Downloading https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz to ./data/cifar/cifar-10-python.tar.gz
170500096it [00:02, 74718714.99it/s]
Files already downloaded and verified
Epoch: [1/30], Batch: [1/500], train accuracy: 0.080000, loss: 0.009003
Epoch: [1/30], Batch: [101/500], train accuracy: 0.400000, loss: 0.008004
Epoch: [1/30], Batch: [201/500], train accuracy: 0.390000, loss: 0.008002
Epoch: [1/30], Batch: [301/500], train accuracy: 0.340000, loss: 0.008003
Epoch: [1/30], Batch: [401/500], train accuracy: 0.400000, loss: 0.007995
100% 500/500 [02:44<00:00, 2.95it/s]
Epoch: [1/30], train loss: 0.008047
Epoch: [1/30], test accuracy: 0.431800, loss: 0.797698
Epoch: [2/30], Batch: [1/500], train accuracy: 0.480000, loss: 0.007946
Epoch: [2/30], Batch: [101/500], train accuracy: 0.360000, loss: 0.007998
Epoch: [2/30], Batch: [201/500], train accuracy: 0.470000, loss: 0.007937
Epoch: [2/30], Batch: [301/500], train accuracy: 0.510000, loss: 0.007817
Epoch: [2/30], Batch: [401/500], train accuracy: 0.400000, loss: 0.007882
100% 500/500 [02:45<00:00, 3.04it/s]
Epoch: [2/30], train loss: 0.007874
Epoch: [2/30], test accuracy: 0.468100, loss: 0.769648
Epoch: [3/30], Batch: [1/500], train accuracy: 0.480000, loss: 0.007770
Epoch: [3/30], Batch: [101/500], train accuracy: 0.500000, loss: 0.007449
Epoch: [3/30], Batch: [201/500], train accuracy: 0.490000, loss: 0.007445
Epoch: [3/30], Batch: [301/500], train accuracy: 0.410000, loss: 0.007163
Epoch: [3/30], Batch: [401/500], train accuracy: 0.450000, loss: 0.007121
100% 500/500 [02:44<00:00, 3.04it/s]
Epoch: [3/30], train loss: 0.007182
Epoch: [3/30], test accuracy: 0.521300, loss: 0.662147
Epoch: [4/30], Batch: [1/500], train accuracy: 0.470000, loss: 0.007082
Epoch: [4/30], Batch: [101/500], train accuracy: 0.560000, loss: 0.006161
Epoch: [4/30], Batch: [201/500], train accuracy: 0.560000, loss: 0.006386
Epoch: [4/30], Batch: [301/500], train accuracy: 0.590000, loss: 0.006173
Epoch: [4/30], Batch: [401/500], train accuracy: 0.560000, loss: 0.006173
100% 500/500 [02:44<00:00, 3.04it/s]
Epoch: [4/30], train loss: 0.006349
Epoch: [4/30], test accuracy: 0.555800, loss: 0.612919
Epoch: [5/30], Batch: [1/500], train accuracy: 0.590000, loss: 0.005984
Epoch: [5/30], Batch: [101/500], train accuracy: 0.540000, loss: 0.005862
Epoch: [5/30], Batch: [201/500], train accuracy: 0.560000, loss: 0.006026
Epoch: [5/30], Batch: [301/500], train accuracy: 0.580000, loss: 0.005553
Epoch: [5/30], Batch: [401/500], train accuracy: 0.680000, loss: 0.005457
100% 500/500 [02:44<00:00, 3.05it/s]
Epoch: [5/30], train loss: 0.005918
Epoch: [5/30], test accuracy: 0.590500, loss: 0.580702
Epoch: [6/30], Batch: [1/500], train accuracy: 0.660000, loss: 0.005525
Epoch: [6/30], Batch: [101/500], train accuracy: 0.580000, loss: 0.005722
Epoch: [6/30], Batch: [201/500], train accuracy: 0.610000, loss: 0.005729
Epoch: [6/30], Batch: [301/500], train accuracy: 0.580000, loss: 0.005752
Epoch: [6/30], Batch: [401/500], train accuracy: 0.570000, loss: 0.005795
100% 500/500 [02:44<00:00, 3.05it/s]
Epoch: [6/30], train loss: 0.005638
Epoch: [6/30], test accuracy: 0.602900, loss: 0.562709
Epoch: [7/30], Batch: [1/500], train accuracy: 0.640000, loss: 0.005054
Epoch: [7/30], Batch: [101/500], train accuracy: 0.630000, loss: 0.005274
Epoch: [7/30], Batch: [201/500], train accuracy: 0.640000, loss: 0.005245
Epoch: [7/30], Batch: [301/500], train accuracy: 0.600000, loss: 0.005418
Epoch: [7/30], Batch: [401/500], train accuracy: 0.630000, loss: 0.004710
100% 500/500 [02:44<00:00, 3.06it/s]
Epoch: [7/30], train loss: 0.005448
Epoch: [7/30], test accuracy: 0.616700, loss: 0.547133
Epoch: [8/30], Batch: [1/500], train accuracy: 0.650000, loss: 0.005194
Epoch: [8/30], Batch: [101/500], train accuracy: 0.690000, loss: 0.004807
Epoch: [8/30], Batch: [201/500], train accuracy: 0.690000, loss: 0.005423
Epoch: [8/30], Batch: [301/500], train accuracy: 0.640000, loss: 0.005231
Epoch: [8/30], Batch: [401/500], train accuracy: 0.670000, loss: 0.004982
100% 500/500 [02:44<00:00, 3.04it/s]
Epoch: [8/30], train loss: 0.005282
Epoch: [8/30], test accuracy: 0.632800, loss: 0.534200
Epoch: [9/30], Batch: [1/500], train accuracy: 0.640000, loss: 0.005729
Epoch: [9/30], Batch: [101/500], train accuracy: 0.700000, loss: 0.004558
Epoch: [9/30], Batch: [201/500], train accuracy: 0.640000, loss: 0.005404
Epoch: [9/30], Batch: [301/500], train accuracy: 0.670000, loss: 0.005204
Epoch: [9/30], Batch: [401/500], train accuracy: 0.600000, loss: 0.005491
100% 500/500 [02:44<00:00, 3.05it/s]
Epoch: [9/30], train loss: 0.005110
Epoch: [9/30], test accuracy: 0.640100, loss: 0.525246
Epoch: [10/30], Batch: [1/500], train accuracy: 0.700000, loss: 0.004635
Epoch: [10/30], Batch: [101/500], train accuracy: 0.670000, loss: 0.005026
Epoch: [10/30], Batch: [201/500], train accuracy: 0.710000, loss: 0.004482
Epoch: [10/30], Batch: [301/500], train accuracy: 0.730000, loss: 0.004045
Epoch: [10/30], Batch: [401/500], train accuracy: 0.640000, loss: 0.005618
100% 500/500 [02:44<00:00, 3.04it/s]
Epoch: [10/30], train loss: 0.005005
Epoch: [10/30], test accuracy: 0.656500, loss: 0.507344
Epoch: [11/30], Batch: [1/500], train accuracy: 0.640000, loss: 0.005273
Epoch: [11/30], Batch: [101/500], train accuracy: 0.640000, loss: 0.005570
Epoch: [11/30], Batch: [201/500], train accuracy: 0.750000, loss: 0.004569
Epoch: [11/30], Batch: [301/500], train accuracy: 0.640000, loss: 0.005356
Epoch: [11/30], Batch: [401/500], train accuracy: 0.670000, loss: 0.004885
100% 500/500 [02:44<00:00, 3.02it/s]
Epoch: [11/30], train loss: 0.004867
Epoch: [11/30], test accuracy: 0.659600, loss: 0.506003
Epoch: [12/30], Batch: [1/500], train accuracy: 0.680000, loss: 0.004995
Epoch: [12/30], Batch: [101/500], train accuracy: 0.650000, loss: 0.004921
Epoch: [12/30], Batch: [201/500], train accuracy: 0.650000, loss: 0.005072
Epoch: [12/30], Batch: [301/500], train accuracy: 0.680000, loss: 0.004890
Epoch: [12/30], Batch: [401/500], train accuracy: 0.600000, loss: 0.005777
100% 500/500 [02:44<00:00, 3.04it/s]
Epoch: [12/30], train loss: 0.004758
Epoch: [12/30], test accuracy: 0.669700, loss: 0.492968
Epoch: [13/30], Batch: [1/500], train accuracy: 0.650000, loss: 0.004795
Epoch: [13/30], Batch: [101/500], train accuracy: 0.730000, loss: 0.004316
Epoch: [13/30], Batch: [201/500], train accuracy: 0.720000, loss: 0.003964
Epoch: [13/30], Batch: [301/500], train accuracy: 0.760000, loss: 0.004180
Epoch: [13/30], Batch: [401/500], train accuracy: 0.710000, loss: 0.004485
100% 500/500 [02:44<00:00, 3.06it/s]
Epoch: [13/30], train loss: 0.004673
Epoch: [13/30], test accuracy: 0.672600, loss: 0.498016
Epoch: [14/30], Batch: [1/500], train accuracy: 0.700000, loss: 0.004716
Epoch: [14/30], Batch: [101/500], train accuracy: 0.720000, loss: 0.004677
Epoch: [14/30], Batch: [201/500], train accuracy: 0.720000, loss: 0.004923
Epoch: [14/30], Batch: [301/500], train accuracy: 0.720000, loss: 0.003978
Epoch: [14/30], Batch: [401/500], train accuracy: 0.760000, loss: 0.004141
100% 500/500 [02:44<00:00, 3.03it/s]
Epoch: [14/30], train loss: 0.004577
Epoch: [14/30], test accuracy: 0.675800, loss: 0.487264
Epoch: [15/30], Batch: [1/500], train accuracy: 0.700000, loss: 0.004650
Epoch: [15/30], Batch: [101/500], train accuracy: 0.790000, loss: 0.003771
Epoch: [15/30], Batch: [201/500], train accuracy: 0.690000, loss: 0.004529
Epoch: [15/30], Batch: [301/500], train accuracy: 0.660000, loss: 0.005128
Epoch: [15/30], Batch: [401/500], train accuracy: 0.730000, loss: 0.004389
100% 500/500 [02:44<00:00, 3.06it/s]
Epoch: [15/30], train loss: 0.004505
Epoch: [15/30], test accuracy: 0.684100, loss: 0.483410
Epoch: [16/30], Batch: [1/500], train accuracy: 0.630000, loss: 0.005254
Epoch: [16/30], Batch: [101/500], train accuracy: 0.770000, loss: 0.004265
Epoch: [16/30], Batch: [201/500], train accuracy: 0.710000, loss: 0.004419
Epoch: [16/30], Batch: [301/500], train accuracy: 0.690000, loss: 0.004336
Epoch: [16/30], Batch: [401/500], train accuracy: 0.740000, loss: 0.004540
100% 500/500 [02:44<00:00, 3.04it/s]
Epoch: [16/30], train loss: 0.004415
Epoch: [16/30], test accuracy: 0.683000, loss: 0.482916
Epoch: [17/30], Batch: [1/500], train accuracy: 0.740000, loss: 0.004360
Epoch: [17/30], Batch: [101/500], train accuracy: 0.630000, loss: 0.005027
Epoch: [17/30], Batch: [201/500], train accuracy: 0.720000, loss: 0.004651
Epoch: [17/30], Batch: [301/500], train accuracy: 0.690000, loss: 0.004591
Epoch: [17/30], Batch: [401/500], train accuracy: 0.800000, loss: 0.003930
100% 500/500 [02:44<00:00, 3.09it/s]
Epoch: [17/30], train loss: nan
Epoch: [17/30], test accuracy: 0.100000, loss: nan
Epoch: [18/30], Batch: [1/500], train accuracy: 0.050000, loss: nan
Epoch: [18/30], Batch: [101/500], train accuracy: 0.100000, loss: nan
Epoch: [18/30], Batch: [201/500], train accuracy: 0.080000, loss: nan
Epoch: [18/30], Batch: [301/500], train accuracy: 0.060000, loss: nan
Epoch: [18/30], Batch: [401/500], train accuracy: 0.040000, loss: nan
100% 500/500 [02:39<00:00, 3.15it/s]
Epoch: [18/30], train loss: nan
Epoch: [18/30], test accuracy: 0.100000, loss: nan
Epoch: [19/30], Batch: [1/500], train accuracy: 0.070000, loss: nan
Epoch: [19/30], Batch: [101/500], train accuracy: 0.130000, loss: nan
Epoch: [19/30], Batch: [201/500], train accuracy: 0.110000, loss: nan
Epoch: [19/30], Batch: [301/500], train accuracy: 0.110000, loss: nan
Epoch: [19/30], Batch: [401/500], train accuracy: 0.170000, loss: nan
100% 500/500 [02:39<00:00, 3.15it/s]
Epoch: [19/30], train loss: nan
Epoch: [19/30], test accuracy: 0.100000, loss: nan
Epoch: [20/30], Batch: [1/500], train accuracy: 0.080000, loss: nan
Epoch: [20/30], Batch: [101/500], train accuracy: 0.110000, loss: nan
Epoch: [20/30], Batch: [201/500], train accuracy: 0.160000, loss: nan
Epoch: [20/30], Batch: [301/500], train accuracy: 0.090000, loss: nan
Epoch: [20/30], Batch: [401/500], train accuracy: 0.080000, loss: nan
100% 500/500 [02:39<00:00, 3.15it/s]
Epoch: [20/30], train loss: nan
Epoch: [20/30], test accuracy: 0.100000, loss: nan
Epoch: [21/30], Batch: [1/500], train accuracy: 0.090000, loss: nan
Epoch: [21/30], Batch: [101/500], train accuracy: 0.110000, loss: nan
Epoch: [21/30], Batch: [201/500], train accuracy: 0.100000, loss: nan
Epoch: [21/30], Batch: [301/500], train accuracy: 0.100000, loss: nan
Epoch: [21/30], Batch: [401/500], train accuracy: 0.110000, loss: nan
100% 500/500 [02:39<00:00, 3.15it/s]
Epoch: [21/30], train loss: nan
Epoch: [21/30], test accuracy: 0.100000, loss: nan
Epoch: [22/30], Batch: [1/500], train accuracy: 0.080000, loss: nan
Epoch: [22/30], Batch: [101/500], train accuracy: 0.160000, loss: nan
Epoch: [22/30], Batch: [201/500], train accuracy: 0.110000, loss: nan
Epoch: [22/30], Batch: [301/500], train accuracy: 0.140000, loss: nan
Epoch: [22/30], Batch: [401/500], train accuracy: 0.100000, loss: nan
100% 500/500 [02:38<00:00, 3.16it/s]
Epoch: [22/30], train loss: nan
Epoch: [22/30], test accuracy: 0.100000, loss: nan
Epoch: [23/30], Batch: [1/500], train accuracy: 0.100000, loss: nan
Epoch: [23/30], Batch: [101/500], train accuracy: 0.080000, loss: nan
Epoch: [23/30], Batch: [201/500], train accuracy: 0.100000, loss: nan
Epoch: [23/30], Batch: [301/500], train accuracy: 0.090000, loss: nan
Epoch: [23/30], Batch: [401/500], train accuracy: 0.100000, loss: nan
100% 500/500 [02:38<00:00, 3.16it/s]
Epoch: [23/30], train loss: nan
Epoch: [23/30], test accuracy: 0.100000, loss: nan
Epoch: [24/30], Batch: [1/500], train accuracy: 0.070000, loss: nan
Epoch: [24/30], Batch: [101/500], train accuracy: 0.110000, loss: nan
Epoch: [24/30], Batch: [201/500], train accuracy: 0.080000, loss: nan
Epoch: [24/30], Batch: [301/500], train accuracy: 0.080000, loss: nan
Epoch: [24/30], Batch: [401/500], train accuracy: 0.110000, loss: nan
100% 500/500 [02:39<00:00, 3.14it/s]
Epoch: [24/30], train loss: nan
Epoch: [24/30], test accuracy: 0.100000, loss: nan
Epoch: [25/30], Batch: [1/500], train accuracy: 0.090000, loss: nan
Epoch: [25/30], Batch: [101/500], train accuracy: 0.070000, loss: nan
Epoch: [25/30], Batch: [201/500], train accuracy: 0.100000, loss: nan
Epoch: [25/30], Batch: [301/500], train accuracy: 0.110000, loss: nan
Epoch: [25/30], Batch: [401/500], train accuracy: 0.110000, loss: nan
100% 500/500 [02:39<00:00, 3.14it/s]
Epoch: [25/30], train loss: nan
Epoch: [25/30], test accuracy: 0.100000, loss: nan
Epoch: [26/30], Batch: [1/500], train accuracy: 0.130000, loss: nan
Epoch: [26/30], Batch: [101/500], train accuracy: 0.050000, loss: nan
Epoch: [26/30], Batch: [201/500], train accuracy: 0.070000, loss: nan
Epoch: [26/30], Batch: [301/500], train accuracy: 0.100000, loss: nan
Epoch: [26/30], Batch: [401/500], train accuracy: 0.120000, loss: nan
100% 500/500 [02:38<00:00, 3.16it/s]
Epoch: [26/30], train loss: nan
Epoch: [26/30], test accuracy: 0.100000, loss: nan
Epoch: [27/30], Batch: [1/500], train accuracy: 0.100000, loss: nan
Epoch: [27/30], Batch: [101/500], train accuracy: 0.090000, loss: nan
Epoch: [27/30], Batch: [201/500], train accuracy: 0.090000, loss: nan
Epoch: [27/30], Batch: [301/500], train accuracy: 0.050000, loss: nan
Epoch: [27/30], Batch: [401/500], train accuracy: 0.090000, loss: nan
100% 500/500 [02:39<00:00, 3.15it/s]
Epoch: [27/30], train loss: nan
Epoch: [27/30], test accuracy: 0.100000, loss: nan
Epoch: [28/30], Batch: [1/500], train accuracy: 0.100000, loss: nan
Epoch: [28/30], Batch: [101/500], train accuracy: 0.080000, loss: nan
Epoch: [28/30], Batch: [201/500], train accuracy: 0.080000, loss: nan
Epoch: [28/30], Batch: [301/500], train accuracy: 0.070000, loss: nan
Epoch: [28/30], Batch: [401/500], train accuracy: 0.100000, loss: nan
100% 500/500 [02:39<00:00, 3.15it/s]
Epoch: [28/30], train loss: nan
Epoch: [28/30], test accuracy: 0.100000, loss: nan
Epoch: [29/30], Batch: [1/500], train accuracy: 0.060000, loss: nan
Epoch: [29/30], Batch: [101/500], train accuracy: 0.090000, loss: nan
Epoch: [29/30], Batch: [201/500], train accuracy: 0.100000, loss: nan
Epoch: [29/30], Batch: [301/500], train accuracy: 0.100000, loss: nan
Epoch: [29/30], Batch: [401/500], train accuracy: 0.100000, loss: nan
100% 500/500 [02:39<00:00, 3.16it/s]
Epoch: [29/30], train loss: nan
Epoch: [29/30], test accuracy: 0.100000, loss: nan
Epoch: [30/30], Batch: [1/500], train accuracy: 0.130000, loss: nan
Epoch: [30/30], Batch: [101/500], train accuracy: 0.080000, loss: nan
Epoch: [30/30], Batch: [201/500], train accuracy: 0.080000, loss: nan
Epoch: [30/30], Batch: [301/500], train accuracy: 0.100000, loss: nan
Epoch: [30/30], Batch: [401/500], train accuracy: 0.110000, loss: nan
100% 500/500 [02:39<00:00, 3.11it/s]
Epoch: [30/30], train loss: nan
Epoch: [30/30], test accuracy: 0.100000, loss: nan