python train.py simus/ep/cnn/xpvgg6_cif10.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 = -4.28833532333374
Total dropped = 0
param norm = 37.16633224487305

Epoch 1 in 701.32 sec
Train accuracy :	0.106	(5323/50000)		Train loss :	2.2979
Val accuracy   :	0.161	(1609/10000)		Val loss :	2.2253
Top-5 val acc  :	0.647	(6472/10000)


Mean log L2 = -4.540948390960693
Total dropped = 0
param norm = 37.3371696472168

Epoch 2 in 277.61 sec
Train accuracy :	0.236	(11778/50000)		Train loss :	2.0395
Val accuracy   :	0.305	(3054/10000)		Val loss :	1.9105
Top-5 val acc  :	0.819	(8194/10000)


Mean log L2 = -4.423960208892822
Total dropped = 0
param norm = 37.712215423583984

Epoch 3 in 277.47 sec
Train accuracy :	0.313	(15636/50000)		Train loss :	1.8355
Val accuracy   :	0.368	(3682/10000)		Val loss :	1.7243
Top-5 val acc  :	0.879	(8793/10000)


Mean log L2 = -4.085474491119385
Total dropped = 0
param norm = 38.135040283203125

Epoch 4 in 275.20 sec
Train accuracy :	0.365	(18230/50000)		Train loss :	1.6908
Val accuracy   :	0.409	(4089/10000)		Val loss :	1.5699
Top-5 val acc  :	0.909	(9087/10000)


Mean log L2 = -4.1050028800964355
Total dropped = 0
param norm = 38.615352630615234

Epoch 5 in 276.90 sec
Train accuracy :	0.41	(20519/50000)		Train loss :	1.5927
Val accuracy   :	0.434	(4343/10000)		Val loss :	1.526
Top-5 val acc  :	0.914	(9138/10000)


Mean log L2 = -3.0860486030578613
Total dropped = 0
param norm = 39.21381378173828

Epoch 6 in 276.75 sec
Train accuracy :	0.445	(22255/50000)		Train loss :	1.5054
Val accuracy   :	0.491	(4906/10000)		Val loss :	1.4054
Top-5 val acc  :	0.928	(9282/10000)


Mean log L2 = -3.137505054473877
Total dropped = 0
param norm = 39.82073211669922

Epoch 7 in 275.07 sec
Train accuracy :	0.481	(24052/50000)		Train loss :	1.4294
Val accuracy   :	0.507	(5068/10000)		Val loss :	1.3497
Top-5 val acc  :	0.931	(9315/10000)


Mean log L2 = -3.0278267860412598
Total dropped = 0
param norm = 40.42002868652344

Epoch 8 in 275.39 sec
Train accuracy :	0.513	(25652/50000)		Train loss :	1.3524
Val accuracy   :	0.518	(5180/10000)		Val loss :	1.343
Top-5 val acc  :	0.937	(9366/10000)


Mean log L2 = -3.038977861404419
Total dropped = 0
param norm = 40.97289276123047

Epoch 9 in 275.19 sec
Train accuracy :	0.54	(26995/50000)		Train loss :	1.2861
Val accuracy   :	0.573	(5725/10000)		Val loss :	1.2046
Top-5 val acc  :	0.95	(9503/10000)


Mean log L2 = -3.0060319900512695
Total dropped = 0
param norm = 41.54519271850586

Epoch 10 in 275.30 sec
Train accuracy :	0.562	(28113/50000)		Train loss :	1.232
Val accuracy   :	0.588	(5884/10000)		Val loss :	1.1706
Top-5 val acc  :	0.95	(9503/10000)


Mean log L2 = -2.7125518321990967
Total dropped = 0
param norm = 42.115142822265625

Epoch 11 in 275.13 sec
Train accuracy :	0.586	(29318/50000)		Train loss :	1.1767
Val accuracy   :	0.604	(6044/10000)		Val loss :	1.1261
Top-5 val acc  :	0.958	(9580/10000)


Mean log L2 = -3.180955410003662
Total dropped = 0
param norm = 42.65808868408203

Epoch 12 in 275.11 sec
Train accuracy :	0.608	(30380/50000)		Train loss :	1.1216
Val accuracy   :	0.608	(6079/10000)		Val loss :	1.1382
Top-5 val acc  :	0.951	(9506/10000)


Mean log L2 = -3.10686993598938
Total dropped = 0
param norm = 43.182708740234375

Epoch 13 in 277.38 sec
Train accuracy :	0.624	(31176/50000)		Train loss :	1.079
Val accuracy   :	0.646	(6459/10000)		Val loss :	1.0462
Top-5 val acc  :	0.958	(9584/10000)


Mean log L2 = -2.9287326335906982
Total dropped = 0
param norm = 43.709373474121094

Epoch 14 in 275.02 sec
Train accuracy :	0.639	(31964/50000)		Train loss :	1.0433
Val accuracy   :	0.636	(6359/10000)		Val loss :	1.0429
Top-5 val acc  :	0.96	(9595/10000)


Mean log L2 = -2.624199628829956
Total dropped = 0
param norm = 44.20522689819336

Epoch 15 in 276.92 sec
Train accuracy :	0.656	(32799/50000)		Train loss :	1.0079
Val accuracy   :	0.635	(6353/10000)		Val loss :	1.0423
Top-5 val acc  :	0.963	(9630/10000)


Mean log L2 = -2.5142247676849365
Total dropped = 0
param norm = 44.66676330566406

Epoch 16 in 275.18 sec
Train accuracy :	0.671	(33541/50000)		Train loss :	0.968
Val accuracy   :	0.673	(6731/10000)		Val loss :	0.9636
Top-5 val acc  :	0.967	(9674/10000)


Mean log L2 = -2.435913562774658
Total dropped = 0
param norm = 45.103118896484375

Epoch 17 in 276.87 sec
Train accuracy :	0.681	(34072/50000)		Train loss :	0.9366
Val accuracy   :	0.666	(6664/10000)		Val loss :	0.9832
Top-5 val acc  :	0.964	(9640/10000)


Mean log L2 = -2.4899802207946777
Total dropped = 0
param norm = 45.523128509521484

Epoch 18 in 275.00 sec
Train accuracy :	0.693	(34661/50000)		Train loss :	0.9084
Val accuracy   :	0.691	(6909/10000)		Val loss :	0.9251
Top-5 val acc  :	0.972	(9720/10000)


Mean log L2 = -2.6695759296417236
Total dropped = 0
param norm = 45.887184143066406

Epoch 19 in 276.91 sec
Train accuracy :	0.705	(35241/50000)		Train loss :	0.8702
Val accuracy   :	0.718	(7180/10000)		Val loss :	0.8386
Top-5 val acc  :	0.976	(9763/10000)


Mean log L2 = -2.6111972332000732
Total dropped = 0
param norm = 46.29048156738281

Epoch 20 in 274.95 sec
Train accuracy :	0.71	(35520/50000)		Train loss :	0.8561
Val accuracy   :	0.712	(7118/10000)		Val loss :	0.8647
Top-5 val acc  :	0.974	(9744/10000)


Mean log L2 = -2.6289303302764893
Total dropped = 0
param norm = 46.64714050292969

Epoch 21 in 276.88 sec
Train accuracy :	0.721	(36067/50000)		Train loss :	0.8278
Val accuracy   :	0.716	(7161/10000)		Val loss :	0.8547
Top-5 val acc  :	0.974	(9737/10000)


Mean log L2 = -2.2671163082122803
Total dropped = 0
param norm = 46.996063232421875

Epoch 22 in 275.05 sec
Train accuracy :	0.728	(36387/50000)		Train loss :	0.8132
Val accuracy   :	0.716	(7155/10000)		Val loss :	0.8373
Top-5 val acc  :	0.975	(9749/10000)


Mean log L2 = -2.612640142440796
Total dropped = 0
param norm = 47.31723403930664

Epoch 23 in 278.91 sec
Train accuracy :	0.741	(37038/50000)		Train loss :	0.7784
Val accuracy   :	0.73	(7301/10000)		Val loss :	0.8036
Top-5 val acc  :	0.977	(9771/10000)


Mean log L2 = -2.600644826889038
Total dropped = 0
param norm = 47.59587860107422

Epoch 24 in 275.22 sec
Train accuracy :	0.749	(37452/50000)		Train loss :	0.7511
Val accuracy   :	0.746	(7455/10000)		Val loss :	0.764
Top-5 val acc  :	0.979	(9791/10000)


Mean log L2 = -2.454271078109741
Total dropped = 0
param norm = 47.84000015258789

Epoch 25 in 275.41 sec
Train accuracy :	0.754	(37717/50000)		Train loss :	0.7357
Val accuracy   :	0.749	(7491/10000)		Val loss :	0.7614
Top-5 val acc  :	0.977	(9766/10000)


Mean log L2 = -2.5736939907073975
Total dropped = 0
param norm = 48.079978942871094

Epoch 26 in 277.08 sec
Train accuracy :	0.762	(38081/50000)		Train loss :	0.721
Val accuracy   :	0.757	(7573/10000)		Val loss :	0.7371
Top-5 val acc  :	0.978	(9777/10000)


Mean log L2 = -2.3970940113067627
Total dropped = 0
param norm = 48.31254959106445

Epoch 27 in 275.15 sec
Train accuracy :	0.769	(38460/50000)		Train loss :	0.698
Val accuracy   :	0.764	(7639/10000)		Val loss :	0.716
Top-5 val acc  :	0.98	(9801/10000)


Mean log L2 = -2.175767183303833
Total dropped = 0
param norm = 48.55116271972656

Epoch 28 in 276.57 sec
Train accuracy :	0.777	(38845/50000)		Train loss :	0.6778
Val accuracy   :	0.768	(7679/10000)		Val loss :	0.707
Top-5 val acc  :	0.982	(9823/10000)


Mean log L2 = -2.5275075435638428
Total dropped = 0
param norm = 48.757110595703125

Epoch 29 in 275.07 sec
Train accuracy :	0.778	(38899/50000)		Train loss :	0.6686
Val accuracy   :	0.771	(7711/10000)		Val loss :	0.6886
Top-5 val acc  :	0.982	(9818/10000)


Mean log L2 = -2.4256937503814697
Total dropped = 0
param norm = 48.93877029418945

Epoch 30 in 277.36 sec
Train accuracy :	0.787	(39342/50000)		Train loss :	0.6501
Val accuracy   :	0.766	(7665/10000)		Val loss :	0.6957
Top-5 val acc  :	0.983	(9834/10000)


Mean log L2 = -2.2263169288635254
Total dropped = 0
param norm = 49.12797927856445

Epoch 31 in 275.26 sec
Train accuracy :	0.791	(39528/50000)		Train loss :	0.6321
Val accuracy   :	0.773	(7727/10000)		Val loss :	0.6831
Top-5 val acc  :	0.981	(9813/10000)


Mean log L2 = -2.3286709785461426
Total dropped = 0
param norm = 49.30169677734375

Epoch 32 in 277.90 sec
Train accuracy :	0.797	(39842/50000)		Train loss :	0.6185
Val accuracy   :	0.77	(7701/10000)		Val loss :	0.6933
Top-5 val acc  :	0.982	(9823/10000)


Mean log L2 = -2.537698745727539
Total dropped = 0
param norm = 49.477596282958984

Epoch 33 in 275.38 sec
Train accuracy :	0.799	(39967/50000)		Train loss :	0.6101
Val accuracy   :	0.787	(7871/10000)		Val loss :	0.6544
Top-5 val acc  :	0.983	(9831/10000)


Mean log L2 = -2.3248062133789062
Total dropped = 0
param norm = 49.64073181152344

Epoch 34 in 275.05 sec
Train accuracy :	0.807	(40333/50000)		Train loss :	0.588
Val accuracy   :	0.784	(7842/10000)		Val loss :	0.65
Top-5 val acc  :	0.984	(9841/10000)


Mean log L2 = -2.269671678543091
Total dropped = 0
param norm = 49.77019500732422

Epoch 35 in 276.44 sec
Train accuracy :	0.809	(40467/50000)		Train loss :	0.5801
Val accuracy   :	0.787	(7869/10000)		Val loss :	0.635
Top-5 val acc  :	0.983	(9832/10000)


Mean log L2 = -2.346245527267456
Total dropped = 0
param norm = 49.90529251098633

Epoch 36 in 274.87 sec
Train accuracy :	0.814	(40693/50000)		Train loss :	0.5655
Val accuracy   :	0.789	(7889/10000)		Val loss :	0.6702
Top-5 val acc  :	0.984	(9837/10000)


Mean log L2 = -2.181074619293213
Total dropped = 0
param norm = 50.032135009765625

Epoch 37 in 277.15 sec
Train accuracy :	0.816	(40817/50000)		Train loss :	0.5565
Val accuracy   :	0.791	(7910/10000)		Val loss :	0.6418
Top-5 val acc  :	0.985	(9850/10000)


Mean log L2 = -2.215590238571167
Total dropped = 0
param norm = 50.10713577270508

Epoch 38 in 274.99 sec
Train accuracy :	0.825	(41228/50000)		Train loss :	0.539
Val accuracy   :	0.784	(7836/10000)		Val loss :	0.6446
Top-5 val acc  :	0.983	(9833/10000)


Mean log L2 = -2.2273943424224854
Total dropped = 0
param norm = 50.188804626464844

Epoch 39 in 276.68 sec
Train accuracy :	0.826	(41318/50000)		Train loss :	0.5319
Val accuracy   :	0.791	(7914/10000)		Val loss :	0.6279
Top-5 val acc  :	0.984	(9842/10000)


Mean log L2 = -2.4277336597442627
Total dropped = 0
param norm = 50.27687072753906

Epoch 40 in 275.64 sec
Train accuracy :	0.831	(41541/50000)		Train loss :	0.5181
Val accuracy   :	0.79	(7899/10000)		Val loss :	0.6416
Top-5 val acc  :	0.985	(9852/10000)


Mean log L2 = -2.145296096801758
Total dropped = 0
param norm = 50.359336853027344

Epoch 41 in 276.94 sec
Train accuracy :	0.835	(41734/50000)		Train loss :	0.5084
Val accuracy   :	0.795	(7955/10000)		Val loss :	0.6358
Top-5 val acc  :	0.985	(9846/10000)


Mean log L2 = -2.3682780265808105
Total dropped = 0
param norm = 50.441383361816406

Epoch 42 in 275.08 sec
Train accuracy :	0.835	(41764/50000)		Train loss :	0.5028
Val accuracy   :	0.806	(8060/10000)		Val loss :	0.5925
Top-5 val acc  :	0.988	(9882/10000)


Mean log L2 = -2.2587568759918213
Total dropped = 0
param norm = 50.521636962890625

Epoch 43 in 275.13 sec
Train accuracy :	0.842	(42092/50000)		Train loss :	0.4884
Val accuracy   :	0.803	(8035/10000)		Val loss :	0.6178
Top-5 val acc  :	0.986	(9857/10000)


Mean log L2 = -2.213169813156128
Total dropped = 0
param norm = 50.57680892944336

Epoch 44 in 275.00 sec
Train accuracy :	0.843	(42137/50000)		Train loss :	0.4776
Val accuracy   :	0.809	(8091/10000)		Val loss :	0.6001
Top-5 val acc  :	0.986	(9862/10000)


Mean log L2 = -2.406815767288208
Total dropped = 0
param norm = 50.627593994140625

Epoch 45 in 275.70 sec
Train accuracy :	0.849	(42456/50000)		Train loss :	0.4665
Val accuracy   :	0.81	(8105/10000)		Val loss :	0.5911
Top-5 val acc  :	0.986	(9859/10000)


Mean log L2 = -1.9549998044967651
Total dropped = 0
param norm = 50.69577407836914

Epoch 46 in 275.13 sec
Train accuracy :	0.852	(42582/50000)		Train loss :	0.4539
Val accuracy   :	0.811	(8114/10000)		Val loss :	0.5993
Top-5 val acc  :	0.986	(9859/10000)


Mean log L2 = -2.186406373977661
Total dropped = 0
param norm = 50.732364654541016

Epoch 47 in 275.19 sec
Train accuracy :	0.854	(42697/50000)		Train loss :	0.4477
Val accuracy   :	0.816	(8158/10000)		Val loss :	0.5906
Top-5 val acc  :	0.987	(9865/10000)


Mean log L2 = -2.028264045715332
Total dropped = 0
param norm = 50.76105499267578

Epoch 48 in 275.27 sec
Train accuracy :	0.86	(42996/50000)		Train loss :	0.4312
Val accuracy   :	0.81	(8103/10000)		Val loss :	0.5791
Top-5 val acc  :	0.987	(9871/10000)


Mean log L2 = -2.0891053676605225
Total dropped = 0
param norm = 50.78069305419922

Epoch 49 in 275.02 sec
Train accuracy :	0.863	(43135/50000)		Train loss :	0.4277
Val accuracy   :	0.814	(8144/10000)		Val loss :	0.5852
Top-5 val acc  :	0.987	(9867/10000)


Mean log L2 = -2.270953416824341
Total dropped = 0
param norm = 50.805973052978516

Epoch 50 in 275.28 sec
Train accuracy :	0.862	(43101/50000)		Train loss :	0.4241
Val accuracy   :	0.818	(8184/10000)		Val loss :	0.5582
Top-5 val acc  :	0.988	(9881/10000)


Mean log L2 = -2.088740587234497
Total dropped = 0
param norm = 50.82707977294922

Epoch 51 in 277.33 sec
Train accuracy :	0.867	(43352/50000)		Train loss :	0.4089
Val accuracy   :	0.817	(8167/10000)		Val loss :	0.5797
Top-5 val acc  :	0.987	(9867/10000)


Mean log L2 = -2.285390615463257
Total dropped = 0
param norm = 50.85181427001953

Epoch 52 in 274.92 sec
Train accuracy :	0.87	(43505/50000)		Train loss :	0.4019
Val accuracy   :	0.824	(8235/10000)		Val loss :	0.5727
Top-5 val acc  :	0.988	(9884/10000)


Mean log L2 = -2.2029190063476562
Total dropped = 0
param norm = 50.864871978759766

Epoch 53 in 275.05 sec
Train accuracy :	0.875	(43743/50000)		Train loss :	0.389
Val accuracy   :	0.82	(8196/10000)		Val loss :	0.5944
Top-5 val acc  :	0.985	(9846/10000)


Mean log L2 = -2.2374987602233887
Total dropped = 0
param norm = 50.872928619384766

Epoch 54 in 274.89 sec
Train accuracy :	0.878	(43900/50000)		Train loss :	0.3825
Val accuracy   :	0.827	(8268/10000)		Val loss :	0.5467
Top-5 val acc  :	0.988	(9877/10000)


Mean log L2 = -2.1617746353149414
Total dropped = 0
param norm = 50.879817962646484

Epoch 55 in 277.24 sec
Train accuracy :	0.879	(43965/50000)		Train loss :	0.3751
Val accuracy   :	0.828	(8283/10000)		Val loss :	0.5439
Top-5 val acc  :	0.987	(9866/10000)


Mean log L2 = -2.1656734943389893
Total dropped = 0
param norm = 50.88690948486328

Epoch 56 in 275.05 sec
Train accuracy :	0.882	(44113/50000)		Train loss :	0.3671
Val accuracy   :	0.822	(8215/10000)		Val loss :	0.5775
Top-5 val acc  :	0.987	(9865/10000)


Mean log L2 = -2.180647373199463
Total dropped = 0
param norm = 50.88772964477539

Epoch 57 in 274.98 sec
Train accuracy :	0.882	(44085/50000)		Train loss :	0.3634
Val accuracy   :	0.829	(8285/10000)		Val loss :	0.5484
Top-5 val acc  :	0.987	(9869/10000)


Mean log L2 = -2.012899398803711
Total dropped = 0
param norm = 50.88492202758789

Epoch 58 in 274.97 sec
Train accuracy :	0.886	(44282/50000)		Train loss :	0.3532
Val accuracy   :	0.831	(8308/10000)		Val loss :	0.5519
Top-5 val acc  :	0.987	(9872/10000)


Mean log L2 = -2.3380959033966064
Total dropped = 0
param norm = 50.886505126953125

Epoch 59 in 275.11 sec
Train accuracy :	0.891	(44559/50000)		Train loss :	0.3407
Val accuracy   :	0.828	(8278/10000)		Val loss :	0.5521
Top-5 val acc  :	0.987	(9872/10000)


Mean log L2 = -2.1706960201263428
Total dropped = 0
param norm = 50.88078689575195

Epoch 60 in 276.58 sec
Train accuracy :	0.891	(44544/50000)		Train loss :	0.3373
Val accuracy   :	0.83	(8299/10000)		Val loss :	0.5303
Top-5 val acc  :	0.988	(9875/10000)


Mean log L2 = -2.043023109436035
Total dropped = 0
param norm = 50.883575439453125

Epoch 61 in 275.11 sec
Train accuracy :	0.894	(44678/50000)		Train loss :	0.3273
Val accuracy   :	0.829	(8289/10000)		Val loss :	0.5629
Top-5 val acc  :	0.987	(9873/10000)


Mean log L2 = -2.3258614540100098
Total dropped = 0
param norm = 50.87396240234375

Epoch 62 in 275.09 sec
Train accuracy :	0.896	(44813/50000)		Train loss :	0.32
Val accuracy   :	0.83	(8303/10000)		Val loss :	0.5652
Top-5 val acc  :	0.986	(9864/10000)


Mean log L2 = -2.2620623111724854
Total dropped = 0
param norm = 50.86463928222656

Epoch 63 in 275.16 sec
Train accuracy :	0.898	(44908/50000)		Train loss :	0.3185
Val accuracy   :	0.826	(8259/10000)		Val loss :	0.5589
Top-5 val acc  :	0.987	(9872/10000)


Mean log L2 = -1.8845922946929932
Total dropped = 0
param norm = 50.852394104003906

Epoch 64 in 275.10 sec
Train accuracy :	0.901	(45037/50000)		Train loss :	0.3075
Val accuracy   :	0.828	(8283/10000)		Val loss :	0.5665
Top-5 val acc  :	0.986	(9858/10000)


Mean log L2 = -2.1967132091522217
Total dropped = 0
param norm = 50.83296585083008

Epoch 65 in 275.10 sec
Train accuracy :	0.902	(45115/50000)		Train loss :	0.3036
Val accuracy   :	0.834	(8338/10000)		Val loss :	0.5558
Top-5 val acc  :	0.988	(9877/10000)


Mean log L2 = -1.8603763580322266
Total dropped = 0
param norm = 50.827449798583984

Epoch 66 in 275.02 sec
Train accuracy :	0.905	(45260/50000)		Train loss :	0.2945
Val accuracy   :	0.833	(8332/10000)		Val loss :	0.5437
Top-5 val acc  :	0.989	(9887/10000)


Mean log L2 = -2.0272507667541504
Total dropped = 0
param norm = 50.81265640258789

Epoch 67 in 275.12 sec
Train accuracy :	0.905	(45229/50000)		Train loss :	0.2963
Val accuracy   :	0.827	(8268/10000)		Val loss :	0.5675
Top-5 val acc  :	0.987	(9874/10000)


Mean log L2 = -2.0358738899230957
Total dropped = 0
param norm = 50.79659652709961

Epoch 68 in 275.27 sec
Train accuracy :	0.907	(45372/50000)		Train loss :	0.2897
Val accuracy   :	0.837	(8374/10000)		Val loss :	0.5454
Top-5 val acc  :	0.987	(9865/10000)


Mean log L2 = -2.1784255504608154
Total dropped = 0
param norm = 50.779457092285156

Epoch 69 in 277.38 sec
Train accuracy :	0.912	(45607/50000)		Train loss :	0.2751
Val accuracy   :	0.838	(8378/10000)		Val loss :	0.5509
Top-5 val acc  :	0.988	(9878/10000)


Mean log L2 = -2.325591802597046
Total dropped = 0
param norm = 50.762821197509766

Epoch 70 in 274.95 sec
Train accuracy :	0.914	(45676/50000)		Train loss :	0.2722
Val accuracy   :	0.838	(8383/10000)		Val loss :	0.5439
Top-5 val acc  :	0.987	(9873/10000)


Mean log L2 = -2.212963581085205
Total dropped = 0
param norm = 50.74918746948242

Epoch 71 in 275.02 sec
Train accuracy :	0.916	(45799/50000)		Train loss :	0.266
Val accuracy   :	0.84	(8395/10000)		Val loss :	0.5433
Top-5 val acc  :	0.988	(9878/10000)


Mean log L2 = -1.964943289756775
Total dropped = 0
param norm = 50.73602294921875

Epoch 72 in 275.00 sec
Train accuracy :	0.918	(45879/50000)		Train loss :	0.2609
Val accuracy   :	0.839	(8394/10000)		Val loss :	0.5428
Top-5 val acc  :	0.989	(9887/10000)


Mean log L2 = -1.9875071048736572
Total dropped = 0
param norm = 50.72160720825195

Epoch 73 in 277.10 sec
Train accuracy :	0.917	(45873/50000)		Train loss :	0.2579
Val accuracy   :	0.842	(8419/10000)		Val loss :	0.5381
Top-5 val acc  :	0.988	(9875/10000)


Mean log L2 = -1.985289454460144
Total dropped = 0
param norm = 50.70832824707031

Epoch 74 in 275.20 sec
Train accuracy :	0.919	(45963/50000)		Train loss :	0.2525
Val accuracy   :	0.839	(8393/10000)		Val loss :	0.532
Top-5 val acc  :	0.989	(9885/10000)


Mean log L2 = -2.018867015838623
Total dropped = 0
param norm = 50.7000617980957

Epoch 75 in 275.21 sec
Train accuracy :	0.922	(46121/50000)		Train loss :	0.2418
Val accuracy   :	0.841	(8406/10000)		Val loss :	0.5473
Top-5 val acc  :	0.988	(9879/10000)


Mean log L2 = -1.961042046546936
Total dropped = 0
param norm = 50.68471145629883

Epoch 76 in 275.00 sec
Train accuracy :	0.922	(46090/50000)		Train loss :	0.2468
Val accuracy   :	0.841	(8408/10000)		Val loss :	0.5554
Top-5 val acc  :	0.988	(9877/10000)


Mean log L2 = -1.9274414777755737
Total dropped = 0
param norm = 50.672969818115234

Epoch 77 in 277.70 sec
Train accuracy :	0.924	(46188/50000)		Train loss :	0.2406
Val accuracy   :	0.843	(8427/10000)		Val loss :	0.5443
Top-5 val acc  :	0.988	(9880/10000)


Mean log L2 = -1.920911431312561
Total dropped = 0
param norm = 50.66307830810547

Epoch 78 in 275.34 sec
Train accuracy :	0.926	(46278/50000)		Train loss :	0.2373
Val accuracy   :	0.844	(8435/10000)		Val loss :	0.5488
Top-5 val acc  :	0.988	(9876/10000)


Mean log L2 = -2.14410662651062
Total dropped = 0
param norm = 50.654029846191406

Epoch 79 in 275.31 sec
Train accuracy :	0.927	(46363/50000)		Train loss :	0.2302
Val accuracy   :	0.843	(8431/10000)		Val loss :	0.5512
Top-5 val acc  :	0.988	(9882/10000)


Mean log L2 = -1.9138482809066772
Total dropped = 0
param norm = 50.645843505859375

Epoch 80 in 275.36 sec
Train accuracy :	0.927	(46346/50000)		Train loss :	0.2291
Val accuracy   :	0.844	(8439/10000)		Val loss :	0.554
Top-5 val acc  :	0.989	(9885/10000)


Mean log L2 = -2.075701951980591
Total dropped = 0
param norm = 50.63837432861328

Epoch 81 in 275.29 sec
Train accuracy :	0.93	(46487/50000)		Train loss :	0.2266
Val accuracy   :	0.845	(8445/10000)		Val loss :	0.5518
Top-5 val acc  :	0.988	(9882/10000)


Mean log L2 = -2.010579824447632
Total dropped = 0
param norm = 50.63165283203125

Epoch 82 in 275.02 sec
Train accuracy :	0.93	(46491/50000)		Train loss :	0.2237
Val accuracy   :	0.845	(8447/10000)		Val loss :	0.5457
Top-5 val acc  :	0.988	(9880/10000)


Mean log L2 = -2.0480597019195557
Total dropped = 0
param norm = 50.626678466796875

Epoch 83 in 275.28 sec
Train accuracy :	0.932	(46610/50000)		Train loss :	0.2181
Val accuracy   :	0.844	(8440/10000)		Val loss :	0.5513
Top-5 val acc  :	0.989	(9888/10000)


Mean log L2 = -2.038062810897827
Total dropped = 0
param norm = 50.6230354309082

Epoch 84 in 275.02 sec
Train accuracy :	0.932	(46617/50000)		Train loss :	0.2161
Val accuracy   :	0.843	(8427/10000)		Val loss :	0.5625
Top-5 val acc  :	0.989	(9886/10000)


Mean log L2 = -2.142735242843628
Total dropped = 0
param norm = 50.61976623535156

Epoch 85 in 275.31 sec
Train accuracy :	0.932	(46592/50000)		Train loss :	0.2163
Val accuracy   :	0.844	(8437/10000)		Val loss :	0.5554
Top-5 val acc  :	0.989	(9886/10000)


Mean log L2 = -2.121692657470703
Total dropped = 0
param norm = 50.61701583862305

Epoch 86 in 277.39 sec
Train accuracy :	0.933	(46633/50000)		Train loss :	0.216
Val accuracy   :	0.845	(8447/10000)		Val loss :	0.5568
Top-5 val acc  :	0.988	(9884/10000)


Mean log L2 = -2.1388680934906006
Total dropped = 0
param norm = 50.61509704589844

Epoch 87 in 275.31 sec
Train accuracy :	0.932	(46614/50000)		Train loss :	0.2168
Val accuracy   :	0.844	(8442/10000)		Val loss :	0.5609
Top-5 val acc  :	0.988	(9883/10000)


Mean log L2 = -2.087834119796753
Total dropped = 0
param norm = 50.613712310791016

Epoch 88 in 275.26 sec
Train accuracy :	0.932	(46611/50000)		Train loss :	0.2157
Val accuracy   :	0.845	(8445/10000)		Val loss :	0.5556
Top-5 val acc  :	0.988	(9883/10000)


Mean log L2 = -1.9925965070724487
Total dropped = 0
param norm = 50.61265563964844

Epoch 89 in 275.01 sec
Train accuracy :	0.934	(46686/50000)		Train loss :	0.2096
Val accuracy   :	0.845	(8453/10000)		Val loss :	0.5579
Top-5 val acc  :	0.988	(9883/10000)


Mean log L2 = -1.9144468307495117
Total dropped = 0
param norm = 50.612464904785156

Epoch 90 in 275.11 sec
Train accuracy :	0.933	(46654/50000)		Train loss :	0.2122
Val accuracy   :	0.844	(8443/10000)		Val loss :	0.5574
Top-5 val acc  :	0.989	(9886/10000)


