why the pretrained model with low accuracy

[lly8752]

Why I use your training model with low initial accuracy? Am I wrong?

cmd:CUDA_VISIBLE_DEVICES='0' python -u train_softmax.py --network y1 --ckpt 2 --loss-type 4 --lr 0.01 --lr-steps 40000,60000,70000 --wd 0.00004 --fc7-wd-mult 10 --emb-size 512 --per-batch-size 90 --margin-s 128 --data-dir ../datasets/faces_ms1m_112x112 --pretrained ../models/MF/model-y1-softmax12,31 --prefix ../models/MF/model-y1-arcface >>& file.txt &

first test:
testing verification..
(12000, 512)
infer time 154.665504
[lfw][2000]XNorm: 22.648476
[lfw][2000]Accuracy-Flip: 0.98717+-0.00563
testing verification..
(14000, 512)
infer time 175.866512
[cfp_fp][2000]XNorm: 19.110292
[cfp_fp][2000]Accuracy-Flip: 0.83271+-0.01969
testing verification..
(12000, 512)
infer time 157.715533
[agedb_30][2000]XNorm: 22.118053
[agedb_30][2000]Accuracy-Flip: 0.90683+-0.01981
saving 1
INFO:root:Saved checkpoint to "../models/MF/model-y1-arcface-0001.params"

[qidiso]

it's right.you need more epochs.

[lly8752]

but i run next, the Accuracy is too low always, why?
Called with argument: Namespace(batch_size=150, beta=1000.0, beta_freeze=0, beta_min=5.0, bn_mom=0.9, ckpt=2, ctx_num=1, cutoff=0, data_dir='../datasets/faces_ms1m_112x112', easy_margin=0, emb_size=512, end_epoch=100000, fc7_lr_mult=1.0, fc7_no_bias=False, fc7_wd_mult=10.0, gamma=0.12, image_channel=3, image_h=112, image_w=112, loss_type=4, lr=0.01, lr_steps='40000,60000,70000', margin=4, margin_a=1.0, margin_b=0.0, margin_m=0.5, margin_s=128.0, max_steps=0, mom=0.9, network='y1', num_classes=85164, num_layers=1, per_batch_size=150, power=1.0, prefix='../models/MF/model-y1-arcface', pretrained='../models/MF/model-y1-arcface,7', rand_mirror=1, rescale_threshold=0, scale=0.9993, target='lfw,cfp_fp,agedb_30', use_deformable=0, verbose=2000, version_act='prelu', version_input=1, version_output='E', version_se=0, version_unit=3, wd=4e-05)

169:[lfw][2000]Accuracy-Flip: 0.98717+-0.00563
174:[cfp_fp][2000]Accuracy-Flip: 0.83271+-0.01969
179:[agedb_30][2000]Accuracy-Flip: 0.90683+-0.01981
289:[lfw][4000]Accuracy-Flip: 0.98867+-0.00452
294:[cfp_fp][4000]Accuracy-Flip: 0.82286+-0.01824
299:[agedb_30][4000]Accuracy-Flip: 0.91833+-0.01916
409:[lfw][6000]Accuracy-Flip: 0.98750+-0.00559
414:[cfp_fp][6000]Accuracy-Flip: 0.83629+-0.01574
419:[agedb_30][6000]Accuracy-Flip: 0.91683+-0.02330
529:[lfw][8000]Accuracy-Flip: 0.98850+-0.00560
534:[cfp_fp][8000]Accuracy-Flip: 0.84043+-0.01742
539:[agedb_30][8000]Accuracy-Flip: 0.92500+-0.01932
649:[lfw][10000]Accuracy-Flip: 0.99000+-0.00527
654:[cfp_fp][10000]Accuracy-Flip: 0.83771+-0.01716
659:[agedb_30][10000]Accuracy-Flip: 0.92433+-0.01703
769:[lfw][12000]Accuracy-Flip: 0.98967+-0.00470
774:[cfp_fp][12000]Accuracy-Flip: 0.83286+-0.02009
779:[agedb_30][12000]Accuracy-Flip: 0.92667+-0.01487
889:[lfw][14000]Accuracy-Flip: 0.99067+-0.00539
894:[cfp_fp][14000]Accuracy-Flip: 0.83529+-0.01643
899:[agedb_30][14000]Accuracy-Flip: 0.92650+-0.01799

170:[lfw][2000]Accuracy-Flip: 0.99117+-0.00472
175:[cfp_fp][2000]Accuracy-Flip: 0.85586+-0.01866
180:[agedb_30][2000]Accuracy-Flip: 0.93150+-0.01431
290:[lfw][4000]Accuracy-Flip: 0.98967+-0.00547
295:[cfp_fp][4000]Accuracy-Flip: 0.84771+-0.01908
300:[agedb_30][4000]Accuracy-Flip: 0.93533+-0.01362
410:[lfw][6000]Accuracy-Flip: 0.99200+-0.00521
415:[cfp_fp][6000]Accuracy-Flip: 0.85329+-0.02204
420:[agedb_30][6000]Accuracy-Flip: 0.93483+-0.01026
530:[lfw][8000]Accuracy-Flip: 0.98983+-0.00529
535:[cfp_fp][8000]Accuracy-Flip: 0.85329+-0.01400
540:[agedb_30][8000]Accuracy-Flip: 0.93833+-0.01312
650:[lfw][10000]Accuracy-Flip: 0.99067+-0.00512
655:[cfp_fp][10000]Accuracy-Flip: 0.86114+-0.01674
660:[agedb_30][10000]Accuracy-Flip: 0.93400+-0.01319
770:[lfw][12000]Accuracy-Flip: 0.99117+-0.00478
775:[cfp_fp][12000]Accuracy-Flip: 0.85786+-0.01863
780:[agedb_30][12000]Accuracy-Flip: 0.93917+-0.01413
890:[lfw][14000]Accuracy-Flip: 0.99033+-0.00452
895:[cfp_fp][14000]Accuracy-Flip: 0.85657+-0.01930
900:[agedb_30][14000]Accuracy-Flip: 0.93517+-0.01235
1010:[lfw][16000]Accuracy-Flip: 0.98933+-0.00588
1015:[cfp_fp][16000]Accuracy-Flip: 0.85971+-0.02075
1020:[agedb_30][16000]Accuracy-Flip: 0.94117+-0.01263
1130:[lfw][18000]Accuracy-Flip: 0.99200+-0.00515
1135:[cfp_fp][18000]Accuracy-Flip: 0.86357+-0.01871
1140:[agedb_30][18000]Accuracy-Flip: 0.93333+-0.01461
1250:[lfw][20000]Accuracy-Flip: 0.99133+-0.00446
1255:[cfp_fp][20000]Accuracy-Flip: 0.85971+-0.02229
1260:[agedb_30][20000]Accuracy-Flip: 0.94067+-0.01131
1370:[lfw][22000]Accuracy-Flip: 0.99167+-0.00532
1375:[cfp_fp][22000]Accuracy-Flip: 0.86114+-0.01518
1380:[agedb_30][22000]Accuracy-Flip: 0.93817+-0.01361
1490:[lfw][24000]Accuracy-Flip: 0.99167+-0.00548
1495:[cfp_fp][24000]Accuracy-Flip: 0.86129+-0.01662
1500:[agedb_30][24000]Accuracy-Flip: 0.93633+-0.01398
1613:[lfw][26000]Accuracy-Flip: 0.99067+-0.00374
1618:[cfp_fp][26000]Accuracy-Flip: 0.86257+-0.01959
1623:[agedb_30][26000]Accuracy-Flip: 0.94100+-0.01198
1733:[lfw][28000]Accuracy-Flip: 0.99267+-0.00490
1738:[cfp_fp][28000]Accuracy-Flip: 0.86529+-0.01650
1743:[agedb_30][28000]Accuracy-Flip: 0.94000+-0.01331
1853:[lfw][30000]Accuracy-Flip: 0.99117+-0.00454
1858:[cfp_fp][30000]Accuracy-Flip: 0.86386+-0.01833
1863:[agedb_30][30000]Accuracy-Flip: 0.94250+-0.01365
1973:[lfw][32000]Accuracy-Flip: 0.99133+-0.00531
1978:[cfp_fp][32000]Accuracy-Flip: 0.86786+-0.01652
1983:[agedb_30][32000]Accuracy-Flip: 0.94067+-0.01278
2093:[lfw][34000]Accuracy-Flip: 0.99267+-0.00403
2098:[cfp_fp][34000]Accuracy-Flip: 0.86400+-0.01953
2103:[agedb_30][34000]Accuracy-Flip: 0.94367+-0.01229
2213:[lfw][36000]Accuracy-Flip: 0.99233+-0.00423
2218:[cfp_fp][36000]Accuracy-Flip: 0.86200+-0.01536
2223:[agedb_30][36000]Accuracy-Flip: 0.94417+-0.01323
2333:[lfw][38000]Accuracy-Flip: 0.99100+-0.00436
2338:[cfp_fp][38000]Accuracy-Flip: 0.86300+-0.01797
2343:[agedb_30][38000]Accuracy-Flip: 0.94267+-0.01259
2454:[lfw][40000]Accuracy-Flip: 0.99200+-0.00499
2459:[cfp_fp][40000]Accuracy-Flip: 0.86671+-0.01821
2464:[agedb_30][40000]Accuracy-Flip: 0.94433+-0.01114
2574:[lfw][42000]Accuracy-Flip: 0.99183+-0.00431
2579:[cfp_fp][42000]Accuracy-Flip: 0.87157+-0.01718
2584:[agedb_30][42000]Accuracy-Flip: 0.94800+-0.01157
2694:[lfw][44000]Accuracy-Flip: 0.99150+-0.00508
2699:[cfp_fp][44000]Accuracy-Flip: 0.87257+-0.01696
2704:[agedb_30][44000]Accuracy-Flip: 0.95000+-0.01046
2814:[lfw][46000]Accuracy-Flip: 0.99250+-0.00449
2819:[cfp_fp][46000]Accuracy-Flip: 0.87200+-0.01728
2824:[agedb_30][46000]Accuracy-Flip: 0.94950+-0.01164
2934:[lfw][48000]Accuracy-Flip: 0.99233+-0.00473
2939:[cfp_fp][48000]Accuracy-Flip: 0.87329+-0.01923
2944:[agedb_30][48000]Accuracy-Flip: 0.94883+-0.01038
3054:[lfw][50000]Accuracy-Flip: 0.99183+-0.00398
3059:[cfp_fp][50000]Accuracy-Flip: 0.86957+-0.01686
3064:[agedb_30][50000]Accuracy-Flip: 0.94833+-0.01160
3177:[lfw][52000]Accuracy-Flip: 0.99167+-0.00408
3182:[cfp_fp][52000]Accuracy-Flip: 0.86943+-0.01649
3187:[agedb_30][52000]Accuracy-Flip: 0.94933+-0.01001
3297:[lfw][54000]Accuracy-Flip: 0.99333+-0.00465
3302:[cfp_fp][54000]Accuracy-Flip: 0.87343+-0.01921
3307:[agedb_30][54000]Accuracy-Flip: 0.95133+-0.01092
3417:[lfw][56000]Accuracy-Flip: 0.99167+-0.00459
3422:[cfp_fp][56000]Accuracy-Flip: 0.87443+-0.01891
3427:[agedb_30][56000]Accuracy-Flip: 0.95050+-0.01067
3537:[lfw][58000]Accuracy-Flip: 0.99167+-0.00428
3542:[cfp_fp][58000]Accuracy-Flip: 0.87343+-0.01803
3547:[agedb_30][58000]Accuracy-Flip: 0.94833+-0.01118
3658:[lfw][60000]Accuracy-Flip: 0.99183+-0.00480
3663:[cfp_fp][60000]Accuracy-Flip: 0.87243+-0.01886
3668:[agedb_30][60000]Accuracy-Flip: 0.94950+-0.01128
3778:[lfw][62000]Accuracy-Flip: 0.99200+-0.00407
3783:[cfp_fp][62000]Accuracy-Flip: 0.87557+-0.01897
3788:[agedb_30][62000]Accuracy-Flip: 0.95050+-0.01033
3898:[lfw][64000]Accuracy-Flip: 0.99100+-0.00501
3903:[cfp_fp][64000]Accuracy-Flip: 0.87300+-0.01884
3908:[agedb_30][64000]Accuracy-Flip: 0.94867+-0.01137
4018:[lfw][66000]Accuracy-Flip: 0.99150+-0.00462
4023:[cfp_fp][66000]Accuracy-Flip: 0.87286+-0.01865
4028:[agedb_30][66000]Accuracy-Flip: 0.95117+-0.01090
4138:[lfw][68000]Accuracy-Flip: 0.99183+-0.00462
4143:[cfp_fp][68000]Accuracy-Flip: 0.87457+-0.01998
4148:[agedb_30][68000]Accuracy-Flip: 0.95100+-0.01106
4259:[lfw][70000]Accuracy-Flip: 0.99100+-0.00528
4264:[cfp_fp][70000]Accuracy-Flip: 0.87371+-0.01835
4269:[agedb_30][70000]Accuracy-Flip: 0.95000+-0.01083
4379:[lfw][72000]Accuracy-Flip: 0.99150+-0.00462
4384:[cfp_fp][72000]Accuracy-Flip: 0.87614+-0.01909
4389:[agedb_30][72000]Accuracy-Flip: 0.95000+-0.01176
4499:[lfw][74000]Accuracy-Flip: 0.99183+-0.00444
4504:[cfp_fp][74000]Accuracy-Flip: 0.87200+-0.01936
4509:[agedb_30][74000]Accuracy-Flip: 0.94850+-0.01161
4619:[lfw][76000]Accuracy-Flip: 0.99150+-0.00480
4624:[cfp_fp][76000]Accuracy-Flip: 0.87414+-0.01937
4629:[agedb_30][76000]Accuracy-Flip: 0.95000+-0.01193
4742:[lfw][78000]Accuracy-Flip: 0.99217+-0.00466
4747:[cfp_fp][78000]Accuracy-Flip: 0.87543+-0.01999
4752:[agedb_30][78000]Accuracy-Flip: 0.94933+-0.01098
4862:[lfw][80000]Accuracy-Flip: 0.99217+-0.00435
4867:[cfp_fp][80000]Accuracy-Flip: 0.87243+-0.01968
4872:[agedb_30][80000]Accuracy-Flip: 0.95083+-0.01081
4982:[lfw][82000]Accuracy-Flip: 0.99217+-0.00472
4987:[cfp_fp][82000]Accuracy-Flip: 0.87543+-0.01759
4992:[agedb_30][82000]Accuracy-Flip: 0.94950+-0.01258
5102:[lfw][84000]Accuracy-Flip: 0.99233+-0.00416
5107:[cfp_fp][84000]Accuracy-Flip: 0.87429+-0.01781
5112:[agedb_30][84000]Accuracy-Flip: 0.95033+-0.01157
5222:[lfw][86000]Accuracy-Flip: 0.99150+-0.00480
5227:[cfp_fp][86000]Accuracy-Flip: 0.87300+-0.01852
5232:[agedb_30][86000]Accuracy-Flip: 0.95117+-0.01148
5342:[lfw][88000]Accuracy-Flip: 0.99183+-0.00497
5347:[cfp_fp][88000]Accuracy-Flip: 0.87357+-0.01903
5352:[agedb_30][88000]Accuracy-Flip: 0.95117+-0.01011
5462:[lfw][90000]Accuracy-Flip: 0.99150+-0.00480
5467:[cfp_fp][90000]Accuracy-Flip: 0.87386+-0.02107
5472:[agedb_30][90000]Accuracy-Flip: 0.95000+-0.01145
5582:[lfw][92000]Accuracy-Flip: 0.99200+-0.00482
5587:[cfp_fp][92000]Accuracy-Flip: 0.87371+-0.01816
5592:[agedb_30][92000]Accuracy-Flip: 0.94800+-0.01135
5702:[lfw][94000]Accuracy-Flip: 0.99150+-0.00462
5707:[cfp_fp][94000]Accuracy-Flip: 0.87314+-0.01776
5712:[agedb_30][94000]Accuracy-Flip: 0.94817+-0.01165
5822:[lfw][96000]Accuracy-Flip: 0.99200+-0.00446
5827:[cfp_fp][96000]Accuracy-Flip: 0.87457+-0.01807
5832:[agedb_30][96000]Accuracy-Flip: 0.94917+-0.01146
5942:[lfw][98000]Accuracy-Flip: 0.99233+-0.00416
5947:[cfp_fp][98000]Accuracy-Flip: 0.87471+-0.01793
5952:[agedb_30][98000]Accuracy-Flip: 0.95133+-0.01064
6062:[lfw][100000]Accuracy-Flip: 0.99217+-0.00435
6067:[cfp_fp][100000]Accuracy-Flip: 0.87543+-0.01748
6072:[agedb_30][100000]Accuracy-Flip: 0.95100+-0.01083
6184:[lfw][102000]Accuracy-Flip: 0.99150+-0.00462
6189:[cfp_fp][102000]Accuracy-Flip: 0.87286+-0.01939
6194:[agedb_30][102000]Accuracy-Flip: 0.94867+-0.01161
6304:[lfw][104000]Accuracy-Flip: 0.99250+-0.00403
6309:[cfp_fp][104000]Accuracy-Flip: 0.87514+-0.01902
6314:[agedb_30][104000]Accuracy-Flip: 0.94950+-0.01209
6424:[lfw][106000]Accuracy-Flip: 0.99283+-0.00495
6429:[cfp_fp][106000]Accuracy-Flip: 0.87386+-0.01945
6434:[agedb_30][106000]Accuracy-Flip: 0.94983+-0.01149
6544:[lfw][108000]Accuracy-Flip: 0.99200+-0.00510
6549:[cfp_fp][108000]Accuracy-Flip: 0.87386+-0.01823
6554:[agedb_30][108000]Accuracy-Flip: 0.94900+-0.01179
6664:[lfw][110000]Accuracy-Flip: 0.99117+-0.00495
6669:[cfp_fp][110000]Accuracy-Flip: 0.87171+-0.01917
6674:[agedb_30][110000]Accuracy-Flip: 0.94800+-0.01190
6784:[lfw][112000]Accuracy-Flip: 0.99200+-0.00482
6789:[cfp_fp][112000]Accuracy-Flip: 0.87200+-0.01994
6794:[agedb_30][112000]Accuracy-Flip: 0.94817+-0.01168
6904:[lfw][114000]Accuracy-Flip: 0.99183+-0.00425
6909:[cfp_fp][114000]Accuracy-Flip: 0.87314+-0.01861
6914:[agedb_30][114000]Accuracy-Flip: 0.94983+-0.01146
7024:[lfw][116000]Accuracy-Flip: 0.99250+-0.00403
7029:[cfp_fp][116000]Accuracy-Flip: 0.87300+-0.01654
7034:[agedb_30][116000]Accuracy-Flip: 0.94967+-0.01095
7144:[lfw][118000]Accuracy-Flip: 0.99200+-0.00464
7149:[cfp_fp][118000]Accuracy-Flip: 0.87286+-0.01912
7154:[agedb_30][118000]Accuracy-Flip: 0.94933+-0.01188
7264:[lfw][120000]Accuracy-Flip: 0.99183+-0.00497
7269:[cfp_fp][120000]Accuracy-Flip: 0.87186+-0.01836
7274:[agedb_30][120000]Accuracy-Flip: 0.94933+-0.01123
7384:[lfw][122000]Accuracy-Flip: 0.99183+-0.00497
7389:[cfp_fp][122000]Accuracy-Flip: 0.87357+-0.01945
7394:[agedb_30][122000]Accuracy-Flip: 0.94833+-0.01249
7504:[lfw][124000]Accuracy-Flip: 0.99150+-0.00462
7509:[cfp_fp][124000]Accuracy-Flip: 0.87386+-0.01927
7514:[agedb_30][124000]Accuracy-Flip: 0.95000+-0.01083
7624:[lfw][126000]Accuracy-Flip: 0.99133+-0.00542
7629:[cfp_fp][126000]Accuracy-Flip: 0.87557+-0.01808
7634:[agedb_30][126000]Accuracy-Flip: 0.95083+-0.01188
7747:[lfw][128000]Accuracy-Flip: 0.99233+-0.00416
7752:[cfp_fp][128000]Accuracy-Flip: 0.87357+-0.01829
7757:[agedb_30][128000]Accuracy-Flip: 0.95017+-0.01124
7867:[lfw][130000]Accuracy-Flip: 0.99217+-0.00435
7872:[cfp_fp][130000]Accuracy-Flip: 0.87371+-0.01771
7877:[agedb_30][130000]Accuracy-Flip: 0.94867+-0.01132
7987:[lfw][132000]Accuracy-Flip: 0.99133+-0.00499
7992:[cfp_fp][132000]Accuracy-Flip: 0.87600+-0.01931
7997:[agedb_30][132000]Accuracy-Flip: 0.95150+-0.01097
8107:[lfw][134000]Accuracy-Flip: 0.99150+-0.00480
8112:[cfp_fp][134000]Accuracy-Flip: 0.87471+-0.01782
8117:[agedb_30][134000]Accuracy-Flip: 0.95033+-0.01137
8227:[lfw][136000]Accuracy-Flip: 0.99117+-0.00483
8232:[cfp_fp][136000]Accuracy-Flip: 0.87200+-0.01815
8237:[agedb_30][136000]Accuracy-Flip: 0.94933+-0.01184
8347:[lfw][138000]Accuracy-Flip: 0.99167+-0.00494
8352:[cfp_fp][138000]Accuracy-Flip: 0.87557+-0.01652
8357:[agedb_30][138000]Accuracy-Flip: 0.94917+-0.01179
8467:[lfw][140000]Accuracy-Flip: 0.99167+-0.00447
8472:[cfp_fp][140000]Accuracy-Flip: 0.87314+-0.01756
8477:[agedb_30][140000]Accuracy-Flip: 0.94867+-0.01157
8587:[lfw][142000]Accuracy-Flip: 0.99150+-0.00474
8592:[cfp_fp][142000]Accuracy-Flip: 0.87386+-0.01921
8597:[agedb_30][142000]Accuracy-Flip: 0.95083+-0.01146
8707:[lfw][144000]Accuracy-Flip: 0.99100+-0.00478
8712:[cfp_fp][144000]Accuracy-Flip: 0.87314+-0.01959
8717:[agedb_30][144000]Accuracy-Flip: 0.94750+-0.01216
8827:[lfw][146000]Accuracy-Flip: 0.99250+-0.00403
8832:[cfp_fp][146000]Accuracy-Flip: 0.87514+-0.01788
8837:[agedb_30][146000]Accuracy-Flip: 0.95133+-0.01061
8947:[lfw][148000]Accuracy-Flip: 0.99183+-0.00480
8952:[cfp_fp][148000]Accuracy-Flip: 0.87329+-0.01880
8957:[agedb_30][148000]Accuracy-Flip: 0.94783+-0.01155
9067:[lfw][150000]Accuracy-Flip: 0.99117+-0.00527
9072:[cfp_fp][150000]Accuracy-Flip: 0.87557+-0.01878
9077:[agedb_30][150000]Accuracy-Flip: 0.94983+-0.01081
9187:[lfw][152000]Accuracy-Flip: 0.99167+-0.00494
9192:[cfp_fp][152000]Accuracy-Flip: 0.87386+-0.01922
9197:[agedb_30][152000]Accuracy-Flip: 0.94867+-0.01171
9310:[lfw][154000]Accuracy-Flip: 0.99250+-0.00403
9315:[cfp_fp][154000]Accuracy-Flip: 0.87543+-0.01910
9320:[agedb_30][154000]Accuracy-Flip: 0.95083+-0.01070
9430:[lfw][156000]Accuracy-Flip: 0.99217+-0.00435
9435:[cfp_fp][156000]Accuracy-Flip: 0.87357+-0.01813
9440:[agedb_30][156000]Accuracy-Flip: 0.94933+-0.01230
9550:[lfw][158000]Accuracy-Flip: 0.99233+-0.00396
9555:[cfp_fp][158000]Accuracy-Flip: 0.87557+-0.01773
9560:[agedb_30][158000]Accuracy-Flip: 0.94917+-0.01091
9670:[lfw][160000]Accuracy-Flip: 0.99167+-0.00465
9675:[cfp_fp][160000]Accuracy-Flip: 0.87329+-0.01801
9680:[agedb_30][160000]Accuracy-Flip: 0.95117+-0.01085
9790:[lfw][162000]Accuracy-Flip: 0.99183+-0.00462
9795:[cfp_fp][162000]Accuracy-Flip: 0.87557+-0.01705
9800:[agedb_30][162000]Accuracy-Flip: 0.95083+-0.01078
9910:[lfw][164000]Accuracy-Flip: 0.99117+-0.00506
9915:[cfp_fp][164000]Accuracy-Flip: 0.87257+-0.01834
9920:[agedb_30][164000]Accuracy-Flip: 0.95000+-0.01138
10030:[lfw][166000]Accuracy-Flip: 0.99200+-0.00407
10035:[cfp_fp][166000]Accuracy-Flip: 0.87557+-0.01949
10040:[agedb_30][166000]Accuracy-Flip: 0.94983+-0.01063
10150:[lfw][168000]Accuracy-Flip: 0.99150+-0.00480
10155:[cfp_fp][168000]Accuracy-Flip: 0.87529+-0.01853
10160:[agedb_30][168000]Accuracy-Flip: 0.95000+-0.01155
10270:[lfw][170000]Accuracy-Flip: 0.99167+-0.00447
10275:[cfp_fp][170000]Accuracy-Flip: 0.87471+-0.01917
10280:[agedb_30][170000]Accuracy-Flip: 0.94917+-0.01188
10390:[lfw][172000]Accuracy-Flip: 0.99217+-0.00415
10395:[cfp_fp][172000]Accuracy-Flip: 0.87600+-0.01864
10400:[agedb_30][172000]Accuracy-Flip: 0.95100+-0.01073
10510:[lfw][174000]Accuracy-Flip: 0.99233+-0.00416
10515:[cfp_fp][174000]Accuracy-Flip: 0.87429+-0.01881
10520:[agedb_30][174000]Accuracy-Flip: 0.95083+-0.01101
10630:[lfw][176000]Accuracy-Flip: 0.99233+-0.00416
10635:[cfp_fp][176000]Accuracy-Flip: 0.87271+-0.02009
10640:[agedb_30][176000]Accuracy-Flip: 0.94983+-0.01153
10753:[lfw][178000]Accuracy-Flip: 0.99200+-0.00458
10758:[cfp_fp][178000]Accuracy-Flip: 0.87314+-0.01914
10763:[agedb_30][178000]Accuracy-Flip: 0.95100+-0.01031
10873:[lfw][180000]Accuracy-Flip: 0.99133+-0.00499
10878:[cfp_fp][180000]Accuracy-Flip: 0.87243+-0.01863
10883:[agedb_30][180000]Accuracy-Flip: 0.95083+-0.01036
10993:[lfw][182000]Accuracy-Flip: 0.99183+-0.00418
10998:[cfp_fp][182000]Accuracy-Flip: 0.87329+-0.01853
11003:[agedb_30][182000]Accuracy-Flip: 0.95083+-0.01188
11113:[lfw][184000]Accuracy-Flip: 0.99183+-0.00462
11118:[cfp_fp][184000]Accuracy-Flip: 0.87414+-0.01864
11123:[agedb_30][184000]Accuracy-Flip: 0.95167+-0.01125
11233:[lfw][186000]Accuracy-Flip: 0.99133+-0.00470
11238:[cfp_fp][186000]Accuracy-Flip: 0.87314+-0.02024
11243:[agedb_30][186000]Accuracy-Flip: 0.95067+-0.01028
11353:[lfw][188000]Accuracy-Flip: 0.99217+-0.00435
11358:[cfp_fp][188000]Accuracy-Flip: 0.87214+-0.01894
11363:[agedb_30][188000]Accuracy-Flip: 0.94967+-0.01171
11473:[lfw][190000]Accuracy-Flip: 0.99150+-0.00529
11478:[cfp_fp][190000]Accuracy-Flip: 0.87543+-0.01694
11483:[agedb_30][190000]Accuracy-Flip: 0.95000+-0.01046
11593:[lfw][192000]Accuracy-Flip: 0.99200+-0.00452
11598:[cfp_fp][192000]Accuracy-Flip: 0.87429+-0.01925
11603:[agedb_30][192000]Accuracy-Flip: 0.95100+-0.01031
11713:[lfw][194000]Accuracy-Flip: 0.99117+-0.00483
11718:[cfp_fp][194000]Accuracy-Flip: 0.87243+-0.01916
11723:[agedb_30][194000]Accuracy-Flip: 0.95117+-0.01111
11833:[lfw][196000]Accuracy-Flip: 0.99117+-0.00527
11838:[cfp_fp][196000]Accuracy-Flip: 0.87186+-0.01838
11843:[agedb_30][196000]Accuracy-Flip: 0.95050+-0.01070
11953:[lfw][198000]Accuracy-Flip: 0.99150+-0.00497
11958:[cfp_fp][198000]Accuracy-Flip: 0.87486+-0.01881
11963:[agedb_30][198000]Accuracy-Flip: 0.94817+-0.01107
12073:[lfw][200000]Accuracy-Flip: 0.99217+-0.00435
12078:[cfp_fp][200000]Accuracy-Flip: 0.87329+-0.01764
12083:[agedb_30][200000]Accuracy-Flip: 0.94967+-0.01194
12193:[lfw][202000]Accuracy-Flip: 0.99250+-0.00403
12198:[cfp_fp][202000]Accuracy-Flip: 0.87286+-0.01864
12203:[agedb_30][202000]Accuracy-Flip: 0.94917+-0.01214
12315:[lfw][204000]Accuracy-Flip: 0.99233+-0.00416
12320:[cfp_fp][204000]Accuracy-Flip: 0.87614+-0.01836
12325:[agedb_30][204000]Accuracy-Flip: 0.94917+-0.01188
12435:[lfw][206000]Accuracy-Flip: 0.99200+-0.00433
12440:[cfp_fp][206000]Accuracy-Flip: 0.87429+-0.01895
12445:[agedb_30][206000]Accuracy-Flip: 0.95167+-0.01035
12555:[lfw][208000]Accuracy-Flip: 0.99183+-0.00462
12560:[cfp_fp][208000]Accuracy-Flip: 0.87443+-0.01863
12565:[agedb_30][208000]Accuracy-Flip: 0.95117+-0.01111
12675:[lfw][210000]Accuracy-Flip: 0.99217+-0.00435
12680:[cfp_fp][210000]Accuracy-Flip: 0.87557+-0.01796
12685:[agedb_30][210000]Accuracy-Flip: 0.95067+-0.01170
12795:[lfw][212000]Accuracy-Flip: 0.99200+-0.00433
12800:[cfp_fp][212000]Accuracy-Flip: 0.87371+-0.01985
12805:[agedb_30][212000]Accuracy-Flip: 0.95033+-0.01122
12915:[lfw][214000]Accuracy-Flip: 0.99233+-0.00416
12920:[cfp_fp][214000]Accuracy-Flip: 0.87529+-0.01737
12925:[agedb_30][214000]Accuracy-Flip: 0.95017+-0.01168
13035:[lfw][216000]Accuracy-Flip: 0.99150+-0.00468
13040:[cfp_fp][216000]Accuracy-Flip: 0.87514+-0.01849
13045:[agedb_30][216000]Accuracy-Flip: 0.94983+-0.01180
13155:[lfw][218000]Accuracy-Flip: 0.99317+-0.00437
13160:[cfp_fp][218000]Accuracy-Flip: 0.87271+-0.01744
13165:[agedb_30][218000]Accuracy-Flip: 0.95067+-0.01062
13275:[lfw][220000]Accuracy-Flip: 0.99167+-0.00494
13280:[cfp_fp][220000]Accuracy-Flip: 0.87443+-0.01926
13285:[agedb_30][220000]Accuracy-Flip: 0.95017+-0.01127
13395:[lfw][222000]Accuracy-Flip: 0.99200+-0.00433
13400:[cfp_fp][222000]Accuracy-Flip: 0.87357+-0.01812
13405:[agedb_30][222000]Accuracy-Flip: 0.95100+-0.01086
13515:[lfw][224000]Accuracy-Flip: 0.99117+-0.00538
13520:[cfp_fp][224000]Accuracy-Flip: 0.87371+-0.01918
13525:[agedb_30][224000]Accuracy-Flip: 0.95100+-0.01126
13635:[lfw][226000]Accuracy-Flip: 0.99183+-0.00474
13640:[cfp_fp][226000]Accuracy-Flip: 0.87414+-0.01812
13645:[agedb_30][226000]Accuracy-Flip: 0.95150+-0.00979
13755:[lfw][228000]Accuracy-Flip: 0.99167+-0.00532
13760:[cfp_fp][228000]Accuracy-Flip: 0.87429+-0.01870
13765:[agedb_30][228000]Accuracy-Flip: 0.95117+-0.01011
13878:[lfw][230000]Accuracy-Flip: 0.99133+-0.00493
13883:[cfp_fp][230000]Accuracy-Flip: 0.87443+-0.01937
13888:[agedb_30][230000]Accuracy-Flip: 0.95083+-0.01121
13998:[lfw][232000]Accuracy-Flip: 0.99183+-0.00480
14003:[cfp_fp][232000]Accuracy-Flip: 0.87229+-0.01862
14008:[agedb_30][232000]Accuracy-Flip: 0.95067+-0.01017
14118:[lfw][234000]Accuracy-Flip: 0.99133+-0.00482
14123:[cfp_fp][234000]Accuracy-Flip: 0.87400+-0.01754
14128:[agedb_30][234000]Accuracy-Flip: 0.95050+-0.01033
14238:[lfw][236000]Accuracy-Flip: 0.99183+-0.00519
14243:[cfp_fp][236000]Accuracy-Flip: 0.87414+-0.01768
14248:[agedb_30][236000]Accuracy-Flip: 0.95067+-0.01065
14358:[lfw][238000]Accuracy-Flip: 0.99183+-0.00462
14363:[cfp_fp][238000]Accuracy-Flip: 0.87486+-0.01831
14368:[agedb_30][238000]Accuracy-Flip: 0.95150+-0.01076
14478:[lfw][240000]Accuracy-Flip: 0.99167+-0.00532
14483:[cfp_fp][240000]Accuracy-Flip: 0.87400+-0.01814
14488:[agedb_30][240000]Accuracy-Flip: 0.94917+-0.01086
14598:[lfw][242000]Accuracy-Flip: 0.99133+-0.00452
14603:[cfp_fp][242000]Accuracy-Flip: 0.87314+-0.01825
14608:[agedb_30][242000]Accuracy-Flip: 0.95133+-0.01132
14718:[lfw][244000]Accuracy-Flip: 0.99200+-0.00464
14723:[cfp_fp][244000]Accuracy-Flip: 0.87386+-0.01878
14728:[agedb_30][244000]Accuracy-Flip: 0.94983+-0.01161
14838:[lfw][246000]Accuracy-Flip: 0.99150+-0.00508
14843:[cfp_fp][246000]Accuracy-Flip: 0.87286+-0.01837
14848:[agedb_30][246000]Accuracy-Flip: 0.95117+-0.01106
14958:[lfw][248000]Accuracy-Flip: 0.99133+-0.00488
14963:[cfp_fp][248000]Accuracy-Flip: 0.87371+-0.01706
14968:[agedb_30][248000]Accuracy-Flip: 0.95083+-0.01091
15078:[lfw][250000]Accuracy-Flip: 0.99183+-0.00418
15083:[cfp_fp][250000]Accuracy-Flip: 0.87143+-0.01780
15088:[agedb_30][250000]Accuracy-Flip: 0.95050+-0.01073
15198:[lfw][252000]Accuracy-Flip: 0.99233+-0.00403
15203:[cfp_fp][252000]Accuracy-Flip: 0.87400+-0.01914
15208:[agedb_30][252000]Accuracy-Flip: 0.95083+-0.01041
15321:[lfw][254000]Accuracy-Flip: 0.99167+-0.00494
15326:[cfp_fp][254000]Accuracy-Flip: 0.87314+-0.01849
15331:[agedb_30][254000]Accuracy-Flip: 0.95117+-0.01017
15441:[lfw][256000]Accuracy-Flip: 0.99167+-0.00511
15446:[cfp_fp][256000]Accuracy-Flip: 0.87243+-0.01926
15451:[agedb_30][256000]Accuracy-Flip: 0.95017+-0.01097
15561:[lfw][258000]Accuracy-Flip: 0.99200+-0.00446
15566:[cfp_fp][258000]Accuracy-Flip: 0.87314+-0.02032
15571:[agedb_30][258000]Accuracy-Flip: 0.94983+-0.01114
15681:[lfw][260000]Accuracy-Flip: 0.99133+-0.00493
15686:[cfp_fp][260000]Accuracy-Flip: 0.87257+-0.01876
15691:[agedb_30][260000]Accuracy-Flip: 0.95017+-0.01081
15801:[lfw][262000]Accuracy-Flip: 0.99167+-0.00494
15806:[cfp_fp][262000]Accuracy-Flip: 0.87157+-0.01815
15811:[agedb_30][262000]Accuracy-Flip: 0.95117+-0.01070
15921:[lfw][264000]Accuracy-Flip: 0.99117+-0.00527
15926:[cfp_fp][264000]Accuracy-Flip: 0.87329+-0.01660
15931:[agedb_30][264000]Accuracy-Flip: 0.95117+-0.01116
16041:[lfw][266000]Accuracy-Flip: 0.99150+-0.00486
16046:[cfp_fp][266000]Accuracy-Flip: 0.87371+-0.01845
16051:[agedb_30][266000]Accuracy-Flip: 0.94983+-0.01170
16161:[lfw][268000]Accuracy-Flip: 0.99133+-0.00515
16166:[cfp_fp][268000]Accuracy-Flip: 0.87386+-0.01975
16171:[agedb_30][268000]Accuracy-Flip: 0.95183+-0.01104
16281:[lfw][270000]Accuracy-Flip: 0.99133+-0.00493
16286:[cfp_fp][270000]Accuracy-Flip: 0.87643+-0.01817
16291:[agedb_30][270000]Accuracy-Flip: 0.95050+-0.01090
16401:[lfw][272000]Accuracy-Flip: 0.99167+-0.00516
16406:[cfp_fp][272000]Accuracy-Flip: 0.87457+-0.01707
16411:[agedb_30][272000]Accuracy-Flip: 0.95150+-0.01007
16521:[lfw][274000]Accuracy-Flip: 0.99167+-0.00494
16526:[cfp_fp][274000]Accuracy-Flip: 0.87357+-0.01861
16531:[agedb_30][274000]Accuracy-Flip: 0.95033+-0.01002
16641:[lfw][276000]Accuracy-Flip: 0.99200+-0.00464
16646:[cfp_fp][276000]Accuracy-Flip: 0.87543+-0.01803
16651:[agedb_30][276000]Accuracy-Flip: 0.95133+-0.01027
16761:[lfw][278000]Accuracy-Flip: 0.99150+-0.00462
16766:[cfp_fp][278000]Accuracy-Flip: 0.87229+-0.01826
16771:[agedb_30][278000]Accuracy-Flip: 0.95100+-0.01119
16884:[lfw][280000]Accuracy-Flip: 0.99217+-0.00435
16889:[cfp_fp][280000]Accuracy-Flip: 0.87500+-0.01853
16894:[agedb_30][280000]Accuracy-Flip: 0.95067+-0.01101
17004:[lfw][282000]Accuracy-Flip: 0.99133+-0.00515
17009:[cfp_fp][282000]Accuracy-Flip: 0.87514+-0.01880
17014:[agedb_30][282000]Accuracy-Flip: 0.95017+-0.01119
17124:[lfw][284000]Accuracy-Flip: 0.99133+-0.00458
17129:[cfp_fp][284000]Accuracy-Flip: 0.87271+-0.01815
17134:[agedb_30][284000]Accuracy-Flip: 0.94967+-0.01077
17244:[lfw][286000]Accuracy-Flip: 0.99117+-0.00489
17249:[cfp_fp][286000]Accuracy-Flip: 0.87429+-0.01864
17254:[agedb_30][286000]Accuracy-Flip: 0.95100+-0.01153
17364:[lfw][288000]Accuracy-Flip: 0.99267+-0.00410
17369:[cfp_fp][288000]Accuracy-Flip: 0.87357+-0.01855
17374:[agedb_30][288000]Accuracy-Flip: 0.95033+-0.01132
17484:[lfw][290000]Accuracy-Flip: 0.99250+-0.00403
17489:[cfp_fp][290000]Accuracy-Flip: 0.87286+-0.01941
17494:[agedb_30][290000]Accuracy-Flip: 0.95183+-0.01071
17604:[lfw][292000]Accuracy-Flip: 0.99267+-0.00410
17609:[cfp_fp][292000]Accuracy-Flip: 0.87471+-0.01927
17614:[agedb_30][292000]Accuracy-Flip: 0.95083+-0.01086
17724:[lfw][294000]Accuracy-Flip: 0.99183+-0.00474
17729:[cfp_fp][294000]Accuracy-Flip: 0.87529+-0.01841
17734:[agedb_30][294000]Accuracy-Flip: 0.95083+-0.01104
17844:[lfw][296000]Accuracy-Flip: 0.99200+-0.00433
17849:[cfp_fp][296000]Accuracy-Flip: 0.87271+-0.01850
17854:[agedb_30][296000]Accuracy-Flip: 0.95083+-0.01104
17964:[lfw][298000]Accuracy-Flip: 0.99183+-0.00437
17969:[cfp_fp][298000]Accuracy-Flip: 0.87300+-0.01756
17974:[agedb_30][298000]Accuracy-Flip: 0.95117+-0.01152
18084:[lfw][300000]Accuracy-Flip: 0.99167+-0.00532
18089:[cfp_fp][300000]Accuracy-Flip: 0.87457+-0.01950
18094:[agedb_30][300000]Accuracy-Flip: 0.94967+-0.01122
18204:[lfw][302000]Accuracy-Flip: 0.99183+-0.00462
18209:[cfp_fp][302000]Accuracy-Flip: 0.87500+-0.01804
18214:[agedb_30][302000]Accuracy-Flip: 0.95100+-0.01155
18324:[lfw][304000]Accuracy-Flip: 0.99250+-0.00403
18329:[cfp_fp][304000]Accuracy-Flip: 0.87443+-0.01962
18334:[agedb_30][304000]Accuracy-Flip: 0.95167+-0.01106
18446:[lfw][306000]Accuracy-Flip: 0.99267+-0.00410
18451:[cfp_fp][306000]Accuracy-Flip: 0.87414+-0.02000
18456:[agedb_30][306000]Accuracy-Flip: 0.95150+-0.01079
18566:[lfw][308000]Accuracy-Flip: 0.99133+-0.00493
18571:[cfp_fp][308000]Accuracy-Flip: 0.87514+-0.01849
18576:[agedb_30][308000]Accuracy-Flip: 0.95083+-0.01036
18686:[lfw][310000]Accuracy-Flip: 0.99217+-0.00472
18691:[cfp_fp][310000]Accuracy-Flip: 0.87557+-0.01735
18696:[agedb_30][310000]Accuracy-Flip: 0.95083+-0.01065
18806:[lfw][312000]Accuracy-Flip: 0.99217+-0.00472
18811:[cfp_fp][312000]Accuracy-Flip: 0.87471+-0.01837
18816:[agedb_30][312000]Accuracy-Flip: 0.95050+-0.01111
18926:[lfw][314000]Accuracy-Flip: 0.99150+-0.00497
18931:[cfp_fp][314000]Accuracy-Flip: 0.87200+-0.01898
18936:[agedb_30][314000]Accuracy-Flip: 0.94983+-0.01189
19046:[lfw][316000]Accuracy-Flip: 0.99250+-0.00403
19051:[cfp_fp][316000]Accuracy-Flip: 0.87257+-0.01973
19056:[agedb_30][316000]Accuracy-Flip: 0.95033+-0.01127
19166:[lfw][318000]Accuracy-Flip: 0.99217+-0.00435
19171:[cfp_fp][318000]Accuracy-Flip: 0.87543+-0.01731
19176:[agedb_30][318000]Accuracy-Flip: 0.95000+-0.01160
19286:[lfw][320000]Accuracy-Flip: 0.99167+-0.00435
19291:[cfp_fp][320000]Accuracy-Flip: 0.87500+-0.01823
19296:[agedb_30][320000]Accuracy-Flip: 0.95017+-0.01099
19406:[lfw][322000]Accuracy-Flip: 0.99183+-0.00497
19411:[cfp_fp][322000]Accuracy-Flip: 0.87329+-0.01868
19416:[agedb_30][322000]Accuracy-Flip: 0.94900+-0.01188
19526:[lfw][324000]Accuracy-Flip: 0.99217+-0.00435
19531:[cfp_fp][324000]Accuracy-Flip: 0.87371+-0.01985
19536:[agedb_30][324000]Accuracy-Flip: 0.95200+-0.01118
19646:[lfw][326000]Accuracy-Flip: 0.99117+-0.00522
19651:[cfp_fp][326000]Accuracy-Flip: 0.87600+-0.01853
19656:[agedb_30][326000]Accuracy-Flip: 0.95050+-0.01088
19766:[lfw][328000]Accuracy-Flip: 0.99117+-0.00483
19771:[cfp_fp][328000]Accuracy-Flip: 0.87529+-0.01797
19776:[agedb_30][328000]Accuracy-Flip: 0.95033+-0.01085
19889:[lfw][330000]Accuracy-Flip: 0.99133+-0.00452
19894:[cfp_fp][330000]Accuracy-Flip: 0.87329+-0.01913
19899:[agedb_30][330000]Accuracy-Flip: 0.95083+-0.01070
20009:[lfw][332000]Accuracy-Flip: 0.99167+-0.00435
20014:[cfp_fp][332000]Accuracy-Flip: 0.87371+-0.01798
20019:[agedb_30][332000]Accuracy-Flip: 0.94950+-0.01162
20129:[lfw][334000]Accuracy-Flip: 0.99233+-0.00442
20134:[cfp_fp][334000]Accuracy-Flip: 0.87486+-0.01856
20139:[agedb_30][334000]Accuracy-Flip: 0.95117+-0.01103
20249:[lfw][336000]Accuracy-Flip: 0.99117+-0.00495
20254:[cfp_fp][336000]Accuracy-Flip: 0.87371+-0.01945
20259:[agedb_30][336000]Accuracy-Flip: 0.95150+-0.01149
20369:[lfw][338000]Accuracy-Flip: 0.99217+-0.00435
20374:[cfp_fp][338000]Accuracy-Flip: 0.87357+-0.01806
20379:[agedb_30][338000]Accuracy-Flip: 0.94950+-0.00995
20489:[lfw][340000]Accuracy-Flip: 0.99183+-0.00450
20494:[cfp_fp][340000]Accuracy-Flip: 0.87186+-0.01836
20499:[agedb_30][340000]Accuracy-Flip: 0.94967+-0.01173
20609:[lfw][342000]Accuracy-Flip: 0.99233+-0.00442
20614:[cfp_fp][342000]Accuracy-Flip: 0.87357+-0.01993
20619:[agedb_30][342000]Accuracy-Flip: 0.95000+-0.01181
20729:[lfw][344000]Accuracy-Flip: 0.99233+-0.00403
20734:[cfp_fp][344000]Accuracy-Flip: 0.87257+-0.01895
20739:[agedb_30][344000]Accuracy-Flip: 0.95067+-0.01128
20849:[lfw][346000]Accuracy-Flip: 0.99183+-0.00462
20854:[cfp_fp][346000]Accuracy-Flip: 0.87429+-0.01900
20859:[agedb_30][346000]Accuracy-Flip: 0.95017+-0.01134
20969:[lfw][348000]Accuracy-Flip: 0.99183+-0.00462
20974:[cfp_fp][348000]Accuracy-Flip: 0.87414+-0.01825
20979:[agedb_30][348000]Accuracy-Flip: 0.95100+-0.01126
21089:[lfw][350000]Accuracy-Flip: 0.99217+-0.00435
21094:[cfp_fp][350000]Accuracy-Flip: 0.87229+-0.01920
21099:[agedb_30][350000]Accuracy-Flip: 0.95067+-0.01111
21209:[lfw][352000]Accuracy-Flip: 0.99267+-0.00403
21214:[cfp_fp][352000]Accuracy-Flip: 0.87286+-0.01748
21219:[agedb_30][352000]Accuracy-Flip: 0.95067+-0.01123
21329:[lfw][354000]Accuracy-Flip: 0.99217+-0.00472
21334:[cfp_fp][354000]Accuracy-Flip: 0.87357+-0.01874
21339:[agedb_30][354000]Accuracy-Flip: 0.95067+-0.01062
21452:[lfw][356000]Accuracy-Flip: 0.99217+-0.00415
21457:[cfp_fp][356000]Accuracy-Flip: 0.87100+-0.01824
21462:[agedb_30][356000]Accuracy-Flip: 0.95067+-0.01028
21572:[lfw][358000]Accuracy-Flip: 0.99167+-0.00477
21577:[cfp_fp][358000]Accuracy-Flip: 0.87343+-0.01936
21582:[agedb_30][358000]Accuracy-Flip: 0.95050+-0.01036
21692:[lfw][360000]Accuracy-Flip: 0.99117+-0.00489
21697:[cfp_fp][360000]Accuracy-Flip: 0.87571+-0.01848
21702:[agedb_30][360000]Accuracy-Flip: 0.95050+-0.01131
21812:[lfw][362000]Accuracy-Flip: 0.99233+-0.00442
21817:[cfp_fp][362000]Accuracy-Flip: 0.87286+-0.01867
21822:[agedb_30][362000]Accuracy-Flip: 0.95150+-0.01107
21932:[lfw][364000]Accuracy-Flip: 0.99167+-0.00477
21937:[cfp_fp][364000]Accuracy-Flip: 0.87329+-0.02003
21942:[agedb_30][364000]Accuracy-Flip: 0.95050+-0.01188
22052:[lfw][366000]Accuracy-Flip: 0.99200+-0.00446
22057:[cfp_fp][366000]Accuracy-Flip: 0.87171+-0.01986
22062:[agedb_30][366000]Accuracy-Flip: 0.95167+-0.01075
22172:[lfw][368000]Accuracy-Flip: 0.99150+-0.00545
22177:[cfp_fp][368000]Accuracy-Flip: 0.87257+-0.01876
22182:[agedb_30][368000]Accuracy-Flip: 0.95100+-0.01044
22292:[lfw][370000]Accuracy-Flip: 0.99200+-0.00452
22297:[cfp_fp][370000]Accuracy-Flip: 0.87486+-0.01839
22302:[agedb_30][370000]Accuracy-Flip: 0.95050+-0.01106
22412:[lfw][372000]Accuracy-Flip: 0.99217+-0.00435
22417:[cfp_fp][372000]Accuracy-Flip: 0.87400+-0.01833
22422:[agedb_30][372000]Accuracy-Flip: 0.95133+-0.01087
22532:[lfw][374000]Accuracy-Flip: 0.99167+-0.00447
22537:[cfp_fp][374000]Accuracy-Flip: 0.87386+-0.01824
22542:[agedb_30][374000]Accuracy-Flip: 0.95133+-0.01077
22652:[lfw][376000]Accuracy-Flip: 0.99233+-0.00442
22657:[cfp_fp][376000]Accuracy-Flip: 0.87486+-0.01914
22662:[agedb_30][376000]Accuracy-Flip: 0.95050+-0.01113
22772:[lfw][378000]Accuracy-Flip: 0.99167+-0.00494
22777:[cfp_fp][378000]Accuracy-Flip: 0.87129+-0.01986
22782:[agedb_30][378000]Accuracy-Flip: 0.95033+-0.01080
22892:[lfw][380000]Accuracy-Flip: 0.99200+-0.00452
22897:[cfp_fp][380000]Accuracy-Flip: 0.87357+-0.01813
22902:[agedb_30][380000]Accuracy-Flip: 0.95033+-0.01108
23015:[lfw][382000]Accuracy-Flip: 0.99167+-0.00428
23020:[cfp_fp][382000]Accuracy-Flip: 0.87314+-0.01835
23025:[agedb_30][382000]Accuracy-Flip: 0.95150+-0.01055
23135:[lfw][384000]Accuracy-Flip: 0.99250+-0.00403
23140:[cfp_fp][384000]Accuracy-Flip: 0.87171+-0.01951
23145:[agedb_30][384000]Accuracy-Flip: 0.95233+-0.01031
23255:[lfw][386000]Accuracy-Flip: 0.99167+-0.00453
23260:[cfp_fp][386000]Accuracy-Flip: 0.87314+-0.01874
23265:[agedb_30][386000]Accuracy-Flip: 0.95100+-0.01218
23375:[lfw][388000]Accuracy-Flip: 0.99183+-0.00462
23380:[cfp_fp][388000]Accuracy-Flip: 0.87300+-0.01918
23385:[agedb_30][388000]Accuracy-Flip: 0.95017+-0.01139
23495:[lfw][390000]Accuracy-Flip: 0.99150+-0.00508
23500:[cfp_fp][390000]Accuracy-Flip: 0.87471+-0.01962
23505:[agedb_30][390000]Accuracy-Flip: 0.94933+-0.01086
23615:[lfw][392000]Accuracy-Flip: 0.99167+-0.00494
23620:[cfp_fp][392000]Accuracy-Flip: 0.87386+-0.01867
23625:[agedb_30][392000]Accuracy-Flip: 0.94900+-0.01155
23735:[lfw][394000]Accuracy-Flip: 0.99250+-0.00461
23740:[cfp_fp][394000]Accuracy-Flip: 0.87443+-0.01936
23745:[agedb_30][394000]Accuracy-Flip: 0.95017+-0.01053
23855:[lfw][396000]Accuracy-Flip: 0.99167+-0.00494
23860:[cfp_fp][396000]Accuracy-Flip: 0.87257+-0.01840
23865:[agedb_30][396000]Accuracy-Flip: 0.94983+-0.01076
23975:[lfw][398000]Accuracy-Flip: 0.99250+-0.00473
23980:[cfp_fp][398000]Accuracy-Flip: 0.87314+-0.01923
23985:[agedb_30][398000]Accuracy-Flip: 0.95017+-0.01149
24095:[lfw][400000]Accuracy-Flip: 0.99183+-0.00480
24100:[cfp_fp][400000]Accuracy-Flip: 0.87229+-0.01861
24105:[agedb_30][400000]Accuracy-Flip: 0.95167+-0.01130
24215:[lfw][402000]Accuracy-Flip: 0.99167+-0.00477
24220:[cfp_fp][402000]Accuracy-Flip: 0.87186+-0.01930
24225:[agedb_30][402000]Accuracy-Flip: 0.95067+-0.01070
24335:[lfw][404000]Accuracy-Flip: 0.99200+-0.00470
24340:[cfp_fp][404000]Accuracy-Flip: 0.87386+-0.02004
24345:[agedb_30][404000]Accuracy-Flip: 0.95183+-0.01089
24457:[lfw][406000]Accuracy-Flip: 0.99267+-0.00410
24462:[cfp_fp][406000]Accuracy-Flip: 0.87543+-0.01923
24467:[agedb_30][406000]Accuracy-Flip: 0.95100+-0.01114
24577:[lfw][408000]Accuracy-Flip: 0.99217+-0.00435
24582:[cfp_fp][408000]Accuracy-Flip: 0.87386+-0.01826
24587:[agedb_30][408000]Accuracy-Flip: 0.94850+-0.01109
24697:[lfw][410000]Accuracy-Flip: 0.99250+-0.00403
24702:[cfp_fp][410000]Accuracy-Flip: 0.87329+-0.01844
24707:[agedb_30][410000]Accuracy-Flip: 0.95200+-0.01019
24817:[lfw][412000]Accuracy-Flip: 0.99200+-0.00470
24822:[cfp_fp][412000]Accuracy-Flip: 0.87557+-0.01798
24827:[agedb_30][412000]Accuracy-Flip: 0.95100+-0.01104
24937:[lfw][414000]Accuracy-Flip: 0.99183+-0.00497
24942:[cfp_fp][414000]Accuracy-Flip: 0.87500+-0.02046
24947:[agedb_30][414000]Accuracy-Flip: 0.95017+-0.01037
25057:[lfw][416000]Accuracy-Flip: 0.99167+-0.00494
25062:[cfp_fp][416000]Accuracy-Flip: 0.87414+-0.01964
25067:[agedb_30][416000]Accuracy-Flip: 0.94933+-0.01179
25177:[lfw][418000]Accuracy-Flip: 0.99150+-0.00508
25182:[cfp_fp][418000]Accuracy-Flip: 0.87529+-0.01803
25187:[agedb_30][418000]Accuracy-Flip: 0.95117+-0.01128
25297:[lfw][420000]Accuracy-Flip: 0.99267+-0.00410
25302:[cfp_fp][420000]Accuracy-Flip: 0.87357+-0.01930
25307:[agedb_30][420000]Accuracy-Flip: 0.95067+-0.01109
25417:[lfw][422000]Accuracy-Flip: 0.99267+-0.00410
25422:[cfp_fp][422000]Accuracy-Flip: 0.87514+-0.01882
25427:[agedb_30][422000]Accuracy-Flip: 0.94933+-0.01193
25537:[lfw][424000]Accuracy-Flip: 0.99200+-0.00446
25542:[cfp_fp][424000]Accuracy-Flip: 0.87186+-0.02030
25547:[agedb_30][424000]Accuracy-Flip: 0.95067+-0.01148
25657:[lfw][426000]Accuracy-Flip: 0.99183+-0.00462
25662:[cfp_fp][426000]Accuracy-Flip: 0.87457+-0.01966
25667:[agedb_30][426000]Accuracy-Flip: 0.95067+-0.01049
25777:[lfw][428000]Accuracy-Flip: 0.99183+-0.00480
25782:[cfp_fp][428000]Accuracy-Flip: 0.87343+-0.01837
25787:[agedb_30][428000]Accuracy-Flip: 0.94967+-0.01090
25897:[lfw][430000]Accuracy-Flip: 0.99183+-0.00462
25902:[cfp_fp][430000]Accuracy-Flip: 0.87543+-0.01839
25907:[agedb_30][430000]Accuracy-Flip: 0.95167+-0.01088
26020:[lfw][432000]Accuracy-Flip: 0.99133+-0.00542
26025:[cfp_fp][432000]Accuracy-Flip: 0.87229+-0.01822
26030:[agedb_30][432000]Accuracy-Flip: 0.95067+-0.01075
26140:[lfw][434000]Accuracy-Flip: 0.99200+-0.00452
26145:[cfp_fp][434000]Accuracy-Flip: 0.87571+-0.01990
26150:[agedb_30][434000]Accuracy-Flip: 0.95100+-0.01172
26260:[lfw][436000]Accuracy-Flip: 0.99183+-0.00462
26265:[cfp_fp][436000]Accuracy-Flip: 0.87257+-0.01932
26270:[agedb_30][436000]Accuracy-Flip: 0.95083+-0.01044
26380:[lfw][438000]Accuracy-Flip: 0.99200+-0.00452
26385:[cfp_fp][438000]Accuracy-Flip: 0.87371+-0.01887
26390:[agedb_30][438000]Accuracy-Flip: 0.95050+-0.01133
26500:[lfw][440000]Accuracy-Flip: 0.99133+-0.00493
26505:[cfp_fp][440000]Accuracy-Flip: 0.87486+-0.01800
26510:[agedb_30][440000]Accuracy-Flip: 0.95133+-0.01082
26620:[lfw][442000]Accuracy-Flip: 0.99217+-0.00415
26625:[cfp_fp][442000]Accuracy-Flip: 0.87271+-0.01918
26630:[agedb_30][442000]Accuracy-Flip: 0.95067+-0.01096
26740:[lfw][444000]Accuracy-Flip: 0.99200+-0.00452
26745:[cfp_fp][444000]Accuracy-Flip: 0.87414+-0.01744
26750:[agedb_30][444000]Accuracy-Flip: 0.95167+-0.01072
26860:[lfw][446000]Accuracy-Flip: 0.99217+-0.00415
26865:[cfp_fp][446000]Accuracy-Flip: 0.87500+-0.01798
26870:[agedb_30][446000]Accuracy-Flip: 0.95033+-0.01130
26980:[lfw][448000]Accuracy-Flip: 0.99150+-0.00508
26985:[cfp_fp][448000]Accuracy-Flip: 0.87271+-0.01926
26990:[agedb_30][448000]Accuracy-Flip: 0.95133+-0.01061
27100:[lfw][450000]Accuracy-Flip: 0.99217+-0.00435
27105:[cfp_fp][450000]Accuracy-Flip: 0.87314+-0.01789
27110:[agedb_30][450000]Accuracy-Flip: 0.95000+-0.01103
27220:[lfw][452000]Accuracy-Flip: 0.99133+-0.00499
27225:[cfp_fp][452000]Accuracy-Flip: 0.87343+-0.01893
27230:[agedb_30][452000]Accuracy-Flip: 0.95133+-0.01130
27340:[lfw][454000]Accuracy-Flip: 0.99217+-0.00435
27345:[cfp_fp][454000]Accuracy-Flip: 0.87629+-0.01916
27350:[agedb_30][454000]Accuracy-Flip: 0.94917+-0.01181
27460:[lfw][456000]Accuracy-Flip: 0.99167+-0.00477
27465:[cfp_fp][456000]Accuracy-Flip: 0.87586+-0.01996
27470:[agedb_30][456000]Accuracy-Flip: 0.95117+-0.01062
27583:[lfw][458000]Accuracy-Flip: 0.99183+-0.00456
27588:[cfp_fp][458000]Accuracy-Flip: 0.87529+-0.01924
27593:[agedb_30][458000]Accuracy-Flip: 0.94950+-0.01113
27703:[lfw][460000]Accuracy-Flip: 0.99083+-0.00528
27708:[cfp_fp][460000]Accuracy-Flip: 0.87286+-0.01866
27713:[agedb_30][460000]Accuracy-Flip: 0.95183+-0.01037
27823:[lfw][462000]Accuracy-Flip: 0.99233+-0.00423
27828:[cfp_fp][462000]Accuracy-Flip: 0.87357+-0.01757
27833:[agedb_30][462000]Accuracy-Flip: 0.95217+-0.01044
27943:[lfw][464000]Accuracy-Flip: 0.99183+-0.00437
27948:[cfp_fp][464000]Accuracy-Flip: 0.87514+-0.01893
27953:[agedb_30][464000]Accuracy-Flip: 0.95117+-0.01090
28063:[lfw][466000]Accuracy-Flip: 0.99200+-0.00446
28068:[cfp_fp][466000]Accuracy-Flip: 0.87300+-0.01950
28073:[agedb_30][466000]Accuracy-Flip: 0.95000+-0.01072
28183:[lfw][468000]Accuracy-Flip: 0.99217+-0.00506
28188:[cfp_fp][468000]Accuracy-Flip: 0.87229+-0.01925
28193:[agedb_30][468000]Accuracy-Flip: 0.95167+-0.01054
28303:[lfw][470000]Accuracy-Flip: 0.99183+-0.00450
28308:[cfp_fp][470000]Accuracy-Flip: 0.87400+-0.01938
28313:[agedb_30][470000]Accuracy-Flip: 0.95133+-0.01080
28423:[lfw][472000]Accuracy-Flip: 0.99183+-0.00462
28428:[cfp_fp][472000]Accuracy-Flip: 0.87357+-0.01775
28433:[agedb_30][472000]Accuracy-Flip: 0.95050+-0.01059
28543:[lfw][474000]Accuracy-Flip: 0.99200+-0.00446
28548:[cfp_fp][474000]Accuracy-Flip: 0.87171+-0.01952
28553:[agedb_30][474000]Accuracy-Flip: 0.94950+-0.01126
28663:[lfw][476000]Accuracy-Flip: 0.99217+-0.00435
28668:[cfp_fp][476000]Accuracy-Flip: 0.87200+-0.01851
28673:[agedb_30][476000]Accuracy-Flip: 0.95133+-0.01103
28783:[lfw][478000]Accuracy-Flip: 0.99200+-0.00446
28788:[cfp_fp][478000]Accuracy-Flip: 0.87329+-0.01877
28793:[agedb_30][478000]Accuracy-Flip: 0.95150+-0.01089
28903:[lfw][480000]Accuracy-Flip: 0.99233+-0.00442
28908:[cfp_fp][480000]Accuracy-Flip: 0.87357+-0.01807
28913:[agedb_30][480000]Accuracy-Flip: 0.95117+-0.01070
29026:[lfw][482000]Accuracy-Flip: 0.99183+-0.00508
29031:[cfp_fp][482000]Accuracy-Flip: 0.87243+-0.01897
29036:[agedb_30][482000]Accuracy-Flip: 0.95050+-0.01126
29146:[lfw][484000]Accuracy-Flip: 0.99250+-0.00473
29151:[cfp_fp][484000]Accuracy-Flip: 0.87257+-0.01853
29156:[agedb_30][484000]Accuracy-Flip: 0.95167+-0.01083
29266:[lfw][486000]Accuracy-Flip: 0.99133+-0.00493
29271:[cfp_fp][486000]Accuracy-Flip: 0.87514+-0.02025
29276:[agedb_30][486000]Accuracy-Flip: 0.95050+-0.01080
29386:[lfw][488000]Accuracy-Flip: 0.99217+-0.00435
29391:[cfp_fp][488000]Accuracy-Flip: 0.87543+-0.01963
29396:[agedb_30][488000]Accuracy-Flip: 0.95000+-0.01147
29506:[lfw][490000]Accuracy-Flip: 0.99233+-0.00416
29511:[cfp_fp][490000]Accuracy-Flip: 0.87629+-0.01915
29516:[agedb_30][490000]Accuracy-Flip: 0.95167+-0.01070
29626:[lfw][492000]Accuracy-Flip: 0.99200+-0.00446
29631:[cfp_fp][492000]Accuracy-Flip: 0.87529+-0.01855
29636:[agedb_30][492000]Accuracy-Flip: 0.95167+-0.01135
29746:[lfw][494000]Accuracy-Flip: 0.99117+-0.00483
29751:[cfp_fp][494000]Accuracy-Flip: 0.87400+-0.01856
29756:[agedb_30][494000]Accuracy-Flip: 0.95217+-0.01052
29866:[lfw][496000]Accuracy-Flip: 0.99200+-0.00452
29871:[cfp_fp][496000]Accuracy-Flip: 0.87429+-0.01875
29876:[agedb_30][496000]Accuracy-Flip: 0.95050+-0.01160
29986:[lfw][498000]Accuracy-Flip: 0.99167+-0.00511
29991:[cfp_fp][498000]Accuracy-Flip: 0.87400+-0.01873
29996:[agedb_30][498000]Accuracy-Flip: 0.95067+-0.01119
30106:[lfw][500000]Accuracy-Flip: 0.99133+-0.00493
30111:[cfp_fp][500000]Accuracy-Flip: 0.87329+-0.01946
30116:[agedb_30][500000]Accuracy-Flip: 0.94967+-0.01069
30226:[lfw][502000]Accuracy-Flip: 0.99217+-0.00435
30231:[cfp_fp][502000]Accuracy-Flip: 0.87414+-0.01895
30236:[agedb_30][502000]Accuracy-Flip: 0.95183+-0.01039
30346:[lfw][504000]Accuracy-Flip: 0.99117+-0.00483
30351:[cfp_fp][504000]Accuracy-Flip: 0.87357+-0.01930
30356:[agedb_30][504000]Accuracy-Flip: 0.95233+-0.01025

[qidiso]

maybe you can try --margin-s 64 first!

[qidiso]

may because your batch size is small!

[chenkingwen]

what's the train dataset you use?@qidiso

[zhangxiaopang88]

Hello, using your pre-training model training-margin-s 128, -margin-s64, my training accuracy has been around 99.3x , you can give some advice, and your arcface training model of not the highest accuracy can share it? We'll retrain on it, I look forward to hearing from you.Thank you