lr: 1e-06
sub_22:Test (Best Model) - Loss: 1.1349 - Accuracy: 0.5441 - F1: 0.5663
sub_12:Test (Best Model) - Loss: 1.6704 - Accuracy: 0.1471 - F1: 0.1447
sub_2:Test (Best Model) - Loss: 1.4603 - Accuracy: 0.2174 - F1: 0.1396
sub_25:Test (Best Model) - Loss: 1.1841 - Accuracy: 0.3913 - F1: 0.3746
sub_5:Test (Best Model) - Loss: 1.3731 - Accuracy: 0.3382 - F1: 0.2980
sub_17:Test (Best Model) - Loss: 1.4627 - Accuracy: 0.2899 - F1: 0.2341
sub_27:Test (Best Model) - Loss: 1.4627 - Accuracy: 0.2899 - F1: 0.2341
sub_1:Test (Best Model) - Loss: 1.3195 - Accuracy: 0.3824 - F1: 0.3699
sub_22:Test (Best Model) - Loss: 1.4352 - Accuracy: 0.2794 - F1: 0.2686
sub_20:Test (Best Model) - Loss: 1.3804 - Accuracy: 0.2500 - F1: 0.2288
sub_12:Test (Best Model) - Loss: 1.2968 - Accuracy: 0.3529 - F1: 0.3377
sub_23:Test (Best Model) - Loss: 1.2347 - Accuracy: 0.3768 - F1: 0.3823
sub_19:Test (Best Model) - Loss: 1.3048 - Accuracy: 0.3676 - F1: 0.3221
sub_13:Test (Best Model) - Loss: 1.5152 - Accuracy: 0.2500 - F1: 0.1989
sub_9:Test (Best Model) - Loss: 1.5249 - Accuracy: 0.2500 - F1: 0.2402
sub_29:Test (Best Model) - Loss: 1.2168 - Accuracy: 0.4118 - F1: 0.3975
sub_16:Test (Best Model) - Loss: 1.5697 - Accuracy: 0.2206 - F1: 0.1929
sub_10:Test (Best Model) - Loss: 1.3000 - Accuracy: 0.3088 - F1: 0.2811
sub_28:Test (Best Model) - Loss: 1.4395 - Accuracy: 0.2206 - F1: 0.2540
sub_11:Test (Best Model) - Loss: 1.4185 - Accuracy: 0.2029 - F1: 0.1955
sub_7:Test (Best Model) - Loss: 1.3090 - Accuracy: 0.3235 - F1: 0.3125
sub_4:Test (Best Model) - Loss: 1.2989 - Accuracy: 0.3333 - F1: 0.3068
sub_18:Test (Best Model) - Loss: 1.3110 - Accuracy: 0.3478 - F1: 0.3316
sub_25:Test (Best Model) - Loss: 1.3130 - Accuracy: 0.3623 - F1: 0.3617
sub_24:Test (Best Model) - Loss: 1.4139 - Accuracy: 0.3676 - F1: 0.3255
sub_22:Test (Best Model) - Loss: 1.4818 - Accuracy: 0.2794 - F1: 0.1724
sub_14:Test (Best Model) - Loss: 1.0988 - Accuracy: 0.4853 - F1: 0.4622
sub_2:Test (Best Model) - Loss: 1.2640 - Accuracy: 0.3478 - F1: 0.3324
sub_6:Test (Best Model) - Loss: 1.2958 - Accuracy: 0.4853 - F1: 0.4282
sub_15:Test (Best Model) - Loss: 1.4105 - Accuracy: 0.3235 - F1: 0.3009
sub_8:Test (Best Model) - Loss: 1.4590 - Accuracy: 0.2647 - F1: 0.2452
sub_26:Test (Best Model) - Loss: 1.2733 - Accuracy: 0.4058 - F1: 0.3616
sub_10:Test (Best Model) - Loss: 1.5458 - Accuracy: 0.1765 - F1: 0.1518
sub_28:Test (Best Model) - Loss: 1.4964 - Accuracy: 0.2794 - F1: 0.2599
sub_16:Test (Best Model) - Loss: 1.4349 - Accuracy: 0.2647 - F1: 0.2434
sub_3:Test (Best Model) - Loss: 1.1006 - Accuracy: 0.5588 - F1: 0.5468
sub_21:Test (Best Model) - Loss: 1.1298 - Accuracy: 0.5735 - F1: 0.5217
sub_4:Test (Best Model) - Loss: 1.4713 - Accuracy: 0.2174 - F1: 0.2055
sub_22:Test (Best Model) - Loss: 1.5235 - Accuracy: 0.1765 - F1: 0.1242
sub_14:Test (Best Model) - Loss: 1.4852 - Accuracy: 0.3824 - F1: 0.2832
sub_23:Test (Best Model) - Loss: 1.3111 - Accuracy: 0.4058 - F1: 0.3444
sub_25:Test (Best Model) - Loss: 1.6983 - Accuracy: 0.3333 - F1: 0.2118
sub_19:Test (Best Model) - Loss: 1.6467 - Accuracy: 0.2059 - F1: 0.1399
sub_24:Test (Best Model) - Loss: 1.3582 - Accuracy: 0.3676 - F1: 0.3382
sub_15:Test (Best Model) - Loss: 1.3240 - Accuracy: 0.3529 - F1: 0.3649
sub_17:Test (Best Model) - Loss: 1.2207 - Accuracy: 0.4928 - F1: 0.4971
sub_27:Test (Best Model) - Loss: 1.2207 - Accuracy: 0.4928 - F1: 0.4971
sub_10:Test (Best Model) - Loss: 1.6065 - Accuracy: 0.2941 - F1: 0.2583
sub_1:Test (Best Model) - Loss: 1.2615 - Accuracy: 0.4412 - F1: 0.4422
sub_7:Test (Best Model) - Loss: 1.2714 - Accuracy: 0.4559 - F1: 0.3871
sub_16:Test (Best Model) - Loss: 1.8048 - Accuracy: 0.2500 - F1: 0.1671
sub_2:Test (Best Model) - Loss: 1.3638 - Accuracy: 0.3478 - F1: 0.2671
sub_18:Test (Best Model) - Loss: 1.2878 - Accuracy: 0.3913 - F1: 0.3783
sub_28:Test (Best Model) - Loss: 1.6568 - Accuracy: 0.2353 - F1: 0.1435
sub_24:Test (Best Model) - Loss: 1.5503 - Accuracy: 0.2941 - F1: 0.1858
sub_20:Test (Best Model) - Loss: 1.4711 - Accuracy: 0.2794 - F1: 0.2195
sub_12:Test (Best Model) - Loss: 1.2405 - Accuracy: 0.3971 - F1: 0.3015
sub_19:Test (Best Model) - Loss: 1.3139 - Accuracy: 0.4265 - F1: 0.2811
sub_9:Test (Best Model) - Loss: 1.3158 - Accuracy: 0.4265 - F1: 0.4052
sub_5:Test (Best Model) - Loss: 1.3103 - Accuracy: 0.3382 - F1: 0.2642
sub_23:Test (Best Model) - Loss: 1.3745 - Accuracy: 0.4348 - F1: 0.3615
sub_13:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.3676 - F1: 0.2684
sub_29:Test (Best Model) - Loss: 1.3777 - Accuracy: 0.3088 - F1: 0.2651
sub_11:Test (Best Model) - Loss: 1.2663 - Accuracy: 0.4493 - F1: 0.4391
sub_22:Test (Best Model) - Loss: 1.4370 - Accuracy: 0.4118 - F1: 0.3239
sub_2:Test (Best Model) - Loss: 1.5208 - Accuracy: 0.2754 - F1: 0.2010
sub_26:Test (Best Model) - Loss: 1.3732 - Accuracy: 0.3188 - F1: 0.2788
sub_28:Test (Best Model) - Loss: 1.3632 - Accuracy: 0.3088 - F1: 0.2412
sub_8:Test (Best Model) - Loss: 1.4183 - Accuracy: 0.3088 - F1: 0.2934
sub_6:Test (Best Model) - Loss: 1.2223 - Accuracy: 0.4412 - F1: 0.4029
sub_12:Test (Best Model) - Loss: 1.4090 - Accuracy: 0.2353 - F1: 0.1769
sub_10:Test (Best Model) - Loss: 1.2523 - Accuracy: 0.4559 - F1: 0.3651
sub_16:Test (Best Model) - Loss: 1.3430 - Accuracy: 0.3971 - F1: 0.2753
sub_21:Test (Best Model) - Loss: 1.2836 - Accuracy: 0.4412 - F1: 0.4357
sub_2:Test (Best Model) - Loss: 1.5803 - Accuracy: 0.2754 - F1: 0.1319
sub_7:Test (Best Model) - Loss: 1.3363 - Accuracy: 0.4853 - F1: 0.4253
sub_8:Test (Best Model) - Loss: 1.4972 - Accuracy: 0.2500 - F1: 0.1974
sub_25:Test (Best Model) - Loss: 1.3551 - Accuracy: 0.4928 - F1: 0.3727
sub_28:Test (Best Model) - Loss: 1.5336 - Accuracy: 0.2794 - F1: 0.1511
sub_17:Test (Best Model) - Loss: 1.4790 - Accuracy: 0.2609 - F1: 0.2428
sub_27:Test (Best Model) - Loss: 1.4790 - Accuracy: 0.2609 - F1: 0.2428
sub_19:Test (Best Model) - Loss: 1.3623 - Accuracy: 0.4118 - F1: 0.3184
sub_12:Test (Best Model) - Loss: 1.7630 - Accuracy: 0.1471 - F1: 0.0894
sub_23:Test (Best Model) - Loss: 1.5286 - Accuracy: 0.2319 - F1: 0.1844
sub_4:Test (Best Model) - Loss: 1.2095 - Accuracy: 0.5217 - F1: 0.4787
sub_16:Test (Best Model) - Loss: 1.7494 - Accuracy: 0.1618 - F1: 0.1105
sub_3:Test (Best Model) - Loss: 1.1978 - Accuracy: 0.4265 - F1: 0.4008
sub_9:Test (Best Model) - Loss: 1.3673 - Accuracy: 0.2647 - F1: 0.1430
sub_25:Test (Best Model) - Loss: 1.4989 - Accuracy: 0.3623 - F1: 0.2689
sub_10:Test (Best Model) - Loss: 1.5483 - Accuracy: 0.2794 - F1: 0.1715
sub_18:Test (Best Model) - Loss: 1.3113 - Accuracy: 0.3768 - F1: 0.3149
sub_20:Test (Best Model) - Loss: 1.3099 - Accuracy: 0.4412 - F1: 0.3378
sub_11:Test (Best Model) - Loss: 1.6534 - Accuracy: 0.2754 - F1: 0.1685
sub_27:Test (Best Model) - Loss: 1.2244 - Accuracy: 0.4493 - F1: 0.3850
sub_22:Test (Best Model) - Loss: 1.2886 - Accuracy: 0.4058 - F1: 0.3734
sub_24:Test (Best Model) - Loss: 1.3354 - Accuracy: 0.3235 - F1: 0.2584
sub_14:Test (Best Model) - Loss: 1.6637 - Accuracy: 0.1029 - F1: 0.0925
sub_17:Test (Best Model) - Loss: 1.2244 - Accuracy: 0.4493 - F1: 0.3850
sub_13:Test (Best Model) - Loss: 1.5472 - Accuracy: 0.3382 - F1: 0.2280
sub_23:Test (Best Model) - Loss: 1.7190 - Accuracy: 0.3333 - F1: 0.2451
sub_29:Test (Best Model) - Loss: 1.5290 - Accuracy: 0.2500 - F1: 0.1076
sub_7:Test (Best Model) - Loss: 1.4422 - Accuracy: 0.3088 - F1: 0.2045
sub_2:Test (Best Model) - Loss: 1.3802 - Accuracy: 0.3235 - F1: 0.2557
sub_4:Test (Best Model) - Loss: 1.5185 - Accuracy: 0.3623 - F1: 0.2684
sub_1:Test (Best Model) - Loss: 1.2316 - Accuracy: 0.4412 - F1: 0.3774
sub_16:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.3382 - F1: 0.3335
sub_3:Test (Best Model) - Loss: 1.6280 - Accuracy: 0.2353 - F1: 0.0964
sub_28:Test (Best Model) - Loss: 1.4998 - Accuracy: 0.1176 - F1: 0.1129
sub_12:Test (Best Model) - Loss: 1.5197 - Accuracy: 0.2174 - F1: 0.2052
sub_19:Test (Best Model) - Loss: 1.8447 - Accuracy: 0.1324 - F1: 0.0847
sub_20:Test (Best Model) - Loss: 1.3173 - Accuracy: 0.4265 - F1: 0.3720
sub_26:Test (Best Model) - Loss: 1.1951 - Accuracy: 0.4783 - F1: 0.4294
sub_6:Test (Best Model) - Loss: 1.5751 - Accuracy: 0.2059 - F1: 0.1466
sub_8:Test (Best Model) - Loss: 1.5229 - Accuracy: 0.2794 - F1: 0.1736
sub_22:Test (Best Model) - Loss: 1.5057 - Accuracy: 0.2464 - F1: 0.1393
sub_13:Test (Best Model) - Loss: 1.5105 - Accuracy: 0.1618 - F1: 0.1056
sub_5:Test (Best Model) - Loss: 1.1831 - Accuracy: 0.2941 - F1: 0.1825
sub_21:Test (Best Model) - Loss: 1.2354 - Accuracy: 0.4559 - F1: 0.3975
sub_2:Test (Best Model) - Loss: 1.5071 - Accuracy: 0.3235 - F1: 0.1975
sub_7:Test (Best Model) - Loss: 1.3908 - Accuracy: 0.2794 - F1: 0.1737
sub_29:Test (Best Model) - Loss: 1.5520 - Accuracy: 0.2353 - F1: 0.1924
sub_23:Test (Best Model) - Loss: 1.7640 - Accuracy: 0.1029 - F1: 0.0802
sub_16:Test (Best Model) - Loss: 1.4513 - Accuracy: 0.2794 - F1: 0.1478
sub_27:Test (Best Model) - Loss: 1.4341 - Accuracy: 0.3043 - F1: 0.1786
sub_1:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.3824 - F1: 0.2721
sub_17:Test (Best Model) - Loss: 1.4341 - Accuracy: 0.3043 - F1: 0.1786
sub_6:Test (Best Model) - Loss: 1.5632 - Accuracy: 0.2500 - F1: 0.1062
sub_4:Test (Best Model) - Loss: 1.6322 - Accuracy: 0.2319 - F1: 0.1708
sub_20:Test (Best Model) - Loss: 1.6306 - Accuracy: 0.2794 - F1: 0.1795
sub_14:Test (Best Model) - Loss: 1.6071 - Accuracy: 0.2353 - F1: 0.1292
sub_18:Test (Best Model) - Loss: 1.4451 - Accuracy: 0.2899 - F1: 0.2663
sub_12:Test (Best Model) - Loss: 1.5293 - Accuracy: 0.2609 - F1: 0.1393
sub_10:Test (Best Model) - Loss: 1.1980 - Accuracy: 0.5441 - F1: 0.4594
sub_15:Test (Best Model) - Loss: 1.0804 - Accuracy: 0.5588 - F1: 0.5340
sub_22:Test (Best Model) - Loss: 1.4557 - Accuracy: 0.3623 - F1: 0.2783
sub_26:Test (Best Model) - Loss: 1.5375 - Accuracy: 0.1884 - F1: 0.1542
sub_28:Test (Best Model) - Loss: 1.8266 - Accuracy: 0.2647 - F1: 0.1111
sub_5:Test (Best Model) - Loss: 1.5304 - Accuracy: 0.2206 - F1: 0.1485
sub_13:Test (Best Model) - Loss: 1.7967 - Accuracy: 0.2500 - F1: 0.1090
sub_11:Test (Best Model) - Loss: 1.5748 - Accuracy: 0.2029 - F1: 0.1297
sub_1:Test (Best Model) - Loss: 1.8487 - Accuracy: 0.1765 - F1: 0.1215
sub_8:Test (Best Model) - Loss: 1.5504 - Accuracy: 0.2794 - F1: 0.1510
sub_29:Test (Best Model) - Loss: 1.7736 - Accuracy: 0.1618 - F1: 0.0733
sub_9:Test (Best Model) - Loss: 1.0983 - Accuracy: 0.5441 - F1: 0.4362
sub_25:Test (Best Model) - Loss: 1.3633 - Accuracy: 0.2794 - F1: 0.2195
sub_6:Test (Best Model) - Loss: 1.6277 - Accuracy: 0.2500 - F1: 0.1049
sub_24:Test (Best Model) - Loss: 1.6977 - Accuracy: 0.2206 - F1: 0.0949
sub_18:Test (Best Model) - Loss: 1.7778 - Accuracy: 0.2609 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.5623 - Accuracy: 0.3235 - F1: 0.2147
sub_4:Test (Best Model) - Loss: 1.1392 - Accuracy: 0.5797 - F1: 0.5582
sub_3:Test (Best Model) - Loss: 1.3993 - Accuracy: 0.3235 - F1: 0.2204
sub_28:Test (Best Model) - Loss: 1.6302 - Accuracy: 0.1618 - F1: 0.1565
sub_21:Test (Best Model) - Loss: 1.4066 - Accuracy: 0.3088 - F1: 0.2517
sub_13:Test (Best Model) - Loss: 1.4835 - Accuracy: 0.1449 - F1: 0.1024
sub_23:Test (Best Model) - Loss: 1.3559 - Accuracy: 0.2059 - F1: 0.1206
sub_12:Test (Best Model) - Loss: 1.4357 - Accuracy: 0.2609 - F1: 0.2203
sub_19:Test (Best Model) - Loss: 1.4761 - Accuracy: 0.3088 - F1: 0.2551
sub_11:Test (Best Model) - Loss: 1.6674 - Accuracy: 0.2029 - F1: 0.0854
sub_14:Test (Best Model) - Loss: 1.6643 - Accuracy: 0.3088 - F1: 0.1779
sub_6:Test (Best Model) - Loss: 1.5337 - Accuracy: 0.2319 - F1: 0.1968
sub_1:Test (Best Model) - Loss: 1.3648 - Accuracy: 0.3913 - F1: 0.3164
sub_8:Test (Best Model) - Loss: 1.3678 - Accuracy: 0.2941 - F1: 0.2740
sub_7:Test (Best Model) - Loss: 1.3232 - Accuracy: 0.3235 - F1: 0.3214
sub_27:Test (Best Model) - Loss: 1.4387 - Accuracy: 0.2754 - F1: 0.1953
sub_2:Test (Best Model) - Loss: 1.6440 - Accuracy: 0.2941 - F1: 0.1620
sub_25:Test (Best Model) - Loss: 1.5264 - Accuracy: 0.2500 - F1: 0.1350
sub_17:Test (Best Model) - Loss: 1.4387 - Accuracy: 0.2754 - F1: 0.1953
sub_4:Test (Best Model) - Loss: 1.4430 - Accuracy: 0.3188 - F1: 0.2088
sub_26:Test (Best Model) - Loss: 1.7418 - Accuracy: 0.2319 - F1: 0.1146
sub_16:Test (Best Model) - Loss: 1.4974 - Accuracy: 0.3088 - F1: 0.2482
sub_3:Test (Best Model) - Loss: 1.7025 - Accuracy: 0.2206 - F1: 0.1094
sub_28:Test (Best Model) - Loss: 1.5645 - Accuracy: 0.2941 - F1: 0.1840
sub_5:Test (Best Model) - Loss: 1.4148 - Accuracy: 0.3235 - F1: 0.2198
sub_13:Test (Best Model) - Loss: 1.4994 - Accuracy: 0.2754 - F1: 0.1339
sub_29:Test (Best Model) - Loss: 1.3265 - Accuracy: 0.3382 - F1: 0.3064
sub_23:Test (Best Model) - Loss: 1.9125 - Accuracy: 0.2647 - F1: 0.1268
sub_12:Test (Best Model) - Loss: 1.3738 - Accuracy: 0.3913 - F1: 0.3400
sub_19:Test (Best Model) - Loss: 1.5520 - Accuracy: 0.2353 - F1: 0.1614
sub_8:Test (Best Model) - Loss: 1.5963 - Accuracy: 0.2941 - F1: 0.1837
sub_2:Test (Best Model) - Loss: 1.4477 - Accuracy: 0.2353 - F1: 0.2385
sub_15:Test (Best Model) - Loss: 1.1830 - Accuracy: 0.4559 - F1: 0.3849
sub_27:Test (Best Model) - Loss: 1.5677 - Accuracy: 0.3913 - F1: 0.2866
sub_7:Test (Best Model) - Loss: 1.5974 - Accuracy: 0.1912 - F1: 0.1279
sub_6:Test (Best Model) - Loss: 1.6468 - Accuracy: 0.3043 - F1: 0.1795
sub_10:Test (Best Model) - Loss: 1.4916 - Accuracy: 0.2794 - F1: 0.1321
sub_20:Test (Best Model) - Loss: 1.3705 - Accuracy: 0.3676 - F1: 0.3440
sub_1:Test (Best Model) - Loss: 1.6782 - Accuracy: 0.1739 - F1: 0.0910
sub_25:Test (Best Model) - Loss: 1.4830 - Accuracy: 0.3088 - F1: 0.2521
sub_4:Test (Best Model) - Loss: 1.5232 - Accuracy: 0.2029 - F1: 0.1213
sub_26:Test (Best Model) - Loss: 1.3291 - Accuracy: 0.3676 - F1: 0.3191
sub_17:Test (Best Model) - Loss: 1.5677 - Accuracy: 0.3913 - F1: 0.2866
sub_21:Test (Best Model) - Loss: 1.4127 - Accuracy: 0.3382 - F1: 0.2089
sub_9:Test (Best Model) - Loss: 1.5011 - Accuracy: 0.3235 - F1: 0.2095
sub_22:Test (Best Model) - Loss: 1.2358 - Accuracy: 0.4783 - F1: 0.4644
sub_18:Test (Best Model) - Loss: 1.3124 - Accuracy: 0.4265 - F1: 0.3702
sub_14:Test (Best Model) - Loss: 1.2049 - Accuracy: 0.4706 - F1: 0.4213
sub_8:Test (Best Model) - Loss: 1.4715 - Accuracy: 0.3382 - F1: 0.2633
sub_15:Test (Best Model) - Loss: 1.6212 - Accuracy: 0.2647 - F1: 0.1426
sub_24:Test (Best Model) - Loss: 1.3039 - Accuracy: 0.4412 - F1: 0.4004
sub_29:Test (Best Model) - Loss: 1.4302 - Accuracy: 0.2647 - F1: 0.1770
sub_16:Test (Best Model) - Loss: 1.4926 - Accuracy: 0.3088 - F1: 0.2694
sub_6:Test (Best Model) - Loss: 1.7837 - Accuracy: 0.2174 - F1: 0.1539
sub_20:Test (Best Model) - Loss: 1.6259 - Accuracy: 0.2500 - F1: 0.1448
sub_7:Test (Best Model) - Loss: 1.4293 - Accuracy: 0.4265 - F1: 0.3304
sub_5:Test (Best Model) - Loss: 1.5071 - Accuracy: 0.1618 - F1: 0.1449
sub_11:Test (Best Model) - Loss: 1.3751 - Accuracy: 0.3478 - F1: 0.3365
sub_28:Test (Best Model) - Loss: 1.6681 - Accuracy: 0.1029 - F1: 0.0928
sub_26:Test (Best Model) - Loss: 1.3974 - Accuracy: 0.3529 - F1: 0.2307
sub_3:Test (Best Model) - Loss: 1.3436 - Accuracy: 0.3478 - F1: 0.3471
sub_18:Test (Best Model) - Loss: 1.4383 - Accuracy: 0.2353 - F1: 0.1482
sub_14:Test (Best Model) - Loss: 1.6961 - Accuracy: 0.2941 - F1: 0.1774
sub_27:Test (Best Model) - Loss: 1.5720 - Accuracy: 0.2609 - F1: 0.1931
sub_23:Test (Best Model) - Loss: 1.8104 - Accuracy: 0.1471 - F1: 0.1067
sub_10:Test (Best Model) - Loss: 1.3191 - Accuracy: 0.3824 - F1: 0.3541
sub_24:Test (Best Model) - Loss: 1.7384 - Accuracy: 0.2941 - F1: 0.1811
sub_17:Test (Best Model) - Loss: 1.5720 - Accuracy: 0.2609 - F1: 0.1931
sub_13:Test (Best Model) - Loss: 1.3608 - Accuracy: 0.4203 - F1: 0.3423
sub_16:Test (Best Model) - Loss: 1.4255 - Accuracy: 0.2647 - F1: 0.2885
sub_19:Test (Best Model) - Loss: 1.6957 - Accuracy: 0.1176 - F1: 0.0870
sub_29:Test (Best Model) - Loss: 1.5486 - Accuracy: 0.3529 - F1: 0.3042
sub_12:Test (Best Model) - Loss: 1.3541 - Accuracy: 0.4203 - F1: 0.4070
sub_20:Test (Best Model) - Loss: 1.4580 - Accuracy: 0.3088 - F1: 0.2014
sub_22:Test (Best Model) - Loss: 1.6175 - Accuracy: 0.1449 - F1: 0.1180
sub_6:Test (Best Model) - Loss: 1.2874 - Accuracy: 0.4348 - F1: 0.3603
sub_1:Test (Best Model) - Loss: 1.5493 - Accuracy: 0.2464 - F1: 0.1500
sub_26:Test (Best Model) - Loss: 1.6692 - Accuracy: 0.2206 - F1: 0.1301
sub_11:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.3913 - F1: 0.2527
sub_15:Test (Best Model) - Loss: 1.5492 - Accuracy: 0.3676 - F1: 0.2949
sub_25:Test (Best Model) - Loss: 1.5058 - Accuracy: 0.2500 - F1: 0.2265
sub_14:Test (Best Model) - Loss: 1.6293 - Accuracy: 0.1176 - F1: 0.1046
sub_3:Test (Best Model) - Loss: 1.5011 - Accuracy: 0.2609 - F1: 0.1125
sub_4:Test (Best Model) - Loss: 1.2584 - Accuracy: 0.4638 - F1: 0.4155
sub_24:Test (Best Model) - Loss: 1.5313 - Accuracy: 0.0882 - F1: 0.0806
sub_9:Test (Best Model) - Loss: 1.4600 - Accuracy: 0.3676 - F1: 0.3178
sub_16:Test (Best Model) - Loss: 1.3454 - Accuracy: 0.3676 - F1: 0.2926
sub_20:Test (Best Model) - Loss: 1.5972 - Accuracy: 0.1324 - F1: 0.1206
sub_1:Test (Best Model) - Loss: 1.5843 - Accuracy: 0.2464 - F1: 0.1822
sub_13:Test (Best Model) - Loss: 1.5633 - Accuracy: 0.3188 - F1: 0.2275
sub_2:Test (Best Model) - Loss: 1.4001 - Accuracy: 0.2206 - F1: 0.2203
sub_14:Test (Best Model) - Loss: 1.4471 - Accuracy: 0.2647 - F1: 0.2381
sub_15:Test (Best Model) - Loss: 1.5837 - Accuracy: 0.2794 - F1: 0.1625
sub_25:Test (Best Model) - Loss: 1.4435 - Accuracy: 0.2500 - F1: 0.2472
sub_5:Test (Best Model) - Loss: 1.7452 - Accuracy: 0.2059 - F1: 0.1085
sub_4:Test (Best Model) - Loss: 1.6408 - Accuracy: 0.1449 - F1: 0.1026
sub_7:Test (Best Model) - Loss: 1.3494 - Accuracy: 0.4706 - F1: 0.4419
sub_24:Test (Best Model) - Loss: 1.5788 - Accuracy: 0.2206 - F1: 0.1488
sub_21:Test (Best Model) - Loss: 1.2222 - Accuracy: 0.4706 - F1: 0.4202
sub_18:Test (Best Model) - Loss: 1.4775 - Accuracy: 0.1471 - F1: 0.0960
sub_6:Test (Best Model) - Loss: 1.5676 - Accuracy: 0.2464 - F1: 0.2183
sub_29:Test (Best Model) - Loss: 1.2484 - Accuracy: 0.4265 - F1: 0.3443
sub_28:Test (Best Model) - Loss: 1.5697 - Accuracy: 0.2353 - F1: 0.0976
sub_19:Test (Best Model) - Loss: 1.4646 - Accuracy: 0.2500 - F1: 0.1689
sub_27:Test (Best Model) - Loss: 1.3668 - Accuracy: 0.2899 - F1: 0.2748
sub_17:Test (Best Model) - Loss: 1.3668 - Accuracy: 0.2899 - F1: 0.2748
sub_16:Test (Best Model) - Loss: 1.6661 - Accuracy: 0.2647 - F1: 0.1910
sub_9:Test (Best Model) - Loss: 1.5872 - Accuracy: 0.2794 - F1: 0.1564
sub_10:Test (Best Model) - Loss: 1.4768 - Accuracy: 0.2794 - F1: 0.2138
sub_8:Test (Best Model) - Loss: 1.3963 - Accuracy: 0.2500 - F1: 0.2295
sub_20:Test (Best Model) - Loss: 1.4441 - Accuracy: 0.2941 - F1: 0.1931
sub_11:Test (Best Model) - Loss: 1.4044 - Accuracy: 0.4493 - F1: 0.3369
sub_14:Test (Best Model) - Loss: 1.5067 - Accuracy: 0.3529 - F1: 0.2641
sub_13:Test (Best Model) - Loss: 1.2695 - Accuracy: 0.4203 - F1: 0.3740
sub_15:Test (Best Model) - Loss: 1.8519 - Accuracy: 0.2500 - F1: 0.1253
sub_26:Test (Best Model) - Loss: 1.7011 - Accuracy: 0.2206 - F1: 0.1965
sub_5:Test (Best Model) - Loss: 1.6246 - Accuracy: 0.1912 - F1: 0.1519
sub_24:Test (Best Model) - Loss: 1.3737 - Accuracy: 0.3971 - F1: 0.3389
sub_4:Test (Best Model) - Loss: 1.4221 - Accuracy: 0.2464 - F1: 0.2105
sub_23:Test (Best Model) - Loss: 1.4737 - Accuracy: 0.2500 - F1: 0.1750
sub_22:Test (Best Model) - Loss: 1.4938 - Accuracy: 0.2353 - F1: 0.2038
sub_28:Test (Best Model) - Loss: 1.8115 - Accuracy: 0.1176 - F1: 0.0718
sub_3:Test (Best Model) - Loss: 1.6031 - Accuracy: 0.2319 - F1: 0.1823
sub_16:Test (Best Model) - Loss: 1.4065 - Accuracy: 0.3676 - F1: 0.2916
sub_27:Test (Best Model) - Loss: 1.4901 - Accuracy: 0.2319 - F1: 0.1991
sub_17:Test (Best Model) - Loss: 1.4901 - Accuracy: 0.2319 - F1: 0.1991
sub_8:Test (Best Model) - Loss: 1.3449 - Accuracy: 0.3971 - F1: 0.3067
sub_9:Test (Best Model) - Loss: 1.6882 - Accuracy: 0.1765 - F1: 0.1520
sub_11:Test (Best Model) - Loss: 1.4920 - Accuracy: 0.2464 - F1: 0.1966
sub_13:Test (Best Model) - Loss: 1.6024 - Accuracy: 0.2500 - F1: 0.1647
sub_21:Test (Best Model) - Loss: 1.4733 - Accuracy: 0.2941 - F1: 0.1881
sub_2:Test (Best Model) - Loss: 1.4663 - Accuracy: 0.3768 - F1: 0.2481
sub_4:Test (Best Model) - Loss: 1.7748 - Accuracy: 0.2319 - F1: 0.1943
sub_18:Test (Best Model) - Loss: 1.4300 - Accuracy: 0.4118 - F1: 0.3393
sub_5:Test (Best Model) - Loss: 1.7729 - Accuracy: 0.2059 - F1: 0.1111
sub_1:Test (Best Model) - Loss: 1.4039 - Accuracy: 0.3333 - F1: 0.3102
sub_29:Test (Best Model) - Loss: 1.4981 - Accuracy: 0.2206 - F1: 0.1974
sub_28:Test (Best Model) - Loss: 1.5922 - Accuracy: 0.1471 - F1: 0.0866
sub_3:Test (Best Model) - Loss: 1.6502 - Accuracy: 0.2464 - F1: 0.1468
sub_16:Test (Best Model) - Loss: 1.2433 - Accuracy: 0.3824 - F1: 0.3126
sub_19:Test (Best Model) - Loss: 1.3433 - Accuracy: 0.4118 - F1: 0.3657
sub_12:Test (Best Model) - Loss: 1.1806 - Accuracy: 0.4265 - F1: 0.4316
sub_6:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2609 - F1: 0.2547
sub_10:Test (Best Model) - Loss: 1.4784 - Accuracy: 0.3333 - F1: 0.2372
sub_11:Test (Best Model) - Loss: 1.2654 - Accuracy: 0.4058 - F1: 0.3228
sub_22:Test (Best Model) - Loss: 1.4844 - Accuracy: 0.2794 - F1: 0.1392
sub_28:Test (Best Model) - Loss: 1.3106 - Accuracy: 0.4118 - F1: 0.3478
sub_29:Test (Best Model) - Loss: 1.3450 - Accuracy: 0.2899 - F1: 0.2524
sub_24:Test (Best Model) - Loss: 1.6150 - Accuracy: 0.2500 - F1: 0.1798
sub_14:Test (Best Model) - Loss: 1.3694 - Accuracy: 0.3382 - F1: 0.2490
sub_12:Test (Best Model) - Loss: 1.6447 - Accuracy: 0.2941 - F1: 0.2205
sub_19:Test (Best Model) - Loss: 1.6290 - Accuracy: 0.1765 - F1: 0.1906
sub_25:Test (Best Model) - Loss: 1.2590 - Accuracy: 0.3382 - F1: 0.3605
sub_13:Test (Best Model) - Loss: 1.4244 - Accuracy: 0.3088 - F1: 0.2518
sub_8:Test (Best Model) - Loss: 1.2845 - Accuracy: 0.3676 - F1: 0.2920
sub_27:Test (Best Model) - Loss: 1.1627 - Accuracy: 0.5441 - F1: 0.3875
sub_17:Test (Best Model) - Loss: 1.1627 - Accuracy: 0.5441 - F1: 0.3875
sub_6:Test (Best Model) - Loss: 1.5461 - Accuracy: 0.4348 - F1: 0.2941
sub_7:Test (Best Model) - Loss: 1.2730 - Accuracy: 0.4853 - F1: 0.4324
sub_18:Test (Best Model) - Loss: 1.5425 - Accuracy: 0.2059 - F1: 0.1611
sub_21:Test (Best Model) - Loss: 1.4579 - Accuracy: 0.3529 - F1: 0.2838
sub_1:Test (Best Model) - Loss: 1.5612 - Accuracy: 0.2941 - F1: 0.2047
sub_2:Test (Best Model) - Loss: 1.4742 - Accuracy: 0.2029 - F1: 0.1760
sub_5:Test (Best Model) - Loss: 1.4184 - Accuracy: 0.2059 - F1: 0.2000
sub_22:Test (Best Model) - Loss: 1.8295 - Accuracy: 0.2206 - F1: 0.1333
sub_26:Test (Best Model) - Loss: 1.5875 - Accuracy: 0.1618 - F1: 0.1062
sub_20:Test (Best Model) - Loss: 1.5231 - Accuracy: 0.2174 - F1: 0.1426
sub_29:Test (Best Model) - Loss: 1.5305 - Accuracy: 0.3043 - F1: 0.2674
sub_16:Test (Best Model) - Loss: 1.3729 - Accuracy: 0.4118 - F1: 0.3377
sub_3:Test (Best Model) - Loss: 1.3747 - Accuracy: 0.4058 - F1: 0.3295
sub_15:Test (Best Model) - Loss: 1.2483 - Accuracy: 0.3971 - F1: 0.3588
sub_12:Test (Best Model) - Loss: 1.6455 - Accuracy: 0.2794 - F1: 0.2385
sub_14:Test (Best Model) - Loss: 1.4269 - Accuracy: 0.2941 - F1: 0.2724
sub_23:Test (Best Model) - Loss: 1.4296 - Accuracy: 0.2609 - F1: 0.2475
sub_11:Test (Best Model) - Loss: 1.4599 - Accuracy: 0.2609 - F1: 0.1887
sub_9:Test (Best Model) - Loss: 1.3528 - Accuracy: 0.3824 - F1: 0.3574
sub_28:Test (Best Model) - Loss: 1.6175 - Accuracy: 0.1324 - F1: 0.1613
sub_2:Test (Best Model) - Loss: 1.6322 - Accuracy: 0.2174 - F1: 0.1313
sub_19:Test (Best Model) - Loss: 1.5998 - Accuracy: 0.2794 - F1: 0.1664
sub_4:Test (Best Model) - Loss: 1.6818 - Accuracy: 0.2174 - F1: 0.1212
sub_22:Test (Best Model) - Loss: 1.3076 - Accuracy: 0.4118 - F1: 0.3597
sub_29:Test (Best Model) - Loss: 1.8470 - Accuracy: 0.1449 - F1: 0.0828
sub_26:Test (Best Model) - Loss: 1.6724 - Accuracy: 0.2500 - F1: 0.1667
sub_20:Test (Best Model) - Loss: 1.7051 - Accuracy: 0.2174 - F1: 0.1403
sub_10:Test (Best Model) - Loss: 1.8319 - Accuracy: 0.1304 - F1: 0.0692
sub_6:Test (Best Model) - Loss: 1.8567 - Accuracy: 0.2029 - F1: 0.0886
sub_18:Test (Best Model) - Loss: 1.5206 - Accuracy: 0.2500 - F1: 0.1417
sub_14:Test (Best Model) - Loss: 2.0014 - Accuracy: 0.0000 - F1: 0.0000
sub_8:Test (Best Model) - Loss: 1.7760 - Accuracy: 0.3382 - F1: 0.2409
sub_23:Test (Best Model) - Loss: 1.5024 - Accuracy: 0.3043 - F1: 0.1752
sub_2:Test (Best Model) - Loss: 1.4551 - Accuracy: 0.3188 - F1: 0.2915
sub_15:Test (Best Model) - Loss: 1.5480 - Accuracy: 0.2353 - F1: 0.2006
sub_7:Test (Best Model) - Loss: 1.2390 - Accuracy: 0.4412 - F1: 0.4132
sub_3:Test (Best Model) - Loss: 1.3899 - Accuracy: 0.3188 - F1: 0.2437
sub_9:Test (Best Model) - Loss: 1.5317 - Accuracy: 0.2206 - F1: 0.1911
sub_24:Test (Best Model) - Loss: 1.6081 - Accuracy: 0.2794 - F1: 0.2051
sub_4:Test (Best Model) - Loss: 0.9198 - Accuracy: 0.7681 - F1: 0.7758
sub_21:Test (Best Model) - Loss: 1.3016 - Accuracy: 0.4559 - F1: 0.4148
sub_26:Test (Best Model) - Loss: 1.4702 - Accuracy: 0.3382 - F1: 0.2344
sub_1:Test (Best Model) - Loss: 1.5986 - Accuracy: 0.2941 - F1: 0.1560
sub_10:Test (Best Model) - Loss: 1.3600 - Accuracy: 0.3623 - F1: 0.3538
sub_17:Test (Best Model) - Loss: 1.5751 - Accuracy: 0.2206 - F1: 0.1504
sub_14:Test (Best Model) - Loss: 1.3790 - Accuracy: 0.3382 - F1: 0.2502
sub_13:Test (Best Model) - Loss: 1.8593 - Accuracy: 0.1029 - F1: 0.0479
sub_6:Test (Best Model) - Loss: 1.1136 - Accuracy: 0.5652 - F1: 0.5298
sub_27:Test (Best Model) - Loss: 1.5751 - Accuracy: 0.2206 - F1: 0.1504
sub_25:Test (Best Model) - Loss: 1.3628 - Accuracy: 0.3824 - F1: 0.2702
sub_2:Test (Best Model) - Loss: 1.5082 - Accuracy: 0.1594 - F1: 0.1572
sub_20:Test (Best Model) - Loss: 1.4863 - Accuracy: 0.2174 - F1: 0.1834
sub_19:Test (Best Model) - Loss: 1.5736 - Accuracy: 0.2206 - F1: 0.1922
sub_12:Test (Best Model) - Loss: 1.1399 - Accuracy: 0.4706 - F1: 0.4636
sub_24:Test (Best Model) - Loss: 1.6566 - Accuracy: 0.2206 - F1: 0.2256
sub_22:Test (Best Model) - Loss: 1.4878 - Accuracy: 0.2353 - F1: 0.2563
sub_26:Test (Best Model) - Loss: 1.7377 - Accuracy: 0.1618 - F1: 0.0942
sub_11:Test (Best Model) - Loss: 1.3814 - Accuracy: 0.3043 - F1: 0.3192
sub_14:Test (Best Model) - Loss: 1.6080 - Accuracy: 0.1765 - F1: 0.1340
sub_18:Test (Best Model) - Loss: 1.6834 - Accuracy: 0.1324 - F1: 0.0841
sub_5:Test (Best Model) - Loss: 1.3627 - Accuracy: 0.1324 - F1: 0.1443
sub_8:Test (Best Model) - Loss: 2.0142 - Accuracy: 0.1324 - F1: 0.0643
sub_4:Test (Best Model) - Loss: 1.2967 - Accuracy: 0.4348 - F1: 0.3960
sub_10:Test (Best Model) - Loss: 1.1283 - Accuracy: 0.4928 - F1: 0.4823
sub_6:Test (Best Model) - Loss: 1.3636 - Accuracy: 0.3333 - F1: 0.3053
sub_12:Test (Best Model) - Loss: 1.3686 - Accuracy: 0.2353 - F1: 0.2461
sub_25:Test (Best Model) - Loss: 1.4314 - Accuracy: 0.3088 - F1: 0.2735
sub_26:Test (Best Model) - Loss: 1.2514 - Accuracy: 0.4118 - F1: 0.4168
sub_1:Test (Best Model) - Loss: 1.7455 - Accuracy: 0.2059 - F1: 0.0875
sub_24:Test (Best Model) - Loss: 1.6874 - Accuracy: 0.0882 - F1: 0.0996
sub_29:Test (Best Model) - Loss: 1.0794 - Accuracy: 0.5652 - F1: 0.5274
sub_19:Test (Best Model) - Loss: 1.0744 - Accuracy: 0.6618 - F1: 0.6581
sub_7:Test (Best Model) - Loss: 1.5304 - Accuracy: 0.2941 - F1: 0.1944
sub_18:Test (Best Model) - Loss: 1.6293 - Accuracy: 0.2206 - F1: 0.1171
sub_8:Test (Best Model) - Loss: 1.1481 - Accuracy: 0.5588 - F1: 0.5082
sub_21:Test (Best Model) - Loss: 1.4683 - Accuracy: 0.2206 - F1: 0.1946
sub_11:Test (Best Model) - Loss: 1.4152 - Accuracy: 0.2754 - F1: 0.2289
sub_10:Test (Best Model) - Loss: 1.4175 - Accuracy: 0.2174 - F1: 0.2067
sub_5:Test (Best Model) - Loss: 1.9405 - Accuracy: 0.3088 - F1: 0.1816
sub_20:Test (Best Model) - Loss: 1.0471 - Accuracy: 0.5507 - F1: 0.5603
sub_13:Test (Best Model) - Loss: 1.3187 - Accuracy: 0.4265 - F1: 0.4011
sub_9:Test (Best Model) - Loss: 1.4713 - Accuracy: 0.1618 - F1: 0.1741
sub_8:Test (Best Model) - Loss: 1.4749 - Accuracy: 0.2059 - F1: 0.1736
sub_15:Test (Best Model) - Loss: 1.4933 - Accuracy: 0.3235 - F1: 0.2970
sub_18:Test (Best Model) - Loss: 1.4411 - Accuracy: 0.2206 - F1: 0.2505
sub_29:Test (Best Model) - Loss: 1.6122 - Accuracy: 0.1594 - F1: 0.1329
sub_26:Test (Best Model) - Loss: 1.4750 - Accuracy: 0.1765 - F1: 0.1150
sub_20:Test (Best Model) - Loss: 1.4155 - Accuracy: 0.2464 - F1: 0.1653
sub_7:Test (Best Model) - Loss: 1.7485 - Accuracy: 0.1029 - F1: 0.0662
sub_3:Test (Best Model) - Loss: 1.3256 - Accuracy: 0.4203 - F1: 0.3213
sub_1:Test (Best Model) - Loss: 1.3434 - Accuracy: 0.3088 - F1: 0.3185
sub_25:Test (Best Model) - Loss: 1.0710 - Accuracy: 0.5000 - F1: 0.5029
sub_24:Test (Best Model) - Loss: 1.4045 - Accuracy: 0.2794 - F1: 0.2790
sub_18:Test (Best Model) - Loss: 1.2893 - Accuracy: 0.3529 - F1: 0.2679
sub_19:Test (Best Model) - Loss: 1.4028 - Accuracy: 0.2941 - F1: 0.2995
sub_15:Test (Best Model) - Loss: 1.6942 - Accuracy: 0.1176 - F1: 0.0772
sub_17:Test (Best Model) - Loss: 1.6661 - Accuracy: 0.2353 - F1: 0.1338
sub_27:Test (Best Model) - Loss: 1.6661 - Accuracy: 0.2353 - F1: 0.1338
sub_3:Test (Best Model) - Loss: 1.5257 - Accuracy: 0.2609 - F1: 0.2004
sub_1:Test (Best Model) - Loss: 1.3260 - Accuracy: 0.2647 - F1: 0.2977
sub_13:Test (Best Model) - Loss: 1.4265 - Accuracy: 0.2647 - F1: 0.1781
sub_9:Test (Best Model) - Loss: 1.7297 - Accuracy: 0.2794 - F1: 0.1599
sub_21:Test (Best Model) - Loss: 1.2083 - Accuracy: 0.5147 - F1: 0.4263
sub_23:Test (Best Model) - Loss: 1.6171 - Accuracy: 0.2899 - F1: 0.2292
sub_25:Test (Best Model) - Loss: 1.6296 - Accuracy: 0.0588 - F1: 0.0727
sub_7:Test (Best Model) - Loss: 1.2174 - Accuracy: 0.4118 - F1: 0.4378
sub_17:Test (Best Model) - Loss: 1.4265 - Accuracy: 0.2647 - F1: 0.2519
sub_27:Test (Best Model) - Loss: 1.4265 - Accuracy: 0.2647 - F1: 0.2519
sub_5:Test (Best Model) - Loss: 1.6195 - Accuracy: 0.1912 - F1: 0.1426
sub_21:Test (Best Model) - Loss: 1.7081 - Accuracy: 0.0735 - F1: 0.0570
sub_11:Test (Best Model) - Loss: 1.3374 - Accuracy: 0.2609 - F1: 0.2405
sub_15:Test (Best Model) - Loss: 1.6599 - Accuracy: 0.2059 - F1: 0.1635
sub_7:Test (Best Model) - Loss: 1.2933 - Accuracy: 0.3529 - F1: 0.2624
sub_23:Test (Best Model) - Loss: 1.1075 - Accuracy: 0.4493 - F1: 0.4440
sub_9:Test (Best Model) - Loss: 1.5127 - Accuracy: 0.1912 - F1: 0.1032
sub_3:Test (Best Model) - Loss: 1.1715 - Accuracy: 0.5507 - F1: 0.5227
sub_21:Test (Best Model) - Loss: 1.6480 - Accuracy: 0.1176 - F1: 0.1433
sub_15:Test (Best Model) - Loss: 1.2953 - Accuracy: 0.3088 - F1: 0.3530
sub_23:Test (Best Model) - Loss: 1.5248 - Accuracy: 0.2029 - F1: 0.2198
sub_5:Test (Best Model) - Loss: 1.2226 - Accuracy: 0.3235 - F1: 0.2865
sub_17:Test (Best Model) - Loss: 1.3048 - Accuracy: 0.4118 - F1: 0.3867
sub_3:Test (Best Model) - Loss: 1.3941 - Accuracy: 0.2899 - F1: 0.3114
sub_27:Test (Best Model) - Loss: 1.3048 - Accuracy: 0.4118 - F1: 0.3867
sub_11:Test (Best Model) - Loss: 1.2006 - Accuracy: 0.3913 - F1: 0.3246
sub_21:Test (Best Model) - Loss: 1.3214 - Accuracy: 0.3382 - F1: 0.2987
sub_15:Test (Best Model) - Loss: 1.3706 - Accuracy: 0.3529 - F1: 0.3543
sub_9:Test (Best Model) - Loss: 1.1312 - Accuracy: 0.3971 - F1: 0.4241
sub_5:Test (Best Model) - Loss: 1.6023 - Accuracy: 0.0441 - F1: 0.0439
sub_21:Test (Best Model) - Loss: 1.5921 - Accuracy: 0.2353 - F1: 0.2239
sub_9:Test (Best Model) - Loss: 1.3907 - Accuracy: 0.1324 - F1: 0.1759

=== Summary Results ===

acc: 30.33 ± 3.05
F1: 24.57 ± 3.23
acc-in: 39.05 ± 3.04
F1-in: 33.68 ± 3.10
