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log_wrn16x8.txt
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log_wrn16x8.txt
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got the python script
=============== RUN 1562805 ===============
Running ...
Namespace(alpha=2.0, batch_size=128, data_dir='/srv/tempdd/svenkata/Datasets/data', dataset='cifar100', decay=0.0001, epochs=2000, gammas=[0.1, 0.1, 0.1], lr_=0.1, manualSeed=None, momentum=0.9, network='wideresnet', ngpu=1, num_classes=100, resume='', save_dir='/nfs/pyrex/raid6/svenkata/weights/AlignMixup_CVPR22/cifar100/', schedule=[500, 1000, 1500], start_epoch=0, workers=8)
Files already downloaded and verified
Files already downloaded and verified
| Wide-Resnet 16x8
DataParallel(
(module): WideResNet_classifier(
(encoder): Wide_ResNet(
(conv1): Conv2d(3, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(layer1): Sequential(
(0): wide_basic(
(bn1): BatchNorm2d(16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv1): Conv2d(16, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(shortcut): Sequential(
(0): Conv2d(16, 128, kernel_size=(1, 1), stride=(1, 1))
)
)
(1): wide_basic(
(bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv1): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(shortcut): Sequential()
)
)
(layer2): Sequential(
(0): wide_basic(
(bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv1): Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))
(shortcut): Sequential(
(0): Conv2d(128, 256, kernel_size=(1, 1), stride=(2, 2))
)
)
(1): wide_basic(
(bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv1): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(shortcut): Sequential()
)
)
(layer3): Sequential(
(0): wide_basic(
(bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv1): Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))
(shortcut): Sequential(
(0): Conv2d(256, 512, kernel_size=(1, 1), stride=(2, 2))
)
)
(1): wide_basic(
(bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv1): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(shortcut): Sequential()
)
)
(bn1): BatchNorm2d(512, eps=1e-05, momentum=0.9, affine=True, track_running_stats=True)
)
(classifier): Linear(in_features=512, out_features=100, bias=True)
)
)
epoch: 0 --> Train loss = 0.0336 Train Accuracy = 4.3980
------> epoch: 0 --> Test loss = 0.0302 Test Accuracy = 9.5600
Saving..
epoch: 1 --> Train loss = 0.0314 Train Accuracy = 7.3180
------> epoch: 1 --> Test loss = 0.0275 Test Accuracy = 15.7800
Saving..
epoch: 2 --> Train loss = 0.0293 Train Accuracy = 11.3000
------> epoch: 2 --> Test loss = 0.0242 Test Accuracy = 24.1300
Saving..
epoch: 3 --> Train loss = 0.0278 Train Accuracy = 14.0820
------> epoch: 3 --> Test loss = 0.0219 Test Accuracy = 29.1000
Saving..
epoch: 4 --> Train loss = 0.0264 Train Accuracy = 17.2920
------> epoch: 4 --> Test loss = 0.0237 Test Accuracy = 26.6200
epoch: 5 --> Train loss = 0.0255 Train Accuracy = 20.3720
------> epoch: 5 --> Test loss = 0.0178 Test Accuracy = 41.1800
Saving..
epoch: 6 --> Train loss = 0.0245 Train Accuracy = 20.4380
------> epoch: 6 --> Test loss = 0.0173 Test Accuracy = 42.8200
Saving..
epoch: 7 --> Train loss = 0.0237 Train Accuracy = 22.9040
------> epoch: 7 --> Test loss = 0.0161 Test Accuracy = 46.1300
Saving..
epoch: 8 --> Train loss = 0.0233 Train Accuracy = 25.0520
------> epoch: 8 --> Test loss = 0.0148 Test Accuracy = 49.7700
Saving..
epoch: 9 --> Train loss = 0.0228 Train Accuracy = 24.2180
------> epoch: 9 --> Test loss = 0.0164 Test Accuracy = 45.9400
epoch: 10 --> Train loss = 0.0223 Train Accuracy = 26.7580
------> epoch: 10 --> Test loss = 0.0141 Test Accuracy = 52.5900
Saving..
epoch: 11 --> Train loss = 0.0220 Train Accuracy = 26.3540
------> epoch: 11 --> Test loss = 0.0131 Test Accuracy = 54.6300
Saving..
epoch: 12 --> Train loss = 0.0213 Train Accuracy = 29.7900
------> epoch: 12 --> Test loss = 0.0125 Test Accuracy = 57.3100
Saving..
epoch: 13 --> Train loss = 0.0212 Train Accuracy = 27.5940
------> epoch: 13 --> Test loss = 0.0130 Test Accuracy = 55.2000
epoch: 14 --> Train loss = 0.0211 Train Accuracy = 29.7680
------> epoch: 14 --> Test loss = 0.0115 Test Accuracy = 60.0800
Saving..
epoch: 15 --> Train loss = 0.0207 Train Accuracy = 31.4640
------> epoch: 15 --> Test loss = 0.0130 Test Accuracy = 56.4500
epoch: 16 --> Train loss = 0.0202 Train Accuracy = 30.2620
------> epoch: 16 --> Test loss = 0.0116 Test Accuracy = 59.6500
epoch: 17 --> Train loss = 0.0202 Train Accuracy = 33.8300
------> epoch: 17 --> Test loss = 0.0114 Test Accuracy = 60.5700
Saving..
epoch: 18 --> Train loss = 0.0200 Train Accuracy = 31.3520
------> epoch: 18 --> Test loss = 0.0123 Test Accuracy = 58.3900
epoch: 19 --> Train loss = 0.0194 Train Accuracy = 31.0660
------> epoch: 19 --> Test loss = 0.0125 Test Accuracy = 59.0400
epoch: 20 --> Train loss = 0.0196 Train Accuracy = 34.3760
------> epoch: 20 --> Test loss = 0.0110 Test Accuracy = 63.1000
Saving..
epoch: 21 --> Train loss = 0.0193 Train Accuracy = 35.5580
------> epoch: 21 --> Test loss = 0.0110 Test Accuracy = 63.4800
Saving..
epoch: 22 --> Train loss = 0.0193 Train Accuracy = 34.3700
------> epoch: 22 --> Test loss = 0.0118 Test Accuracy = 61.0600
epoch: 23 --> Train loss = 0.0186 Train Accuracy = 34.8480
------> epoch: 23 --> Test loss = 0.0103 Test Accuracy = 64.1900
Saving..
epoch: 24 --> Train loss = 0.0189 Train Accuracy = 35.6320
------> epoch: 24 --> Test loss = 0.0108 Test Accuracy = 63.9600
epoch: 25 --> Train loss = 0.0188 Train Accuracy = 35.7160
------> epoch: 25 --> Test loss = 0.0105 Test Accuracy = 64.0500
epoch: 26 --> Train loss = 0.0184 Train Accuracy = 36.0480
------> epoch: 26 --> Test loss = 0.0128 Test Accuracy = 58.5500
epoch: 27 --> Train loss = 0.0188 Train Accuracy = 35.1140
------> epoch: 27 --> Test loss = 0.0098 Test Accuracy = 66.2800
Saving..
epoch: 28 --> Train loss = 0.0185 Train Accuracy = 35.2860
------> epoch: 28 --> Test loss = 0.0112 Test Accuracy = 62.7000
epoch: 29 --> Train loss = 0.0182 Train Accuracy = 36.9000
------> epoch: 29 --> Test loss = 0.0109 Test Accuracy = 63.3600
epoch: 30 --> Train loss = 0.0181 Train Accuracy = 35.2800
------> epoch: 30 --> Test loss = 0.0113 Test Accuracy = 62.7400
epoch: 31 --> Train loss = 0.0183 Train Accuracy = 37.9540
------> epoch: 31 --> Test loss = 0.0103 Test Accuracy = 65.7700
epoch: 32 --> Train loss = 0.0179 Train Accuracy = 36.4720
------> epoch: 32 --> Test loss = 0.0113 Test Accuracy = 62.5800
epoch: 33 --> Train loss = 0.0180 Train Accuracy = 37.2260
------> epoch: 33 --> Test loss = 0.0097 Test Accuracy = 67.0000
Saving..
epoch: 34 --> Train loss = 0.0180 Train Accuracy = 36.5500
------> epoch: 34 --> Test loss = 0.0105 Test Accuracy = 64.6800
epoch: 35 --> Train loss = 0.0178 Train Accuracy = 38.5260
------> epoch: 35 --> Test loss = 0.0101 Test Accuracy = 65.5200
epoch: 36 --> Train loss = 0.0175 Train Accuracy = 38.1940
------> epoch: 36 --> Test loss = 0.0102 Test Accuracy = 66.1100
epoch: 37 --> Train loss = 0.0178 Train Accuracy = 38.0460
------> epoch: 37 --> Test loss = 0.0104 Test Accuracy = 65.7000
epoch: 38 --> Train loss = 0.0172 Train Accuracy = 37.4180
------> epoch: 38 --> Test loss = 0.0099 Test Accuracy = 66.2200
epoch: 39 --> Train loss = 0.0172 Train Accuracy = 38.6280
------> epoch: 39 --> Test loss = 0.0101 Test Accuracy = 66.5600
epoch: 40 --> Train loss = 0.0174 Train Accuracy = 40.1160
------> epoch: 40 --> Test loss = 0.0097 Test Accuracy = 67.0700
Saving..
epoch: 41 --> Train loss = 0.0173 Train Accuracy = 40.3360
------> epoch: 41 --> Test loss = 0.0096 Test Accuracy = 67.4300
Saving..
epoch: 42 --> Train loss = 0.0171 Train Accuracy = 40.1140
------> epoch: 42 --> Test loss = 0.0097 Test Accuracy = 66.1200
epoch: 43 --> Train loss = 0.0173 Train Accuracy = 36.3680
------> epoch: 43 --> Test loss = 0.0096 Test Accuracy = 66.3600
epoch: 44 --> Train loss = 0.0171 Train Accuracy = 39.5880
------> epoch: 44 --> Test loss = 0.0097 Test Accuracy = 67.1900
epoch: 45 --> Train loss = 0.0171 Train Accuracy = 38.7360
------> epoch: 45 --> Test loss = 0.0099 Test Accuracy = 67.0300
epoch: 46 --> Train loss = 0.0173 Train Accuracy = 35.6460
------> epoch: 46 --> Test loss = 0.0108 Test Accuracy = 65.0000
epoch: 47 --> Train loss = 0.0170 Train Accuracy = 41.7520
------> epoch: 47 --> Test loss = 0.0096 Test Accuracy = 67.8300
Saving..
epoch: 48 --> Train loss = 0.0167 Train Accuracy = 41.4180
------> epoch: 48 --> Test loss = 0.0104 Test Accuracy = 66.4900
epoch: 49 --> Train loss = 0.0170 Train Accuracy = 38.2780
------> epoch: 49 --> Test loss = 0.0102 Test Accuracy = 66.7100
epoch: 50 --> Train loss = 0.0169 Train Accuracy = 41.6000
------> epoch: 50 --> Test loss = 0.0093 Test Accuracy = 68.3200
Saving..
epoch: 51 --> Train loss = 0.0170 Train Accuracy = 39.4440
------> epoch: 51 --> Test loss = 0.0091 Test Accuracy = 69.0700
Saving..
epoch: 52 --> Train loss = 0.0168 Train Accuracy = 43.0720
------> epoch: 52 --> Test loss = 0.0092 Test Accuracy = 68.1400
epoch: 53 --> Train loss = 0.0166 Train Accuracy = 40.6300
------> epoch: 53 --> Test loss = 0.0087 Test Accuracy = 69.5500
Saving..
epoch: 54 --> Train loss = 0.0168 Train Accuracy = 41.4460
------> epoch: 54 --> Test loss = 0.0101 Test Accuracy = 65.9200
epoch: 55 --> Train loss = 0.0163 Train Accuracy = 39.5720
------> epoch: 55 --> Test loss = 0.0104 Test Accuracy = 65.4800
epoch: 56 --> Train loss = 0.0167 Train Accuracy = 37.7740
------> epoch: 56 --> Test loss = 0.0099 Test Accuracy = 66.4100
epoch: 57 --> Train loss = 0.0164 Train Accuracy = 42.3220
------> epoch: 57 --> Test loss = 0.0097 Test Accuracy = 67.4200
epoch: 58 --> Train loss = 0.0168 Train Accuracy = 41.1220
------> epoch: 58 --> Test loss = 0.0097 Test Accuracy = 67.7400
epoch: 59 --> Train loss = 0.0163 Train Accuracy = 39.1720
------> epoch: 59 --> Test loss = 0.0092 Test Accuracy = 69.1300
epoch: 60 --> Train loss = 0.0167 Train Accuracy = 41.4120
------> epoch: 60 --> Test loss = 0.0098 Test Accuracy = 66.8800
epoch: 61 --> Train loss = 0.0165 Train Accuracy = 40.3100
------> epoch: 61 --> Test loss = 0.0091 Test Accuracy = 68.4500
epoch: 62 --> Train loss = 0.0167 Train Accuracy = 38.2400
------> epoch: 62 --> Test loss = 0.0091 Test Accuracy = 68.7400
epoch: 63 --> Train loss = 0.0162 Train Accuracy = 44.2940
------> epoch: 63 --> Test loss = 0.0100 Test Accuracy = 67.3500
epoch: 64 --> Train loss = 0.0161 Train Accuracy = 42.7280
------> epoch: 64 --> Test loss = 0.0103 Test Accuracy = 66.5100
epoch: 65 --> Train loss = 0.0165 Train Accuracy = 39.3420
------> epoch: 65 --> Test loss = 0.0094 Test Accuracy = 68.7900
epoch: 66 --> Train loss = 0.0167 Train Accuracy = 41.4260
------> epoch: 66 --> Test loss = 0.0097 Test Accuracy = 67.3400
epoch: 67 --> Train loss = 0.0166 Train Accuracy = 42.9020
------> epoch: 67 --> Test loss = 0.0093 Test Accuracy = 68.9500
epoch: 68 --> Train loss = 0.0161 Train Accuracy = 42.8040
------> epoch: 68 --> Test loss = 0.0099 Test Accuracy = 67.7000
epoch: 69 --> Train loss = 0.0163 Train Accuracy = 41.2440
------> epoch: 69 --> Test loss = 0.0095 Test Accuracy = 68.5000
epoch: 70 --> Train loss = 0.0165 Train Accuracy = 40.3420
------> epoch: 70 --> Test loss = 0.0098 Test Accuracy = 67.7200
epoch: 71 --> Train loss = 0.0162 Train Accuracy = 38.8400
------> epoch: 71 --> Test loss = 0.0100 Test Accuracy = 67.6600
epoch: 72 --> Train loss = 0.0163 Train Accuracy = 41.3480
------> epoch: 72 --> Test loss = 0.0091 Test Accuracy = 69.2500
epoch: 73 --> Train loss = 0.0164 Train Accuracy = 42.5840
------> epoch: 73 --> Test loss = 0.0105 Test Accuracy = 67.0500
epoch: 74 --> Train loss = 0.0161 Train Accuracy = 41.3360
------> epoch: 74 --> Test loss = 0.0102 Test Accuracy = 66.9500
epoch: 75 --> Train loss = 0.0166 Train Accuracy = 39.9800
------> epoch: 75 --> Test loss = 0.0098 Test Accuracy = 67.1700
epoch: 76 --> Train loss = 0.0161 Train Accuracy = 40.5800
------> epoch: 76 --> Test loss = 0.0094 Test Accuracy = 69.1100
epoch: 77 --> Train loss = 0.0159 Train Accuracy = 43.1480
------> epoch: 77 --> Test loss = 0.0094 Test Accuracy = 69.1900
epoch: 78 --> Train loss = 0.0161 Train Accuracy = 43.6140
------> epoch: 78 --> Test loss = 0.0097 Test Accuracy = 67.8200
epoch: 79 --> Train loss = 0.0160 Train Accuracy = 41.8880
------> epoch: 79 --> Test loss = 0.0092 Test Accuracy = 69.2900
epoch: 80 --> Train loss = 0.0157 Train Accuracy = 45.9840
------> epoch: 80 --> Test loss = 0.0104 Test Accuracy = 66.6100
epoch: 81 --> Train loss = 0.0164 Train Accuracy = 43.2280
------> epoch: 81 --> Test loss = 0.0100 Test Accuracy = 67.1200
epoch: 82 --> Train loss = 0.0161 Train Accuracy = 42.6460
------> epoch: 82 --> Test loss = 0.0089 Test Accuracy = 69.9900
Saving..
epoch: 83 --> Train loss = 0.0161 Train Accuracy = 43.3600
------> epoch: 83 --> Test loss = 0.0097 Test Accuracy = 67.6900
epoch: 84 --> Train loss = 0.0162 Train Accuracy = 42.2160
------> epoch: 84 --> Test loss = 0.0092 Test Accuracy = 68.9200
epoch: 85 --> Train loss = 0.0159 Train Accuracy = 39.9040
------> epoch: 85 --> Test loss = 0.0095 Test Accuracy = 69.1000
epoch: 86 --> Train loss = 0.0155 Train Accuracy = 43.0880
------> epoch: 86 --> Test loss = 0.0099 Test Accuracy = 67.3100
epoch: 87 --> Train loss = 0.0159 Train Accuracy = 41.2220
------> epoch: 87 --> Test loss = 0.0105 Test Accuracy = 65.4900
epoch: 88 --> Train loss = 0.0158 Train Accuracy = 42.6400
------> epoch: 88 --> Test loss = 0.0104 Test Accuracy = 66.8000
epoch: 89 --> Train loss = 0.0157 Train Accuracy = 44.4260
------> epoch: 89 --> Test loss = 0.0108 Test Accuracy = 65.2900
epoch: 90 --> Train loss = 0.0157 Train Accuracy = 42.0860
------> epoch: 90 --> Test loss = 0.0090 Test Accuracy = 69.5000
epoch: 91 --> Train loss = 0.0157 Train Accuracy = 42.2660
------> epoch: 91 --> Test loss = 0.0097 Test Accuracy = 68.3800
epoch: 92 --> Train loss = 0.0156 Train Accuracy = 42.0380
------> epoch: 92 --> Test loss = 0.0091 Test Accuracy = 69.4400
epoch: 93 --> Train loss = 0.0157 Train Accuracy = 41.0460
------> epoch: 93 --> Test loss = 0.0088 Test Accuracy = 70.6200
Saving..
epoch: 94 --> Train loss = 0.0161 Train Accuracy = 42.7060
------> epoch: 94 --> Test loss = 0.0098 Test Accuracy = 68.8700
epoch: 95 --> Train loss = 0.0157 Train Accuracy = 45.4500
------> epoch: 95 --> Test loss = 0.0092 Test Accuracy = 69.3200
epoch: 96 --> Train loss = 0.0158 Train Accuracy = 43.1560
------> epoch: 96 --> Test loss = 0.0098 Test Accuracy = 67.4700
epoch: 97 --> Train loss = 0.0161 Train Accuracy = 42.7580
------> epoch: 97 --> Test loss = 0.0092 Test Accuracy = 69.2200
epoch: 98 --> Train loss = 0.0159 Train Accuracy = 41.8980
------> epoch: 98 --> Test loss = 0.0089 Test Accuracy = 70.7400
Saving..
epoch: 99 --> Train loss = 0.0157 Train Accuracy = 43.1340
------> epoch: 99 --> Test loss = 0.0108 Test Accuracy = 65.7600
epoch: 100 --> Train loss = 0.0158 Train Accuracy = 40.7420
------> epoch: 100 --> Test loss = 0.0096 Test Accuracy = 69.0800
epoch: 101 --> Train loss = 0.0159 Train Accuracy = 41.4480
------> epoch: 101 --> Test loss = 0.0088 Test Accuracy = 70.4300
epoch: 102 --> Train loss = 0.0156 Train Accuracy = 43.2780
------> epoch: 102 --> Test loss = 0.0096 Test Accuracy = 68.3300
epoch: 103 --> Train loss = 0.0158 Train Accuracy = 41.2100
------> epoch: 103 --> Test loss = 0.0109 Test Accuracy = 65.1600
epoch: 104 --> Train loss = 0.0159 Train Accuracy = 41.4680
------> epoch: 104 --> Test loss = 0.0092 Test Accuracy = 69.4100
epoch: 105 --> Train loss = 0.0156 Train Accuracy = 43.7440
------> epoch: 105 --> Test loss = 0.0098 Test Accuracy = 68.4600
epoch: 106 --> Train loss = 0.0152 Train Accuracy = 44.0720
------> epoch: 106 --> Test loss = 0.0095 Test Accuracy = 68.5000
epoch: 107 --> Train loss = 0.0158 Train Accuracy = 41.8680
------> epoch: 107 --> Test loss = 0.0105 Test Accuracy = 65.2400
epoch: 108 --> Train loss = 0.0158 Train Accuracy = 43.8840
------> epoch: 108 --> Test loss = 0.0087 Test Accuracy = 70.3100
epoch: 109 --> Train loss = 0.0159 Train Accuracy = 42.0040
------> epoch: 109 --> Test loss = 0.0092 Test Accuracy = 69.1000
epoch: 110 --> Train loss = 0.0157 Train Accuracy = 42.2500
------> epoch: 110 --> Test loss = 0.0097 Test Accuracy = 69.1500
epoch: 111 --> Train loss = 0.0156 Train Accuracy = 43.8140
------> epoch: 111 --> Test loss = 0.0090 Test Accuracy = 70.2300
epoch: 112 --> Train loss = 0.0157 Train Accuracy = 42.6480
------> epoch: 112 --> Test loss = 0.0089 Test Accuracy = 70.2500
epoch: 113 --> Train loss = 0.0156 Train Accuracy = 42.2300
------> epoch: 113 --> Test loss = 0.0119 Test Accuracy = 61.9500
epoch: 114 --> Train loss = 0.0155 Train Accuracy = 41.9700
------> epoch: 114 --> Test loss = 0.0100 Test Accuracy = 67.8300
epoch: 115 --> Train loss = 0.0156 Train Accuracy = 42.9020
------> epoch: 115 --> Test loss = 0.0091 Test Accuracy = 69.9200
epoch: 116 --> Train loss = 0.0156 Train Accuracy = 38.8520
------> epoch: 116 --> Test loss = 0.0086 Test Accuracy = 70.4000
epoch: 117 --> Train loss = 0.0157 Train Accuracy = 44.7740
------> epoch: 117 --> Test loss = 0.0100 Test Accuracy = 67.0400
epoch: 118 --> Train loss = 0.0153 Train Accuracy = 43.9640
------> epoch: 118 --> Test loss = 0.0086 Test Accuracy = 71.5400
Saving..
epoch: 119 --> Train loss = 0.0156 Train Accuracy = 43.6180
------> epoch: 119 --> Test loss = 0.0096 Test Accuracy = 68.4000
epoch: 120 --> Train loss = 0.0155 Train Accuracy = 44.7560
------> epoch: 120 --> Test loss = 0.0103 Test Accuracy = 65.7300
epoch: 121 --> Train loss = 0.0160 Train Accuracy = 42.7460
------> epoch: 121 --> Test loss = 0.0091 Test Accuracy = 69.1300
epoch: 122 --> Train loss = 0.0155 Train Accuracy = 42.2380
------> epoch: 122 --> Test loss = 0.0090 Test Accuracy = 70.4200
epoch: 123 --> Train loss = 0.0158 Train Accuracy = 43.3840
------> epoch: 123 --> Test loss = 0.0100 Test Accuracy = 66.9300
epoch: 124 --> Train loss = 0.0155 Train Accuracy = 45.1980
------> epoch: 124 --> Test loss = 0.0097 Test Accuracy = 68.5200
epoch: 125 --> Train loss = 0.0155 Train Accuracy = 45.0540
------> epoch: 125 --> Test loss = 0.0088 Test Accuracy = 70.4900
epoch: 126 --> Train loss = 0.0157 Train Accuracy = 42.1060
------> epoch: 126 --> Test loss = 0.0105 Test Accuracy = 65.8000
epoch: 127 --> Train loss = 0.0156 Train Accuracy = 41.9600
------> epoch: 127 --> Test loss = 0.0090 Test Accuracy = 69.7900
epoch: 128 --> Train loss = 0.0155 Train Accuracy = 41.0560
------> epoch: 128 --> Test loss = 0.0095 Test Accuracy = 68.9800
epoch: 129 --> Train loss = 0.0156 Train Accuracy = 43.8360
------> epoch: 129 --> Test loss = 0.0092 Test Accuracy = 69.2100
epoch: 130 --> Train loss = 0.0156 Train Accuracy = 45.7800
------> epoch: 130 --> Test loss = 0.0095 Test Accuracy = 68.4700
epoch: 131 --> Train loss = 0.0151 Train Accuracy = 40.8960
------> epoch: 131 --> Test loss = 0.0099 Test Accuracy = 68.3800
epoch: 132 --> Train loss = 0.0154 Train Accuracy = 42.1740
------> epoch: 132 --> Test loss = 0.0095 Test Accuracy = 69.0000
epoch: 133 --> Train loss = 0.0156 Train Accuracy = 45.0800
------> epoch: 133 --> Test loss = 0.0097 Test Accuracy = 68.0400
epoch: 134 --> Train loss = 0.0153 Train Accuracy = 43.0120
------> epoch: 134 --> Test loss = 0.0085 Test Accuracy = 71.5100
epoch: 135 --> Train loss = 0.0156 Train Accuracy = 43.0240
------> epoch: 135 --> Test loss = 0.0091 Test Accuracy = 69.8700
epoch: 136 --> Train loss = 0.0155 Train Accuracy = 45.3880
------> epoch: 136 --> Test loss = 0.0088 Test Accuracy = 70.6700
epoch: 137 --> Train loss = 0.0156 Train Accuracy = 45.2280
------> epoch: 137 --> Test loss = 0.0090 Test Accuracy = 70.2900
epoch: 138 --> Train loss = 0.0152 Train Accuracy = 41.1720
------> epoch: 138 --> Test loss = 0.0109 Test Accuracy = 65.1600
epoch: 139 --> Train loss = 0.0155 Train Accuracy = 39.8260
------> epoch: 139 --> Test loss = 0.0099 Test Accuracy = 67.8700
epoch: 140 --> Train loss = 0.0156 Train Accuracy = 42.7900
------> epoch: 140 --> Test loss = 0.0097 Test Accuracy = 67.6400
epoch: 141 --> Train loss = 0.0155 Train Accuracy = 40.7020
------> epoch: 141 --> Test loss = 0.0105 Test Accuracy = 66.3200
epoch: 142 --> Train loss = 0.0152 Train Accuracy = 40.7000
------> epoch: 142 --> Test loss = 0.0101 Test Accuracy = 67.0200
epoch: 143 --> Train loss = 0.0150 Train Accuracy = 40.3920
------> epoch: 143 --> Test loss = 0.0096 Test Accuracy = 68.0400
epoch: 144 --> Train loss = 0.0154 Train Accuracy = 43.1220
------> epoch: 144 --> Test loss = 0.0098 Test Accuracy = 67.9900
epoch: 145 --> Train loss = 0.0154 Train Accuracy = 40.3680
------> epoch: 145 --> Test loss = 0.0096 Test Accuracy = 69.0700
epoch: 146 --> Train loss = 0.0160 Train Accuracy = 44.3760
------> epoch: 146 --> Test loss = 0.0106 Test Accuracy = 65.9100
epoch: 147 --> Train loss = 0.0150 Train Accuracy = 46.2700
------> epoch: 147 --> Test loss = 0.0094 Test Accuracy = 68.5500
epoch: 148 --> Train loss = 0.0155 Train Accuracy = 45.5760
------> epoch: 148 --> Test loss = 0.0091 Test Accuracy = 70.1300
epoch: 149 --> Train loss = 0.0154 Train Accuracy = 45.3480
------> epoch: 149 --> Test loss = 0.0088 Test Accuracy = 70.6300
epoch: 150 --> Train loss = 0.0153 Train Accuracy = 41.2340
------> epoch: 150 --> Test loss = 0.0102 Test Accuracy = 66.9900
epoch: 151 --> Train loss = 0.0154 Train Accuracy = 42.4980
------> epoch: 151 --> Test loss = 0.0095 Test Accuracy = 68.6700
epoch: 152 --> Train loss = 0.0157 Train Accuracy = 44.0360
------> epoch: 152 --> Test loss = 0.0097 Test Accuracy = 68.9300
epoch: 153 --> Train loss = 0.0154 Train Accuracy = 41.6700
------> epoch: 153 --> Test loss = 0.0089 Test Accuracy = 70.4100
epoch: 154 --> Train loss = 0.0152 Train Accuracy = 45.3860
------> epoch: 154 --> Test loss = 0.0090 Test Accuracy = 70.6600
epoch: 155 --> Train loss = 0.0149 Train Accuracy = 43.7600
------> epoch: 155 --> Test loss = 0.0095 Test Accuracy = 68.8600
epoch: 156 --> Train loss = 0.0156 Train Accuracy = 43.5720
------> epoch: 156 --> Test loss = 0.0096 Test Accuracy = 68.3100
epoch: 157 --> Train loss = 0.0152 Train Accuracy = 43.6440
------> epoch: 157 --> Test loss = 0.0096 Test Accuracy = 68.3400
epoch: 158 --> Train loss = 0.0157 Train Accuracy = 42.8740
------> epoch: 158 --> Test loss = 0.0100 Test Accuracy = 68.0400
epoch: 159 --> Train loss = 0.0152 Train Accuracy = 44.9380
------> epoch: 159 --> Test loss = 0.0099 Test Accuracy = 67.5600
epoch: 160 --> Train loss = 0.0149 Train Accuracy = 46.2360
------> epoch: 160 --> Test loss = 0.0090 Test Accuracy = 70.4200
epoch: 161 --> Train loss = 0.0151 Train Accuracy = 40.0500
------> epoch: 161 --> Test loss = 0.0100 Test Accuracy = 67.6500
epoch: 162 --> Train loss = 0.0153 Train Accuracy = 42.8120
------> epoch: 162 --> Test loss = 0.0088 Test Accuracy = 70.7200
epoch: 163 --> Train loss = 0.0155 Train Accuracy = 43.1400
------> epoch: 163 --> Test loss = 0.0091 Test Accuracy = 69.4500
epoch: 164 --> Train loss = 0.0153 Train Accuracy = 43.6140
------> epoch: 164 --> Test loss = 0.0091 Test Accuracy = 70.4500
epoch: 165 --> Train loss = 0.0149 Train Accuracy = 41.6960
------> epoch: 165 --> Test loss = 0.0089 Test Accuracy = 70.8700
epoch: 166 --> Train loss = 0.0152 Train Accuracy = 48.1780
------> epoch: 166 --> Test loss = 0.0103 Test Accuracy = 65.8900
epoch: 167 --> Train loss = 0.0155 Train Accuracy = 42.7640
------> epoch: 167 --> Test loss = 0.0096 Test Accuracy = 69.0500
epoch: 168 --> Train loss = 0.0151 Train Accuracy = 44.2260
------> epoch: 168 --> Test loss = 0.0099 Test Accuracy = 68.2900
epoch: 169 --> Train loss = 0.0154 Train Accuracy = 39.9780
------> epoch: 169 --> Test loss = 0.0095 Test Accuracy = 67.9600
epoch: 170 --> Train loss = 0.0153 Train Accuracy = 46.6580
------> epoch: 170 --> Test loss = 0.0101 Test Accuracy = 67.9600
epoch: 171 --> Train loss = 0.0156 Train Accuracy = 45.5580
------> epoch: 171 --> Test loss = 0.0093 Test Accuracy = 69.5300
epoch: 172 --> Train loss = 0.0155 Train Accuracy = 42.9580
------> epoch: 172 --> Test loss = 0.0095 Test Accuracy = 68.5200
epoch: 173 --> Train loss = 0.0156 Train Accuracy = 44.7340
------> epoch: 173 --> Test loss = 0.0105 Test Accuracy = 67.6200
epoch: 174 --> Train loss = 0.0152 Train Accuracy = 41.5600
------> epoch: 174 --> Test loss = 0.0093 Test Accuracy = 68.6700
epoch: 175 --> Train loss = 0.0154 Train Accuracy = 43.9980
------> epoch: 175 --> Test loss = 0.0097 Test Accuracy = 67.7700
epoch: 176 --> Train loss = 0.0155 Train Accuracy = 42.8280
------> epoch: 176 --> Test loss = 0.0098 Test Accuracy = 68.8200
epoch: 177 --> Train loss = 0.0154 Train Accuracy = 41.9580
------> epoch: 177 --> Test loss = 0.0094 Test Accuracy = 69.3200
epoch: 178 --> Train loss = 0.0153 Train Accuracy = 42.8260
------> epoch: 178 --> Test loss = 0.0095 Test Accuracy = 68.7600
epoch: 179 --> Train loss = 0.0148 Train Accuracy = 41.2360
------> epoch: 179 --> Test loss = 0.0093 Test Accuracy = 68.9100
epoch: 180 --> Train loss = 0.0149 Train Accuracy = 45.5000
------> epoch: 180 --> Test loss = 0.0102 Test Accuracy = 67.3200
epoch: 181 --> Train loss = 0.0155 Train Accuracy = 44.9060
------> epoch: 181 --> Test loss = 0.0091 Test Accuracy = 70.3700
epoch: 182 --> Train loss = 0.0156 Train Accuracy = 42.3960
------> epoch: 182 --> Test loss = 0.0107 Test Accuracy = 66.5800
epoch: 183 --> Train loss = 0.0155 Train Accuracy = 45.1700
------> epoch: 183 --> Test loss = 0.0103 Test Accuracy = 66.7400
epoch: 184 --> Train loss = 0.0156 Train Accuracy = 44.1780
------> epoch: 184 --> Test loss = 0.0098 Test Accuracy = 68.5600
epoch: 185 --> Train loss = 0.0151 Train Accuracy = 44.5600
------> epoch: 185 --> Test loss = 0.0094 Test Accuracy = 69.2800
epoch: 186 --> Train loss = 0.0154 Train Accuracy = 42.2760
------> epoch: 186 --> Test loss = 0.0095 Test Accuracy = 69.2300
epoch: 187 --> Train loss = 0.0153 Train Accuracy = 45.8900
------> epoch: 187 --> Test loss = 0.0090 Test Accuracy = 69.9300
epoch: 188 --> Train loss = 0.0156 Train Accuracy = 43.5460
------> epoch: 188 --> Test loss = 0.0102 Test Accuracy = 66.9900
epoch: 189 --> Train loss = 0.0149 Train Accuracy = 43.0660
------> epoch: 189 --> Test loss = 0.0094 Test Accuracy = 69.5300
epoch: 190 --> Train loss = 0.0153 Train Accuracy = 44.8620
------> epoch: 190 --> Test loss = 0.0098 Test Accuracy = 68.1500
epoch: 191 --> Train loss = 0.0152 Train Accuracy = 47.0560
------> epoch: 191 --> Test loss = 0.0087 Test Accuracy = 70.9300
epoch: 192 --> Train loss = 0.0149 Train Accuracy = 44.8460
------> epoch: 192 --> Test loss = 0.0094 Test Accuracy = 69.2100
epoch: 193 --> Train loss = 0.0153 Train Accuracy = 42.9820
------> epoch: 193 --> Test loss = 0.0093 Test Accuracy = 69.5700
epoch: 194 --> Train loss = 0.0152 Train Accuracy = 42.8220
------> epoch: 194 --> Test loss = 0.0092 Test Accuracy = 70.0000
epoch: 195 --> Train loss = 0.0152 Train Accuracy = 43.2700
------> epoch: 195 --> Test loss = 0.0088 Test Accuracy = 69.9200
epoch: 196 --> Train loss = 0.0151 Train Accuracy = 42.2440
------> epoch: 196 --> Test loss = 0.0096 Test Accuracy = 68.9500
epoch: 197 --> Train loss = 0.0152 Train Accuracy = 43.2500
------> epoch: 197 --> Test loss = 0.0093 Test Accuracy = 70.0600
epoch: 198 --> Train loss = 0.0153 Train Accuracy = 45.9640
------> epoch: 198 --> Test loss = 0.0103 Test Accuracy = 66.8600
epoch: 199 --> Train loss = 0.0155 Train Accuracy = 43.1120
------> epoch: 199 --> Test loss = 0.0099 Test Accuracy = 67.6700
epoch: 200 --> Train loss = 0.0154 Train Accuracy = 39.7580
------> epoch: 200 --> Test loss = 0.0097 Test Accuracy = 68.5300
epoch: 201 --> Train loss = 0.0155 Train Accuracy = 42.1460
------> epoch: 201 --> Test loss = 0.0094 Test Accuracy = 69.1900
epoch: 202 --> Train loss = 0.0152 Train Accuracy = 44.4660
------> epoch: 202 --> Test loss = 0.0090 Test Accuracy = 70.3600
epoch: 203 --> Train loss = 0.0150 Train Accuracy = 43.6140
------> epoch: 203 --> Test loss = 0.0102 Test Accuracy = 66.6800
epoch: 204 --> Train loss = 0.0155 Train Accuracy = 45.0100
------> epoch: 204 --> Test loss = 0.0102 Test Accuracy = 67.7600
epoch: 205 --> Train loss = 0.0150 Train Accuracy = 43.8480
------> epoch: 205 --> Test loss = 0.0102 Test Accuracy = 67.5200
epoch: 206 --> Train loss = 0.0152 Train Accuracy = 43.0840
------> epoch: 206 --> Test loss = 0.0092 Test Accuracy = 69.8100
epoch: 207 --> Train loss = 0.0149 Train Accuracy = 43.6580
------> epoch: 207 --> Test loss = 0.0089 Test Accuracy = 70.6300
epoch: 208 --> Train loss = 0.0150 Train Accuracy = 42.3000
------> epoch: 208 --> Test loss = 0.0086 Test Accuracy = 71.4400
epoch: 209 --> Train loss = 0.0154 Train Accuracy = 41.6160
------> epoch: 209 --> Test loss = 0.0099 Test Accuracy = 68.5400
epoch: 210 --> Train loss = 0.0151 Train Accuracy = 45.0720
------> epoch: 210 --> Test loss = 0.0089 Test Accuracy = 70.5900
epoch: 211 --> Train loss = 0.0151 Train Accuracy = 44.8000
------> epoch: 211 --> Test loss = 0.0096 Test Accuracy = 69.0900
epoch: 212 --> Train loss = 0.0150 Train Accuracy = 45.0420
------> epoch: 212 --> Test loss = 0.0090 Test Accuracy = 70.1600
epoch: 213 --> Train loss = 0.0151 Train Accuracy = 41.7840
------> epoch: 213 --> Test loss = 0.0095 Test Accuracy = 69.3000
epoch: 214 --> Train loss = 0.0153 Train Accuracy = 41.5200
------> epoch: 214 --> Test loss = 0.0094 Test Accuracy = 68.9800
epoch: 215 --> Train loss = 0.0152 Train Accuracy = 42.8260
------> epoch: 215 --> Test loss = 0.0095 Test Accuracy = 69.4700
epoch: 216 --> Train loss = 0.0151 Train Accuracy = 42.9260
------> epoch: 216 --> Test loss = 0.0106 Test Accuracy = 66.2600
epoch: 217 --> Train loss = 0.0153 Train Accuracy = 45.5100
------> epoch: 217 --> Test loss = 0.0102 Test Accuracy = 67.2500
epoch: 218 --> Train loss = 0.0150 Train Accuracy = 45.5280
------> epoch: 218 --> Test loss = 0.0090 Test Accuracy = 70.5600
epoch: 219 --> Train loss = 0.0148 Train Accuracy = 43.6860
------> epoch: 219 --> Test loss = 0.0091 Test Accuracy = 70.2900
epoch: 220 --> Train loss = 0.0151 Train Accuracy = 43.8540
------> epoch: 220 --> Test loss = 0.0090 Test Accuracy = 69.9000
epoch: 221 --> Train loss = 0.0148 Train Accuracy = 44.6220
------> epoch: 221 --> Test loss = 0.0093 Test Accuracy = 69.3200
epoch: 222 --> Train loss = 0.0146 Train Accuracy = 44.6900
------> epoch: 222 --> Test loss = 0.0102 Test Accuracy = 67.3700
epoch: 223 --> Train loss = 0.0148 Train Accuracy = 41.2500
------> epoch: 223 --> Test loss = 0.0092 Test Accuracy = 69.7400
epoch: 224 --> Train loss = 0.0151 Train Accuracy = 43.7680
------> epoch: 224 --> Test loss = 0.0098 Test Accuracy = 68.2400
epoch: 225 --> Train loss = 0.0152 Train Accuracy = 42.4420
------> epoch: 225 --> Test loss = 0.0103 Test Accuracy = 67.2000
epoch: 226 --> Train loss = 0.0151 Train Accuracy = 42.1500
------> epoch: 226 --> Test loss = 0.0091 Test Accuracy = 70.9600
epoch: 227 --> Train loss = 0.0149 Train Accuracy = 46.1560
------> epoch: 227 --> Test loss = 0.0085 Test Accuracy = 71.6600
Saving..
epoch: 228 --> Train loss = 0.0154 Train Accuracy = 38.6860
------> epoch: 228 --> Test loss = 0.0096 Test Accuracy = 68.4300
epoch: 229 --> Train loss = 0.0147 Train Accuracy = 45.1300
------> epoch: 229 --> Test loss = 0.0095 Test Accuracy = 68.5700
epoch: 230 --> Train loss = 0.0150 Train Accuracy = 43.1900
------> epoch: 230 --> Test loss = 0.0093 Test Accuracy = 69.1200
epoch: 231 --> Train loss = 0.0153 Train Accuracy = 43.8640
------> epoch: 231 --> Test loss = 0.0096 Test Accuracy = 68.9100
epoch: 232 --> Train loss = 0.0152 Train Accuracy = 43.9480
------> epoch: 232 --> Test loss = 0.0100 Test Accuracy = 67.6100
epoch: 233 --> Train loss = 0.0150 Train Accuracy = 43.1420
------> epoch: 233 --> Test loss = 0.0092 Test Accuracy = 69.6500
epoch: 234 --> Train loss = 0.0152 Train Accuracy = 42.5580
------> epoch: 234 --> Test loss = 0.0092 Test Accuracy = 69.8400
epoch: 235 --> Train loss = 0.0151 Train Accuracy = 45.2940
------> epoch: 235 --> Test loss = 0.0097 Test Accuracy = 68.0000
epoch: 236 --> Train loss = 0.0153 Train Accuracy = 43.2800
------> epoch: 236 --> Test loss = 0.0092 Test Accuracy = 69.7700
epoch: 237 --> Train loss = 0.0150 Train Accuracy = 43.8940
------> epoch: 237 --> Test loss = 0.0094 Test Accuracy = 68.9200
epoch: 238 --> Train loss = 0.0152 Train Accuracy = 44.6580
------> epoch: 238 --> Test loss = 0.0086 Test Accuracy = 71.4000
epoch: 239 --> Train loss = 0.0151 Train Accuracy = 44.6740
------> epoch: 239 --> Test loss = 0.0084 Test Accuracy = 71.4000
epoch: 240 --> Train loss = 0.0153 Train Accuracy = 44.9260
------> epoch: 240 --> Test loss = 0.0098 Test Accuracy = 68.6700
epoch: 241 --> Train loss = 0.0151 Train Accuracy = 41.7760
------> epoch: 241 --> Test loss = 0.0095 Test Accuracy = 69.1000
epoch: 242 --> Train loss = 0.0152 Train Accuracy = 44.4800
------> epoch: 242 --> Test loss = 0.0094 Test Accuracy = 69.5500
epoch: 243 --> Train loss = 0.0149 Train Accuracy = 44.2760
------> epoch: 243 --> Test loss = 0.0100 Test Accuracy = 68.3400
epoch: 244 --> Train loss = 0.0149 Train Accuracy = 45.2860
------> epoch: 244 --> Test loss = 0.0084 Test Accuracy = 71.5600
epoch: 245 --> Train loss = 0.0152 Train Accuracy = 42.3860
------> epoch: 245 --> Test loss = 0.0090 Test Accuracy = 70.8600
epoch: 246 --> Train loss = 0.0148 Train Accuracy = 42.2520
------> epoch: 246 --> Test loss = 0.0084 Test Accuracy = 72.3300
Saving..
epoch: 247 --> Train loss = 0.0153 Train Accuracy = 42.8500
------> epoch: 247 --> Test loss = 0.0088 Test Accuracy = 71.0500
epoch: 248 --> Train loss = 0.0150 Train Accuracy = 43.8180
------> epoch: 248 --> Test loss = 0.0093 Test Accuracy = 69.6900
epoch: 249 --> Train loss = 0.0155 Train Accuracy = 42.6960
------> epoch: 249 --> Test loss = 0.0094 Test Accuracy = 68.8300
epoch: 250 --> Train loss = 0.0149 Train Accuracy = 41.5840
------> epoch: 250 --> Test loss = 0.0099 Test Accuracy = 68.3100
epoch: 251 --> Train loss = 0.0149 Train Accuracy = 44.2140
------> epoch: 251 --> Test loss = 0.0100 Test Accuracy = 68.2300
epoch: 252 --> Train loss = 0.0153 Train Accuracy = 44.3100
------> epoch: 252 --> Test loss = 0.0093 Test Accuracy = 70.1800
epoch: 253 --> Train loss = 0.0152 Train Accuracy = 43.5800
------> epoch: 253 --> Test loss = 0.0095 Test Accuracy = 69.2100
epoch: 254 --> Train loss = 0.0149 Train Accuracy = 43.8180
------> epoch: 254 --> Test loss = 0.0098 Test Accuracy = 67.6900
epoch: 255 --> Train loss = 0.0147 Train Accuracy = 44.5340
------> epoch: 255 --> Test loss = 0.0097 Test Accuracy = 68.7800
epoch: 256 --> Train loss = 0.0151 Train Accuracy = 44.8880
------> epoch: 256 --> Test loss = 0.0093 Test Accuracy = 69.1800
epoch: 257 --> Train loss = 0.0151 Train Accuracy = 42.6660
------> epoch: 257 --> Test loss = 0.0092 Test Accuracy = 68.8800
epoch: 258 --> Train loss = 0.0153 Train Accuracy = 42.8280
------> epoch: 258 --> Test loss = 0.0090 Test Accuracy = 70.5600
epoch: 259 --> Train loss = 0.0151 Train Accuracy = 45.6820
------> epoch: 259 --> Test loss = 0.0096 Test Accuracy = 69.3400
epoch: 260 --> Train loss = 0.0153 Train Accuracy = 44.6040
------> epoch: 260 --> Test loss = 0.0094 Test Accuracy = 69.3000
epoch: 261 --> Train loss = 0.0150 Train Accuracy = 43.6940
------> epoch: 261 --> Test loss = 0.0097 Test Accuracy = 69.0400
epoch: 262 --> Train loss = 0.0149 Train Accuracy = 45.2080
------> epoch: 262 --> Test loss = 0.0102 Test Accuracy = 66.5800
epoch: 263 --> Train loss = 0.0151 Train Accuracy = 41.9160
------> epoch: 263 --> Test loss = 0.0118 Test Accuracy = 63.3900
epoch: 264 --> Train loss = 0.0150 Train Accuracy = 44.2240
------> epoch: 264 --> Test loss = 0.0086 Test Accuracy = 70.7400
epoch: 265 --> Train loss = 0.0153 Train Accuracy = 44.7760
------> epoch: 265 --> Test loss = 0.0106 Test Accuracy = 66.6800
epoch: 266 --> Train loss = 0.0150 Train Accuracy = 45.9900
------> epoch: 266 --> Test loss = 0.0101 Test Accuracy = 67.5200
epoch: 267 --> Train loss = 0.0153 Train Accuracy = 47.7660
------> epoch: 267 --> Test loss = 0.0093 Test Accuracy = 69.3200
epoch: 268 --> Train loss = 0.0147 Train Accuracy = 44.6420
------> epoch: 268 --> Test loss = 0.0097 Test Accuracy = 68.7700
epoch: 269 --> Train loss = 0.0148 Train Accuracy = 44.4400
------> epoch: 269 --> Test loss = 0.0093 Test Accuracy = 69.7100
epoch: 270 --> Train loss = 0.0148 Train Accuracy = 44.6540
------> epoch: 270 --> Test loss = 0.0096 Test Accuracy = 69.7700
epoch: 271 --> Train loss = 0.0151 Train Accuracy = 43.3840
------> epoch: 271 --> Test loss = 0.0100 Test Accuracy = 68.3900
epoch: 272 --> Train loss = 0.0147 Train Accuracy = 43.8580
------> epoch: 272 --> Test loss = 0.0094 Test Accuracy = 68.9600
epoch: 273 --> Train loss = 0.0149 Train Accuracy = 43.5140
------> epoch: 273 --> Test loss = 0.0099 Test Accuracy = 68.1800
epoch: 274 --> Train loss = 0.0152 Train Accuracy = 44.8300
------> epoch: 274 --> Test loss = 0.0092 Test Accuracy = 69.5400
epoch: 275 --> Train loss = 0.0148 Train Accuracy = 45.3840
------> epoch: 275 --> Test loss = 0.0095 Test Accuracy = 68.8900
epoch: 276 --> Train loss = 0.0151 Train Accuracy = 46.4500
------> epoch: 276 --> Test loss = 0.0097 Test Accuracy = 68.8800
epoch: 277 --> Train loss = 0.0144 Train Accuracy = 43.5480
------> epoch: 277 --> Test loss = 0.0096 Test Accuracy = 69.5400
epoch: 278 --> Train loss = 0.0151 Train Accuracy = 42.9380
------> epoch: 278 --> Test loss = 0.0116 Test Accuracy = 63.2400
epoch: 279 --> Train loss = 0.0148 Train Accuracy = 39.5320
------> epoch: 279 --> Test loss = 0.0090 Test Accuracy = 70.2000
epoch: 280 --> Train loss = 0.0147 Train Accuracy = 42.2400
------> epoch: 280 --> Test loss = 0.0095 Test Accuracy = 69.7700
epoch: 281 --> Train loss = 0.0149 Train Accuracy = 43.9420
------> epoch: 281 --> Test loss = 0.0097 Test Accuracy = 68.6300
epoch: 282 --> Train loss = 0.0150 Train Accuracy = 43.9760
------> epoch: 282 --> Test loss = 0.0107 Test Accuracy = 66.5800
epoch: 283 --> Train loss = 0.0151 Train Accuracy = 43.2080
------> epoch: 283 --> Test loss = 0.0094 Test Accuracy = 68.8700
epoch: 284 --> Train loss = 0.0145 Train Accuracy = 43.0740
------> epoch: 284 --> Test loss = 0.0090 Test Accuracy = 70.5500
epoch: 285 --> Train loss = 0.0148 Train Accuracy = 43.3800
------> epoch: 285 --> Test loss = 0.0101 Test Accuracy = 67.1900
epoch: 286 --> Train loss = 0.0152 Train Accuracy = 43.2000
------> epoch: 286 --> Test loss = 0.0100 Test Accuracy = 67.9400
epoch: 287 --> Train loss = 0.0150 Train Accuracy = 44.2540
------> epoch: 287 --> Test loss = 0.0098 Test Accuracy = 68.3100
epoch: 288 --> Train loss = 0.0148 Train Accuracy = 43.4120
------> epoch: 288 --> Test loss = 0.0094 Test Accuracy = 69.4200
epoch: 289 --> Train loss = 0.0147 Train Accuracy = 44.2660
------> epoch: 289 --> Test loss = 0.0091 Test Accuracy = 70.1500
epoch: 290 --> Train loss = 0.0151 Train Accuracy = 42.0460
------> epoch: 290 --> Test loss = 0.0090 Test Accuracy = 70.4200
epoch: 291 --> Train loss = 0.0148 Train Accuracy = 43.3960
------> epoch: 291 --> Test loss = 0.0104 Test Accuracy = 66.5500
epoch: 292 --> Train loss = 0.0149 Train Accuracy = 43.9160
------> epoch: 292 --> Test loss = 0.0092 Test Accuracy = 69.2400
epoch: 293 --> Train loss = 0.0150 Train Accuracy = 40.7680
------> epoch: 293 --> Test loss = 0.0091 Test Accuracy = 70.0000
epoch: 294 --> Train loss = 0.0148 Train Accuracy = 45.0520
------> epoch: 294 --> Test loss = 0.0097 Test Accuracy = 68.2500
epoch: 295 --> Train loss = 0.0149 Train Accuracy = 45.3800
------> epoch: 295 --> Test loss = 0.0106 Test Accuracy = 66.5800
epoch: 296 --> Train loss = 0.0150 Train Accuracy = 43.9820
------> epoch: 296 --> Test loss = 0.0110 Test Accuracy = 65.1100
epoch: 297 --> Train loss = 0.0151 Train Accuracy = 43.3940
------> epoch: 297 --> Test loss = 0.0098 Test Accuracy = 68.3000
epoch: 298 --> Train loss = 0.0152 Train Accuracy = 41.8380
------> epoch: 298 --> Test loss = 0.0090 Test Accuracy = 70.5800
epoch: 299 --> Train loss = 0.0148 Train Accuracy = 44.8780
------> epoch: 299 --> Test loss = 0.0095 Test Accuracy = 69.1200
epoch: 300 --> Train loss = 0.0146 Train Accuracy = 43.5740
------> epoch: 300 --> Test loss = 0.0095 Test Accuracy = 69.5500
epoch: 301 --> Train loss = 0.0148 Train Accuracy = 45.2640
------> epoch: 301 --> Test loss = 0.0100 Test Accuracy = 67.3800
epoch: 302 --> Train loss = 0.0148 Train Accuracy = 45.3120
------> epoch: 302 --> Test loss = 0.0103 Test Accuracy = 66.7500
epoch: 303 --> Train loss = 0.0146 Train Accuracy = 46.4760
------> epoch: 303 --> Test loss = 0.0102 Test Accuracy = 66.8500
epoch: 304 --> Train loss = 0.0151 Train Accuracy = 44.0240
------> epoch: 304 --> Test loss = 0.0098 Test Accuracy = 68.1200
epoch: 305 --> Train loss = 0.0152 Train Accuracy = 46.7200
------> epoch: 305 --> Test loss = 0.0094 Test Accuracy = 69.6600
epoch: 306 --> Train loss = 0.0148 Train Accuracy = 44.3940
------> epoch: 306 --> Test loss = 0.0093 Test Accuracy = 70.2500
epoch: 307 --> Train loss = 0.0148 Train Accuracy = 43.4240
------> epoch: 307 --> Test loss = 0.0093 Test Accuracy = 69.7300
epoch: 308 --> Train loss = 0.0151 Train Accuracy = 43.5620
------> epoch: 308 --> Test loss = 0.0093 Test Accuracy = 70.0300
epoch: 309 --> Train loss = 0.0147 Train Accuracy = 42.6820
------> epoch: 309 --> Test loss = 0.0099 Test Accuracy = 68.2000
epoch: 310 --> Train loss = 0.0150 Train Accuracy = 44.5280
------> epoch: 310 --> Test loss = 0.0093 Test Accuracy = 69.4300
epoch: 311 --> Train loss = 0.0150 Train Accuracy = 44.3560
------> epoch: 311 --> Test loss = 0.0103 Test Accuracy = 66.6400
epoch: 312 --> Train loss = 0.0151 Train Accuracy = 44.8780
------> epoch: 312 --> Test loss = 0.0097 Test Accuracy = 69.1200
epoch: 313 --> Train loss = 0.0148 Train Accuracy = 40.9940
------> epoch: 313 --> Test loss = 0.0091 Test Accuracy = 70.3000
epoch: 314 --> Train loss = 0.0148 Train Accuracy = 45.1660
------> epoch: 314 --> Test loss = 0.0092 Test Accuracy = 70.2400
epoch: 315 --> Train loss = 0.0148 Train Accuracy = 42.0600
------> epoch: 315 --> Test loss = 0.0092 Test Accuracy = 69.7800
epoch: 316 --> Train loss = 0.0148 Train Accuracy = 42.7280
------> epoch: 316 --> Test loss = 0.0089 Test Accuracy = 71.3400
epoch: 317 --> Train loss = 0.0153 Train Accuracy = 44.1480
------> epoch: 317 --> Test loss = 0.0098 Test Accuracy = 68.5200
epoch: 318 --> Train loss = 0.0151 Train Accuracy = 47.6420
------> epoch: 318 --> Test loss = 0.0100 Test Accuracy = 67.6900
epoch: 319 --> Train loss = 0.0150 Train Accuracy = 42.8880
------> epoch: 319 --> Test loss = 0.0088 Test Accuracy = 70.8100
epoch: 320 --> Train loss = 0.0152 Train Accuracy = 45.2420
------> epoch: 320 --> Test loss = 0.0092 Test Accuracy = 70.7600
epoch: 321 --> Train loss = 0.0149 Train Accuracy = 44.2620
------> epoch: 321 --> Test loss = 0.0094 Test Accuracy = 69.3700
epoch: 322 --> Train loss = 0.0149 Train Accuracy = 45.5560
------> epoch: 322 --> Test loss = 0.0088 Test Accuracy = 70.7500
epoch: 323 --> Train loss = 0.0144 Train Accuracy = 48.4740
------> epoch: 323 --> Test loss = 0.0088 Test Accuracy = 70.9200
epoch: 324 --> Train loss = 0.0145 Train Accuracy = 44.5180
------> epoch: 324 --> Test loss = 0.0091 Test Accuracy = 70.3400
epoch: 325 --> Train loss = 0.0147 Train Accuracy = 44.1220
------> epoch: 325 --> Test loss = 0.0101 Test Accuracy = 66.5200
epoch: 326 --> Train loss = 0.0149 Train Accuracy = 41.4280
------> epoch: 326 --> Test loss = 0.0105 Test Accuracy = 66.5700
epoch: 327 --> Train loss = 0.0147 Train Accuracy = 46.9460
------> epoch: 327 --> Test loss = 0.0096 Test Accuracy = 68.2600
epoch: 328 --> Train loss = 0.0151 Train Accuracy = 42.7400
------> epoch: 328 --> Test loss = 0.0097 Test Accuracy = 68.7300
epoch: 329 --> Train loss = 0.0149 Train Accuracy = 45.3960
------> epoch: 329 --> Test loss = 0.0083 Test Accuracy = 72.4200
Saving..
epoch: 330 --> Train loss = 0.0146 Train Accuracy = 43.1100
------> epoch: 330 --> Test loss = 0.0085 Test Accuracy = 71.7300
epoch: 331 --> Train loss = 0.0150 Train Accuracy = 43.5620
------> epoch: 331 --> Test loss = 0.0093 Test Accuracy = 69.9600
epoch: 332 --> Train loss = 0.0152 Train Accuracy = 44.7660
------> epoch: 332 --> Test loss = 0.0099 Test Accuracy = 68.3400
epoch: 333 --> Train loss = 0.0147 Train Accuracy = 45.1560
------> epoch: 333 --> Test loss = 0.0090 Test Accuracy = 70.6000
epoch: 334 --> Train loss = 0.0149 Train Accuracy = 43.9800
------> epoch: 334 --> Test loss = 0.0097 Test Accuracy = 67.9800
epoch: 335 --> Train loss = 0.0150 Train Accuracy = 41.3980
------> epoch: 335 --> Test loss = 0.0092 Test Accuracy = 70.1200
epoch: 336 --> Train loss = 0.0145 Train Accuracy = 43.5140
------> epoch: 336 --> Test loss = 0.0095 Test Accuracy = 68.7500
epoch: 337 --> Train loss = 0.0145 Train Accuracy = 46.8740
------> epoch: 337 --> Test loss = 0.0089 Test Accuracy = 70.4000
epoch: 338 --> Train loss = 0.0149 Train Accuracy = 45.5300
------> epoch: 338 --> Test loss = 0.0099 Test Accuracy = 68.7400
epoch: 339 --> Train loss = 0.0149 Train Accuracy = 43.4200
------> epoch: 339 --> Test loss = 0.0108 Test Accuracy = 66.1400
epoch: 340 --> Train loss = 0.0145 Train Accuracy = 44.2860
------> epoch: 340 --> Test loss = 0.0095 Test Accuracy = 69.2200
epoch: 341 --> Train loss = 0.0149 Train Accuracy = 43.7520
------> epoch: 341 --> Test loss = 0.0097 Test Accuracy = 69.1100
epoch: 342 --> Train loss = 0.0147 Train Accuracy = 46.6800
------> epoch: 342 --> Test loss = 0.0089 Test Accuracy = 71.3600
epoch: 343 --> Train loss = 0.0152 Train Accuracy = 43.0460
------> epoch: 343 --> Test loss = 0.0094 Test Accuracy = 69.4400
epoch: 344 --> Train loss = 0.0146 Train Accuracy = 46.4940
------> epoch: 344 --> Test loss = 0.0101 Test Accuracy = 66.9000
epoch: 345 --> Train loss = 0.0150 Train Accuracy = 47.9720
------> epoch: 345 --> Test loss = 0.0093 Test Accuracy = 69.8600
epoch: 346 --> Train loss = 0.0146 Train Accuracy = 43.8500
------> epoch: 346 --> Test loss = 0.0100 Test Accuracy = 67.8800
epoch: 347 --> Train loss = 0.0149 Train Accuracy = 44.6680
------> epoch: 347 --> Test loss = 0.0092 Test Accuracy = 70.3900
epoch: 348 --> Train loss = 0.0149 Train Accuracy = 42.2020
------> epoch: 348 --> Test loss = 0.0095 Test Accuracy = 69.7900
epoch: 349 --> Train loss = 0.0152 Train Accuracy = 40.9600
------> epoch: 349 --> Test loss = 0.0097 Test Accuracy = 69.1500
epoch: 350 --> Train loss = 0.0149 Train Accuracy = 43.1020
------> epoch: 350 --> Test loss = 0.0106 Test Accuracy = 66.6800
epoch: 351 --> Train loss = 0.0149 Train Accuracy = 42.9940
------> epoch: 351 --> Test loss = 0.0093 Test Accuracy = 69.6500
epoch: 352 --> Train loss = 0.0148 Train Accuracy = 45.1240
------> epoch: 352 --> Test loss = 0.0090 Test Accuracy = 70.1800
epoch: 353 --> Train loss = 0.0144 Train Accuracy = 41.2840
------> epoch: 353 --> Test loss = 0.0086 Test Accuracy = 71.1200
epoch: 354 --> Train loss = 0.0151 Train Accuracy = 45.6040
------> epoch: 354 --> Test loss = 0.0092 Test Accuracy = 70.0600
epoch: 355 --> Train loss = 0.0146 Train Accuracy = 42.2380
------> epoch: 355 --> Test loss = 0.0099 Test Accuracy = 68.0000
epoch: 356 --> Train loss = 0.0147 Train Accuracy = 43.7400
------> epoch: 356 --> Test loss = 0.0083 Test Accuracy = 72.1500
epoch: 357 --> Train loss = 0.0147 Train Accuracy = 44.4800
------> epoch: 357 --> Test loss = 0.0097 Test Accuracy = 67.8400
epoch: 358 --> Train loss = 0.0147 Train Accuracy = 45.1760
------> epoch: 358 --> Test loss = 0.0091 Test Accuracy = 71.0700
epoch: 359 --> Train loss = 0.0146 Train Accuracy = 47.6700
------> epoch: 359 --> Test loss = 0.0095 Test Accuracy = 68.6700
epoch: 360 --> Train loss = 0.0146 Train Accuracy = 44.7260
------> epoch: 360 --> Test loss = 0.0089 Test Accuracy = 70.7200
epoch: 361 --> Train loss = 0.0147 Train Accuracy = 43.4040
------> epoch: 361 --> Test loss = 0.0104 Test Accuracy = 66.8600
epoch: 362 --> Train loss = 0.0153 Train Accuracy = 42.2200
------> epoch: 362 --> Test loss = 0.0101 Test Accuracy = 66.7300
epoch: 363 --> Train loss = 0.0148 Train Accuracy = 41.5160
------> epoch: 363 --> Test loss = 0.0096 Test Accuracy = 69.7400
epoch: 364 --> Train loss = 0.0151 Train Accuracy = 40.6500
------> epoch: 364 --> Test loss = 0.0104 Test Accuracy = 66.1500
epoch: 365 --> Train loss = 0.0150 Train Accuracy = 42.1020
------> epoch: 365 --> Test loss = 0.0096 Test Accuracy = 68.4400
epoch: 366 --> Train loss = 0.0150 Train Accuracy = 43.3080
------> epoch: 366 --> Test loss = 0.0091 Test Accuracy = 69.6600
epoch: 367 --> Train loss = 0.0151 Train Accuracy = 43.8580
------> epoch: 367 --> Test loss = 0.0099 Test Accuracy = 68.1800
epoch: 368 --> Train loss = 0.0151 Train Accuracy = 43.7540
------> epoch: 368 --> Test loss = 0.0100 Test Accuracy = 68.0700
epoch: 369 --> Train loss = 0.0147 Train Accuracy = 46.2900
------> epoch: 369 --> Test loss = 0.0091 Test Accuracy = 70.1500
epoch: 370 --> Train loss = 0.0150 Train Accuracy = 43.4880
------> epoch: 370 --> Test loss = 0.0094 Test Accuracy = 69.4400
epoch: 371 --> Train loss = 0.0145 Train Accuracy = 45.7560
------> epoch: 371 --> Test loss = 0.0100 Test Accuracy = 68.4700
epoch: 372 --> Train loss = 0.0147 Train Accuracy = 45.5200
------> epoch: 372 --> Test loss = 0.0101 Test Accuracy = 66.5500
epoch: 373 --> Train loss = 0.0150 Train Accuracy = 42.9020
------> epoch: 373 --> Test loss = 0.0092 Test Accuracy = 69.7400
epoch: 374 --> Train loss = 0.0147 Train Accuracy = 42.6780
------> epoch: 374 --> Test loss = 0.0088 Test Accuracy = 71.4600
epoch: 375 --> Train loss = 0.0150 Train Accuracy = 47.0580
------> epoch: 375 --> Test loss = 0.0095 Test Accuracy = 69.8800
epoch: 376 --> Train loss = 0.0149 Train Accuracy = 43.3900
------> epoch: 376 --> Test loss = 0.0104 Test Accuracy = 66.2200
epoch: 377 --> Train loss = 0.0147 Train Accuracy = 43.4900
------> epoch: 377 --> Test loss = 0.0102 Test Accuracy = 68.0400
epoch: 378 --> Train loss = 0.0147 Train Accuracy = 40.6480
------> epoch: 378 --> Test loss = 0.0088 Test Accuracy = 70.7600
epoch: 379 --> Train loss = 0.0147 Train Accuracy = 45.5160
------> epoch: 379 --> Test loss = 0.0088 Test Accuracy = 70.5900
epoch: 380 --> Train loss = 0.0147 Train Accuracy = 42.5540
------> epoch: 380 --> Test loss = 0.0091 Test Accuracy = 69.9200
epoch: 381 --> Train loss = 0.0147 Train Accuracy = 45.3700
------> epoch: 381 --> Test loss = 0.0097 Test Accuracy = 68.4800
epoch: 382 --> Train loss = 0.0147 Train Accuracy = 43.9120
------> epoch: 382 --> Test loss = 0.0097 Test Accuracy = 68.7600
epoch: 383 --> Train loss = 0.0146 Train Accuracy = 43.2360
------> epoch: 383 --> Test loss = 0.0087 Test Accuracy = 70.7200
epoch: 384 --> Train loss = 0.0151 Train Accuracy = 44.8500
------> epoch: 384 --> Test loss = 0.0093 Test Accuracy = 69.4300
epoch: 385 --> Train loss = 0.0149 Train Accuracy = 45.7120
------> epoch: 385 --> Test loss = 0.0092 Test Accuracy = 70.1600
epoch: 386 --> Train loss = 0.0152 Train Accuracy = 42.4840
------> epoch: 386 --> Test loss = 0.0090 Test Accuracy = 70.7600
epoch: 387 --> Train loss = 0.0146 Train Accuracy = 45.4240
------> epoch: 387 --> Test loss = 0.0088 Test Accuracy = 70.9100
epoch: 388 --> Train loss = 0.0152 Train Accuracy = 43.3760
------> epoch: 388 --> Test loss = 0.0096 Test Accuracy = 69.2700
epoch: 389 --> Train loss = 0.0150 Train Accuracy = 43.9820
------> epoch: 389 --> Test loss = 0.0095 Test Accuracy = 69.2500
epoch: 390 --> Train loss = 0.0146 Train Accuracy = 45.2220
------> epoch: 390 --> Test loss = 0.0101 Test Accuracy = 68.4600
epoch: 391 --> Train loss = 0.0148 Train Accuracy = 43.6120
------> epoch: 391 --> Test loss = 0.0095 Test Accuracy = 68.5500
epoch: 392 --> Train loss = 0.0153 Train Accuracy = 42.2160
------> epoch: 392 --> Test loss = 0.0102 Test Accuracy = 66.8300
epoch: 393 --> Train loss = 0.0149 Train Accuracy = 44.8360
------> epoch: 393 --> Test loss = 0.0094 Test Accuracy = 68.7700
epoch: 394 --> Train loss = 0.0145 Train Accuracy = 42.9700
------> epoch: 394 --> Test loss = 0.0095 Test Accuracy = 68.7200
epoch: 395 --> Train loss = 0.0150 Train Accuracy = 44.7300
------> epoch: 395 --> Test loss = 0.0092 Test Accuracy = 70.9300
epoch: 396 --> Train loss = 0.0150 Train Accuracy = 41.7660
------> epoch: 396 --> Test loss = 0.0097 Test Accuracy = 68.6200
epoch: 397 --> Train loss = 0.0147 Train Accuracy = 45.3420
------> epoch: 397 --> Test loss = 0.0100 Test Accuracy = 68.4200
epoch: 398 --> Train loss = 0.0147 Train Accuracy = 44.0480
------> epoch: 398 --> Test loss = 0.0095 Test Accuracy = 69.7400
epoch: 399 --> Train loss = 0.0148 Train Accuracy = 43.7280
------> epoch: 399 --> Test loss = 0.0104 Test Accuracy = 66.2700
epoch: 400 --> Train loss = 0.0149 Train Accuracy = 42.6880
------> epoch: 400 --> Test loss = 0.0089 Test Accuracy = 71.0200
epoch: 401 --> Train loss = 0.0144 Train Accuracy = 42.9320
------> epoch: 401 --> Test loss = 0.0088 Test Accuracy = 71.1100
epoch: 402 --> Train loss = 0.0147 Train Accuracy = 43.3880
------> epoch: 402 --> Test loss = 0.0098 Test Accuracy = 69.0600
epoch: 403 --> Train loss = 0.0148 Train Accuracy = 44.8260
------> epoch: 403 --> Test loss = 0.0090 Test Accuracy = 70.7400
epoch: 404 --> Train loss = 0.0151 Train Accuracy = 43.6420
------> epoch: 404 --> Test loss = 0.0102 Test Accuracy = 67.6600
epoch: 405 --> Train loss = 0.0150 Train Accuracy = 43.0980
------> epoch: 405 --> Test loss = 0.0096 Test Accuracy = 68.9200
epoch: 406 --> Train loss = 0.0149 Train Accuracy = 46.0020
------> epoch: 406 --> Test loss = 0.0091 Test Accuracy = 70.4900
epoch: 407 --> Train loss = 0.0147 Train Accuracy = 42.4480
------> epoch: 407 --> Test loss = 0.0085 Test Accuracy = 71.8100
epoch: 408 --> Train loss = 0.0146 Train Accuracy = 42.8160
------> epoch: 408 --> Test loss = 0.0098 Test Accuracy = 69.2000
epoch: 409 --> Train loss = 0.0147 Train Accuracy = 44.6980
------> epoch: 409 --> Test loss = 0.0090 Test Accuracy = 70.7700
epoch: 410 --> Train loss = 0.0151 Train Accuracy = 44.0160
------> epoch: 410 --> Test loss = 0.0088 Test Accuracy = 71.9800
epoch: 411 --> Train loss = 0.0150 Train Accuracy = 42.3880
------> epoch: 411 --> Test loss = 0.0097 Test Accuracy = 69.1100
epoch: 412 --> Train loss = 0.0147 Train Accuracy = 43.4840
------> epoch: 412 --> Test loss = 0.0095 Test Accuracy = 69.5000
epoch: 413 --> Train loss = 0.0152 Train Accuracy = 45.1120
------> epoch: 413 --> Test loss = 0.0096 Test Accuracy = 69.2200
epoch: 414 --> Train loss = 0.0148 Train Accuracy = 41.8860
------> epoch: 414 --> Test loss = 0.0092 Test Accuracy = 70.0600
epoch: 415 --> Train loss = 0.0150 Train Accuracy = 41.7360
------> epoch: 415 --> Test loss = 0.0096 Test Accuracy = 68.4200
epoch: 416 --> Train loss = 0.0147 Train Accuracy = 45.6280
------> epoch: 416 --> Test loss = 0.0102 Test Accuracy = 67.3800
epoch: 417 --> Train loss = 0.0148 Train Accuracy = 42.3300
------> epoch: 417 --> Test loss = 0.0087 Test Accuracy = 71.7300
epoch: 418 --> Train loss = 0.0149 Train Accuracy = 41.4340
------> epoch: 418 --> Test loss = 0.0098 Test Accuracy = 68.7400
epoch: 419 --> Train loss = 0.0147 Train Accuracy = 43.0380
------> epoch: 419 --> Test loss = 0.0095 Test Accuracy = 69.0300
epoch: 420 --> Train loss = 0.0147 Train Accuracy = 45.2720
------> epoch: 420 --> Test loss = 0.0085 Test Accuracy = 71.9400
epoch: 421 --> Train loss = 0.0150 Train Accuracy = 44.7380
------> epoch: 421 --> Test loss = 0.0088 Test Accuracy = 71.7500
epoch: 422 --> Train loss = 0.0148 Train Accuracy = 44.5160
------> epoch: 422 --> Test loss = 0.0102 Test Accuracy = 67.4100
epoch: 423 --> Train loss = 0.0147 Train Accuracy = 44.6520
------> epoch: 423 --> Test loss = 0.0103 Test Accuracy = 66.3200
epoch: 424 --> Train loss = 0.0150 Train Accuracy = 42.2660
------> epoch: 424 --> Test loss = 0.0090 Test Accuracy = 70.9600
epoch: 425 --> Train loss = 0.0149 Train Accuracy = 42.4160
------> epoch: 425 --> Test loss = 0.0096 Test Accuracy = 69.2900
epoch: 426 --> Train loss = 0.0148 Train Accuracy = 44.5300
------> epoch: 426 --> Test loss = 0.0085 Test Accuracy = 72.0000
epoch: 427 --> Train loss = 0.0143 Train Accuracy = 41.8740
------> epoch: 427 --> Test loss = 0.0089 Test Accuracy = 70.6100
epoch: 428 --> Train loss = 0.0143 Train Accuracy = 42.9280
------> epoch: 428 --> Test loss = 0.0096 Test Accuracy = 69.1400
epoch: 429 --> Train loss = 0.0147 Train Accuracy = 40.5040
------> epoch: 429 --> Test loss = 0.0093 Test Accuracy = 69.2900
epoch: 430 --> Train loss = 0.0146 Train Accuracy = 45.0020
------> epoch: 430 --> Test loss = 0.0108 Test Accuracy = 65.9700
epoch: 431 --> Train loss = 0.0148 Train Accuracy = 44.7180
------> epoch: 431 --> Test loss = 0.0089 Test Accuracy = 71.0800
epoch: 432 --> Train loss = 0.0147 Train Accuracy = 43.2980
------> epoch: 432 --> Test loss = 0.0094 Test Accuracy = 69.9400
epoch: 433 --> Train loss = 0.0146 Train Accuracy = 44.0320
------> epoch: 433 --> Test loss = 0.0105 Test Accuracy = 66.6600
epoch: 434 --> Train loss = 0.0150 Train Accuracy = 45.7920
------> epoch: 434 --> Test loss = 0.0096 Test Accuracy = 69.5400
epoch: 435 --> Train loss = 0.0149 Train Accuracy = 41.1740
------> epoch: 435 --> Test loss = 0.0099 Test Accuracy = 68.1900
epoch: 436 --> Train loss = 0.0149 Train Accuracy = 46.2300
------> epoch: 436 --> Test loss = 0.0107 Test Accuracy = 66.0300
epoch: 437 --> Train loss = 0.0145 Train Accuracy = 45.4080
------> epoch: 437 --> Test loss = 0.0099 Test Accuracy = 67.6300
epoch: 438 --> Train loss = 0.0144 Train Accuracy = 46.3780
------> epoch: 438 --> Test loss = 0.0097 Test Accuracy = 68.8400
epoch: 439 --> Train loss = 0.0147 Train Accuracy = 45.0860
------> epoch: 439 --> Test loss = 0.0106 Test Accuracy = 65.4900
epoch: 440 --> Train loss = 0.0143 Train Accuracy = 43.0640
------> epoch: 440 --> Test loss = 0.0099 Test Accuracy = 68.5200
epoch: 441 --> Train loss = 0.0145 Train Accuracy = 42.5940
------> epoch: 441 --> Test loss = 0.0095 Test Accuracy = 69.2200
epoch: 442 --> Train loss = 0.0149 Train Accuracy = 47.1180
------> epoch: 442 --> Test loss = 0.0086 Test Accuracy = 71.6000
epoch: 443 --> Train loss = 0.0143 Train Accuracy = 44.7740
------> epoch: 443 --> Test loss = 0.0097 Test Accuracy = 69.2100
epoch: 444 --> Train loss = 0.0146 Train Accuracy = 44.5040
------> epoch: 444 --> Test loss = 0.0092 Test Accuracy = 69.9800
epoch: 445 --> Train loss = 0.0146 Train Accuracy = 43.8380
------> epoch: 445 --> Test loss = 0.0095 Test Accuracy = 69.5300
epoch: 446 --> Train loss = 0.0149 Train Accuracy = 43.0080
------> epoch: 446 --> Test loss = 0.0095 Test Accuracy = 69.5800
epoch: 447 --> Train loss = 0.0151 Train Accuracy = 50.2560
------> epoch: 447 --> Test loss = 0.0084 Test Accuracy = 72.0300
epoch: 448 --> Train loss = 0.0147 Train Accuracy = 40.3860
------> epoch: 448 --> Test loss = 0.0089 Test Accuracy = 70.9300