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 = -4.833076000213623
Total dropped = 0
param norm = 37.136627197265625

Epoch 1 in 704.16 sec
Train accuracy :	0.105	(5250/50000)		Train loss :	2.3051
Val accuracy   :	0.145	(1451/10000)		Val loss :	2.2802
Top-5 val acc  :	0.594	(5942/10000)


Mean log L2 = -4.393438816070557
Total dropped = 0
param norm = 37.24264907836914

Epoch 2 in 280.11 sec
Train accuracy :	0.222	(11106/50000)		Train loss :	2.0785
Val accuracy   :	0.265	(2653/10000)		Val loss :	1.9995
Top-5 val acc  :	0.794	(7937/10000)


Mean log L2 = -3.9050965309143066
Total dropped = 0
param norm = 37.58197784423828

Epoch 3 in 279.43 sec
Train accuracy :	0.295	(14744/50000)		Train loss :	1.8994
Val accuracy   :	0.318	(3177/10000)		Val loss :	1.8883
Top-5 val acc  :	0.839	(8393/10000)


Mean log L2 = -4.5077385902404785
Total dropped = 0
param norm = 38.04129409790039

Epoch 4 in 277.22 sec
Train accuracy :	0.363	(18172/50000)		Train loss :	1.739
Val accuracy   :	0.408	(4079/10000)		Val loss :	1.6235
Top-5 val acc  :	0.896	(8960/10000)


Mean log L2 = -3.710369825363159
Total dropped = 0
param norm = 38.476009368896484

Epoch 5 in 279.44 sec
Train accuracy :	0.4	(20024/50000)		Train loss :	1.6249
Val accuracy   :	0.444	(4441/10000)		Val loss :	1.5143
Top-5 val acc  :	0.915	(9148/10000)


Mean log L2 = -4.091197490692139
Total dropped = 0
param norm = 38.894500732421875

Epoch 6 in 279.12 sec
Train accuracy :	0.44	(22024/50000)		Train loss :	1.528
Val accuracy   :	0.481	(4810/10000)		Val loss :	1.4212
Top-5 val acc  :	0.927	(9269/10000)


Mean log L2 = -3.3622207641601562
Total dropped = 0
param norm = 39.39266586303711

Epoch 7 in 277.33 sec
Train accuracy :	0.466	(23292/50000)		Train loss :	1.4594
Val accuracy   :	0.505	(5052/10000)		Val loss :	1.3644
Top-5 val acc  :	0.935	(9354/10000)


Mean log L2 = -3.0904223918914795
Total dropped = 0
param norm = 39.9215087890625

Epoch 8 in 277.76 sec
Train accuracy :	0.506	(25276/50000)		Train loss :	1.3716
Val accuracy   :	0.543	(5435/10000)		Val loss :	1.2809
Top-5 val acc  :	0.941	(9414/10000)


Mean log L2 = -3.0695009231567383
Total dropped = 0
param norm = 40.50446701049805

Epoch 9 in 277.34 sec
Train accuracy :	0.536	(26815/50000)		Train loss :	1.2883
Val accuracy   :	0.56	(5597/10000)		Val loss :	1.2387
Top-5 val acc  :	0.945	(9445/10000)


Mean log L2 = -3.148712635040283
Total dropped = 0
param norm = 41.1268196105957

Epoch 10 in 277.77 sec
Train accuracy :	0.563	(28161/50000)		Train loss :	1.2307
Val accuracy   :	0.575	(5750/10000)		Val loss :	1.2208
Top-5 val acc  :	0.951	(9509/10000)


Mean log L2 = -2.722670316696167
Total dropped = 0
param norm = 41.71280288696289

Epoch 11 in 277.69 sec
Train accuracy :	0.592	(29594/50000)		Train loss :	1.1626
Val accuracy   :	0.608	(6080/10000)		Val loss :	1.1298
Top-5 val acc  :	0.958	(9583/10000)


Mean log L2 = -2.9529049396514893
Total dropped = 0
param norm = 42.248878479003906

Epoch 12 in 277.31 sec
Train accuracy :	0.612	(30594/50000)		Train loss :	1.11
Val accuracy   :	0.631	(6311/10000)		Val loss :	1.0878
Top-5 val acc  :	0.957	(9573/10000)


Mean log L2 = -2.7650821208953857
Total dropped = 0
param norm = 42.87920379638672

Epoch 13 in 277.20 sec
Train accuracy :	0.634	(31683/50000)		Train loss :	1.0566
Val accuracy   :	0.654	(6537/10000)		Val loss :	1.0029
Top-5 val acc  :	0.965	(9647/10000)


Mean log L2 = -2.8230230808258057
Total dropped = 0
param norm = 43.4565544128418

Epoch 14 in 279.35 sec
Train accuracy :	0.651	(32568/50000)		Train loss :	1.013
Val accuracy   :	0.667	(6668/10000)		Val loss :	0.981
Top-5 val acc  :	0.965	(9654/10000)


Mean log L2 = -2.997408390045166
Total dropped = 0
param norm = 43.96275329589844

Epoch 15 in 277.25 sec
Train accuracy :	0.673	(33654/50000)		Train loss :	0.9641
Val accuracy   :	0.682	(6825/10000)		Val loss :	0.9285
Top-5 val acc  :	0.969	(9686/10000)


Mean log L2 = -3.0431158542633057
Total dropped = 0
param norm = 44.465179443359375

Epoch 16 in 277.49 sec
Train accuracy :	0.685	(34255/50000)		Train loss :	0.9317
Val accuracy   :	0.676	(6764/10000)		Val loss :	0.9608
Top-5 val acc  :	0.965	(9648/10000)


Mean log L2 = -2.803826093673706
Total dropped = 0
param norm = 44.990299224853516

Epoch 17 in 277.58 sec
Train accuracy :	0.694	(34723/50000)		Train loss :	0.9053
Val accuracy   :	0.684	(6844/10000)		Val loss :	0.9285
Top-5 val acc  :	0.969	(9685/10000)


Mean log L2 = -2.7854580879211426
Total dropped = 0
param norm = 45.47084045410156

Epoch 18 in 277.52 sec
Train accuracy :	0.707	(35365/50000)		Train loss :	0.8702
Val accuracy   :	0.718	(7177/10000)		Val loss :	0.8309
Top-5 val acc  :	0.975	(9750/10000)


Mean log L2 = -2.7359108924865723
Total dropped = 0
param norm = 45.89017105102539

Epoch 19 in 279.00 sec
Train accuracy :	0.717	(35836/50000)		Train loss :	0.8419
Val accuracy   :	0.71	(7103/10000)		Val loss :	0.8591
Top-5 val acc  :	0.973	(9733/10000)


Mean log L2 = -2.764970064163208
Total dropped = 0
param norm = 46.26836395263672

Epoch 20 in 276.88 sec
Train accuracy :	0.726	(36285/50000)		Train loss :	0.8179
Val accuracy   :	0.729	(7290/10000)		Val loss :	0.8234
Top-5 val acc  :	0.974	(9738/10000)


Mean log L2 = -2.949169397354126
Total dropped = 0
param norm = 46.64418029785156

Epoch 21 in 279.09 sec
Train accuracy :	0.738	(36918/50000)		Train loss :	0.7883
Val accuracy   :	0.743	(7430/10000)		Val loss :	0.7746
Top-5 val acc  :	0.977	(9768/10000)


Mean log L2 = -2.5411174297332764
Total dropped = 0
param norm = 47.01968002319336

Epoch 22 in 276.97 sec
Train accuracy :	0.745	(37259/50000)		Train loss :	0.7697
Val accuracy   :	0.747	(7470/10000)		Val loss :	0.772
Top-5 val acc  :	0.977	(9765/10000)


Mean log L2 = -2.7445640563964844
Total dropped = 0
param norm = 47.36575698852539

Epoch 23 in 281.03 sec
Train accuracy :	0.754	(37684/50000)		Train loss :	0.7413
Val accuracy   :	0.744	(7442/10000)		Val loss :	0.7726
Top-5 val acc  :	0.978	(9780/10000)


Mean log L2 = -2.8700902462005615
Total dropped = 0
param norm = 47.67100143432617

Epoch 24 in 276.90 sec
Train accuracy :	0.76	(37980/50000)		Train loss :	0.7272
Val accuracy   :	0.744	(7440/10000)		Val loss :	0.7722
Top-5 val acc  :	0.979	(9794/10000)


Mean log L2 = -2.427417516708374
Total dropped = 0
param norm = 47.97407150268555

Epoch 25 in 277.72 sec
Train accuracy :	0.768	(38413/50000)		Train loss :	0.6988
Val accuracy   :	0.732	(7318/10000)		Val loss :	0.8117
Top-5 val acc  :	0.976	(9764/10000)


Mean log L2 = -2.524017095565796
Total dropped = 0
param norm = 48.2519645690918

Epoch 26 in 277.30 sec
Train accuracy :	0.772	(38600/50000)		Train loss :	0.6916
Val accuracy   :	0.766	(7658/10000)		Val loss :	0.6933
Top-5 val acc  :	0.982	(9823/10000)


Mean log L2 = -2.805774450302124
Total dropped = 0
param norm = 48.50682830810547

Epoch 27 in 276.85 sec
Train accuracy :	0.779	(38970/50000)		Train loss :	0.6706
Val accuracy   :	0.764	(7645/10000)		Val loss :	0.7189
Top-5 val acc  :	0.98	(9798/10000)


Mean log L2 = -2.4150121212005615
Total dropped = 0
param norm = 48.74492645263672

Epoch 28 in 276.77 sec
Train accuracy :	0.784	(39205/50000)		Train loss :	0.6538
Val accuracy   :	0.779	(7792/10000)		Val loss :	0.6691
Top-5 val acc  :	0.983	(9828/10000)


Mean log L2 = -2.6890134811401367
Total dropped = 0
param norm = 48.967124938964844

Epoch 29 in 276.97 sec
Train accuracy :	0.795	(39737/50000)		Train loss :	0.6264
Val accuracy   :	0.769	(7688/10000)		Val loss :	0.7028
Top-5 val acc  :	0.978	(9782/10000)


Mean log L2 = -2.4414124488830566
Total dropped = 0
param norm = 49.190223693847656

Epoch 30 in 277.14 sec
Train accuracy :	0.796	(39794/50000)		Train loss :	0.6207
Val accuracy   :	0.781	(7813/10000)		Val loss :	0.6706
Top-5 val acc  :	0.983	(9826/10000)


Mean log L2 = -2.4065113067626953
Total dropped = 0
param norm = 49.374027252197266

Epoch 31 in 277.44 sec
Train accuracy :	0.804	(40180/50000)		Train loss :	0.6039
Val accuracy   :	0.779	(7792/10000)		Val loss :	0.6704
Top-5 val acc  :	0.981	(9811/10000)


Mean log L2 = -2.4013302326202393
Total dropped = 0
param norm = 49.57610321044922

Epoch 32 in 277.75 sec
Train accuracy :	0.804	(40219/50000)		Train loss :	0.5944
Val accuracy   :	0.782	(7820/10000)		Val loss :	0.666
Top-5 val acc  :	0.981	(9808/10000)


Mean log L2 = -2.1927647590637207
Total dropped = 0
param norm = 49.747169494628906

Epoch 33 in 277.24 sec
Train accuracy :	0.811	(40556/50000)		Train loss :	0.5751
Val accuracy   :	0.785	(7847/10000)		Val loss :	0.6633
Top-5 val acc  :	0.983	(9832/10000)


Mean log L2 = -2.383742570877075
Total dropped = 0
param norm = 49.8955192565918

Epoch 34 in 277.17 sec
Train accuracy :	0.818	(40919/50000)		Train loss :	0.5613
Val accuracy   :	0.793	(7931/10000)		Val loss :	0.6364
Top-5 val acc  :	0.985	(9851/10000)


Mean log L2 = -2.3609790802001953
Total dropped = 0
param norm = 50.03717803955078

Epoch 35 in 278.48 sec
Train accuracy :	0.82	(41006/50000)		Train loss :	0.5483
Val accuracy   :	0.789	(7892/10000)		Val loss :	0.6584
Top-5 val acc  :	0.983	(9832/10000)


Mean log L2 = -2.22003173828125
Total dropped = 0
param norm = 50.158870697021484

Epoch 36 in 276.29 sec
Train accuracy :	0.823	(41158/50000)		Train loss :	0.5407
Val accuracy   :	0.782	(7824/10000)		Val loss :	0.6659
Top-5 val acc  :	0.983	(9832/10000)


Mean log L2 = -2.5395092964172363
Total dropped = 0
param norm = 50.27810287475586

Epoch 37 in 276.95 sec
Train accuracy :	0.83	(41506/50000)		Train loss :	0.5237
Val accuracy   :	0.795	(7952/10000)		Val loss :	0.6222
Top-5 val acc  :	0.986	(9861/10000)


Mean log L2 = -2.470492362976074
Total dropped = 0
param norm = 50.39735412597656

Epoch 38 in 276.57 sec
Train accuracy :	0.832	(41579/50000)		Train loss :	0.5156
Val accuracy   :	0.804	(8040/10000)		Val loss :	0.5998
Top-5 val acc  :	0.985	(9854/10000)


Mean log L2 = -2.586390733718872
Total dropped = 0
param norm = 50.4987678527832

Epoch 39 in 276.90 sec
Train accuracy :	0.836	(41821/50000)		Train loss :	0.5035
Val accuracy   :	0.777	(7766/10000)		Val loss :	0.6887
Top-5 val acc  :	0.983	(9830/10000)


Mean log L2 = -2.416513442993164
Total dropped = 0
param norm = 50.59283447265625

Epoch 40 in 277.00 sec
Train accuracy :	0.84	(42011/50000)		Train loss :	0.4945
Val accuracy   :	0.811	(8106/10000)		Val loss :	0.5888
Top-5 val acc  :	0.985	(9851/10000)


Mean log L2 = -2.3343780040740967
Total dropped = 0
param norm = 50.68144989013672

Epoch 41 in 276.98 sec
Train accuracy :	0.842	(42099/50000)		Train loss :	0.488
Val accuracy   :	0.805	(8051/10000)		Val loss :	0.6054
Top-5 val acc  :	0.984	(9839/10000)


Mean log L2 = -2.4425156116485596
Total dropped = 0
param norm = 50.76393127441406

Epoch 42 in 276.87 sec
Train accuracy :	0.846	(42308/50000)		Train loss :	0.474
Val accuracy   :	0.802	(8021/10000)		Val loss :	0.6071
Top-5 val acc  :	0.985	(9850/10000)


Mean log L2 = -2.497141122817993
Total dropped = 0
param norm = 50.85004806518555

Epoch 43 in 276.78 sec
Train accuracy :	0.848	(42393/50000)		Train loss :	0.4644
Val accuracy   :	0.807	(8067/10000)		Val loss :	0.6207
Top-5 val acc  :	0.986	(9861/10000)


Mean log L2 = -2.259934186935425
Total dropped = 0
param norm = 50.90572738647461

Epoch 44 in 276.96 sec
Train accuracy :	0.853	(42660/50000)		Train loss :	0.4501
Val accuracy   :	0.819	(8191/10000)		Val loss :	0.5739
Top-5 val acc  :	0.988	(9883/10000)


Mean log L2 = -2.24991774559021
Total dropped = 0
param norm = 50.94611740112305

Epoch 45 in 279.19 sec
Train accuracy :	0.857	(42834/50000)		Train loss :	0.445
Val accuracy   :	0.817	(8169/10000)		Val loss :	0.5789
Top-5 val acc  :	0.988	(9880/10000)


Mean log L2 = -2.2809319496154785
Total dropped = 0
param norm = 51.013633728027344

Epoch 46 in 277.24 sec
Train accuracy :	0.856	(42801/50000)		Train loss :	0.4395
Val accuracy   :	0.818	(8183/10000)		Val loss :	0.5626
Top-5 val acc  :	0.988	(9875/10000)


Mean log L2 = -2.1145784854888916
Total dropped = 0
param norm = 51.049983978271484

Epoch 47 in 278.43 sec
Train accuracy :	0.862	(43120/50000)		Train loss :	0.4235
Val accuracy   :	0.812	(8117/10000)		Val loss :	0.5855
Top-5 val acc  :	0.988	(9878/10000)


Mean log L2 = -2.3537399768829346
Total dropped = 0
param norm = 51.086856842041016

Epoch 48 in 277.09 sec
Train accuracy :	0.865	(43229/50000)		Train loss :	0.4186
Val accuracy   :	0.818	(8183/10000)		Val loss :	0.5577
Top-5 val acc  :	0.986	(9864/10000)


Mean log L2 = -2.3502025604248047
Total dropped = 0
param norm = 51.10844421386719

Epoch 49 in 280.76 sec
Train accuracy :	0.869	(43463/50000)		Train loss :	0.4059
Val accuracy   :	0.818	(8184/10000)		Val loss :	0.5779
Top-5 val acc  :	0.988	(9878/10000)


Mean log L2 = -2.2254891395568848
Total dropped = 0
param norm = 51.12678527832031

Epoch 50 in 277.37 sec
Train accuracy :	0.871	(43539/50000)		Train loss :	0.3981
Val accuracy   :	0.825	(8245/10000)		Val loss :	0.5663
Top-5 val acc  :	0.987	(9867/10000)


Mean log L2 = -2.0807876586914062
Total dropped = 0
param norm = 51.126625061035156

Epoch 51 in 278.46 sec
Train accuracy :	0.873	(43668/50000)		Train loss :	0.3883
Val accuracy   :	0.821	(8213/10000)		Val loss :	0.5562
Top-5 val acc  :	0.988	(9884/10000)


Mean log L2 = -2.2179954051971436
Total dropped = 0
param norm = 51.14434814453125

Epoch 52 in 277.06 sec
Train accuracy :	0.878	(43887/50000)		Train loss :	0.3778
Val accuracy   :	0.818	(8180/10000)		Val loss :	0.5846
Top-5 val acc  :	0.984	(9837/10000)


Mean log L2 = -2.1297993659973145
Total dropped = 0
param norm = 51.156089782714844

Epoch 53 in 279.76 sec
Train accuracy :	0.882	(44116/50000)		Train loss :	0.3693
Val accuracy   :	0.829	(8285/10000)		Val loss :	0.5627
Top-5 val acc  :	0.987	(9868/10000)


Mean log L2 = -2.0806031227111816
Total dropped = 0
param norm = 51.14863204956055

Epoch 54 in 276.72 sec
Train accuracy :	0.882	(44100/50000)		Train loss :	0.3642
Val accuracy   :	0.833	(8332/10000)		Val loss :	0.5385
Top-5 val acc  :	0.989	(9885/10000)


Mean log L2 = -2.3901851177215576
Total dropped = 0
param norm = 51.14986038208008

Epoch 55 in 278.82 sec
Train accuracy :	0.887	(44352/50000)		Train loss :	0.3526
Val accuracy   :	0.83	(8304/10000)		Val loss :	0.5479
Top-5 val acc  :	0.986	(9863/10000)


Mean log L2 = -2.2019646167755127
Total dropped = 0
param norm = 51.16434097290039

Epoch 56 in 277.15 sec
Train accuracy :	0.888	(44399/50000)		Train loss :	0.3465
Val accuracy   :	0.836	(8357/10000)		Val loss :	0.5655
Top-5 val acc  :	0.987	(9869/10000)


Mean log L2 = -2.2692511081695557
Total dropped = 0
param norm = 51.1433219909668

Epoch 57 in 278.84 sec
Train accuracy :	0.89	(44509/50000)		Train loss :	0.3413
Val accuracy   :	0.83	(8298/10000)		Val loss :	0.5488
Top-5 val acc  :	0.987	(9867/10000)


Mean log L2 = -2.3482553958892822
Total dropped = 0
param norm = 51.13555908203125

Epoch 58 in 278.37 sec
Train accuracy :	0.894	(44703/50000)		Train loss :	0.332
Val accuracy   :	0.829	(8289/10000)		Val loss :	0.5515
Top-5 val acc  :	0.988	(9884/10000)


Mean log L2 = -2.206348180770874
Total dropped = 0
param norm = 51.13146209716797

Epoch 59 in 277.35 sec
Train accuracy :	0.895	(44770/50000)		Train loss :	0.3238
Val accuracy   :	0.833	(8327/10000)		Val loss :	0.5386
Top-5 val acc  :	0.989	(9885/10000)


Mean log L2 = -2.5051372051239014
Total dropped = 0
param norm = 51.1085319519043

Epoch 60 in 276.89 sec
Train accuracy :	0.897	(44853/50000)		Train loss :	0.3186
Val accuracy   :	0.83	(8304/10000)		Val loss :	0.5643
Top-5 val acc  :	0.988	(9876/10000)


Mean log L2 = -2.0645902156829834
Total dropped = 0
param norm = 51.09292221069336

Epoch 61 in 277.31 sec
Train accuracy :	0.902	(45113/50000)		Train loss :	0.3097
Val accuracy   :	0.838	(8384/10000)		Val loss :	0.5196
Top-5 val acc  :	0.989	(9894/10000)


Mean log L2 = -2.3256492614746094
Total dropped = 0
param norm = 51.07723617553711

Epoch 62 in 276.99 sec
Train accuracy :	0.901	(45059/50000)		Train loss :	0.3035
Val accuracy   :	0.841	(8408/10000)		Val loss :	0.5417
Top-5 val acc  :	0.987	(9874/10000)


Mean log L2 = -2.239453077316284
Total dropped = 0
param norm = 51.06178665161133

Epoch 63 in 276.84 sec
Train accuracy :	0.906	(45282/50000)		Train loss :	0.2935
Val accuracy   :	0.84	(8404/10000)		Val loss :	0.5342
Top-5 val acc  :	0.988	(9883/10000)


Mean log L2 = -2.1322133541107178
Total dropped = 0
param norm = 51.040863037109375

Epoch 64 in 277.05 sec
Train accuracy :	0.908	(45410/50000)		Train loss :	0.2897
Val accuracy   :	0.834	(8344/10000)		Val loss :	0.5509
Top-5 val acc  :	0.987	(9869/10000)


Mean log L2 = -2.3784737586975098
Total dropped = 0
param norm = 51.006797790527344

Epoch 65 in 277.20 sec
Train accuracy :	0.911	(45554/50000)		Train loss :	0.2821
Val accuracy   :	0.84	(8395/10000)		Val loss :	0.5366
Top-5 val acc  :	0.988	(9879/10000)


Mean log L2 = -2.3609211444854736
Total dropped = 0
param norm = 50.987937927246094

Epoch 66 in 276.93 sec
Train accuracy :	0.91	(45513/50000)		Train loss :	0.2762
Val accuracy   :	0.84	(8401/10000)		Val loss :	0.5426
Top-5 val acc  :	0.988	(9881/10000)


Mean log L2 = -2.229965925216675
Total dropped = 0
param norm = 50.95909118652344

Epoch 67 in 276.96 sec
Train accuracy :	0.912	(45576/50000)		Train loss :	0.2764
Val accuracy   :	0.843	(8429/10000)		Val loss :	0.5344
Top-5 val acc  :	0.989	(9893/10000)


Mean log L2 = -2.234727144241333
Total dropped = 0
param norm = 50.93902587890625

Epoch 68 in 277.27 sec
Train accuracy :	0.915	(45766/50000)		Train loss :	0.2684
Val accuracy   :	0.834	(8337/10000)		Val loss :	0.5649
Top-5 val acc  :	0.989	(9888/10000)


Mean log L2 = -2.398345947265625
Total dropped = 0
param norm = 50.9166374206543

Epoch 69 in 277.45 sec
Train accuracy :	0.917	(45866/50000)		Train loss :	0.2625
Val accuracy   :	0.839	(8390/10000)		Val loss :	0.5452
Top-5 val acc  :	0.989	(9888/10000)


Mean log L2 = -2.222200870513916
Total dropped = 0
param norm = 50.892913818359375

Epoch 70 in 277.31 sec
Train accuracy :	0.919	(45960/50000)		Train loss :	0.2559
Val accuracy   :	0.839	(8391/10000)		Val loss :	0.5446
Top-5 val acc  :	0.99	(9895/10000)


Mean log L2 = -2.201582908630371
Total dropped = 0
param norm = 50.86793899536133

Epoch 71 in 277.08 sec
Train accuracy :	0.92	(45994/50000)		Train loss :	0.2526
Val accuracy   :	0.836	(8356/10000)		Val loss :	0.5722
Top-5 val acc  :	0.988	(9880/10000)


Mean log L2 = -2.3072917461395264
Total dropped = 0
param norm = 50.842796325683594

Epoch 72 in 277.13 sec
Train accuracy :	0.923	(46157/50000)		Train loss :	0.2453
Val accuracy   :	0.843	(8431/10000)		Val loss :	0.5493
Top-5 val acc  :	0.988	(9877/10000)


Mean log L2 = -2.2005531787872314
Total dropped = 0
param norm = 50.82362747192383

Epoch 73 in 276.97 sec
Train accuracy :	0.924	(46193/50000)		Train loss :	0.2436
Val accuracy   :	0.845	(8446/10000)		Val loss :	0.5582
Top-5 val acc  :	0.988	(9883/10000)


Mean log L2 = -2.331958055496216
Total dropped = 0
param norm = 50.803367614746094

Epoch 74 in 278.65 sec
Train accuracy :	0.925	(46244/50000)		Train loss :	0.2395
Val accuracy   :	0.844	(8443/10000)		Val loss :	0.5356
Top-5 val acc  :	0.989	(9894/10000)


Mean log L2 = -2.1720242500305176
Total dropped = 0
param norm = 50.78103256225586

Epoch 75 in 277.47 sec
Train accuracy :	0.925	(46272/50000)		Train loss :	0.2348
Val accuracy   :	0.841	(8414/10000)		Val loss :	0.5388
Top-5 val acc  :	0.989	(9892/10000)


Mean log L2 = -2.1741878986358643
Total dropped = 0
param norm = 50.76060485839844

Epoch 76 in 277.48 sec
Train accuracy :	0.929	(46437/50000)		Train loss :	0.2292
Val accuracy   :	0.843	(8431/10000)		Val loss :	0.5478
Top-5 val acc  :	0.988	(9881/10000)


Mean log L2 = -2.178922414779663
Total dropped = 0
param norm = 50.74055099487305

Epoch 77 in 277.79 sec
Train accuracy :	0.929	(46456/50000)		Train loss :	0.2271
Val accuracy   :	0.844	(8441/10000)		Val loss :	0.538
Top-5 val acc  :	0.989	(9886/10000)


Mean log L2 = -2.239490270614624
Total dropped = 0
param norm = 50.71488571166992

Epoch 78 in 277.25 sec
Train accuracy :	0.928	(46414/50000)		Train loss :	0.2311
Val accuracy   :	0.84	(8404/10000)		Val loss :	0.5504
Top-5 val acc  :	0.989	(9887/10000)


Mean log L2 = -2.050983190536499
Total dropped = 0
param norm = 50.695919036865234

Epoch 79 in 278.86 sec
Train accuracy :	0.93	(46514/50000)		Train loss :	0.2231
Val accuracy   :	0.845	(8451/10000)		Val loss :	0.5539
Top-5 val acc  :	0.988	(9878/10000)


Mean log L2 = -2.3080475330352783
Total dropped = 0
param norm = 50.67888641357422

Epoch 80 in 276.77 sec
Train accuracy :	0.931	(46534/50000)		Train loss :	0.2254
Val accuracy   :	0.844	(8435/10000)		Val loss :	0.5497
Top-5 val acc  :	0.988	(9879/10000)


Mean log L2 = -2.426589250564575
Total dropped = 0
param norm = 50.66428756713867

Epoch 81 in 278.92 sec
Train accuracy :	0.931	(46574/50000)		Train loss :	0.2215
Val accuracy   :	0.843	(8434/10000)		Val loss :	0.5588
Top-5 val acc  :	0.988	(9879/10000)


Mean log L2 = -2.1728861331939697
Total dropped = 0
param norm = 50.650482177734375

Epoch 82 in 276.87 sec
Train accuracy :	0.93	(46524/50000)		Train loss :	0.2216
Val accuracy   :	0.843	(8433/10000)		Val loss :	0.5576
Top-5 val acc  :	0.987	(9874/10000)


Mean log L2 = -2.222925901412964
Total dropped = 0
param norm = 50.63724136352539

Epoch 83 in 276.70 sec
Train accuracy :	0.931	(46564/50000)		Train loss :	0.2229
Val accuracy   :	0.841	(8411/10000)		Val loss :	0.5557
Top-5 val acc  :	0.987	(9868/10000)


Mean log L2 = -2.2682130336761475
Total dropped = 0
param norm = 50.62632369995117

Epoch 84 in 276.93 sec
Train accuracy :	0.93	(46519/50000)		Train loss :	0.2244
Val accuracy   :	0.845	(8453/10000)		Val loss :	0.5495
Top-5 val acc  :	0.988	(9878/10000)


Mean log L2 = -2.468435049057007
Total dropped = 0
param norm = 50.617889404296875

Epoch 85 in 276.54 sec
Train accuracy :	0.932	(46597/50000)		Train loss :	0.2211
Val accuracy   :	0.843	(8425/10000)		Val loss :	0.5592
Top-5 val acc  :	0.987	(9869/10000)


Mean log L2 = -2.227057456970215
Total dropped = 0
param norm = 50.60934066772461

Epoch 86 in 277.30 sec
Train accuracy :	0.931	(46552/50000)		Train loss :	0.2248
Val accuracy   :	0.844	(8441/10000)		Val loss :	0.5541
Top-5 val acc  :	0.987	(9867/10000)


Mean log L2 = -2.1504666805267334
Total dropped = 0
param norm = 50.604671478271484

Epoch 87 in 276.41 sec
Train accuracy :	0.932	(46578/50000)		Train loss :	0.2215
Val accuracy   :	0.843	(8433/10000)		Val loss :	0.5591
Top-5 val acc  :	0.986	(9862/10000)


Mean log L2 = -2.1353065967559814
Total dropped = 0
param norm = 50.60092544555664

Epoch 88 in 277.21 sec
Train accuracy :	0.931	(46573/50000)		Train loss :	0.2234
Val accuracy   :	0.843	(8430/10000)		Val loss :	0.5572
Top-5 val acc  :	0.987	(9865/10000)


Mean log L2 = -2.2662675380706787
Total dropped = 0
param norm = 50.5988655090332

Epoch 89 in 277.12 sec
Train accuracy :	0.933	(46631/50000)		Train loss :	0.2196
Val accuracy   :	0.844	(8440/10000)		Val loss :	0.5584
Top-5 val acc  :	0.986	(9864/10000)


Mean log L2 = -2.31461501121521
Total dropped = 0
param norm = 50.598201751708984

Epoch 90 in 277.18 sec
Train accuracy :	0.933	(46630/50000)		Train loss :	0.2211
Val accuracy   :	0.844	(8442/10000)		Val loss :	0.5589
Top-5 val acc  :	0.986	(9860/10000)


