - F1: 0.3299
sub_22:Test (Best Model) - Loss: 6.9083 - Accuracy: 0.3824 - F1: 0.3862
sub_22:Test (Best Model) - Loss: 4.6890 - Accuracy: 0.3478 - F1: 0.3300
sub_22:Test (Best Model) - Loss: 3.7542 - Accuracy: 0.3768 - F1: 0.3692
sub_22:Test (Best Model) - Loss: 5.5082 - Accuracy: 0.3333 - F1: 0.3408
sub_22:Test (Best Model) - Loss: 4.9089 - Accuracy: 0.2754 - F1: 0.2605
sub_22:Test (Best Model) - Loss: 4.7365 - Accuracy: 0.3478 - F1: 0.3519
sub_22:Test (Best Model) - Loss: 4.9262 - Accuracy: 0.3676 - F1: 0.3684
sub_22:Test (Best Model) - Loss: 5.5580 - Accuracy: 0.2941 - F1: 0.2819
sub_22:Test (Best Model) - Loss: 5.6092 - Accuracy: 0.2647 - F1: 0.2424
sub_22:Test (Best Model) - Loss: 4.7689 - Accuracy: 0.3088 - F1: 0.2895
sub_22:Test (Best Model) - Loss: 4.9309 - Accuracy: 0.3824 - F1: 0.4009
sub_23:Test (Best Model) - Loss: 7.9690 - Accuracy: 0.2464 - F1: 0.2239
sub_23:Test (Best Model) - Loss: 5.3705 - Accuracy: 0.3913 - F1: 0.3870
sub_23:Test (Best Model) - Loss: 5.9656 - Accuracy: 0.2754 - F1: 0.2589
sub_23:Test (Best Model) - Loss: 4.7290 - Accuracy: 0.3623 - F1: 0.3451
sub_23:Test (Best Model) - Loss: 5.9094 - Accuracy: 0.3043 - F1: 0.3088
sub_23:Test (Best Model) - Loss: 6.7493 - Accuracy: 0.3235 - F1: 0.2715
sub_23:Test (Best Model) - Loss: 4.2938 - Accuracy: 0.3529 - F1: 0.3506
sub_23:Test (Best Model) - Loss: 6.2663 - Accuracy: 0.2500 - F1: 0.2489
sub_23:Test (Best Model) - Loss: 4.0565 - Accuracy: 0.3088 - F1: 0.3026
sub_23:Test (Best Model) - Loss: 4.4847 - Accuracy: 0.3529 - F1: 0.3308
sub_23:Test (Best Model) - Loss: 12.8119 - Accuracy: 0.2609 - F1: 0.2054
sub_23:Test (Best Model) - Loss: 9.5587 - Accuracy: 0.3043 - F1: 0.3091
sub_23:Test (Best Model) - Loss: 9.1113 - Accuracy: 0.2899 - F1: 0.2686
sub_23:Test (Best Model) - Loss: 9.7769 - Accuracy: 0.3623 - F1: 0.3448
sub_23:Test (Best Model) - Loss: 8.7361 - Accuracy: 0.2754 - F1: 0.2146
sub_24:Test (Best Model) - Loss: 9.0635 - Accuracy: 0.2206 - F1: 0.2066
sub_24:Test (Best Model) - Loss: 6.2118 - Accuracy: 0.3529 - F1: 0.3565
sub_24:Test (Best Model) - Loss: 6.9657 - Accuracy: 0.2500 - F1: 0.2345
sub_24:Test (Best Model) - Loss: 6.9686 - Accuracy: 0.3088 - F1: 0.3055
sub_24:Test (Best Model) - Loss: 4.1760 - Accuracy: 0.3676 - F1: 0.3673
sub_24:Test (Best Model) - Loss: 4.2638 - Accuracy: 0.3824 - F1: 0.3833
sub_24:Test (Best Model) - Loss: 5.0287 - Accuracy: 0.3382 - F1: 0.3356
sub_24:Test (Best Model) - Loss: 4.3317 - Accuracy: 0.3676 - F1: 0.3502
sub_24:Test (Best Model) - Loss: 4.6604 - Accuracy: 0.4118 - F1: 0.4058
sub_24:Test (Best Model) - Loss: 4.6480 - Accuracy: 0.3088 - F1: 0.2666
sub_24:Test (Best Model) - Loss: 5.3013 - Accuracy: 0.2941 - F1: 0.2901
sub_24:Test (Best Model) - Loss: 5.9529 - Accuracy: 0.2794 - F1: 0.2675
sub_24:Test (Best Model) - Loss: 5.3036 - Accuracy: 0.3088 - F1: 0.3082
sub_24:Test (Best Model) - Loss: 6.0061 - Accuracy: 0.2794 - F1: 0.2875
sub_24:Test (Best Model) - Loss: 5.7296 - Accuracy: 0.3088 - F1: 0.2855
sub_25:Test (Best Model) - Loss: 6.5136 - Accuracy: 0.3623 - F1: 0.3250
sub_25:Test (Best Model) - Loss: 5.9896 - Accuracy: 0.3913 - F1: 0.3854
sub_25:Test (Best Model) - Loss: 4.9921 - Accuracy: 0.3623 - F1: 0.3375
sub_25:Test (Best Model) - Loss: 5.8987 - Accuracy: 0.3623 - F1: 0.3415
sub_25:Test (Best Model) - Loss: 6.5815 - Accuracy: 0.2899 - F1: 0.2707
sub_25:Test (Best Model) - Loss: 4.9200 - Accuracy: 0.2941 - F1: 0.2790
sub_25:Test (Best Model) - Loss: 8.4089 - Accuracy: 0.2794 - F1: 0.2755
sub_25:Test (Best Model) - Loss: 4.2640 - Accuracy: 0.3971 - F1: 0.3567
sub_25:Test (Best Model) - Loss: 5.5090 - Accuracy: 0.4559 - F1: 0.4038
sub_25:Test (Best Model) - Loss: 4.4417 - Accuracy: 0.4412 - F1: 0.3594
sub_25:Test (Best Model) - Loss: 6.3795 - Accuracy: 0.3971 - F1: 0.3810
sub_25:Test (Best Model) - Loss: 7.0858 - Accuracy: 0.3971 - F1: 0.3655
sub_25:Test (Best Model) - Loss: 5.8804 - Accuracy: 0.3824 - F1: 0.3385
sub_25:Test (Best Model) - Loss: 5.3754 - Accuracy: 0.3529 - F1: 0.3175
sub_25:Test (Best Model) - Loss: 5.5087 - Accuracy: 0.3529 - F1: 0.3123
sub_26:Test (Best Model) - Loss: 4.7546 - Accuracy: 0.4348 - F1: 0.4419
sub_26:Test (Best Model) - Loss: 6.3307 - Accuracy: 0.2609 - F1: 0.2539
sub_26:Test (Best Model) - Loss: 4.2889 - Accuracy: 0.3623 - F1: 0.3639
sub_26:Test (Best Model) - Loss: 3.3044 - Accuracy: 0.4348 - F1: 0.4538
sub_26:Test (Best Model) - Loss: 5.8511 - Accuracy: 0.4348 - F1: 0.4308
sub_26:Test (Best Model) - Loss: 4.5970 - Accuracy: 0.2647 - F1: 0.2609
sub_26:Test (Best Model) - Loss: 6.8318 - Accuracy: 0.2059 - F1: 0.2179
sub_26:Test (Best Model) - Loss: 4.9529 - Accuracy: 0.3382 - F1: 0.3479
sub_26:Test (Best Model) - Loss: 5.9792 - Accuracy: 0.3382 - F1: 0.3458
sub_26:Test (Best Model) - Loss: 5.4152 - Accuracy: 0.2500 - F1: 0.2787
sub_26:Test (Best Model) - Loss: 5.9050 - Accuracy: 0.4853 - F1: 0.4912
sub_26:Test (Best Model) - Loss: 7.4676 - Accuracy: 0.3529 - F1: 0.3686
sub_26:Test (Best Model) - Loss: 7.2019 - Accuracy: 0.4706 - F1: 0.4801
sub_26:Test (Best Model) - Loss: 6.3113 - Accuracy: 0.5000 - F1: 0.4985
sub_26:Test (Best Model) - Loss: 5.2517 - Accuracy: 0.4706 - F1: 0.4706
sub_27:Test (Best Model) - Loss: 6.0544 - Accuracy: 0.3623 - F1: 0.3553
sub_27:Test (Best Model) - Loss: 3.8916 - Accuracy: 0.3768 - F1: 0.3614
sub_27:Test (Best Model) - Loss: 6.1982 - Accuracy: 0.3478 - F1: 0.3252
sub_27:Test (Best Model) - Loss: 4.0859 - Accuracy: 0.4203 - F1: 0.4269
sub_27:Test (Best Model) - Loss: 4.5851 - Accuracy: 0.3913 - F1: 0.3895
sub_27:Test (Best Model) - Loss: 8.3113 - Accuracy: 0.3043 - F1: 0.2234
sub_27:Test (Best Model) - Loss: 7.9427 - Accuracy: 0.3478 - F1: 0.2864
sub_27:Test (Best Model) - Loss: 5.8351 - Accuracy: 0.3768 - F1: 0.3268
sub_27:Test (Best Model) - Loss: 7.8277 - Accuracy: 0.3623 - F1: 0.3145
sub_27:Test (Best Model) - Loss: 8.0677 - Accuracy: 0.3188 - F1: 0.2828
sub_27:Test (Best Model) - Loss: 5.7916 - Accuracy: 0.4118 - F1: 0.4168
sub_27:Test (Best Model) - Loss: 5.9615 - Accuracy: 0.3529 - F1: 0.3522
sub_27:Test (Best Model) - Loss: 7.1823 - Accuracy: 0.3382 - F1: 0.3357
sub_27:Test (Best Model) - Loss: 6.5580 - Accuracy: 0.3824 - F1: 0.3826
sub_27:Test (Best Model) - Loss: 7.3973 - Accuracy: 0.3382 - F1: 0.3378
sub_28:Test (Best Model) - Loss: 7.4770 - Accuracy: 0.2500 - F1: 0.2330
sub_28:Test (Best Model) - Loss: 8.0193 - Accuracy: 0.2206 - F1: 0.2173
sub_28:Test (Best Model) - Loss: 9.4509 - Accuracy: 0.2941 - F1: 0.2694
sub_28:Test (Best Model) - Loss: 7.3031 - Accuracy: 0.2941 - F1: 0.2552
sub_28:Test (Best Model) - Loss: 8.0589 - Accuracy: 0.2941 - F1: 0.2723
sub_28:Test (Best Model) - Loss: 17.3110 - Accuracy: 0.1912 - F1: 0.1837
sub_28:Test (Best Model) - Loss: 13.8836 - Accuracy: 0.1912 - F1: 0.1797
sub_28:Test (Best Model) - Loss: 13.2195 - Accuracy: 0.1912 - F1: 0.1961
sub_28:Test (Best Model) - Loss: 15.6210 - Accuracy: 0.2353 - F1: 0.2120
sub_28:Test (Best Model) - Loss: 12.2455 - Accuracy: 0.2353 - F1: 0.2214
sub_28:Test (Best Model) - Loss: 4.4683 - Accuracy: 0.2941 - F1: 0.2829
sub_28:Test (Best Model) - Loss: 4.2386 - Accuracy: 0.2794 - F1: 0.2758
sub_28:Test (Best Model) - Loss: 3.0303 - Accuracy: 0.4118 - F1: 0.4163
sub_28:Test (Best Model) - Loss: 3.5662 - Accuracy: 0.3971 - F1: 0.3862
sub_28:Test (Best Model) - Loss: 4.2942 - Accuracy: 0.3382 - F1: 0.3127
sub_29:Test (Best Model) - Loss: 8.3302 - Accuracy: 0.5000 - F1: 0.5009
sub_29:Test (Best Model) - Loss: 8.4531 - Accuracy: 0.2941 - F1: 0.3150
sub_29:Test (Best Model) - Loss: 7.6547 - Accuracy: 0.4412 - F1: 0.4579
sub_29:Test (Best Model) - Loss: 6.9953 - Accuracy: 0.4559 - F1: 0.4804
sub_29:Test (Best Model) - Loss: 6.6408 - Accuracy: 0.4706 - F1: 0.4921
sub_29:Test (Best Model) - Loss: 4.2167 - Accuracy: 0.4265 - F1: 0.4364
sub_29:Test (Best Model) - Loss: 4.2661 - Accuracy: 0.4412 - F1: 0.4553
sub_29:Test (Best Model) - Loss: 4.5652 - Accuracy: 0.4265 - F1: 0.4345
sub_29:Test (Best Model) - Loss: 4.4745 - Accuracy: 0.4412 - F1: 0.4550
sub_29:Test (Best Model) - Loss: 4.0871 - Accuracy: 0.4118 - F1: 0.4398
sub_29:Test (Best Model) - Loss: 4.4896 - Accuracy: 0.4928 - F1: 0.4994
sub_29:Test (Best Model) - Loss: 6.0942 - Accuracy: 0.4493 - F1: 0.4587
sub_29:Test (Best Model) - Loss: 4.6387 - Accuracy: 0.5072 - F1: 0.5274
sub_29:Test (Best Model) - Loss: 4.4523 - Accuracy: 0.5072 - F1: 0.5245
sub_29:Test (Best Model) - Loss: 4.5521 - Accuracy: 0.5072 - F1: 0.5236

=== Summary Results ===

acc: 33.69 ± 4.28
F1: 32.66 ± 4.69
acc-in: 40.28 ± 4.23
F1-in: 38.45 ± 4.39
