hello
hello

📌S Retain class distribution for seed 4:
Class 0: 4500
Class 1: 4500
Class 2: 4500
Class 3: 4500
Class 4: 4500
Class 5: 4500
Class 6: 4500
Class 7: 4500
Class 8: 4500
Class 9: 4500

📌S Forget class distribution for seed 4:
Class 0: 500
Class 1: 500
Class 2: 500
Class 3: 500
Class 4: 500
Class 5: 500
Class 6: 500
Class 7: 500
Class 8: 500
Class 9: 500

📊 Updated class distribution:
Retain set:
  Class 0: 4625
  Class 1: 4625
  Class 2: 4625
  Class 3: 4625
  Class 4: 4625
  Class 5: 4625
  Class 6: 4625
  Class 7: 4625
  Class 8: 4625
  Class 9: 4625
Forget set:
  Class 0: 375
  Class 1: 375
  Class 2: 375
  Class 3: 375
  Class 4: 375
  Class 5: 375
  Class 6: 375
  Class 7: 375
  Class 8: 375
  Class 9: 375
hello
hello
⚠️ Warning: Retain train loader may not be shuffled.
Training Epoch: 1 [256/46250]	Loss: 2.4716	LR: 0.000000
Training Epoch: 1 [512/46250]	Loss: 2.4601	LR: 0.000552
Training Epoch: 1 [768/46250]	Loss: 2.4823	LR: 0.001105
Training Epoch: 1 [1024/46250]	Loss: 2.4076	LR: 0.001657
Training Epoch: 1 [1280/46250]	Loss: 2.3843	LR: 0.002210
Training Epoch: 1 [1536/46250]	Loss: 2.2453	LR: 0.002762
Training Epoch: 1 [1792/46250]	Loss: 2.0528	LR: 0.003315
Training Epoch: 1 [2048/46250]	Loss: 2.0092	LR: 0.003867
Training Epoch: 1 [2304/46250]	Loss: 1.7669	LR: 0.004420
Training Epoch: 1 [2560/46250]	Loss: 1.5276	LR: 0.004972
Training Epoch: 1 [2816/46250]	Loss: 1.2718	LR: 0.005525
Training Epoch: 1 [3072/46250]	Loss: 1.1117	LR: 0.006077
Training Epoch: 1 [3328/46250]	Loss: 0.9022	LR: 0.006630
Training Epoch: 1 [3584/46250]	Loss: 0.6427	LR: 0.007182
Training Epoch: 1 [3840/46250]	Loss: 0.5267	LR: 0.007735
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Training Epoch: 1 [4352/46250]	Loss: 0.3927	LR: 0.008840
Training Epoch: 1 [4608/46250]	Loss: 0.2912	LR: 0.009392
Training Epoch: 1 [4864/46250]	Loss: 0.2657	LR: 0.009945
Training Epoch: 1 [5120/46250]	Loss: 0.2476	LR: 0.010497
Training Epoch: 1 [5376/46250]	Loss: 0.2356	LR: 0.011050
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Training Epoch: 1 [5888/46250]	Loss: 0.1966	LR: 0.012155
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Training Epoch: 1 [7424/46250]	Loss: 0.2269	LR: 0.015470
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Training Epoch: 1 [8192/46250]	Loss: 0.2165	LR: 0.017127
Training Epoch: 1 [8448/46250]	Loss: 0.2814	LR: 0.017680
Training Epoch: 1 [8704/46250]	Loss: 0.2382	LR: 0.018232
Training Epoch: 1 [8960/46250]	Loss: 0.2456	LR: 0.018785
Training Epoch: 1 [9216/46250]	Loss: 0.1980	LR: 0.019337
Training Epoch: 1 [9472/46250]	Loss: 0.3243	LR: 0.019890
Training Epoch: 1 [9728/46250]	Loss: 0.2920	LR: 0.020442
Training Epoch: 1 [9984/46250]	Loss: 0.1702	LR: 0.020994
Training Epoch: 1 [10240/46250]	Loss: 0.1863	LR: 0.021547
Training Epoch: 1 [10496/46250]	Loss: 0.1861	LR: 0.022099
Training Epoch: 1 [10752/46250]	Loss: 0.1682	LR: 0.022652
Training Epoch: 1 [11008/46250]	Loss: 0.2839	LR: 0.023204
Training Epoch: 1 [11264/46250]	Loss: 0.1434	LR: 0.023757
Training Epoch: 1 [11520/46250]	Loss: 0.2605	LR: 0.024309
Training Epoch: 1 [11776/46250]	Loss: 0.2641	LR: 0.024862
Training Epoch: 1 [12032/46250]	Loss: 0.2316	LR: 0.025414
Training Epoch: 1 [12288/46250]	Loss: 0.1985	LR: 0.025967
Training Epoch: 1 [12544/46250]	Loss: 0.1999	LR: 0.026519
Training Epoch: 1 [12800/46250]	Loss: 0.1810	LR: 0.027072
Training Epoch: 1 [13056/46250]	Loss: 0.2453	LR: 0.027624
Training Epoch: 1 [13312/46250]	Loss: 0.1761	LR: 0.028177
Training Epoch: 1 [13568/46250]	Loss: 0.3135	LR: 0.028729
Training Epoch: 1 [13824/46250]	Loss: 0.1780	LR: 0.029282
Training Epoch: 1 [14080/46250]	Loss: 0.1722	LR: 0.029834
Training Epoch: 1 [14336/46250]	Loss: 0.2372	LR: 0.030387
Training Epoch: 1 [14592/46250]	Loss: 0.2969	LR: 0.030939
Training Epoch: 1 [14848/46250]	Loss: 0.2757	LR: 0.031492
Training Epoch: 1 [15104/46250]	Loss: 0.2183	LR: 0.032044
Training Epoch: 1 [15360/46250]	Loss: 0.2139	LR: 0.032597
Training Epoch: 1 [15616/46250]	Loss: 0.1489	LR: 0.033149
Training Epoch: 1 [15872/46250]	Loss: 0.2037	LR: 0.033702
Training Epoch: 1 [16128/46250]	Loss: 0.1853	LR: 0.034254
Training Epoch: 1 [16384/46250]	Loss: 0.3619	LR: 0.034807
Training Epoch: 1 [16640/46250]	Loss: 0.2590	LR: 0.035359
Training Epoch: 1 [16896/46250]	Loss: 0.2367	LR: 0.035912
Training Epoch: 1 [17152/46250]	Loss: 0.1735	LR: 0.036464
Training Epoch: 1 [17408/46250]	Loss: 0.2887	LR: 0.037017
Training Epoch: 1 [17664/46250]	Loss: 0.1857	LR: 0.037569
Training Epoch: 1 [17920/46250]	Loss: 0.2627	LR: 0.038122
Training Epoch: 1 [18176/46250]	Loss: 0.2874	LR: 0.038674
Training Epoch: 1 [18432/46250]	Loss: 0.2021	LR: 0.039227
Training Epoch: 1 [18688/46250]	Loss: 0.1865	LR: 0.039779
Training Epoch: 1 [18944/46250]	Loss: 0.2072	LR: 0.040331
Training Epoch: 1 [19200/46250]	Loss: 0.3055	LR: 0.040884
Training Epoch: 1 [19456/46250]	Loss: 0.1309	LR: 0.041436
Training Epoch: 1 [19712/46250]	Loss: 0.2134	LR: 0.041989
Training Epoch: 1 [19968/46250]	Loss: 0.3186	LR: 0.042541
Training Epoch: 1 [20224/46250]	Loss: 0.2085	LR: 0.043094
Training Epoch: 1 [20480/46250]	Loss: 0.3650	LR: 0.043646
Training Epoch: 1 [20736/46250]	Loss: 0.2788	LR: 0.044199
Training Epoch: 1 [20992/46250]	Loss: 0.2680	LR: 0.044751
Training Epoch: 1 [21248/46250]	Loss: 0.2380	LR: 0.045304
Training Epoch: 1 [21504/46250]	Loss: 0.3390	LR: 0.045856
Training Epoch: 1 [21760/46250]	Loss: 0.2595	LR: 0.046409
Training Epoch: 1 [22016/46250]	Loss: 0.2458	LR: 0.046961
Training Epoch: 1 [22272/46250]	Loss: 0.2642	LR: 0.047514
Training Epoch: 1 [22528/46250]	Loss: 0.2389	LR: 0.048066
Training Epoch: 1 [22784/46250]	Loss: 0.2491	LR: 0.048619
Training Epoch: 1 [23040/46250]	Loss: 0.2251	LR: 0.049171
Training Epoch: 1 [23296/46250]	Loss: 0.1918	LR: 0.049724
Training Epoch: 1 [23552/46250]	Loss: 0.2392	LR: 0.050276
Training Epoch: 1 [23808/46250]	Loss: 0.1639	LR: 0.050829
Training Epoch: 1 [24064/46250]	Loss: 0.1875	LR: 0.051381
Training Epoch: 1 [24320/46250]	Loss: 0.1567	LR: 0.051934
Training Epoch: 1 [24576/46250]	Loss: 0.2055	LR: 0.052486
Training Epoch: 1 [24832/46250]	Loss: 0.2156	LR: 0.053039
Training Epoch: 1 [25088/46250]	Loss: 0.2694	LR: 0.053591
Training Epoch: 1 [25344/46250]	Loss: 0.2025	LR: 0.054144
Training Epoch: 1 [25600/46250]	Loss: 0.2282	LR: 0.054696
Training Epoch: 1 [25856/46250]	Loss: 0.2691	LR: 0.055249
Training Epoch: 1 [26112/46250]	Loss: 0.2716	LR: 0.055801
Training Epoch: 1 [26368/46250]	Loss: 0.2399	LR: 0.056354
Training Epoch: 1 [26624/46250]	Loss: 0.2076	LR: 0.056906
Training Epoch: 1 [26880/46250]	Loss: 0.1696	LR: 0.057459
Training Epoch: 1 [27136/46250]	Loss: 0.1935	LR: 0.058011
Training Epoch: 1 [27392/46250]	Loss: 0.1877	LR: 0.058564
Training Epoch: 1 [27648/46250]	Loss: 0.1512	LR: 0.059116
Training Epoch: 1 [27904/46250]	Loss: 0.1287	LR: 0.059669
Training Epoch: 1 [28160/46250]	Loss: 0.1712	LR: 0.060221
Training Epoch: 1 [28416/46250]	Loss: 0.3644	LR: 0.060773
Training Epoch: 1 [28672/46250]	Loss: 0.1418	LR: 0.061326
Training Epoch: 1 [28928/46250]	Loss: 0.2799	LR: 0.061878
Training Epoch: 1 [29184/46250]	Loss: 0.1045	LR: 0.062431
Training Epoch: 1 [29440/46250]	Loss: 0.1527	LR: 0.062983
Training Epoch: 1 [29696/46250]	Loss: 0.3647	LR: 0.063536
Training Epoch: 1 [29952/46250]	Loss: 0.1870	LR: 0.064088
Training Epoch: 1 [30208/46250]	Loss: 0.2143	LR: 0.064641
Training Epoch: 1 [30464/46250]	Loss: 0.2777	LR: 0.065193
Training Epoch: 1 [30720/46250]	Loss: 0.1340	LR: 0.065746
Training Epoch: 1 [30976/46250]	Loss: 0.1906	LR: 0.066298
Training Epoch: 1 [31232/46250]	Loss: 0.2908	LR: 0.066851
Training Epoch: 1 [31488/46250]	Loss: 0.2045	LR: 0.067403
Training Epoch: 1 [31744/46250]	Loss: 0.1702	LR: 0.067956
Training Epoch: 1 [32000/46250]	Loss: 0.1685	LR: 0.068508
Training Epoch: 1 [32256/46250]	Loss: 0.4218	LR: 0.069061
Training Epoch: 1 [32512/46250]	Loss: 0.1849	LR: 0.069613
Training Epoch: 1 [32768/46250]	Loss: 0.1788	LR: 0.070166
Training Epoch: 1 [33024/46250]	Loss: 0.4051	LR: 0.070718
Training Epoch: 1 [33280/46250]	Loss: 0.1654	LR: 0.071271
Training Epoch: 1 [33536/46250]	Loss: 0.1830	LR: 0.071823
Training Epoch: 1 [33792/46250]	Loss: 0.5356	LR: 0.072376
Training Epoch: 1 [34048/46250]	Loss: 0.2878	LR: 0.072928
Training Epoch: 1 [34304/46250]	Loss: 0.2754	LR: 0.073481
Training Epoch: 1 [34560/46250]	Loss: 0.4114	LR: 0.074033
Training Epoch: 1 [34816/46250]	Loss: 0.5658	LR: 0.074586
Training Epoch: 1 [35072/46250]	Loss: 0.3737	LR: 0.075138
Training Epoch: 1 [35328/46250]	Loss: 0.2925	LR: 0.075691
Training Epoch: 1 [35584/46250]	Loss: 0.7270	LR: 0.076243
Training Epoch: 1 [35840/46250]	Loss: 0.3724	LR: 0.076796
Training Epoch: 1 [36096/46250]	Loss: 0.5399	LR: 0.077348
Training Epoch: 1 [36352/46250]	Loss: 0.5516	LR: 0.077901
Training Epoch: 1 [36608/46250]	Loss: 0.5645	LR: 0.078453
Training Epoch: 1 [36864/46250]	Loss: 0.4234	LR: 0.079006
Training Epoch: 1 [37120/46250]	Loss: 0.5489	LR: 0.079558
Training Epoch: 1 [37376/46250]	Loss: 0.4155	LR: 0.080110
Training Epoch: 1 [37632/46250]	Loss: 0.4375	LR: 0.080663
Training Epoch: 1 [37888/46250]	Loss: 0.5454	LR: 0.081215
Training Epoch: 1 [38144/46250]	Loss: 0.4320	LR: 0.081768
Training Epoch: 1 [38400/46250]	Loss: 0.5752	LR: 0.082320
Training Epoch: 1 [38656/46250]	Loss: 0.6508	LR: 0.082873
Training Epoch: 1 [38912/46250]	Loss: 0.4942	LR: 0.083425
Training Epoch: 1 [39168/46250]	Loss: 0.4326	LR: 0.083978
Training Epoch: 1 [39424/46250]	Loss: 0.2401	LR: 0.084530
Training Epoch: 1 [39680/46250]	Loss: 0.3847	LR: 0.085083
Training Epoch: 1 [39936/46250]	Loss: 0.3101	LR: 0.085635
Training Epoch: 1 [40192/46250]	Loss: 0.3279	LR: 0.086188
Training Epoch: 1 [40448/46250]	Loss: 0.3730	LR: 0.086740
Training Epoch: 1 [40704/46250]	Loss: 0.3020	LR: 0.087293
Training Epoch: 1 [40960/46250]	Loss: 0.3275	LR: 0.087845
Training Epoch: 1 [41216/46250]	Loss: 0.3213	LR: 0.088398
Training Epoch: 1 [41472/46250]	Loss: 0.3717	LR: 0.088950
Training Epoch: 1 [41728/46250]	Loss: 0.5001	LR: 0.089503
Training Epoch: 1 [41984/46250]	Loss: 0.2758	LR: 0.090055
Training Epoch: 1 [42240/46250]	Loss: 0.4322	LR: 0.090608
Training Epoch: 1 [42496/46250]	Loss: 0.4393	LR: 0.091160
Training Epoch: 1 [42752/46250]	Loss: 0.2476	LR: 0.091713
Training Epoch: 1 [43008/46250]	Loss: 0.2675	LR: 0.092265
Training Epoch: 1 [43264/46250]	Loss: 0.2544	LR: 0.092818
Training Epoch: 1 [43520/46250]	Loss: 0.2036	LR: 0.093370
Training Epoch: 1 [43776/46250]	Loss: 0.4603	LR: 0.093923
Training Epoch: 1 [44032/46250]	Loss: 0.3584	LR: 0.094475
Training Epoch: 1 [44288/46250]	Loss: 0.2640	LR: 0.095028
Training Epoch: 1 [44544/46250]	Loss: 0.2901	LR: 0.095580
Training Epoch: 1 [44800/46250]	Loss: 0.3105	LR: 0.096133
Training Epoch: 1 [45056/46250]	Loss: 0.1842	LR: 0.096685
Training Epoch: 1 [45312/46250]	Loss: 0.4980	LR: 0.097238
Training Epoch: 1 [45568/46250]	Loss: 0.2677	LR: 0.097790
Training Epoch: 1 [45824/46250]	Loss: 0.2671	LR: 0.098343
Training Epoch: 1 [46080/46250]	Loss: 0.4539	LR: 0.098895
Training Epoch: 1 [46250/46250]	Loss: 0.3770	LR: 0.099448
Epoch 1 - Average Train Loss: 0.4036, Train Accuracy: 0.8706
Epoch 1 training time consumed: 335.02s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.0008, Accuracy: 0.9344, Time consumed:23.57s
Saving weights file to checkpoint/retrain/ViT/Thursday_17_July_2025_22h_40m_43s/ViT-Cifar10-seed4-ret25-1-best.pth
Training Epoch: 2 [256/46250]	Loss: 0.2215	LR: 0.100000
Training Epoch: 2 [512/46250]	Loss: 0.1973	LR: 0.100000
Training Epoch: 2 [768/46250]	Loss: 0.2706	LR: 0.100000
Training Epoch: 2 [1024/46250]	Loss: 0.2117	LR: 0.100000
Training Epoch: 2 [1280/46250]	Loss: 0.2858	LR: 0.100000
Training Epoch: 2 [1536/46250]	Loss: 0.3017	LR: 0.100000
Training Epoch: 2 [1792/46250]	Loss: 0.2242	LR: 0.100000
Training Epoch: 2 [2048/46250]	Loss: 0.2286	LR: 0.100000
Training Epoch: 2 [2304/46250]	Loss: 0.2442	LR: 0.100000
Training Epoch: 2 [2560/46250]	Loss: 0.3076	LR: 0.100000
Training Epoch: 2 [2816/46250]	Loss: 0.3561	LR: 0.100000
Training Epoch: 2 [3072/46250]	Loss: 0.2688	LR: 0.100000
Training Epoch: 2 [3328/46250]	Loss: 0.2013	LR: 0.100000
Training Epoch: 2 [3584/46250]	Loss: 0.2342	LR: 0.100000
Training Epoch: 2 [3840/46250]	Loss: 0.2246	LR: 0.100000
Training Epoch: 2 [4096/46250]	Loss: 0.2507	LR: 0.100000
Training Epoch: 2 [4352/46250]	Loss: 0.4630	LR: 0.100000
Training Epoch: 2 [4608/46250]	Loss: 0.2997	LR: 0.100000
Training Epoch: 2 [4864/46250]	Loss: 0.3111	LR: 0.100000
Training Epoch: 2 [5120/46250]	Loss: 0.2759	LR: 0.100000
Training Epoch: 2 [5376/46250]	Loss: 0.2213	LR: 0.100000
Training Epoch: 2 [5632/46250]	Loss: 0.3646	LR: 0.100000
Training Epoch: 2 [5888/46250]	Loss: 0.3605	LR: 0.100000
Training Epoch: 2 [6144/46250]	Loss: 0.3703	LR: 0.100000
Training Epoch: 2 [6400/46250]	Loss: 0.3116	LR: 0.100000
Training Epoch: 2 [6656/46250]	Loss: 0.2408	LR: 0.100000
Training Epoch: 2 [6912/46250]	Loss: 0.2678	LR: 0.100000
Training Epoch: 2 [7168/46250]	Loss: 0.2513	LR: 0.100000
Training Epoch: 2 [7424/46250]	Loss: 0.3181	LR: 0.100000
Training Epoch: 2 [7680/46250]	Loss: 0.3169	LR: 0.100000
Training Epoch: 2 [7936/46250]	Loss: 0.1702	LR: 0.100000
Training Epoch: 2 [8192/46250]	Loss: 0.2651	LR: 0.100000
Training Epoch: 2 [8448/46250]	Loss: 0.2846	LR: 0.100000
Training Epoch: 2 [8704/46250]	Loss: 0.2348	LR: 0.100000
Training Epoch: 2 [8960/46250]	Loss: 0.2725	LR: 0.100000
Training Epoch: 2 [9216/46250]	Loss: 0.3049	LR: 0.100000
Training Epoch: 2 [9472/46250]	Loss: 0.2213	LR: 0.100000
Training Epoch: 2 [9728/46250]	Loss: 0.3518	LR: 0.100000
Training Epoch: 2 [9984/46250]	Loss: 0.2505	LR: 0.100000
Training Epoch: 2 [10240/46250]	Loss: 0.2410	LR: 0.100000
Training Epoch: 2 [10496/46250]	Loss: 0.2751	LR: 0.100000
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Training Epoch: 2 [11008/46250]	Loss: 0.2118	LR: 0.100000
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Training Epoch: 2 [13056/46250]	Loss: 0.2086	LR: 0.100000
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Training Epoch: 2 [13568/46250]	Loss: 0.2090	LR: 0.100000
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Training Epoch: 2 [14336/46250]	Loss: 0.3129	LR: 0.100000
Training Epoch: 2 [14592/46250]	Loss: 0.1783	LR: 0.100000
Training Epoch: 2 [14848/46250]	Loss: 0.2814	LR: 0.100000
Training Epoch: 2 [15104/46250]	Loss: 0.2622	LR: 0.100000
Training Epoch: 2 [15360/46250]	Loss: 0.2516	LR: 0.100000
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Training Epoch: 2 [15872/46250]	Loss: 0.2472	LR: 0.100000
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Training Epoch: 2 [16896/46250]	Loss: 0.1598	LR: 0.100000
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Training Epoch: 2 [19200/46250]	Loss: 0.2451	LR: 0.100000
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Training Epoch: 2 [22272/46250]	Loss: 0.2477	LR: 0.100000
Training Epoch: 2 [22528/46250]	Loss: 0.2129	LR: 0.100000
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Training Epoch: 2 [23808/46250]	Loss: 0.1875	LR: 0.100000
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Training Epoch: 2 [26368/46250]	Loss: 3.3369	LR: 0.100000
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Training Epoch: 2 [37376/46250]	Loss: 4001.3152	LR: 0.100000
Training Epoch: 2 [37632/46250]	Loss: nan	LR: 0.100000
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Training Epoch: 2 [46080/46250]	Loss: nan	LR: 0.100000
Training Epoch: 2 [46250/46250]	Loss: nan	LR: 0.100000
Epoch 2 - Average Train Loss: nan, Train Accuracy: 0.5550
Epoch 2 training time consumed: 334.27s
Evaluating Network.....
Test set: Epoch: 2, Average loss: nan, Accuracy: 0.1000, Time consumed:23.50s
Training Epoch: 3 [256/46250]	Loss: nan	LR: 0.100000
Training Epoch: 3 [512/46250]	Loss: nan	LR: 0.100000
Training Epoch: 3 [768/46250]	Loss: nan	LR: 0.100000
Training Epoch: 3 [1024/46250]	Loss: nan	LR: 0.100000
Training Epoch: 3 [1280/46250]	Loss: nan	LR: 0.100000
Training Epoch: 3 [1536/46250]	Loss: nan	LR: 0.100000
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Training Epoch: 3 [3072/46250]	Loss: nan	LR: 0.100000
Training Epoch: 3 [3328/46250]	Loss: nan	LR: 0.100000
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Training Epoch: 3 [46250/46250]	Loss: nan	LR: 0.100000
Epoch 3 - Average Train Loss: nan, Train Accuracy: 0.1000
Epoch 3 training time consumed: 333.64s
Evaluating Network.....
Test set: Epoch: 3, Average loss: nan, Accuracy: 0.1000, Time consumed:23.50s
Training Epoch: 4 [256/46250]	Loss: nan	LR: 0.100000
Training Epoch: 4 [512/46250]	Loss: nan	LR: 0.100000
Training Epoch: 4 [768/46250]	Loss: nan	LR: 0.100000
Training Epoch: 4 [1024/46250]	Loss: nan	LR: 0.100000
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Training Epoch: 4 [46080/46250]	Loss: nan	LR: 0.100000
Training Epoch: 4 [46250/46250]	Loss: nan	LR: 0.100000
Epoch 4 - Average Train Loss: nan, Train Accuracy: 0.1000
Epoch 4 training time consumed: 333.50s
Evaluating Network.....
Test set: Epoch: 4, Average loss: nan, Accuracy: 0.1000, Time consumed:23.50s
Training Epoch: 5 [256/46250]	Loss: nan	LR: 0.100000
Training Epoch: 5 [512/46250]	Loss: nan	LR: 0.100000
Training Epoch: 5 [768/46250]	Loss: nan	LR: 0.100000
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Training Epoch: 5 [46250/46250]	Loss: nan	LR: 0.100000
Epoch 5 - Average Train Loss: nan, Train Accuracy: 0.1000
Epoch 5 training time consumed: 333.75s
Evaluating Network.....
Test set: Epoch: 5, Average loss: nan, Accuracy: 0.1000, Time consumed:23.48s
Training Epoch: 6 [256/46250]	Loss: nan	LR: 0.100000
Training Epoch: 6 [512/46250]	Loss: nan	LR: 0.100000
Training Epoch: 6 [768/46250]	Loss: nan	LR: 0.100000
Training Epoch: 6 [1024/46250]	Loss: nan	LR: 0.100000
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Training Epoch: 6 [46250/46250]	Loss: nan	LR: 0.100000
Epoch 6 - Average Train Loss: nan, Train Accuracy: 0.1000
Epoch 6 training time consumed: 333.65s
Evaluating Network.....
Test set: Epoch: 6, Average loss: nan, Accuracy: 0.1000, Time consumed:23.49s
Training Epoch: 7 [256/46250]	Loss: nan	LR: 0.020000
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Training Epoch: 7 [45568/46250]	Loss: nan	LR: 0.020000
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Training Epoch: 7 [46080/46250]	Loss: nan	LR: 0.020000
Training Epoch: 7 [46250/46250]	Loss: nan	LR: 0.020000
Epoch 7 - Average Train Loss: nan, Train Accuracy: 0.1000
Epoch 7 training time consumed: 334.20s
Evaluating Network.....
Test set: Epoch: 7, Average loss: nan, Accuracy: 0.1000, Time consumed:23.50s
Training Epoch: 8 [256/46250]	Loss: nan	LR: 0.020000
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Training Epoch: 8 [46250/46250]	Loss: nan	LR: 0.020000
Epoch 8 - Average Train Loss: nan, Train Accuracy: 0.1000
Epoch 8 training time consumed: 333.74s
Evaluating Network.....
Test set: Epoch: 8, Average loss: nan, Accuracy: 0.1000, Time consumed:23.50s
Valid (Test) Dl:  10000
Train Dl:  50000
Retain Train Dl:  46250
Forget Train Dl:  3750
Retain Valid Dl:  46250
Forget Valid Dl:  3750
retain_prob Distribution: 10000 samples
test_prob Distribution: 10000 samples
forget_prob Distribution: 3750 samples
Set1 Distribution: 3750 samples
Set2 Distribution: 3750 samples
Set1 Distribution: 3750 samples
Set2 Distribution: 3750 samples
Set1 Distribution: 10000 samples
Set2 Distribution: 10000 samples
Set1 Distribution: 10000 samples
Set2 Distribution: 10000 samples
Test Accuracy: 10.05859375
Retain Accuracy: 10.010917663574219
Zero-Retain Forget (ZRF): nan
Membership Inference Attack (MIA): 0.0
Forget vs Retain Membership Inference Attack (MIA): 0.492
Forget vs Test Membership Inference Attack (MIA): 0.492
Test vs Retain Membership Inference Attack (MIA): 0.49525
Train vs Test Membership Inference Attack (MIA): 0.49525
Forget Set Accuracy (Df): 9.765625
Method Execution Time: 5273.58 seconds
