python train.py simus/ep/cnn/xpvgg6_cif10_max.json

Input   :	 (32, 32, 3)
Layer 1 :	 (16, 16, 128)
Layer 2 :	 (16, 16, 128)
Layer 3 :	 (8, 8, 256)
Layer 4 :	 (6, 6, 256)
Layer 5 :	 (3, 3, 512)
Layer 6 :	 (1, 1, 512)

Mean log L2 = -4.083841800689697
Total dropped = 0
param norm = 37.510162353515625

Epoch 1 in 460.66 sec
Train accuracy :	0.221	(11054/50000)		Train loss :	2.0837
Val accuracy   :	0.335	(3349/10000)		Val loss :	1.8745
Top-5 val acc  :	0.829	(8294/10000)


Mean log L2 = -3.7505404949188232
Total dropped = 0
param norm = 38.04888916015625

Epoch 2 in 253.90 sec
Train accuracy :	0.351	(17564/50000)		Train loss :	1.7915
Val accuracy   :	0.406	(4057/10000)		Val loss :	1.6388
Top-5 val acc  :	0.898	(8979/10000)


Mean log L2 = -3.649296522140503
Total dropped = 0
param norm = 38.68620300292969

Epoch 3 in 253.71 sec
Train accuracy :	0.405	(20230/50000)		Train loss :	1.6339
Val accuracy   :	0.4	(3997/10000)		Val loss :	1.6354
Top-5 val acc  :	0.897	(8966/10000)


Mean log L2 = -3.964395523071289
Total dropped = 0
param norm = 39.36008071899414

Epoch 4 in 251.55 sec
Train accuracy :	0.447	(22358/50000)		Train loss :	1.524
Val accuracy   :	0.481	(4815/10000)		Val loss :	1.4297
Top-5 val acc  :	0.927	(9275/10000)


Mean log L2 = -3.601414203643799
Total dropped = 0
param norm = 40.033695220947266

Epoch 5 in 253.13 sec
Train accuracy :	0.478	(23904/50000)		Train loss :	1.4457
Val accuracy   :	0.512	(5122/10000)		Val loss :	1.3499
Top-5 val acc  :	0.935	(9347/10000)


Mean log L2 = -3.823822021484375
Total dropped = 0
param norm = 40.74036407470703

Epoch 6 in 253.21 sec
Train accuracy :	0.505	(25255/50000)		Train loss :	1.3712
Val accuracy   :	0.527	(5272/10000)		Val loss :	1.3301
Top-5 val acc  :	0.936	(9358/10000)


Mean log L2 = -3.743147373199463
Total dropped = 0
param norm = 41.48622512817383

Epoch 7 in 251.62 sec
Train accuracy :	0.525	(26262/50000)		Train loss :	1.3301
Val accuracy   :	0.544	(5439/10000)		Val loss :	1.2726
Top-5 val acc  :	0.946	(9455/10000)


Mean log L2 = -3.7838082313537598
Total dropped = 0
param norm = 42.25892639160156

Epoch 8 in 251.56 sec
Train accuracy :	0.548	(27398/50000)		Train loss :	1.2831
Val accuracy   :	0.549	(5493/10000)		Val loss :	1.2815
Top-5 val acc  :	0.939	(9387/10000)


Mean log L2 = -3.6815381050109863
Total dropped = 0
param norm = 43.12128448486328

Epoch 9 in 251.16 sec
Train accuracy :	0.566	(28279/50000)		Train loss :	1.247
Val accuracy   :	0.567	(5669/10000)		Val loss :	1.2322
Top-5 val acc  :	0.95	(9497/10000)


Mean log L2 = -3.9620888233184814
Total dropped = 0
param norm = 43.9595947265625

Epoch 10 in 251.53 sec
Train accuracy :	0.584	(29176/50000)		Train loss :	1.2104
Val accuracy   :	0.585	(5850/10000)		Val loss :	1.2066
Top-5 val acc  :	0.95	(9501/10000)


Mean log L2 = -3.7660272121429443
Total dropped = 0
param norm = 44.75973892211914

Epoch 11 in 251.15 sec
Train accuracy :	0.598	(29914/50000)		Train loss :	1.17
Val accuracy   :	0.613	(6125/10000)		Val loss :	1.1249
Top-5 val acc  :	0.958	(9576/10000)


Mean log L2 = -3.675213575363159
Total dropped = 0
param norm = 45.500186920166016

Epoch 12 in 251.24 sec
Train accuracy :	0.614	(30697/50000)		Train loss :	1.1332
Val accuracy   :	0.63	(6297/10000)		Val loss :	1.0922
Top-5 val acc  :	0.961	(9606/10000)


Mean log L2 = -3.8236076831817627
Total dropped = 0
param norm = 46.216060638427734

Epoch 13 in 253.30 sec
Train accuracy :	0.624	(31204/50000)		Train loss :	1.1083
Val accuracy   :	0.623	(6231/10000)		Val loss :	1.1085
Top-5 val acc  :	0.956	(9556/10000)


Mean log L2 = -3.75028395652771
Total dropped = 0
param norm = 46.86281967163086

Epoch 14 in 251.13 sec
Train accuracy :	0.639	(31933/50000)		Train loss :	1.0713
Val accuracy   :	0.656	(6556/10000)		Val loss :	1.0276
Top-5 val acc  :	0.96	(9600/10000)


Mean log L2 = -3.6102893352508545
Total dropped = 0
param norm = 47.448829650878906

Epoch 15 in 252.92 sec
Train accuracy :	0.649	(32474/50000)		Train loss :	1.043
Val accuracy   :	0.635	(6346/10000)		Val loss :	1.0736
Top-5 val acc  :	0.958	(9577/10000)


Mean log L2 = -3.363818407058716
Total dropped = 0
param norm = 47.984336853027344

Epoch 16 in 250.90 sec
Train accuracy :	0.66	(33008/50000)		Train loss :	1.0152
Val accuracy   :	0.671	(6714/10000)		Val loss :	0.9952
Top-5 val acc  :	0.963	(9633/10000)


Mean log L2 = -3.4976937770843506
Total dropped = 0
param norm = 48.47135543823242

Epoch 17 in 252.79 sec
Train accuracy :	0.669	(33445/50000)		Train loss :	0.9975
Val accuracy   :	0.658	(6578/10000)		Val loss :	1.0196
Top-5 val acc  :	0.962	(9621/10000)


Mean log L2 = -3.4524314403533936
Total dropped = 0
param norm = 48.919864654541016

Epoch 18 in 251.00 sec
Train accuracy :	0.675	(33745/50000)		Train loss :	0.9765
Val accuracy   :	0.678	(6785/10000)		Val loss :	0.969
Top-5 val acc  :	0.967	(9672/10000)


Mean log L2 = -3.7825303077697754
Total dropped = 0
param norm = 49.33008575439453

Epoch 19 in 253.18 sec
Train accuracy :	0.683	(34130/50000)		Train loss :	0.9597
Val accuracy   :	0.673	(6734/10000)		Val loss :	1.0092
Top-5 val acc  :	0.954	(9541/10000)


Mean log L2 = -3.201838254928589
Total dropped = 0
param norm = 49.70755386352539

Epoch 20 in 250.98 sec
Train accuracy :	0.692	(34597/50000)		Train loss :	0.9326
Val accuracy   :	0.692	(6919/10000)		Val loss :	0.9368
Top-5 val acc  :	0.963	(9628/10000)


Mean log L2 = -3.298527479171753
Total dropped = 0
param norm = 50.03849792480469

Epoch 21 in 252.90 sec
Train accuracy :	0.697	(34852/50000)		Train loss :	0.918
Val accuracy   :	0.689	(6890/10000)		Val loss :	0.943
Top-5 val acc  :	0.966	(9656/10000)


Mean log L2 = -3.3175277709960938
Total dropped = 0
param norm = 50.34038543701172

Epoch 22 in 250.99 sec
Train accuracy :	0.705	(35257/50000)		Train loss :	0.8964
Val accuracy   :	0.69	(6896/10000)		Val loss :	0.9421
Top-5 val acc  :	0.965	(9648/10000)


Mean log L2 = -3.4710404872894287
Total dropped = 0
param norm = 50.63385009765625

Epoch 23 in 254.98 sec
Train accuracy :	0.709	(35472/50000)		Train loss :	0.8863
Val accuracy   :	0.706	(7063/10000)		Val loss :	0.8913
Top-5 val acc  :	0.969	(9691/10000)


Mean log L2 = -3.334925889968872
Total dropped = 0
param norm = 50.86600112915039

Epoch 24 in 250.90 sec
Train accuracy :	0.716	(35797/50000)		Train loss :	0.8699
Val accuracy   :	0.715	(7150/10000)		Val loss :	0.8681
Top-5 val acc  :	0.972	(9724/10000)


Mean log L2 = -3.2029507160186768
Total dropped = 0
param norm = 51.11613464355469

Epoch 25 in 251.46 sec
Train accuracy :	0.726	(36286/50000)		Train loss :	0.847
Val accuracy   :	0.706	(7057/10000)		Val loss :	0.8886
Top-5 val acc  :	0.969	(9686/10000)


Mean log L2 = -3.244884967803955
Total dropped = 0
param norm = 51.34312438964844

Epoch 26 in 253.10 sec
Train accuracy :	0.729	(36427/50000)		Train loss :	0.8342
Val accuracy   :	0.716	(7162/10000)		Val loss :	0.8765
Top-5 val acc  :	0.969	(9686/10000)


Mean log L2 = -3.277280569076538
Total dropped = 0
param norm = 51.560142517089844

Epoch 27 in 250.93 sec
Train accuracy :	0.73	(36478/50000)		Train loss :	0.8285
Val accuracy   :	0.702	(7021/10000)		Val loss :	0.9022
Top-5 val acc  :	0.969	(9694/10000)


Mean log L2 = -2.995856523513794
Total dropped = 0
param norm = 51.772674560546875

Epoch 28 in 252.75 sec
Train accuracy :	0.732	(36604/50000)		Train loss :	0.8257
Val accuracy   :	0.727	(7273/10000)		Val loss :	0.8369
Top-5 val acc  :	0.971	(9713/10000)


Mean log L2 = -3.206205368041992
Total dropped = 0
param norm = 51.96254348754883

Epoch 29 in 251.09 sec
Train accuracy :	0.74	(37008/50000)		Train loss :	0.7997
Val accuracy   :	0.718	(7178/10000)		Val loss :	0.8568
Top-5 val acc  :	0.97	(9702/10000)


Mean log L2 = -3.1205501556396484
Total dropped = 0
param norm = 52.141815185546875

Epoch 30 in 253.33 sec
Train accuracy :	0.739	(36953/50000)		Train loss :	0.8041
Val accuracy   :	0.699	(6991/10000)		Val loss :	0.9193
Top-5 val acc  :	0.967	(9673/10000)


Mean log L2 = -3.185218572616577
Total dropped = 0
param norm = 52.30282211303711

Epoch 31 in 251.22 sec
Train accuracy :	0.747	(37327/50000)		Train loss :	0.7856
Val accuracy   :	0.73	(7297/10000)		Val loss :	0.8243
Top-5 val acc  :	0.969	(9693/10000)


Mean log L2 = -3.1944427490234375
Total dropped = 0
param norm = 52.429443359375

Epoch 32 in 253.97 sec
Train accuracy :	0.75	(37502/50000)		Train loss :	0.7713
Val accuracy   :	0.729	(7289/10000)		Val loss :	0.8149
Top-5 val acc  :	0.972	(9722/10000)


Mean log L2 = -3.1805779933929443
Total dropped = 0
param norm = 52.54257583618164

Epoch 33 in 251.17 sec
Train accuracy :	0.753	(37669/50000)		Train loss :	0.764
Val accuracy   :	0.726	(7257/10000)		Val loss :	0.836
Top-5 val acc  :	0.972	(9724/10000)


Mean log L2 = -3.3095176219940186
Total dropped = 0
param norm = 52.675270080566406

Epoch 34 in 250.81 sec
Train accuracy :	0.756	(37801/50000)		Train loss :	0.7612
Val accuracy   :	0.748	(7483/10000)		Val loss :	0.7821
Top-5 val acc  :	0.976	(9762/10000)


Mean log L2 = -3.072725772857666
Total dropped = 0
param norm = 52.79008865356445

Epoch 35 in 252.63 sec
Train accuracy :	0.765	(38236/50000)		Train loss :	0.7331
Val accuracy   :	0.747	(7465/10000)		Val loss :	0.7771
Top-5 val acc  :	0.974	(9744/10000)


Mean log L2 = -3.0402560234069824
Total dropped = 0
param norm = 52.87468719482422

Epoch 36 in 251.01 sec
Train accuracy :	0.766	(38288/50000)		Train loss :	0.7299
Val accuracy   :	0.733	(7326/10000)		Val loss :	0.8356
Top-5 val acc  :	0.968	(9684/10000)


Mean log L2 = -3.2116572856903076
Total dropped = 0
param norm = 52.95912170410156

Epoch 37 in 253.02 sec
Train accuracy :	0.766	(38306/50000)		Train loss :	0.726
Val accuracy   :	0.748	(7482/10000)		Val loss :	0.8042
Top-5 val acc  :	0.971	(9714/10000)


Mean log L2 = -2.9740397930145264
Total dropped = 0
param norm = 53.015052795410156

Epoch 38 in 250.81 sec
Train accuracy :	0.772	(38622/50000)		Train loss :	0.7135
Val accuracy   :	0.753	(7529/10000)		Val loss :	0.7882
Top-5 val acc  :	0.973	(9725/10000)


Mean log L2 = -3.2695178985595703
Total dropped = 0
param norm = 53.070098876953125

Epoch 39 in 252.84 sec
Train accuracy :	0.774	(38718/50000)		Train loss :	0.7102
Val accuracy   :	0.749	(7493/10000)		Val loss :	0.7943
Top-5 val acc  :	0.974	(9741/10000)


Mean log L2 = -3.4363975524902344
Total dropped = 0
param norm = 53.117523193359375

Epoch 40 in 251.49 sec
Train accuracy :	0.775	(38768/50000)		Train loss :	0.7026
Val accuracy   :	0.747	(7467/10000)		Val loss :	0.7734
Top-5 val acc  :	0.976	(9759/10000)


Mean log L2 = -3.2094509601593018
Total dropped = 0
param norm = 53.166107177734375

Epoch 41 in 252.74 sec
Train accuracy :	0.779	(38948/50000)		Train loss :	0.6928
Val accuracy   :	0.754	(7538/10000)		Val loss :	0.7682
Top-5 val acc  :	0.975	(9754/10000)


Mean log L2 = -3.0240533351898193
Total dropped = 0
param norm = 53.21437072753906

Epoch 42 in 251.00 sec
Train accuracy :	0.782	(39086/50000)		Train loss :	0.6855
Val accuracy   :	0.751	(7510/10000)		Val loss :	0.7719
Top-5 val acc  :	0.972	(9724/10000)


Mean log L2 = -3.103160858154297
Total dropped = 0
param norm = 53.230873107910156

Epoch 43 in 251.04 sec
Train accuracy :	0.783	(39169/50000)		Train loss :	0.6758
Val accuracy   :	0.762	(7623/10000)		Val loss :	0.7472
Top-5 val acc  :	0.979	(9785/10000)


Mean log L2 = -2.959737777709961
Total dropped = 0
param norm = 53.26216506958008

Epoch 44 in 251.05 sec
Train accuracy :	0.787	(39335/50000)		Train loss :	0.664
Val accuracy   :	0.763	(7632/10000)		Val loss :	0.7488
Top-5 val acc  :	0.973	(9726/10000)


Mean log L2 = -3.0603487491607666
Total dropped = 0
param norm = 53.30371856689453

Epoch 45 in 251.62 sec
Train accuracy :	0.789	(39461/50000)		Train loss :	0.661
Val accuracy   :	0.766	(7656/10000)		Val loss :	0.7466
Top-5 val acc  :	0.976	(9762/10000)


Mean log L2 = -3.4073097705841064
Total dropped = 0
param norm = 53.31932067871094

Epoch 46 in 250.95 sec
Train accuracy :	0.795	(39727/50000)		Train loss :	0.6434
Val accuracy   :	0.759	(7589/10000)		Val loss :	0.7586
Top-5 val acc  :	0.973	(9732/10000)


Mean log L2 = -3.0593717098236084
Total dropped = 0
param norm = 53.337684631347656

Epoch 47 in 251.14 sec
Train accuracy :	0.797	(39827/50000)		Train loss :	0.6393
Val accuracy   :	0.759	(7586/10000)		Val loss :	0.742
Top-5 val acc  :	0.978	(9784/10000)


Mean log L2 = -2.995408296585083
Total dropped = 0
param norm = 53.36146545410156

Epoch 48 in 250.88 sec
Train accuracy :	0.795	(39738/50000)		Train loss :	0.6428
Val accuracy   :	0.769	(7695/10000)		Val loss :	0.7274
Top-5 val acc  :	0.98	(9796/10000)


Mean log L2 = -3.013658285140991
Total dropped = 0
param norm = 53.38042449951172

Epoch 49 in 250.96 sec
Train accuracy :	0.798	(39884/50000)		Train loss :	0.6324
Val accuracy   :	0.769	(7687/10000)		Val loss :	0.7358
Top-5 val acc  :	0.977	(9769/10000)


Mean log L2 = -3.409454345703125
Total dropped = 0
param norm = 53.39128112792969

Epoch 50 in 251.34 sec
Train accuracy :	0.799	(39957/50000)		Train loss :	0.6256
Val accuracy   :	0.776	(7757/10000)		Val loss :	0.7018
Top-5 val acc  :	0.978	(9781/10000)


Mean log L2 = -3.197499990463257
Total dropped = 0
param norm = 53.39717102050781

Epoch 51 in 253.24 sec
Train accuracy :	0.804	(40199/50000)		Train loss :	0.6207
Val accuracy   :	0.772	(7722/10000)		Val loss :	0.7377
Top-5 val acc  :	0.977	(9774/10000)


Mean log L2 = -3.2187659740448
Total dropped = 0
param norm = 53.401824951171875

Epoch 52 in 251.24 sec
Train accuracy :	0.804	(40183/50000)		Train loss :	0.6187
Val accuracy   :	0.771	(7706/10000)		Val loss :	0.7293
Top-5 val acc  :	0.978	(9777/10000)


Mean log L2 = -2.976465940475464
Total dropped = 0
param norm = 53.403221130371094

Epoch 53 in 250.89 sec
Train accuracy :	0.805	(40247/50000)		Train loss :	0.6094
Val accuracy   :	0.77	(7703/10000)		Val loss :	0.7259
Top-5 val acc  :	0.977	(9771/10000)


Mean log L2 = -3.1367881298065186
Total dropped = 0
param norm = 53.397727966308594

Epoch 54 in 250.98 sec
Train accuracy :	0.81	(40476/50000)		Train loss :	0.6009
Val accuracy   :	0.774	(7743/10000)		Val loss :	0.7117
Top-5 val acc  :	0.976	(9764/10000)


Mean log L2 = -3.236994981765747
Total dropped = 0
param norm = 53.39345169067383

Epoch 55 in 253.14 sec
Train accuracy :	0.811	(40537/50000)		Train loss :	0.5953
Val accuracy   :	0.779	(7786/10000)		Val loss :	0.6897
Top-5 val acc  :	0.979	(9794/10000)


Mean log L2 = -3.2772891521453857
Total dropped = 0
param norm = 53.393096923828125

Epoch 56 in 251.05 sec
Train accuracy :	0.815	(40750/50000)		Train loss :	0.587
Val accuracy   :	0.775	(7749/10000)		Val loss :	0.7227
Top-5 val acc  :	0.978	(9779/10000)


Mean log L2 = -3.2488744258880615
Total dropped = 0
param norm = 53.38215255737305

Epoch 57 in 251.02 sec
Train accuracy :	0.818	(40900/50000)		Train loss :	0.5751
Val accuracy   :	0.777	(7775/10000)		Val loss :	0.7061
Top-5 val acc  :	0.979	(9785/10000)


Mean log L2 = -3.3207461833953857
Total dropped = 0
param norm = 53.364402770996094

Epoch 58 in 251.05 sec
Train accuracy :	0.819	(40945/50000)		Train loss :	0.5738
Val accuracy   :	0.78	(7799/10000)		Val loss :	0.6866
Top-5 val acc  :	0.98	(9798/10000)


Mean log L2 = -3.119474411010742
Total dropped = 0
param norm = 53.34273910522461

Epoch 59 in 251.02 sec
Train accuracy :	0.819	(40962/50000)		Train loss :	0.5719
Val accuracy   :	0.785	(7853/10000)		Val loss :	0.6847
Top-5 val acc  :	0.981	(9806/10000)


Mean log L2 = -3.276165008544922
Total dropped = 0
param norm = 53.32707977294922

Epoch 60 in 252.71 sec
Train accuracy :	0.822	(41089/50000)		Train loss :	0.5638
Val accuracy   :	0.783	(7826/10000)		Val loss :	0.7051
Top-5 val acc  :	0.978	(9776/10000)


Mean log L2 = -3.061631679534912
Total dropped = 0
param norm = 53.306575775146484

Epoch 61 in 250.98 sec
Train accuracy :	0.824	(41176/50000)		Train loss :	0.5581
Val accuracy   :	0.784	(7845/10000)		Val loss :	0.6836
Top-5 val acc  :	0.979	(9788/10000)


Mean log L2 = -3.235476016998291
Total dropped = 0
param norm = 53.283241271972656

Epoch 62 in 250.93 sec
Train accuracy :	0.824	(41192/50000)		Train loss :	0.5527
Val accuracy   :	0.786	(7864/10000)		Val loss :	0.6777
Top-5 val acc  :	0.98	(9798/10000)


Mean log L2 = -3.228771924972534
Total dropped = 0
param norm = 53.26188278198242

Epoch 63 in 251.19 sec
Train accuracy :	0.823	(41147/50000)		Train loss :	0.5553
Val accuracy   :	0.789	(7890/10000)		Val loss :	0.678
Top-5 val acc  :	0.979	(9786/10000)


Mean log L2 = -3.1554250717163086
Total dropped = 0
param norm = 53.24110412597656

Epoch 64 in 250.99 sec
Train accuracy :	0.829	(41446/50000)		Train loss :	0.5375
Val accuracy   :	0.783	(7831/10000)		Val loss :	0.6809
Top-5 val acc  :	0.98	(9796/10000)


Mean log L2 = -3.134239912033081
Total dropped = 0
param norm = 53.21897888183594

Epoch 65 in 250.90 sec
Train accuracy :	0.831	(41563/50000)		Train loss :	0.534
Val accuracy   :	0.781	(7806/10000)		Val loss :	0.6949
Top-5 val acc  :	0.976	(9764/10000)


Mean log L2 = -3.1812593936920166
Total dropped = 0
param norm = 53.1953239440918

Epoch 66 in 250.92 sec
Train accuracy :	0.83	(41497/50000)		Train loss :	0.5354
Val accuracy   :	0.787	(7868/10000)		Val loss :	0.677
Top-5 val acc  :	0.979	(9787/10000)


Mean log L2 = -3.1621170043945312
Total dropped = 0
param norm = 53.17506408691406

Epoch 67 in 251.37 sec
Train accuracy :	0.834	(41700/50000)		Train loss :	0.527
Val accuracy   :	0.786	(7864/10000)		Val loss :	0.6864
Top-5 val acc  :	0.978	(9783/10000)


Mean log L2 = -2.979970693588257
Total dropped = 0
param norm = 53.155921936035156

Epoch 68 in 251.43 sec
Train accuracy :	0.834	(41696/50000)		Train loss :	0.5249
Val accuracy   :	0.785	(7850/10000)		Val loss :	0.6723
Top-5 val acc  :	0.979	(9789/10000)


Mean log L2 = -3.1559109687805176
Total dropped = 0
param norm = 53.13425064086914

Epoch 69 in 253.51 sec
Train accuracy :	0.837	(41835/50000)		Train loss :	0.519
Val accuracy   :	0.796	(7965/10000)		Val loss :	0.6651
Top-5 val acc  :	0.98	(9796/10000)


Mean log L2 = -3.046870708465576
Total dropped = 0
param norm = 53.1129035949707

Epoch 70 in 250.81 sec
Train accuracy :	0.839	(41974/50000)		Train loss :	0.5109
Val accuracy   :	0.796	(7958/10000)		Val loss :	0.6642
Top-5 val acc  :	0.979	(9787/10000)


Mean log L2 = -3.0024614334106445
Total dropped = 0
param norm = 53.094329833984375

Epoch 71 in 251.02 sec
Train accuracy :	0.841	(42053/50000)		Train loss :	0.5058
Val accuracy   :	0.793	(7927/10000)		Val loss :	0.6632
Top-5 val acc  :	0.981	(9806/10000)


Mean log L2 = -3.0702273845672607
Total dropped = 0
param norm = 53.079139709472656

Epoch 72 in 250.94 sec
Train accuracy :	0.843	(42132/50000)		Train loss :	0.5042
Val accuracy   :	0.797	(7972/10000)		Val loss :	0.6639
Top-5 val acc  :	0.98	(9795/10000)


Mean log L2 = -3.071937084197998
Total dropped = 0
param norm = 53.06125259399414

Epoch 73 in 252.94 sec
Train accuracy :	0.841	(42054/50000)		Train loss :	0.5022
Val accuracy   :	0.8	(7998/10000)		Val loss :	0.6516
Top-5 val acc  :	0.981	(9808/10000)


Mean log L2 = -3.036569118499756
Total dropped = 0
param norm = 53.045162200927734

Epoch 74 in 250.95 sec
Train accuracy :	0.843	(42155/50000)		Train loss :	0.4944
Val accuracy   :	0.797	(7969/10000)		Val loss :	0.6579
Top-5 val acc  :	0.981	(9807/10000)


Mean log L2 = -3.258984327316284
Total dropped = 0
param norm = 53.03105926513672

Epoch 75 in 250.93 sec
Train accuracy :	0.845	(42250/50000)		Train loss :	0.4905
Val accuracy   :	0.8	(8005/10000)		Val loss :	0.6528
Top-5 val acc  :	0.98	(9799/10000)


Mean log L2 = -2.857001781463623
Total dropped = 0
param norm = 53.017547607421875

Epoch 76 in 250.95 sec
Train accuracy :	0.846	(42276/50000)		Train loss :	0.4882
Val accuracy   :	0.801	(8009/10000)		Val loss :	0.6497
Top-5 val acc  :	0.98	(9796/10000)


Mean log L2 = -3.0785140991210938
Total dropped = 0
param norm = 53.006019592285156

Epoch 77 in 253.39 sec
Train accuracy :	0.846	(42314/50000)		Train loss :	0.4883
Val accuracy   :	0.799	(7987/10000)		Val loss :	0.6574
Top-5 val acc  :	0.981	(9807/10000)


Mean log L2 = -3.0990960597991943
Total dropped = 0
param norm = 52.99568176269531

Epoch 78 in 251.39 sec
Train accuracy :	0.846	(42318/50000)		Train loss :	0.4844
Val accuracy   :	0.8	(8002/10000)		Val loss :	0.6501
Top-5 val acc  :	0.981	(9810/10000)


Mean log L2 = -3.4453530311584473
Total dropped = 0
param norm = 52.98666000366211

Epoch 79 in 251.60 sec
Train accuracy :	0.848	(42384/50000)		Train loss :	0.4833
Val accuracy   :	0.798	(7979/10000)		Val loss :	0.6524
Top-5 val acc  :	0.981	(9807/10000)


Mean log L2 = -3.247364044189453
Total dropped = 0
param norm = 52.97852325439453

Epoch 80 in 251.57 sec
Train accuracy :	0.847	(42355/50000)		Train loss :	0.4842
Val accuracy   :	0.8	(8003/10000)		Val loss :	0.6519
Top-5 val acc  :	0.98	(9804/10000)


Mean log L2 = -3.035036087036133
Total dropped = 0
param norm = 52.97198486328125

Epoch 81 in 251.16 sec
Train accuracy :	0.85	(42475/50000)		Train loss :	0.4783
Val accuracy   :	0.8	(8005/10000)		Val loss :	0.6507
Top-5 val acc  :	0.981	(9808/10000)


Mean log L2 = -3.1998164653778076
Total dropped = 0
param norm = 52.967247009277344

Epoch 82 in 250.89 sec
Train accuracy :	0.85	(42488/50000)		Train loss :	0.475
Val accuracy   :	0.801	(8006/10000)		Val loss :	0.6522
Top-5 val acc  :	0.98	(9803/10000)


Mean log L2 = -3.0409631729125977
Total dropped = 0
param norm = 52.9627571105957

Epoch 83 in 251.24 sec
Train accuracy :	0.852	(42595/50000)		Train loss :	0.4728
Val accuracy   :	0.802	(8025/10000)		Val loss :	0.6474
Top-5 val acc  :	0.981	(9809/10000)


Mean log L2 = -3.191126585006714
Total dropped = 0
param norm = 52.95957946777344

Epoch 84 in 250.98 sec
Train accuracy :	0.852	(42578/50000)		Train loss :	0.4736
Val accuracy   :	0.8	(8004/10000)		Val loss :	0.652
Top-5 val acc  :	0.981	(9806/10000)


Mean log L2 = -3.4460983276367188
Total dropped = 0
param norm = 52.956871032714844

Epoch 85 in 251.39 sec
Train accuracy :	0.852	(42609/50000)		Train loss :	0.4721
Val accuracy   :	0.801	(8010/10000)		Val loss :	0.6501
Top-5 val acc  :	0.981	(9810/10000)


Mean log L2 = -2.9211537837982178
Total dropped = 0
param norm = 52.95450973510742

Epoch 86 in 253.66 sec
Train accuracy :	0.85	(42505/50000)		Train loss :	0.4746
Val accuracy   :	0.801	(8006/10000)		Val loss :	0.6498
Top-5 val acc  :	0.981	(9807/10000)


Mean log L2 = -3.142002582550049
Total dropped = 0
param norm = 52.953006744384766

Epoch 87 in 251.44 sec
Train accuracy :	0.853	(42661/50000)		Train loss :	0.4685
Val accuracy   :	0.801	(8010/10000)		Val loss :	0.6482
Top-5 val acc  :	0.981	(9808/10000)


Mean log L2 = -3.052483081817627
Total dropped = 0
param norm = 52.951725006103516

Epoch 88 in 251.20 sec
Train accuracy :	0.852	(42583/50000)		Train loss :	0.4715
Val accuracy   :	0.802	(8024/10000)		Val loss :	0.6497
Top-5 val acc  :	0.98	(9800/10000)


Mean log L2 = -3.1921536922454834
Total dropped = 0
param norm = 52.950565338134766

Epoch 89 in 250.89 sec
Train accuracy :	0.85	(42524/50000)		Train loss :	0.4714
Val accuracy   :	0.803	(8029/10000)		Val loss :	0.6488
Top-5 val acc  :	0.981	(9806/10000)


Mean log L2 = -3.0442910194396973
Total dropped = 0
param norm = 52.950565338134766

Epoch 90 in 250.91 sec
Train accuracy :	0.854	(42693/50000)		Train loss :	0.4646
Val accuracy   :	0.802	(8025/10000)		Val loss :	0.649
Top-5 val acc  :	0.98	(9802/10000)


