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accuracy_log.txt
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1042 lines (747 loc) · 19.2 KB
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;-*- mode: outline -*-
* ooh, 95%
!!
time ./nc
loaded from pickle
train
shape(features) = (34799, 32, 32, 3)
shape(labels) = (34799,)
valid
shape(features) = (4410, 32, 32, 3)
shape(labels) = (4410,)
test
shape(features) = (12630, 32, 32, 3)
shape(labels) = (12630,)
n_classes = 43
X is a <class 'int'>
shape(features) = (34799, 32, 32, 3)
shape(labels) = (34799,)
Number of training examples = 34799
Number of validation examples = 4410
Number of testing examples = 12630
Image data shape = (32,32)
Number of classes = 43
rate = 0.00095
mu = 0
sigma = 0.1
EPOCHS = 128
BATCH_SIZE = 64
GOOD_ENOUGH = 0.97
2018-11-29 14:51:11.155940: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2018-11-29 14:51:11.155961: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2018-11-29 14:51:11.155969: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2018-11-29 14:51:11.155994: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2018-11-29 14:51:11.156001: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
Training...
EPOCH 1 ...
Validation Accuracy = 0.806
EPOCH 2 ...
Validation Accuracy = 0.891
EPOCH 3 ...
Validation Accuracy = 0.883
EPOCH 4 ...
Validation Accuracy = 0.892
EPOCH 5 ...
Validation Accuracy = 0.900
EPOCH 6 ...
Validation Accuracy = 0.904
EPOCH 7 ...
Validation Accuracy = 0.886
EPOCH 8 ...
Validation Accuracy = 0.920
EPOCH 9 ...
Validation Accuracy = 0.918
EPOCH 10 ...
Validation Accuracy = 0.914
EPOCH 11 ...
Validation Accuracy = 0.916
EPOCH 12 ...
Validation Accuracy = 0.917
EPOCH 13 ...
Validation Accuracy = 0.913
EPOCH 14 ...
Validation Accuracy = 0.928
EPOCH 15 ...
Validation Accuracy = 0.936
EPOCH 16 ...
Validation Accuracy = 0.925
EPOCH 17 ...
Validation Accuracy = 0.910
EPOCH 18 ...
Validation Accuracy = 0.925
EPOCH 19 ...
Validation Accuracy = 0.933
EPOCH 20 ...
Validation Accuracy = 0.933
EPOCH 21 ...
Validation Accuracy = 0.906
EPOCH 22 ...
Validation Accuracy = 0.918
EPOCH 23 ...
Validation Accuracy = 0.926
EPOCH 24 ...
Validation Accuracy = 0.945
EPOCH 25 ...
Validation Accuracy = 0.930
EPOCH 26 ...
Validation Accuracy = 0.930
EPOCH 27 ...
Validation Accuracy = 0.941
EPOCH 28 ...
Validation Accuracy = 0.947
EPOCH 29 ...
Validation Accuracy = 0.924
EPOCH 30 ...
Validation Accuracy = 0.928
EPOCH 31 ...
Validation Accuracy = 0.932
EPOCH 32 ...
Validation Accuracy = 0.941
EPOCH 33 ...
Validation Accuracy = 0.944
EPOCH 34 ...
Validation Accuracy = 0.943
EPOCH 35 ...
Validation Accuracy = 0.944
EPOCH 36 ...
Validation Accuracy = 0.942
EPOCH 37 ...
Validation Accuracy = 0.945
EPOCH 38 ...
Validation Accuracy = 0.945
EPOCH 39 ...
Validation Accuracy = 0.944
EPOCH 40 ...
Validation Accuracy = 0.944
EPOCH 41 ...
Validation Accuracy = 0.946
EPOCH 42 ...
Validation Accuracy = 0.947
EPOCH 43 ...
Validation Accuracy = 0.946
EPOCH 44 ...
Validation Accuracy = 0.945
EPOCH 45 ...
Validation Accuracy = 0.915
EPOCH 46 ...
Validation Accuracy = 0.942
EPOCH 47 ...
Validation Accuracy = 0.943
EPOCH 48 ...
Validation Accuracy = 0.943
EPOCH 49 ...
Validation Accuracy = 0.927
EPOCH 50 ...
Validation Accuracy = 0.941
EPOCH 51 ...
Validation Accuracy = 0.932
EPOCH 52 ...
Validation Accuracy = 0.927
EPOCH 53 ...
Validation Accuracy = 0.951
EPOCH 54 ...
Validation Accuracy = 0.947
EPOCH 55 ...
Validation Accuracy = 0.937
EPOCH 56 ...
Validation Accuracy = 0.927
EPOCH 57 ...
Validation Accuracy = 0.936
EPOCH 58 ...
Validation Accuracy = 0.936
EPOCH 59 ...
Validation Accuracy = 0.927
EPOCH 60 ...
Validation Accuracy = 0.944
EPOCH 61 ...
Validation Accuracy = 0.947
EPOCH 62 ...
Validation Accuracy = 0.928
EPOCH 63 ...
Validation Accuracy = 0.950
EPOCH 64 ...
Validation Accuracy = 0.946
EPOCH 65 ...
Validation Accuracy = 0.941
EPOCH 66 ...
Validation Accuracy = 0.938
EPOCH 67 ...
Validation Accuracy = 0.936
EPOCH 68 ...
Validation Accuracy = 0.946
EPOCH 69 ...
Validation Accuracy = 0.933
EPOCH 70 ...
Validation Accuracy = 0.942
EPOCH 71 ...
Validation Accuracy = 0.915
EPOCH 72 ...
Validation Accuracy = 0.942
EPOCH 73 ...
Validation Accuracy = 0.932
EPOCH 74 ...
Validation Accuracy = 0.953
EPOCH 75 ...
Validation Accuracy = 0.931
EPOCH 76 ...
Validation Accuracy = 0.940
EPOCH 77 ...
Validation Accuracy = 0.942
EPOCH 78 ...
Validation Accuracy = 0.940
EPOCH 79 ...
Validation Accuracy = 0.940
EPOCH 80 ...
Validation Accuracy = 0.944
EPOCH 81 ...
Validation Accuracy = 0.937
EPOCH 82 ...
Validation Accuracy = 0.933
EPOCH 83 ...
Validation Accuracy = 0.955
EPOCH 84 ...
Validation Accuracy = 0.948
EPOCH 85 ...
Validation Accuracy = 0.949
EPOCH 86 ...
Validation Accuracy = 0.937
EPOCH 87 ...
Validation Accuracy = 0.941
EPOCH 88 ...
Validation Accuracy = 0.931
EPOCH 89 ...
Validation Accuracy = 0.940
EPOCH 90 ...
Validation Accuracy = 0.951
EPOCH 91 ...
Validation Accuracy = 0.933
EPOCH 92 ...
Validation Accuracy = 0.947
EPOCH 93 ...
Validation Accuracy = 0.945
EPOCH 94 ...
Validation Accuracy = 0.937
EPOCH 95 ...
Validation Accuracy = 0.953
EPOCH 96 ...
Validation Accuracy = 0.949
EPOCH 97 ...
Validation Accuracy = 0.949
EPOCH 98 ...
Validation Accuracy = 0.945
EPOCH 99 ...
Validation Accuracy = 0.942
EPOCH 100 ...
Validation Accuracy = 0.945
EPOCH 101 ...
Validation Accuracy = 0.941
EPOCH 102 ...
Validation Accuracy = 0.947
EPOCH 103 ...
Validation Accuracy = 0.943
EPOCH 104 ...
Validation Accuracy = 0.937
EPOCH 105 ...
Validation Accuracy = 0.939
EPOCH 106 ...
Validation Accuracy = 0.955
EPOCH 107 ...
Validation Accuracy = 0.936
EPOCH 108 ...
Validation Accuracy = 0.954
EPOCH 109 ...
Validation Accuracy = 0.948
EPOCH 110 ...
Validation Accuracy = 0.947
EPOCH 111 ...
Validation Accuracy = 0.944
EPOCH 112 ...
Validation Accuracy = 0.956
EPOCH 113 ...
Validation Accuracy = 0.938
EPOCH 114 ...
Validation Accuracy = 0.947
EPOCH 115 ...
Validation Accuracy = 0.934
EPOCH 116 ...
Validation Accuracy = 0.946
EPOCH 117 ...
Validation Accuracy = 0.949
EPOCH 118 ...
Validation Accuracy = 0.956
EPOCH 119 ...
Validation Accuracy = 0.942
EPOCH 120 ...
Validation Accuracy = 0.956
EPOCH 121 ...
Validation Accuracy = 0.951
EPOCH 122 ...
Validation Accuracy = 0.944
EPOCH 123 ...
Validation Accuracy = 0.950
EPOCH 124 ...
Validation Accuracy = 0.931
EPOCH 125 ...
Validation Accuracy = 0.941
EPOCH 126 ...
Validation Accuracy = 0.956
EPOCH 127 ...
Validation Accuracy = 0.940
EPOCH 128 ...
Validation Accuracy = 0.950
Model saved
Test Accuracy = 0.928
real 32m0.818s
user 113m16.202s
sys 18m6.100s
* normalization on, 64 epocs, 93.3%
time ./nc
loaded from pickle
train
shape(features) = (34799, 32, 32, 3)
shape(labels) = (34799,)
valid
shape(features) = (4410, 32, 32, 3)
shape(labels) = (4410,)
test
shape(features) = (12630, 32, 32, 3)
shape(labels) = (12630,)
n_classes = 43
X is a <class 'int'>
shape(features) = (34799, 32, 32, 3)
shape(labels) = (34799,)
Number of training examples = 34799
Number of validation examples = 4410
Number of testing examples = 12630
Image data shape = (32,32)
Number of classes = 43
rate = 0.00095
mu = 0
sigma = 0.1
EPOCHS = 64
BATCH_SIZE = 128
GOOD_ENOUGH = 0.97
2018-11-29 11:08:57.679644: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2018-11-29 11:08:57.679664: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2018-11-29 11:08:57.679691: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2018-11-29 11:08:57.679698: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2018-11-29 11:08:57.679704: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
Training...
EPOCH 1 ...
Validation Accuracy = 0.729
EPOCH 2 ...
Validation Accuracy = 0.827
EPOCH 3 ...
Validation Accuracy = 0.859
EPOCH 4 ...
Validation Accuracy = 0.866
EPOCH 5 ...
Validation Accuracy = 0.895
EPOCH 6 ...
Validation Accuracy = 0.893
EPOCH 7 ...
Validation Accuracy = 0.909
EPOCH 8 ...
Validation Accuracy = 0.894
EPOCH 9 ...
Validation Accuracy = 0.906
EPOCH 10 ...
Validation Accuracy = 0.912
EPOCH 11 ...
Validation Accuracy = 0.905
EPOCH 12 ...
Validation Accuracy = 0.909
EPOCH 13 ...
Validation Accuracy = 0.921
EPOCH 14 ...
Validation Accuracy = 0.915
EPOCH 15 ...
Validation Accuracy = 0.893
EPOCH 16 ...
Validation Accuracy = 0.922
EPOCH 17 ...
Validation Accuracy = 0.907
EPOCH 18 ...
Validation Accuracy = 0.928
EPOCH 19 ...
Validation Accuracy = 0.929
EPOCH 20 ...
Validation Accuracy = 0.896
EPOCH 21 ...
Validation Accuracy = 0.918
EPOCH 22 ...
Validation Accuracy = 0.922
EPOCH 23 ...
Validation Accuracy = 0.924
EPOCH 24 ...
Validation Accuracy = 0.920
EPOCH 25 ...
Validation Accuracy = 0.927
EPOCH 26 ...
Validation Accuracy = 0.917
EPOCH 27 ...
Validation Accuracy = 0.924
EPOCH 28 ...
Validation Accuracy = 0.919
EPOCH 29 ...
Validation Accuracy = 0.920
EPOCH 30 ...
Validation Accuracy = 0.933
EPOCH 31 ...
Validation Accuracy = 0.936
EPOCH 32 ...
Validation Accuracy = 0.936
EPOCH 33 ...
Validation Accuracy = 0.905
EPOCH 34 ...
Validation Accuracy = 0.924
EPOCH 35 ...
Validation Accuracy = 0.934
EPOCH 36 ...
Validation Accuracy = 0.930
EPOCH 37 ...
Validation Accuracy = 0.938
EPOCH 38 ...
Validation Accuracy = 0.940
EPOCH 39 ...
Validation Accuracy = 0.931
EPOCH 40 ...
Validation Accuracy = 0.937
EPOCH 41 ...
Validation Accuracy = 0.929
EPOCH 42 ...
Validation Accuracy = 0.938
EPOCH 43 ...
Validation Accuracy = 0.930
EPOCH 44 ...
Validation Accuracy = 0.932
EPOCH 45 ...
Validation Accuracy = 0.938
EPOCH 46 ...
Validation Accuracy = 0.942
EPOCH 47 ...
Validation Accuracy = 0.941
EPOCH 48 ...
Validation Accuracy = 0.942
EPOCH 49 ...
Validation Accuracy = 0.942
EPOCH 50 ...
Validation Accuracy = 0.942
EPOCH 51 ...
Validation Accuracy = 0.941
EPOCH 52 ...
Validation Accuracy = 0.942
EPOCH 53 ...
Validation Accuracy = 0.942
EPOCH 54 ...
Validation Accuracy = 0.941
EPOCH 55 ...
Validation Accuracy = 0.941
EPOCH 56 ...
Validation Accuracy = 0.941
EPOCH 57 ...
Validation Accuracy = 0.941
EPOCH 58 ...
Validation Accuracy = 0.940
EPOCH 59 ...
Validation Accuracy = 0.939
EPOCH 60 ...
Validation Accuracy = 0.940
EPOCH 61 ...
Validation Accuracy = 0.940
EPOCH 62 ...
Validation Accuracy = 0.940
EPOCH 63 ...
Validation Accuracy = 0.940
EPOCH 64 ...
Validation Accuracy = 0.939
Model saved
Test Accuracy = 0.933
real 15m25.197s
user 56m50.943s
sys 8m50.848s
* 11/29/18 @ 1035, normalization ON, .942 after 27 epochs
!!
time ./nc
loaded from pickle
train
shape(features) = (34799, 32, 32, 3)
shape(labels) = (34799,)
valid
shape(features) = (4410, 32, 32, 3)
shape(labels) = (4410,)
test
shape(features) = (12630, 32, 32, 3)
shape(labels) = (12630,)
n_classes = 43
X is a <class 'int'>
shape(features) = (34799, 32, 32, 3)
shape(labels) = (34799,)
Number of training examples = 34799
Number of validation examples = 4410
Number of testing examples = 12630
Image data shape = (32,32)
Number of classes = 43
rate = 0.00095
mu = 0
sigma = 0.1
EPOCHS = 64
BATCH_SIZE = 64
GOOD_ENOUGH = 0.94
2018-11-29 09:16:24.012491: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2018-11-29 09:16:24.012517: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2018-11-29 09:16:24.012542: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2018-11-29 09:16:24.012548: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2018-11-29 09:16:24.012554: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
Training...
EPOCH 1 ...
Validation Accuracy = 0.795
EPOCH 2 ...
Validation Accuracy = 0.880
EPOCH 3 ...
Validation Accuracy = 0.890
EPOCH 4 ...
Validation Accuracy = 0.891
EPOCH 5 ...
Validation Accuracy = 0.904
EPOCH 6 ...
Validation Accuracy = 0.895
EPOCH 7 ...
Validation Accuracy = 0.917
EPOCH 8 ...
Validation Accuracy = 0.893
EPOCH 9 ...
Validation Accuracy = 0.905
EPOCH 10 ...
Validation Accuracy = 0.932
EPOCH 11 ...
Validation Accuracy = 0.927
EPOCH 12 ...
Validation Accuracy = 0.913
EPOCH 13 ...
Validation Accuracy = 0.879
EPOCH 14 ...
Validation Accuracy = 0.912
EPOCH 15 ...
Validation Accuracy = 0.924
EPOCH 16 ...
Validation Accuracy = 0.933
EPOCH 17 ...
Validation Accuracy = 0.925
EPOCH 18 ...
Validation Accuracy = 0.940
EPOCH 19 ...
Validation Accuracy = 0.927
EPOCH 20 ...
Validation Accuracy = 0.936
EPOCH 21 ...
Validation Accuracy = 0.917
EPOCH 22 ...
Validation Accuracy = 0.926
EPOCH 23 ...
Validation Accuracy = 0.922
EPOCH 24 ...
Validation Accuracy = 0.919
EPOCH 25 ...
Validation Accuracy = 0.930
EPOCH 26 ...
Validation Accuracy = 0.937
EPOCH 27 ...
Validation Accuracy = 0.942
better than good enough
Model saved
Test Accuracy = 0.935
real 6m53.338s
user 24m9.036s
sys 3m48.446s
* .933: no normalization
!!
time ./nc
loaded from pickle
train
shape(features) = (34799, 32, 32, 3)
shape(labels) = (34799,)
valid
shape(features) = (4410, 32, 32, 3)
shape(labels) = (4410,)
test
shape(features) = (12630, 32, 32, 3)
shape(labels) = (12630,)
n_classes = 43
X is a <class 'int'>
shape(features) = (34799, 32, 32, 3)
shape(labels) = (34799,)
Number of training examples = 34799
Number of validation examples = 4410
Number of testing examples = 12630
Image data shape = (32,32)
Number of classes = 43
rate = 0.00095
mu = 0
sigma = 0.1
EPOCHS = 64
BATCH_SIZE = 64
GOOD_ENOUGH = 0.94
2018-11-29 08:52:55.104304: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2018-11-29 08:52:55.104324: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2018-11-29 08:52:55.104347: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2018-11-29 08:52:55.104353: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2018-11-29 08:52:55.104380: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
Training...
EPOCH 1 ...
Validation Accuracy = 0.725
EPOCH 2 ...
Validation Accuracy = 0.822
EPOCH 3 ...
Validation Accuracy = 0.855
EPOCH 4 ...
Validation Accuracy = 0.867
EPOCH 5 ...
Validation Accuracy = 0.872
EPOCH 6 ...
Validation Accuracy = 0.894
EPOCH 7 ...
Validation Accuracy = 0.883
EPOCH 8 ...
Validation Accuracy = 0.876
EPOCH 9 ...
Validation Accuracy = 0.885
EPOCH 10 ...
Validation Accuracy = 0.902
EPOCH 11 ...
Validation Accuracy = 0.901
EPOCH 12 ...
Validation Accuracy = 0.888
EPOCH 13 ...
Validation Accuracy = 0.885
EPOCH 14 ...
Validation Accuracy = 0.905
EPOCH 15 ...
Validation Accuracy = 0.894
EPOCH 16 ...
Validation Accuracy = 0.897
EPOCH 17 ...
Validation Accuracy = 0.903
EPOCH 18 ...
Validation Accuracy = 0.911
EPOCH 19 ...
Validation Accuracy = 0.915
EPOCH 20 ...
Validation Accuracy = 0.930
EPOCH 21 ...
Validation Accuracy = 0.875
EPOCH 22 ...
Validation Accuracy = 0.914
EPOCH 23 ...
Validation Accuracy = 0.891
EPOCH 24 ...
Validation Accuracy = 0.907
EPOCH 25 ...
Validation Accuracy = 0.911
EPOCH 26 ...
Validation Accuracy = 0.890
EPOCH 27 ...
Validation Accuracy = 0.898
EPOCH 28 ...
Validation Accuracy = 0.881
EPOCH 29 ...
Validation Accuracy = 0.901
EPOCH 30 ...
Validation Accuracy = 0.906
EPOCH 31 ...
Validation Accuracy = 0.915
EPOCH 32 ...
Validation Accuracy = 0.885
EPOCH 33 ...
Validation Accuracy = 0.909
EPOCH 34 ...
Validation Accuracy = 0.920
EPOCH 35 ...
Validation Accuracy = 0.902
EPOCH 36 ...
Validation Accuracy = 0.910
EPOCH 37 ...
Validation Accuracy = 0.930
EPOCH 38 ...
Validation Accuracy = 0.918
EPOCH 39 ...
Validation Accuracy = 0.922
EPOCH 40 ...
Validation Accuracy = 0.929
EPOCH 41 ...
Validation Accuracy = 0.928
EPOCH 42 ...
Validation Accuracy = 0.909
EPOCH 43 ...
Validation Accuracy = 0.912
EPOCH 44 ...
Validation Accuracy = 0.920
EPOCH 45 ...
Validation Accuracy = 0.892
EPOCH 46 ...
Validation Accuracy = 0.917
EPOCH 47 ...
Validation Accuracy = 0.917
EPOCH 48 ...
Validation Accuracy = 0.908
EPOCH 49 ...
Validation Accuracy = 0.898
EPOCH 50 ...
Validation Accuracy = 0.914
EPOCH 51 ...
Validation Accuracy = 0.914
EPOCH 52 ...
Validation Accuracy = 0.915
EPOCH 53 ...
Validation Accuracy = 0.893
EPOCH 54 ...
Validation Accuracy = 0.910
EPOCH 55 ...
Validation Accuracy = 0.916
EPOCH 56 ...
Validation Accuracy = 0.925
EPOCH 57 ...
Validation Accuracy = 0.919
EPOCH 58 ...
Validation Accuracy = 0.915
EPOCH 59 ...
Validation Accuracy = 0.918
EPOCH 60 ...
Validation Accuracy = 0.915
EPOCH 61 ...
Validation Accuracy = 0.898
EPOCH 62 ...