python train.py simus/ep/cnn/xpvgg4_im32.json

Input   :	 (32, 32, 3)
Layer 1 :	 (16, 16, 128)
Layer 2 :	 (8, 8, 256)
Layer 3 :	 (4, 4, 512)
Layer 4 :	 (1, 1, 512)

Mean log L2 = -3.019334077835083
Total dropped = 0
param norm = 68.79529571533203

Epoch 1 in 4937.78 sec
Train accuracy :	0.038	(49229/1281024)		Train loss :	5.9667
Val accuracy   :	0.088	(4387/50000)		Val loss :	5.1493
Top-5 val acc  :	0.226	(11280/50000)


Mean log L2 = -2.202737808227539
Total dropped = 0
param norm = 94.78780364990234

Epoch 2 in 4742.53 sec
Train accuracy :	0.131	(168190/1281024)		Train loss :	4.7279
Val accuracy   :	0.15	(7509/50000)		Val loss :	4.5412
Top-5 val acc  :	0.334	(16711/50000)


Mean log L2 = -1.5246508121490479
Total dropped = 0
param norm = 110.03145599365234

Epoch 3 in 4748.77 sec
Train accuracy :	0.175	(224214/1281024)		Train loss :	4.3498
Val accuracy   :	0.176	(8782/50000)		Val loss :	4.3476
Top-5 val acc  :	0.368	(18402/50000)


Mean log L2 = -1.3902920484542847
Total dropped = 0
param norm = 119.47327423095703

Epoch 4 in 4756.56 sec
Train accuracy :	0.194	(248953/1281024)		Train loss :	4.1969
Val accuracy   :	0.183	(9146/50000)		Val loss :	4.2767
Top-5 val acc  :	0.382	(19113/50000)


Mean log L2 = -1.172983169555664
Total dropped = 0
param norm = 125.5358657836914

Epoch 5 in 4746.77 sec
Train accuracy :	0.204	(261444/1281024)		Train loss :	4.1323
Val accuracy   :	0.185	(9252/50000)		Val loss :	4.252
Top-5 val acc  :	0.387	(19363/50000)


Mean log L2 = -0.9671891927719116
Total dropped = 0
param norm = 129.4168243408203

Epoch 6 in 4740.81 sec
Train accuracy :	0.208	(266156/1281024)		Train loss :	4.1047
Val accuracy   :	0.194	(9711/50000)		Val loss :	4.2288
Top-5 val acc  :	0.393	(19640/50000)


Mean log L2 = -1.0880323648452759
Total dropped = 0
param norm = 132.14476013183594

Epoch 7 in 4741.43 sec
Train accuracy :	0.211	(269780/1281024)		Train loss :	4.0897
Val accuracy   :	0.193	(9669/50000)		Val loss :	4.2231
Top-5 val acc  :	0.394	(19719/50000)


Mean log L2 = -1.0518946647644043
Total dropped = 0
param norm = 133.94618225097656

Epoch 8 in 4739.12 sec
Train accuracy :	0.213	(273265/1281024)		Train loss :	4.0709
Val accuracy   :	0.195	(9737/50000)		Val loss :	4.2112
Top-5 val acc  :	0.397	(19837/50000)


Mean log L2 = -0.9482219815254211
Total dropped = 0
param norm = 135.2449493408203

Epoch 9 in 4744.18 sec
Train accuracy :	0.216	(276955/1281024)		Train loss :	4.0534
Val accuracy   :	0.196	(9806/50000)		Val loss :	4.194
Top-5 val acc  :	0.4	(19976/50000)


Mean log L2 = -0.882622480392456
Total dropped = 0
param norm = 135.94308471679688

Epoch 10 in 4745.07 sec
Train accuracy :	0.219	(280020/1281024)		Train loss :	4.0373
Val accuracy   :	0.2	(10001/50000)		Val loss :	4.1738
Top-5 val acc  :	0.403	(20150/50000)


Mean log L2 = -0.9316374063491821
Total dropped = 0
param norm = 136.80857849121094

Epoch 11 in 4741.91 sec
Train accuracy :	0.22	(281865/1281024)		Train loss :	4.021
Val accuracy   :	0.198	(9877/50000)		Val loss :	4.1893
Top-5 val acc  :	0.401	(20069/50000)


Mean log L2 = -0.9645698070526123
Total dropped = 0
param norm = 137.42965698242188

Epoch 12 in 4754.24 sec
Train accuracy :	0.222	(285022/1281024)		Train loss :	4.0056
Val accuracy   :	0.2	(10006/50000)		Val loss :	4.168
Top-5 val acc  :	0.403	(20169/50000)


Mean log L2 = -0.9588576555252075
Total dropped = 0
param norm = 137.94818115234375

Epoch 13 in 4745.75 sec
Train accuracy :	0.225	(287835/1281024)		Train loss :	3.9897
Val accuracy   :	0.203	(10164/50000)		Val loss :	4.137
Top-5 val acc  :	0.412	(20584/50000)


Mean log L2 = -0.9288004636764526
Total dropped = 0
param norm = 138.50242614746094

Epoch 14 in 4740.71 sec
Train accuracy :	0.225	(288747/1281024)		Train loss :	3.9848
Val accuracy   :	0.203	(10148/50000)		Val loss :	4.1556
Top-5 val acc  :	0.406	(20305/50000)


Mean log L2 = -0.9424126744270325
Total dropped = 0
param norm = 138.56578063964844

Epoch 15 in 4747.01 sec
Train accuracy :	0.227	(291338/1281024)		Train loss :	3.9695
Val accuracy   :	0.203	(10146/50000)		Val loss :	4.1395
Top-5 val acc  :	0.411	(20553/50000)


Mean log L2 = -0.9725666046142578
Total dropped = 0
param norm = 138.58917236328125

Epoch 16 in 4743.54 sec
Train accuracy :	0.23	(294205/1281024)		Train loss :	3.954
Val accuracy   :	0.204	(10217/50000)		Val loss :	4.1438
Top-5 val acc  :	0.409	(20469/50000)


Mean log L2 = -0.9301553964614868
Total dropped = 0
param norm = 138.39796447753906

Epoch 17 in 4742.65 sec
Train accuracy :	0.232	(297059/1281024)		Train loss :	3.9357
Val accuracy   :	0.209	(10463/50000)		Val loss :	4.101
Top-5 val acc  :	0.417	(20846/50000)


Mean log L2 = -0.9967221021652222
Total dropped = 0
param norm = 138.4557647705078

Epoch 18 in 4934.45 sec
Train accuracy :	0.235	(300842/1281024)		Train loss :	3.9156
Val accuracy   :	0.213	(10645/50000)		Val loss :	4.0586
Top-5 val acc  :	0.425	(21250/50000)


Mean log L2 = -1.0083673000335693
Total dropped = 0
param norm = 138.53131103515625

Epoch 19 in 4746.68 sec
Train accuracy :	0.237	(304060/1281024)		Train loss :	3.8979
Val accuracy   :	0.209	(10443/50000)		Val loss :	4.0878
Top-5 val acc  :	0.419	(20951/50000)


Mean log L2 = -1.1107420921325684
Total dropped = 0
param norm = 138.3762969970703

Epoch 20 in 4747.42 sec
Train accuracy :	0.24	(306888/1281024)		Train loss :	3.8798
Val accuracy   :	0.213	(10650/50000)		Val loss :	4.0444
Top-5 val acc  :	0.424	(21222/50000)


Mean log L2 = -1.1119108200073242
Total dropped = 0
param norm = 138.383056640625

Epoch 21 in 4744.13 sec
Train accuracy :	0.242	(310461/1281024)		Train loss :	3.8625
Val accuracy   :	0.216	(10810/50000)		Val loss :	4.0461
Top-5 val acc  :	0.427	(21365/50000)


Mean log L2 = -1.1119756698608398
Total dropped = 0
param norm = 138.47262573242188

Epoch 22 in 4743.48 sec
Train accuracy :	0.244	(313184/1281024)		Train loss :	3.8454
Val accuracy   :	0.218	(10891/50000)		Val loss :	4.0243
Top-5 val acc  :	0.431	(21542/50000)


Mean log L2 = -1.1399511098861694
Total dropped = 0
param norm = 138.3961944580078

Epoch 23 in 4743.56 sec
Train accuracy :	0.247	(316172/1281024)		Train loss :	3.8272
Val accuracy   :	0.219	(10971/50000)		Val loss :	4.0121
Top-5 val acc  :	0.435	(21755/50000)


Mean log L2 = -1.1224560737609863
Total dropped = 0
param norm = 138.33349609375

Epoch 24 in 4741.45 sec
Train accuracy :	0.249	(319306/1281024)		Train loss :	3.8096
Val accuracy   :	0.218	(10922/50000)		Val loss :	4.0166
Top-5 val acc  :	0.433	(21628/50000)


Mean log L2 = -1.1201908588409424
Total dropped = 0
param norm = 138.19607543945312

Epoch 25 in 4742.58 sec
Train accuracy :	0.252	(322382/1281024)		Train loss :	3.792
Val accuracy   :	0.223	(11156/50000)		Val loss :	3.9952
Top-5 val acc  :	0.436	(21793/50000)


Mean log L2 = -1.1776005029678345
Total dropped = 0
param norm = 138.0364990234375

Epoch 26 in 4744.60 sec
Train accuracy :	0.254	(324926/1281024)		Train loss :	3.7776
Val accuracy   :	0.226	(11317/50000)		Val loss :	3.9572
Top-5 val acc  :	0.442	(22097/50000)


Mean log L2 = -1.1719218492507935
Total dropped = 0
param norm = 138.0836944580078

Epoch 27 in 4744.57 sec
Train accuracy :	0.257	(328901/1281024)		Train loss :	3.7555
Val accuracy   :	0.231	(11537/50000)		Val loss :	3.9342
Top-5 val acc  :	0.447	(22335/50000)


Mean log L2 = -1.1914494037628174
Total dropped = 0
param norm = 137.84947204589844

Epoch 28 in 4743.22 sec
Train accuracy :	0.258	(331007/1281024)		Train loss :	3.7452
Val accuracy   :	0.231	(11566/50000)		Val loss :	3.9252
Top-5 val acc  :	0.446	(22294/50000)


Mean log L2 = -1.259247064590454
Total dropped = 0
param norm = 137.46853637695312

Epoch 29 in 4740.87 sec
Train accuracy :	0.262	(334993/1281024)		Train loss :	3.7223
Val accuracy   :	0.234	(11679/50000)		Val loss :	3.9181
Top-5 val acc  :	0.449	(22450/50000)


Mean log L2 = -1.4404813051223755
Total dropped = 0
param norm = 137.3680419921875

Epoch 30 in 4745.08 sec
Train accuracy :	0.265	(338906/1281024)		Train loss :	3.7003
Val accuracy   :	0.235	(11739/50000)		Val loss :	3.9056
Top-5 val acc  :	0.451	(22551/50000)


Mean log L2 = -1.3028852939605713
Total dropped = 0
param norm = 137.22447204589844

Epoch 31 in 4742.77 sec
Train accuracy :	0.268	(343024/1281024)		Train loss :	3.6783
Val accuracy   :	0.24	(12008/50000)		Val loss :	3.8708
Top-5 val acc  :	0.459	(22959/50000)


Mean log L2 = -1.4164105653762817
Total dropped = 0
param norm = 136.967529296875

Epoch 32 in 4747.46 sec
Train accuracy :	0.271	(346755/1281024)		Train loss :	3.6573
Val accuracy   :	0.241	(12061/50000)		Val loss :	3.852
Top-5 val acc  :	0.462	(23101/50000)


Mean log L2 = -1.4087238311767578
Total dropped = 0
param norm = 136.89602661132812

Epoch 33 in 4745.76 sec
Train accuracy :	0.273	(350273/1281024)		Train loss :	3.6367
Val accuracy   :	0.241	(12052/50000)		Val loss :	3.8411
Top-5 val acc  :	0.463	(23153/50000)


Mean log L2 = -1.4423937797546387
Total dropped = 0
param norm = 136.67320251464844

Epoch 34 in 4748.94 sec
Train accuracy :	0.277	(355022/1281024)		Train loss :	3.6158
Val accuracy   :	0.245	(12236/50000)		Val loss :	3.8456
Top-5 val acc  :	0.463	(23167/50000)


Mean log L2 = -1.598750352859497
Total dropped = 0
param norm = 136.48435974121094

Epoch 35 in 4940.38 sec
Train accuracy :	0.28	(358504/1281024)		Train loss :	3.596
Val accuracy   :	0.247	(12337/50000)		Val loss :	3.8063
Top-5 val acc  :	0.47	(23517/50000)


Mean log L2 = -1.5707913637161255
Total dropped = 0
param norm = 136.19078063964844

Epoch 36 in 4747.89 sec
Train accuracy :	0.283	(362851/1281024)		Train loss :	3.5746
Val accuracy   :	0.251	(12550/50000)		Val loss :	3.7874
Top-5 val acc  :	0.475	(23736/50000)


Mean log L2 = -1.5263402462005615
Total dropped = 0
param norm = 135.96961975097656

Epoch 37 in 4745.72 sec
Train accuracy :	0.286	(365958/1281024)		Train loss :	3.5552
Val accuracy   :	0.249	(12440/50000)		Val loss :	3.8192
Top-5 val acc  :	0.468	(23377/50000)


Mean log L2 = -1.7102090120315552
Total dropped = 0
param norm = 135.75064086914062

Epoch 38 in 4743.74 sec
Train accuracy :	0.289	(370595/1281024)		Train loss :	3.5308
Val accuracy   :	0.251	(12573/50000)		Val loss :	3.7897
Top-5 val acc  :	0.474	(23676/50000)


Mean log L2 = -1.6753828525543213
Total dropped = 0
param norm = 135.48199462890625

Epoch 39 in 4749.82 sec
Train accuracy :	0.292	(373869/1281024)		Train loss :	3.5108
Val accuracy   :	0.256	(12805/50000)		Val loss :	3.7574
Top-5 val acc  :	0.479	(23943/50000)


Mean log L2 = -1.6343567371368408
Total dropped = 0
param norm = 135.08009338378906

Epoch 40 in 4744.34 sec
Train accuracy :	0.295	(377821/1281024)		Train loss :	3.4933
Val accuracy   :	0.258	(12891/50000)		Val loss :	3.743
Top-5 val acc  :	0.482	(24088/50000)


Mean log L2 = -1.880774974822998
Total dropped = 0
param norm = 134.81381225585938

Epoch 41 in 4742.93 sec
Train accuracy :	0.298	(381444/1281024)		Train loss :	3.4727
Val accuracy   :	0.262	(13078/50000)		Val loss :	3.7171
Top-5 val acc  :	0.486	(24279/50000)


Mean log L2 = -1.8095893859863281
Total dropped = 0
param norm = 134.4760284423828

Epoch 42 in 4742.02 sec
Train accuracy :	0.302	(386475/1281024)		Train loss :	3.4492
Val accuracy   :	0.263	(13154/50000)		Val loss :	3.6933
Top-5 val acc  :	0.49	(24511/50000)


Mean log L2 = -1.8779805898666382
Total dropped = 0
param norm = 134.1976776123047

Epoch 43 in 4746.05 sec
Train accuracy :	0.305	(390351/1281024)		Train loss :	3.4274
Val accuracy   :	0.272	(13579/50000)		Val loss :	3.6534
Top-5 val acc  :	0.497	(24848/50000)


Mean log L2 = -1.7997536659240723
Total dropped = 0
param norm = 133.85919189453125

Epoch 44 in 4745.96 sec
Train accuracy :	0.308	(394227/1281024)		Train loss :	3.4096
Val accuracy   :	0.269	(13434/50000)		Val loss :	3.6499
Top-5 val acc  :	0.498	(24886/50000)


Mean log L2 = -1.8681799173355103
Total dropped = 0
param norm = 133.56951904296875

Epoch 45 in 4748.27 sec
Train accuracy :	0.312	(399186/1281024)		Train loss :	3.3833
Val accuracy   :	0.275	(13762/50000)		Val loss :	3.6384
Top-5 val acc  :	0.502	(25086/50000)


Mean log L2 = -2.004380464553833
Total dropped = 0
param norm = 133.22621154785156

Epoch 46 in 4743.71 sec
Train accuracy :	0.316	(404370/1281024)		Train loss :	3.3593
Val accuracy   :	0.275	(13763/50000)		Val loss :	3.6296
Top-5 val acc  :	0.502	(25118/50000)


Mean log L2 = -2.147406578063965
Total dropped = 0
param norm = 132.85189819335938

Epoch 47 in 4747.57 sec
Train accuracy :	0.319	(409259/1281024)		Train loss :	3.3335
Val accuracy   :	0.274	(13694/50000)		Val loss :	3.6142
Top-5 val acc  :	0.502	(25114/50000)


Mean log L2 = -2.016040563583374
Total dropped = 0
param norm = 132.47052001953125

Epoch 48 in 4743.31 sec
Train accuracy :	0.322	(412060/1281024)		Train loss :	3.3175
Val accuracy   :	0.281	(14074/50000)		Val loss :	3.571
Top-5 val acc  :	0.511	(25543/50000)


Mean log L2 = -2.1885452270507812
Total dropped = 0
param norm = 132.1356201171875

Epoch 49 in 4742.97 sec
Train accuracy :	0.324	(414762/1281024)		Train loss :	3.308
Val accuracy   :	0.281	(14028/50000)		Val loss :	3.5897
Top-5 val acc  :	0.51	(25512/50000)


Mean log L2 = -2.1892948150634766
Total dropped = 0
param norm = 131.7693328857422

Epoch 50 in 4743.89 sec
Train accuracy :	0.328	(420409/1281024)		Train loss :	3.2798
Val accuracy   :	0.29	(14493/50000)		Val loss :	3.5222
Top-5 val acc  :	0.521	(26054/50000)


Mean log L2 = -2.3640952110290527
Total dropped = 0
param norm = 131.4804229736328

Epoch 51 in 4786.98 sec
Train accuracy :	0.331	(424302/1281024)		Train loss :	3.2593
Val accuracy   :	0.29	(14495/50000)		Val loss :	3.5148
Top-5 val acc  :	0.522	(26084/50000)


Mean log L2 = -2.1689884662628174
Total dropped = 0
param norm = 131.1680145263672

Epoch 52 in 4938.71 sec
Train accuracy :	0.335	(429256/1281024)		Train loss :	3.232
Val accuracy   :	0.288	(14419/50000)		Val loss :	3.5275
Top-5 val acc  :	0.521	(26057/50000)


Mean log L2 = -2.2715349197387695
Total dropped = 0
param norm = 130.85984802246094

Epoch 53 in 4748.38 sec
Train accuracy :	0.337	(431205/1281024)		Train loss :	3.2253
Val accuracy   :	0.293	(14653/50000)		Val loss :	3.4905
Top-5 val acc  :	0.529	(26453/50000)


Mean log L2 = -2.396120548248291
Total dropped = 0
param norm = 130.45555114746094

Epoch 54 in 4744.99 sec
Train accuracy :	0.342	(438661/1281024)		Train loss :	3.1885
Val accuracy   :	0.298	(14906/50000)		Val loss :	3.4698
Top-5 val acc  :	0.531	(26537/50000)


Mean log L2 = -2.3291163444519043
Total dropped = 0
param norm = 130.16299438476562

Epoch 55 in 4742.66 sec
Train accuracy :	0.346	(442689/1281024)		Train loss :	3.1708
Val accuracy   :	0.303	(15127/50000)		Val loss :	3.4406
Top-5 val acc  :	0.536	(26818/50000)


Mean log L2 = -2.3297903537750244
Total dropped = 0
param norm = 129.63040161132812

Epoch 56 in 4739.73 sec
Train accuracy :	0.351	(449217/1281024)		Train loss :	3.1389
Val accuracy   :	0.304	(15179/50000)		Val loss :	3.4467
Top-5 val acc  :	0.535	(26745/50000)


Mean log L2 = -2.401048421859741
Total dropped = 0
param norm = 129.1959228515625

Epoch 57 in 4740.08 sec
Train accuracy :	0.354	(453442/1281024)		Train loss :	3.1171
Val accuracy   :	0.309	(15474/50000)		Val loss :	3.4073
Top-5 val acc  :	0.542	(27104/50000)


Mean log L2 = -2.304309129714966
Total dropped = 0
param norm = 128.84658813476562

Epoch 58 in 4739.60 sec
Train accuracy :	0.357	(457712/1281024)		Train loss :	3.0979
Val accuracy   :	0.309	(15430/50000)		Val loss :	3.4027
Top-5 val acc  :	0.542	(27094/50000)


Mean log L2 = -2.3387293815612793
Total dropped = 0
param norm = 128.5991668701172

Epoch 59 in 4747.80 sec
Train accuracy :	0.36	(461234/1281024)		Train loss :	3.082
Val accuracy   :	0.307	(15357/50000)		Val loss :	3.4227
Top-5 val acc  :	0.54	(27011/50000)


Mean log L2 = -2.4398884773254395
Total dropped = 0
param norm = 128.34841918945312

Epoch 60 in 4745.03 sec
Train accuracy :	0.361	(462939/1281024)		Train loss :	3.0774
Val accuracy   :	0.311	(15532/50000)		Val loss :	3.4063
Top-5 val acc  :	0.542	(27100/50000)


Mean log L2 = -2.3828182220458984
Total dropped = 0
param norm = 128.5647430419922

Epoch 61 in 4753.17 sec
Train accuracy :	0.358	(458323/1281024)		Train loss :	3.0949
Val accuracy   :	0.306	(15293/50000)		Val loss :	3.4096
Top-5 val acc  :	0.543	(27164/50000)


Mean log L2 = -2.481781005859375
Total dropped = 0
param norm = 128.62213134765625

Epoch 62 in 4748.79 sec
Train accuracy :	0.361	(462158/1281024)		Train loss :	3.0798
Val accuracy   :	0.313	(15663/50000)		Val loss :	3.3814
Top-5 val acc  :	0.545	(27271/50000)


Mean log L2 = -2.5311708450317383
Total dropped = 0
param norm = 128.9602813720703

Epoch 63 in 4743.09 sec
Train accuracy :	0.361	(461863/1281024)		Train loss :	3.0831
Val accuracy   :	0.303	(15148/50000)		Val loss :	3.4305
Top-5 val acc  :	0.539	(26958/50000)


Mean log L2 = -2.5334181785583496
Total dropped = 0
param norm = 129.7994842529297

Epoch 64 in 4748.72 sec
Train accuracy :	0.351	(449727/1281024)		Train loss :	3.1467
Val accuracy   :	0.315	(15735/50000)		Val loss :	3.3592
Top-5 val acc  :	0.551	(27563/50000)


Mean log L2 = -2.4843616485595703
Total dropped = 0
param norm = 129.69146728515625

Epoch 65 in 4748.16 sec
Train accuracy :	0.366	(468885/1281024)		Train loss :	3.0491
Val accuracy   :	0.315	(15758/50000)		Val loss :	3.3454
Top-5 val acc  :	0.553	(27626/50000)


Mean log L2 = -2.450510025024414
Total dropped = 0
param norm = 129.39598083496094

Epoch 66 in 4751.80 sec
Train accuracy :	0.37	(473824/1281024)		Train loss :	3.0286
Val accuracy   :	0.317	(15856/50000)		Val loss :	3.3384
Top-5 val acc  :	0.555	(27771/50000)


Mean log L2 = -2.6357765197753906
Total dropped = 0
param norm = 129.28883361816406

Epoch 67 in 4744.56 sec
Train accuracy :	0.372	(476784/1281024)		Train loss :	3.0121
Val accuracy   :	0.322	(16096/50000)		Val loss :	3.3203
Top-5 val acc  :	0.556	(27816/50000)


Mean log L2 = -2.826016426086426
Total dropped = 0
param norm = 128.41339111328125

Epoch 68 in 4783.50 sec
Train accuracy :	0.383	(491033/1281024)		Train loss :	2.9427
Val accuracy   :	0.329	(16450/50000)		Val loss :	3.2805
Top-5 val acc  :	0.565	(28243/50000)


Mean log L2 = -2.7306935787200928
Total dropped = 0
param norm = 127.58106231689453

Epoch 69 in 4934.76 sec
Train accuracy :	0.39	(499007/1281024)		Train loss :	2.9055
Val accuracy   :	0.331	(16571/50000)		Val loss :	3.2517
Top-5 val acc  :	0.568	(28400/50000)


Mean log L2 = -2.7479755878448486
Total dropped = 0
param norm = 126.76475524902344

Epoch 70 in 4740.76 sec
Train accuracy :	0.395	(505468/1281024)		Train loss :	2.8762
Val accuracy   :	0.335	(16757/50000)		Val loss :	3.2261
Top-5 val acc  :	0.573	(28653/50000)


Mean log L2 = -2.6787874698638916
Total dropped = 0
param norm = 126.06549072265625

Epoch 71 in 4751.24 sec
Train accuracy :	0.4	(512099/1281024)		Train loss :	2.8481
Val accuracy   :	0.338	(16898/50000)		Val loss :	3.2206
Top-5 val acc  :	0.574	(28723/50000)


Mean log L2 = -2.6725850105285645
Total dropped = 0
param norm = 125.38066101074219

Epoch 72 in 4745.99 sec
Train accuracy :	0.404	(517267/1281024)		Train loss :	2.8223
Val accuracy   :	0.339	(16925/50000)		Val loss :	3.201
Top-5 val acc  :	0.58	(28982/50000)


Mean log L2 = -2.595263957977295
Total dropped = 0
param norm = 124.77538299560547

Epoch 73 in 4744.77 sec
Train accuracy :	0.408	(522576/1281024)		Train loss :	2.7996
Val accuracy   :	0.341	(17041/50000)		Val loss :	3.1902
Top-5 val acc  :	0.579	(28943/50000)


Mean log L2 = -2.5193674564361572
Total dropped = 0
param norm = 124.21601104736328

Epoch 74 in 4745.16 sec
Train accuracy :	0.412	(527412/1281024)		Train loss :	2.7779
Val accuracy   :	0.346	(17309/50000)		Val loss :	3.1674
Top-5 val acc  :	0.584	(29205/50000)


Mean log L2 = -2.661874771118164
Total dropped = 0
param norm = 123.67771911621094

Epoch 75 in 4746.30 sec
Train accuracy :	0.415	(532116/1281024)		Train loss :	2.7553
Val accuracy   :	0.349	(17473/50000)		Val loss :	3.1433
Top-5 val acc  :	0.588	(29391/50000)


Mean log L2 = -2.7150285243988037
Total dropped = 0
param norm = 123.19298553466797

Epoch 76 in 4749.67 sec
Train accuracy :	0.419	(537291/1281024)		Train loss :	2.7327
Val accuracy   :	0.347	(17354/50000)		Val loss :	3.1468
Top-5 val acc  :	0.587	(29374/50000)


Mean log L2 = -2.602719783782959
Total dropped = 0
param norm = 122.74332427978516

Epoch 77 in 4748.74 sec
Train accuracy :	0.423	(542057/1281024)		Train loss :	2.7119
Val accuracy   :	0.352	(17609/50000)		Val loss :	3.1316
Top-5 val acc  :	0.591	(29525/50000)


Mean log L2 = -2.6139254570007324
Total dropped = 0
param norm = 122.3310317993164

Epoch 78 in 4759.90 sec
Train accuracy :	0.426	(546230/1281024)		Train loss :	2.6919
Val accuracy   :	0.355	(17761/50000)		Val loss :	3.1069
Top-5 val acc  :	0.594	(29699/50000)


Mean log L2 = -2.649256944656372
Total dropped = 0
param norm = 121.95907592773438

Epoch 79 in 4739.73 sec
Train accuracy :	0.43	(550298/1281024)		Train loss :	2.6744
Val accuracy   :	0.354	(17694/50000)		Val loss :	3.1079
Top-5 val acc  :	0.595	(29733/50000)


Mean log L2 = -2.5108132362365723
Total dropped = 0
param norm = 121.63202667236328

Epoch 80 in 4769.58 sec
Train accuracy :	0.433	(554233/1281024)		Train loss :	2.6565
Val accuracy   :	0.356	(17781/50000)		Val loss :	3.0971
Top-5 val acc  :	0.596	(29811/50000)


Mean log L2 = -2.55045747756958
Total dropped = 0
param norm = 121.34255981445312

Epoch 81 in 4740.89 sec
Train accuracy :	0.436	(558099/1281024)		Train loss :	2.6389
Val accuracy   :	0.358	(17907/50000)		Val loss :	3.0848
Top-5 val acc  :	0.599	(29928/50000)


Mean log L2 = -2.5745317935943604
Total dropped = 0
param norm = 121.08808135986328

Epoch 82 in 4747.11 sec
Train accuracy :	0.438	(561727/1281024)		Train loss :	2.6247
Val accuracy   :	0.359	(17974/50000)		Val loss :	3.0711
Top-5 val acc  :	0.601	(30034/50000)


Mean log L2 = -2.5028891563415527
Total dropped = 0
param norm = 120.87551879882812

Epoch 83 in 4742.49 sec
Train accuracy :	0.441	(564624/1281024)		Train loss :	2.6103
Val accuracy   :	0.36	(18007/50000)		Val loss :	3.0647
Top-5 val acc  :	0.602	(30095/50000)


Mean log L2 = -2.4722964763641357
Total dropped = 0
param norm = 120.69351959228516

Epoch 84 in 4745.68 sec
Train accuracy :	0.443	(566919/1281024)		Train loss :	2.6032
Val accuracy   :	0.361	(18051/50000)		Val loss :	3.0696
Top-5 val acc  :	0.6	(30014/50000)


Mean log L2 = -2.499821662902832
Total dropped = 0
param norm = 120.55585479736328

Epoch 85 in 4742.19 sec
Train accuracy :	0.443	(567655/1281024)		Train loss :	2.6008
Val accuracy   :	0.36	(17985/50000)		Val loss :	3.0755
Top-5 val acc  :	0.6	(30017/50000)


Mean log L2 = -2.4873225688934326
Total dropped = 0
param norm = 120.44284057617188

Epoch 86 in 4935.28 sec
Train accuracy :	0.443	(567541/1281024)		Train loss :	2.6076
Val accuracy   :	0.36	(17993/50000)		Val loss :	3.0806
Top-5 val acc  :	0.599	(29973/50000)


Mean log L2 = -2.3561244010925293
Total dropped = 0
param norm = 120.36772918701172

Epoch 87 in 4741.65 sec
Train accuracy :	0.442	(565613/1281024)		Train loss :	2.6184
Val accuracy   :	0.358	(17879/50000)		Val loss :	3.1008
Top-5 val acc  :	0.596	(29785/50000)


Mean log L2 = -2.44258451461792
Total dropped = 0
param norm = 120.32239532470703

Epoch 88 in 4743.72 sec
Train accuracy :	0.44	(564158/1281024)		Train loss :	2.6299
Val accuracy   :	0.36	(17998/50000)		Val loss :	3.0839
Top-5 val acc  :	0.598	(29911/50000)


Mean log L2 = -2.4399704933166504
Total dropped = 0
param norm = 120.28910064697266

Epoch 89 in 4738.37 sec
Train accuracy :	0.443	(567949/1281024)		Train loss :	2.6037
Val accuracy   :	0.361	(18050/50000)		Val loss :	3.0734
Top-5 val acc  :	0.599	(29968/50000)


Mean log L2 = -2.4291837215423584
Total dropped = 0
param norm = 120.25148010253906

Epoch 90 in 4735.55 sec
Train accuracy :	0.445	(570494/1281024)		Train loss :	2.5952
Val accuracy   :	0.361	(18075/50000)		Val loss :	3.0728
Top-5 val acc  :	0.6	(30009/50000)


