In [2]:
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets("./datasets", one_hot=True, reshape=False)
import tensorflow as tf
# Parameters
learning_rate = 0.00001
epochs = 10
batch_size = 128
# Number of samples to calculate validation and accuracy
# Decrease this if you're running out of memory to calculate accuracy
test_valid_size = 256
# Network Parameters
n_classes = 10 # MNIST total classes (0-9 digits)
dropout = 0.75 # Dropout, probability to keep units
Extracting ./datasets/train-images-idx3-ubyte.gz
Extracting ./datasets/train-labels-idx1-ubyte.gz
Extracting ./datasets/t10k-images-idx3-ubyte.gz
Extracting ./datasets/t10k-labels-idx1-ubyte.gz
In [3]:
# Store layers weight & bias
weights = {
'wc1': tf.Variable(tf.random_normal([5, 5, 1, 32])),
'wc2': tf.Variable(tf.random_normal([5, 5, 32, 64])),
'wd1': tf.Variable(tf.random_normal([7*7*64, 1024])),
'out': tf.Variable(tf.random_normal([1024, n_classes]))}
biases = {
'bc1': tf.Variable(tf.random_normal([32])),
'bc2': tf.Variable(tf.random_normal([64])),
'bd1': tf.Variable(tf.random_normal([1024])),
'out': tf.Variable(tf.random_normal([n_classes]))}
In [4]:
def conv2d(x, W, b, strides=1):
x = tf.nn.conv2d(x, W, strides=[1, strides, strides, 1], padding='SAME')
x = tf.nn.bias_add(x, b)
return tf.nn.relu(x)
In [5]:
def maxpool2d(x, k=2):
return tf.nn.max_pool(
x,
ksize=[1, k, k, 1],
strides=[1, k, k, 1],
padding='SAME')
In [6]:
def conv_net(x, weights, biases, dropout):
# Layer 1 - 28*28*1 to 14*14*32
conv1 = conv2d(x, weights['wc1'], biases['bc1'])
conv1 = maxpool2d(conv1, k=2)
# Layer 2 - 14*14*32 to 7*7*64
conv2 = conv2d(conv1, weights['wc2'], biases['bc2'])
conv2 = maxpool2d(conv2, k=2)
# Fully connected layer - 7*7*64 to 1024
fc1 = tf.reshape(conv2, [-1, weights['wd1'].get_shape().as_list()[0]])
fc1 = tf.add(tf.matmul(fc1, weights['wd1']), biases['bd1'])
fc1 = tf.nn.relu(fc1)
fc1 = tf.nn.dropout(fc1, dropout)
# Output Layer - class prediction - 1024 to 10
out = tf.add(tf.matmul(fc1, weights['out']), biases['out'])
return out
In [7]:
# tf Graph input
x = tf.placeholder(tf.float32, [None, 28, 28, 1])
y = tf.placeholder(tf.float32, [None, n_classes])
keep_prob = tf.placeholder(tf.float32)
# Model
logits = conv_net(x, weights, biases, keep_prob)
# Define loss and optimizer
cost = tf.reduce_mean(\
tf.nn.softmax_cross_entropy_with_logits(logits=logits, labels=y))
optimizer = tf.train.GradientDescentOptimizer(learning_rate=learning_rate)\
.minimize(cost)
# Accuracy
correct_pred = tf.equal(tf.argmax(logits, 1), tf.argmax(y, 1))
accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))
# Initializing the variables
init = tf. global_variables_initializer()
# Launch the graph
with tf.Session() as sess:
sess.run(init)
for epoch in range(epochs):
for batch in range(mnist.train.num_examples//batch_size):
batch_x, batch_y = mnist.train.next_batch(batch_size)
sess.run(optimizer, feed_dict={
x: batch_x,
y: batch_y,
keep_prob: dropout})
# Calculate batch loss and accuracy
loss = sess.run(cost, feed_dict={
x: batch_x,
y: batch_y,
keep_prob: 1.})
valid_acc = sess.run(accuracy, feed_dict={
x: mnist.validation.images[:test_valid_size],
y: mnist.validation.labels[:test_valid_size],
keep_prob: 1.})
print('Epoch {:>2}, Batch {:>3} -'
'Loss: {:>10.4f} Validation Accuracy: {:.6f}'.format(
epoch + 1,
batch + 1,
loss,
valid_acc))
# Calculate Test Accuracy
test_acc = sess.run(accuracy, feed_dict={
x: mnist.test.images[:test_valid_size],
y: mnist.test.labels[:test_valid_size],
keep_prob: 1.})
print('Testing Accuracy: {}'.format(test_acc))
Epoch 1, Batch 1 -Loss: 68955.1562 Validation Accuracy: 0.128906
Epoch 1, Batch 2 -Loss: 46622.2500 Validation Accuracy: 0.171875
Epoch 1, Batch 3 -Loss: 45081.6250 Validation Accuracy: 0.175781
Epoch 1, Batch 4 -Loss: 40587.3984 Validation Accuracy: 0.203125
Epoch 1, Batch 5 -Loss: 33074.4844 Validation Accuracy: 0.195312
Epoch 1, Batch 6 -Loss: 29567.8438 Validation Accuracy: 0.246094
Epoch 1, Batch 7 -Loss: 27875.5000 Validation Accuracy: 0.257812
Epoch 1, Batch 8 -Loss: 25540.8750 Validation Accuracy: 0.292969
Epoch 1, Batch 9 -Loss: 22063.2422 Validation Accuracy: 0.273438
Epoch 1, Batch 10 -Loss: 24570.9688 Validation Accuracy: 0.273438
Epoch 1, Batch 11 -Loss: 21995.1582 Validation Accuracy: 0.285156
Epoch 1, Batch 12 -Loss: 20450.8145 Validation Accuracy: 0.296875
Epoch 1, Batch 13 -Loss: 17407.4922 Validation Accuracy: 0.289062
Epoch 1, Batch 14 -Loss: 19531.2422 Validation Accuracy: 0.308594
Epoch 1, Batch 15 -Loss: 22675.8652 Validation Accuracy: 0.312500
Epoch 1, Batch 16 -Loss: 15106.1875 Validation Accuracy: 0.324219
Epoch 1, Batch 17 -Loss: 18247.8750 Validation Accuracy: 0.320312
Epoch 1, Batch 18 -Loss: 17848.2852 Validation Accuracy: 0.300781
Epoch 1, Batch 19 -Loss: 15894.7432 Validation Accuracy: 0.304688
Epoch 1, Batch 20 -Loss: 18796.7422 Validation Accuracy: 0.324219
Epoch 1, Batch 21 -Loss: 14939.3154 Validation Accuracy: 0.351562
Epoch 1, Batch 22 -Loss: 12598.2686 Validation Accuracy: 0.328125
Epoch 1, Batch 23 -Loss: 12100.1455 Validation Accuracy: 0.347656
Epoch 1, Batch 24 -Loss: 10792.6875 Validation Accuracy: 0.371094
Epoch 1, Batch 25 -Loss: 9076.4336 Validation Accuracy: 0.378906
Epoch 1, Batch 26 -Loss: 12575.9443 Validation Accuracy: 0.398438
Epoch 1, Batch 27 -Loss: 15381.8535 Validation Accuracy: 0.406250
Epoch 1, Batch 28 -Loss: 13316.5000 Validation Accuracy: 0.398438
Epoch 1, Batch 29 -Loss: 14920.6621 Validation Accuracy: 0.402344
Epoch 1, Batch 30 -Loss: 13389.0684 Validation Accuracy: 0.421875
Epoch 1, Batch 31 -Loss: 11907.6143 Validation Accuracy: 0.417969
Epoch 1, Batch 32 -Loss: 11909.7852 Validation Accuracy: 0.417969
Epoch 1, Batch 33 -Loss: 13359.0137 Validation Accuracy: 0.429688
Epoch 1, Batch 34 -Loss: 10654.3115 Validation Accuracy: 0.414062
Epoch 1, Batch 35 -Loss: 9137.1973 Validation Accuracy: 0.437500
Epoch 1, Batch 36 -Loss: 12130.1855 Validation Accuracy: 0.433594
Epoch 1, Batch 37 -Loss: 10370.7891 Validation Accuracy: 0.437500
Epoch 1, Batch 38 -Loss: 9514.3379 Validation Accuracy: 0.437500
Epoch 1, Batch 39 -Loss: 8244.5703 Validation Accuracy: 0.441406
Epoch 1, Batch 40 -Loss: 10710.9453 Validation Accuracy: 0.464844
Epoch 1, Batch 41 -Loss: 9611.5117 Validation Accuracy: 0.457031
Epoch 1, Batch 42 -Loss: 11882.1016 Validation Accuracy: 0.468750
Epoch 1, Batch 43 -Loss: 8996.2520 Validation Accuracy: 0.468750
Epoch 1, Batch 44 -Loss: 9165.3848 Validation Accuracy: 0.472656
Epoch 1, Batch 45 -Loss: 8989.5615 Validation Accuracy: 0.492188
Epoch 1, Batch 46 -Loss: 10022.9883 Validation Accuracy: 0.484375
Epoch 1, Batch 47 -Loss: 8328.5703 Validation Accuracy: 0.488281
Epoch 1, Batch 48 -Loss: 8951.6113 Validation Accuracy: 0.500000
Epoch 1, Batch 49 -Loss: 8936.1631 Validation Accuracy: 0.503906
Epoch 1, Batch 50 -Loss: 7453.4087 Validation Accuracy: 0.507812
Epoch 1, Batch 51 -Loss: 6852.6143 Validation Accuracy: 0.507812
Epoch 1, Batch 52 -Loss: 8372.1367 Validation Accuracy: 0.503906
Epoch 1, Batch 53 -Loss: 7197.2876 Validation Accuracy: 0.519531
Epoch 1, Batch 54 -Loss: 8347.2910 Validation Accuracy: 0.515625
Epoch 1, Batch 55 -Loss: 9162.3750 Validation Accuracy: 0.515625
Epoch 1, Batch 56 -Loss: 5692.8589 Validation Accuracy: 0.527344
Epoch 1, Batch 57 -Loss: 6616.1016 Validation Accuracy: 0.523438
Epoch 1, Batch 58 -Loss: 8290.9160 Validation Accuracy: 0.531250
Epoch 1, Batch 59 -Loss: 8666.4492 Validation Accuracy: 0.527344
Epoch 1, Batch 60 -Loss: 9941.5215 Validation Accuracy: 0.527344
Epoch 1, Batch 61 -Loss: 7101.5234 Validation Accuracy: 0.531250
Epoch 1, Batch 62 -Loss: 7003.8179 Validation Accuracy: 0.554688
Epoch 1, Batch 63 -Loss: 8825.6973 Validation Accuracy: 0.546875
Epoch 1, Batch 64 -Loss: 8707.4482 Validation Accuracy: 0.566406
Epoch 1, Batch 65 -Loss: 6020.0547 Validation Accuracy: 0.570312
Epoch 1, Batch 66 -Loss: 7216.1982 Validation Accuracy: 0.574219
Epoch 1, Batch 67 -Loss: 8707.2891 Validation Accuracy: 0.582031
Epoch 1, Batch 68 -Loss: 7025.2178 Validation Accuracy: 0.582031
Epoch 1, Batch 69 -Loss: 4723.0981 Validation Accuracy: 0.601562
Epoch 1, Batch 70 -Loss: 7465.8960 Validation Accuracy: 0.601562
Epoch 1, Batch 71 -Loss: 7246.7939 Validation Accuracy: 0.597656
Epoch 1, Batch 72 -Loss: 8037.2847 Validation Accuracy: 0.589844
Epoch 1, Batch 73 -Loss: 6980.6406 Validation Accuracy: 0.609375
Epoch 1, Batch 74 -Loss: 6208.1836 Validation Accuracy: 0.605469
Epoch 1, Batch 75 -Loss: 7501.9585 Validation Accuracy: 0.621094
Epoch 1, Batch 76 -Loss: 11515.7402 Validation Accuracy: 0.617188
Epoch 1, Batch 77 -Loss: 11395.4248 Validation Accuracy: 0.613281
Epoch 1, Batch 78 -Loss: 5184.1870 Validation Accuracy: 0.613281
Epoch 1, Batch 79 -Loss: 5925.6538 Validation Accuracy: 0.625000
Epoch 1, Batch 80 -Loss: 5383.0586 Validation Accuracy: 0.617188
Epoch 1, Batch 81 -Loss: 5720.8208 Validation Accuracy: 0.621094
Epoch 1, Batch 82 -Loss: 4611.1782 Validation Accuracy: 0.621094
Epoch 1, Batch 83 -Loss: 5294.4966 Validation Accuracy: 0.613281
Epoch 1, Batch 84 -Loss: 5540.7646 Validation Accuracy: 0.621094
Epoch 1, Batch 85 -Loss: 6971.5186 Validation Accuracy: 0.628906
Epoch 1, Batch 86 -Loss: 7003.8584 Validation Accuracy: 0.621094
Epoch 1, Batch 87 -Loss: 7643.5024 Validation Accuracy: 0.621094
Epoch 1, Batch 88 -Loss: 4950.8047 Validation Accuracy: 0.617188
Epoch 1, Batch 89 -Loss: 6914.6265 Validation Accuracy: 0.617188
Epoch 1, Batch 90 -Loss: 4880.4658 Validation Accuracy: 0.628906
Epoch 1, Batch 91 -Loss: 4849.3789 Validation Accuracy: 0.636719
Epoch 1, Batch 92 -Loss: 6525.9497 Validation Accuracy: 0.636719
Epoch 1, Batch 93 -Loss: 6306.2393 Validation Accuracy: 0.640625
Epoch 1, Batch 94 -Loss: 5936.0996 Validation Accuracy: 0.640625
Epoch 1, Batch 95 -Loss: 5710.0879 Validation Accuracy: 0.640625
Epoch 1, Batch 96 -Loss: 4949.6709 Validation Accuracy: 0.640625
Epoch 1, Batch 97 -Loss: 4959.6523 Validation Accuracy: 0.648438
Epoch 1, Batch 98 -Loss: 4998.1685 Validation Accuracy: 0.644531
Epoch 1, Batch 99 -Loss: 4992.7529 Validation Accuracy: 0.640625
Epoch 1, Batch 100 -Loss: 5826.1846 Validation Accuracy: 0.640625
Epoch 1, Batch 101 -Loss: 7025.9590 Validation Accuracy: 0.656250
Epoch 1, Batch 102 -Loss: 4503.7549 Validation Accuracy: 0.656250
Epoch 1, Batch 103 -Loss: 4811.9419 Validation Accuracy: 0.652344
Epoch 1, Batch 104 -Loss: 5250.2642 Validation Accuracy: 0.656250
Epoch 1, Batch 105 -Loss: 7394.9336 Validation Accuracy: 0.656250
Epoch 1, Batch 106 -Loss: 6235.3994 Validation Accuracy: 0.660156
Epoch 1, Batch 107 -Loss: 4640.2661 Validation Accuracy: 0.656250
Epoch 1, Batch 108 -Loss: 4703.5542 Validation Accuracy: 0.671875
Epoch 1, Batch 109 -Loss: 4702.2153 Validation Accuracy: 0.671875
Epoch 1, Batch 110 -Loss: 4113.9736 Validation Accuracy: 0.667969
Epoch 1, Batch 111 -Loss: 4998.6782 Validation Accuracy: 0.667969
Epoch 1, Batch 112 -Loss: 4928.8706 Validation Accuracy: 0.664062
Epoch 1, Batch 113 -Loss: 4400.9795 Validation Accuracy: 0.671875
Epoch 1, Batch 114 -Loss: 3838.0320 Validation Accuracy: 0.687500
Epoch 1, Batch 115 -Loss: 3314.9714 Validation Accuracy: 0.679688
Epoch 1, Batch 116 -Loss: 4155.3960 Validation Accuracy: 0.675781
Epoch 1, Batch 117 -Loss: 5354.2773 Validation Accuracy: 0.671875
Epoch 1, Batch 118 -Loss: 7551.3354 Validation Accuracy: 0.652344
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Epoch 1, Batch 120 -Loss: 3033.2009 Validation Accuracy: 0.664062
Epoch 1, Batch 121 -Loss: 3636.8179 Validation Accuracy: 0.675781
Epoch 1, Batch 122 -Loss: 4403.9414 Validation Accuracy: 0.683594
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Epoch 1, Batch 131 -Loss: 3794.3308 Validation Accuracy: 0.691406
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Epoch 1, Batch 134 -Loss: 5336.8809 Validation Accuracy: 0.703125
Epoch 1, Batch 135 -Loss: 5119.6226 Validation Accuracy: 0.687500
Epoch 1, Batch 136 -Loss: 2397.9773 Validation Accuracy: 0.695312
Epoch 1, Batch 137 -Loss: 5205.5669 Validation Accuracy: 0.695312
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Epoch 1, Batch 139 -Loss: 5001.0791 Validation Accuracy: 0.695312
Epoch 1, Batch 140 -Loss: 4149.7334 Validation Accuracy: 0.699219
Epoch 1, Batch 141 -Loss: 2534.8633 Validation Accuracy: 0.714844
Epoch 1, Batch 142 -Loss: 3720.5542 Validation Accuracy: 0.703125
Epoch 1, Batch 143 -Loss: 3625.0059 Validation Accuracy: 0.714844
Epoch 1, Batch 144 -Loss: 3222.8899 Validation Accuracy: 0.718750
Epoch 1, Batch 145 -Loss: 4173.7896 Validation Accuracy: 0.726562
Epoch 1, Batch 146 -Loss: 3272.0630 Validation Accuracy: 0.730469
Epoch 1, Batch 147 -Loss: 4324.1650 Validation Accuracy: 0.734375
Epoch 1, Batch 148 -Loss: 2745.3723 Validation Accuracy: 0.734375
Epoch 1, Batch 149 -Loss: 3511.4558 Validation Accuracy: 0.730469
Epoch 1, Batch 150 -Loss: 2812.9053 Validation Accuracy: 0.734375
Epoch 1, Batch 151 -Loss: 4084.8584 Validation Accuracy: 0.730469
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Epoch 1, Batch 153 -Loss: 3437.7788 Validation Accuracy: 0.750000
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Epoch 1, Batch 155 -Loss: 5315.0352 Validation Accuracy: 0.742188
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Epoch 1, Batch 160 -Loss: 2550.0347 Validation Accuracy: 0.742188
Epoch 1, Batch 161 -Loss: 3019.7957 Validation Accuracy: 0.750000
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Epoch 1, Batch 166 -Loss: 1662.2238 Validation Accuracy: 0.746094
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Epoch 1, Batch 169 -Loss: 3949.4219 Validation Accuracy: 0.765625
Epoch 1, Batch 170 -Loss: 4708.5098 Validation Accuracy: 0.761719
Epoch 1, Batch 171 -Loss: 2422.6594 Validation Accuracy: 0.757812
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Epoch 1, Batch 174 -Loss: 4727.0410 Validation Accuracy: 0.753906
Epoch 1, Batch 175 -Loss: 2837.3140 Validation Accuracy: 0.765625
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Epoch 1, Batch 185 -Loss: 3366.2146 Validation Accuracy: 0.773438
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Epoch 1, Batch 189 -Loss: 4334.8423 Validation Accuracy: 0.769531
Epoch 1, Batch 190 -Loss: 2884.3447 Validation Accuracy: 0.789062
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Epoch 1, Batch 196 -Loss: 2741.1724 Validation Accuracy: 0.785156
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Epoch 1, Batch 202 -Loss: 3327.5000 Validation Accuracy: 0.769531
Epoch 1, Batch 203 -Loss: 4139.4077 Validation Accuracy: 0.785156
Epoch 1, Batch 204 -Loss: 2506.2585 Validation Accuracy: 0.781250
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Epoch 1, Batch 206 -Loss: 4541.5273 Validation Accuracy: 0.765625
Epoch 1, Batch 207 -Loss: 3416.7651 Validation Accuracy: 0.757812
Epoch 1, Batch 208 -Loss: 2259.3911 Validation Accuracy: 0.761719
Epoch 1, Batch 209 -Loss: 3879.3208 Validation Accuracy: 0.757812
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Epoch 1, Batch 212 -Loss: 3283.2534 Validation Accuracy: 0.769531
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Epoch 1, Batch 233 -Loss: 2371.9202 Validation Accuracy: 0.781250
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Epoch 1, Batch 235 -Loss: 2341.1230 Validation Accuracy: 0.773438
Epoch 1, Batch 236 -Loss: 3402.2375 Validation Accuracy: 0.781250
Epoch 1, Batch 237 -Loss: 2174.2695 Validation Accuracy: 0.777344
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Epoch 1, Batch 249 -Loss: 2808.1328 Validation Accuracy: 0.789062
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Epoch 4, Batch 2 -Loss: 1022.8265 Validation Accuracy: 0.843750
Epoch 4, Batch 3 -Loss: 536.9534 Validation Accuracy: 0.839844
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Epoch 7, Batch 1 -Loss: 320.3347 Validation Accuracy: 0.847656
Epoch 7, Batch 2 -Loss: 487.1453 Validation Accuracy: 0.847656
Epoch 7, Batch 3 -Loss: 297.4707 Validation Accuracy: 0.847656
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Epoch 8, Batch 2 -Loss: 256.2677 Validation Accuracy: 0.871094
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Epoch 9, Batch 1 -Loss: 275.8586 Validation Accuracy: 0.847656
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Epoch 9, Batch 428 -Loss: 212.8190 Validation Accuracy: 0.851562
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Epoch 10, Batch 1 -Loss: 182.8447 Validation Accuracy: 0.851562
Epoch 10, Batch 2 -Loss: 277.5263 Validation Accuracy: 0.855469
Epoch 10, Batch 3 -Loss: 190.5294 Validation Accuracy: 0.855469
Epoch 10, Batch 4 -Loss: 213.0079 Validation Accuracy: 0.855469
Epoch 10, Batch 5 -Loss: 230.2874 Validation Accuracy: 0.855469
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Epoch 10, Batch 8 -Loss: 224.9131 Validation Accuracy: 0.855469
Epoch 10, Batch 9 -Loss: 265.7495 Validation Accuracy: 0.855469
Epoch 10, Batch 10 -Loss: 296.6539 Validation Accuracy: 0.851562
Epoch 10, Batch 11 -Loss: 192.7961 Validation Accuracy: 0.847656
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Epoch 10, Batch 306 -Loss: 210.0687 Validation Accuracy: 0.851562
Epoch 10, Batch 307 -Loss: 262.7710 Validation Accuracy: 0.851562
Epoch 10, Batch 308 -Loss: 383.4124 Validation Accuracy: 0.851562
Epoch 10, Batch 309 -Loss: 336.5646 Validation Accuracy: 0.851562
Epoch 10, Batch 310 -Loss: 244.2411 Validation Accuracy: 0.851562
Epoch 10, Batch 311 -Loss: 211.3526 Validation Accuracy: 0.851562
Epoch 10, Batch 312 -Loss: 299.9221 Validation Accuracy: 0.851562
Epoch 10, Batch 313 -Loss: 192.0581 Validation Accuracy: 0.851562
Epoch 10, Batch 314 -Loss: 215.3174 Validation Accuracy: 0.851562
Epoch 10, Batch 315 -Loss: 157.9661 Validation Accuracy: 0.851562
Epoch 10, Batch 316 -Loss: 148.0336 Validation Accuracy: 0.851562
Epoch 10, Batch 317 -Loss: 268.0213 Validation Accuracy: 0.851562
Epoch 10, Batch 318 -Loss: 244.5275 Validation Accuracy: 0.847656
Epoch 10, Batch 319 -Loss: 269.5344 Validation Accuracy: 0.843750
Epoch 10, Batch 320 -Loss: 326.4865 Validation Accuracy: 0.843750
Epoch 10, Batch 321 -Loss: 204.1736 Validation Accuracy: 0.843750
Epoch 10, Batch 322 -Loss: 340.5053 Validation Accuracy: 0.847656
Epoch 10, Batch 323 -Loss: 253.0433 Validation Accuracy: 0.843750
Epoch 10, Batch 324 -Loss: 162.8828 Validation Accuracy: 0.847656
Epoch 10, Batch 325 -Loss: 346.3888 Validation Accuracy: 0.847656
Epoch 10, Batch 326 -Loss: 304.2673 Validation Accuracy: 0.847656
Epoch 10, Batch 327 -Loss: 333.2947 Validation Accuracy: 0.847656
Epoch 10, Batch 328 -Loss: 252.5321 Validation Accuracy: 0.847656
Epoch 10, Batch 329 -Loss: 209.1962 Validation Accuracy: 0.847656
Epoch 10, Batch 330 -Loss: 318.3674 Validation Accuracy: 0.847656
Epoch 10, Batch 331 -Loss: 317.7911 Validation Accuracy: 0.843750
Epoch 10, Batch 332 -Loss: 178.3752 Validation Accuracy: 0.839844
Epoch 10, Batch 333 -Loss: 269.3614 Validation Accuracy: 0.839844
Epoch 10, Batch 334 -Loss: 423.8649 Validation Accuracy: 0.839844
Epoch 10, Batch 335 -Loss: 197.3669 Validation Accuracy: 0.843750
Epoch 10, Batch 336 -Loss: 254.4191 Validation Accuracy: 0.847656
Epoch 10, Batch 337 -Loss: 176.6880 Validation Accuracy: 0.843750
Epoch 10, Batch 338 -Loss: 156.2082 Validation Accuracy: 0.843750
Epoch 10, Batch 339 -Loss: 130.4751 Validation Accuracy: 0.847656
Epoch 10, Batch 340 -Loss: 159.4729 Validation Accuracy: 0.847656
Epoch 10, Batch 341 -Loss: 251.8539 Validation Accuracy: 0.847656
Epoch 10, Batch 342 -Loss: 223.4588 Validation Accuracy: 0.843750
Epoch 10, Batch 343 -Loss: 139.2714 Validation Accuracy: 0.839844
Epoch 10, Batch 344 -Loss: 197.0405 Validation Accuracy: 0.843750
Epoch 10, Batch 345 -Loss: 222.4214 Validation Accuracy: 0.847656
Epoch 10, Batch 346 -Loss: 140.8755 Validation Accuracy: 0.847656
Epoch 10, Batch 347 -Loss: 277.2391 Validation Accuracy: 0.843750
Epoch 10, Batch 348 -Loss: 288.4977 Validation Accuracy: 0.843750
Epoch 10, Batch 349 -Loss: 183.2747 Validation Accuracy: 0.843750
Epoch 10, Batch 350 -Loss: 234.2558 Validation Accuracy: 0.843750
Epoch 10, Batch 351 -Loss: 162.8089 Validation Accuracy: 0.847656
Epoch 10, Batch 352 -Loss: 279.8721 Validation Accuracy: 0.855469
Epoch 10, Batch 353 -Loss: 270.5099 Validation Accuracy: 0.851562
Epoch 10, Batch 354 -Loss: 204.6241 Validation Accuracy: 0.847656
Epoch 10, Batch 355 -Loss: 388.1801 Validation Accuracy: 0.847656
Epoch 10, Batch 356 -Loss: 134.4018 Validation Accuracy: 0.847656
Epoch 10, Batch 357 -Loss: 361.1046 Validation Accuracy: 0.847656
Epoch 10, Batch 358 -Loss: 218.2697 Validation Accuracy: 0.851562
Epoch 10, Batch 359 -Loss: 215.2564 Validation Accuracy: 0.851562
Epoch 10, Batch 360 -Loss: 213.2860 Validation Accuracy: 0.855469
Epoch 10, Batch 361 -Loss: 217.3979 Validation Accuracy: 0.851562
Epoch 10, Batch 362 -Loss: 164.1691 Validation Accuracy: 0.855469
Epoch 10, Batch 363 -Loss: 206.1730 Validation Accuracy: 0.855469
Epoch 10, Batch 364 -Loss: 175.1278 Validation Accuracy: 0.855469
Epoch 10, Batch 365 -Loss: 106.0941 Validation Accuracy: 0.855469
Epoch 10, Batch 366 -Loss: 331.8605 Validation Accuracy: 0.859375
Epoch 10, Batch 367 -Loss: 315.7259 Validation Accuracy: 0.863281
Epoch 10, Batch 368 -Loss: 235.2732 Validation Accuracy: 0.855469
Epoch 10, Batch 369 -Loss: 221.3303 Validation Accuracy: 0.851562
Epoch 10, Batch 370 -Loss: 267.0507 Validation Accuracy: 0.855469
Epoch 10, Batch 371 -Loss: 320.8347 Validation Accuracy: 0.859375
Epoch 10, Batch 372 -Loss: 186.1115 Validation Accuracy: 0.859375
Epoch 10, Batch 373 -Loss: 137.2839 Validation Accuracy: 0.855469
Epoch 10, Batch 374 -Loss: 215.3467 Validation Accuracy: 0.851562
Epoch 10, Batch 375 -Loss: 236.5959 Validation Accuracy: 0.859375
Epoch 10, Batch 376 -Loss: 149.1123 Validation Accuracy: 0.859375
Epoch 10, Batch 377 -Loss: 382.7107 Validation Accuracy: 0.855469
Epoch 10, Batch 378 -Loss: 120.3204 Validation Accuracy: 0.855469
Epoch 10, Batch 379 -Loss: 222.8512 Validation Accuracy: 0.855469
Epoch 10, Batch 380 -Loss: 254.5342 Validation Accuracy: 0.855469
Epoch 10, Batch 381 -Loss: 170.4722 Validation Accuracy: 0.859375
Epoch 10, Batch 382 -Loss: 297.3031 Validation Accuracy: 0.855469
Epoch 10, Batch 383 -Loss: 312.8719 Validation Accuracy: 0.851562
Epoch 10, Batch 384 -Loss: 211.3493 Validation Accuracy: 0.855469
Epoch 10, Batch 385 -Loss: 276.5640 Validation Accuracy: 0.851562
Epoch 10, Batch 386 -Loss: 343.1379 Validation Accuracy: 0.851562
Epoch 10, Batch 387 -Loss: 155.0746 Validation Accuracy: 0.855469
Epoch 10, Batch 388 -Loss: 180.5411 Validation Accuracy: 0.851562
Epoch 10, Batch 389 -Loss: 223.0739 Validation Accuracy: 0.855469
Epoch 10, Batch 390 -Loss: 235.8642 Validation Accuracy: 0.859375
Epoch 10, Batch 391 -Loss: 179.2617 Validation Accuracy: 0.855469
Epoch 10, Batch 392 -Loss: 142.9981 Validation Accuracy: 0.851562
Epoch 10, Batch 393 -Loss: 219.5248 Validation Accuracy: 0.855469
Epoch 10, Batch 394 -Loss: 206.1728 Validation Accuracy: 0.855469
Epoch 10, Batch 395 -Loss: 188.4494 Validation Accuracy: 0.851562
Epoch 10, Batch 396 -Loss: 261.8113 Validation Accuracy: 0.855469
Epoch 10, Batch 397 -Loss: 238.8462 Validation Accuracy: 0.851562
Epoch 10, Batch 398 -Loss: 170.5622 Validation Accuracy: 0.851562
Epoch 10, Batch 399 -Loss: 218.0620 Validation Accuracy: 0.847656
Epoch 10, Batch 400 -Loss: 265.4469 Validation Accuracy: 0.843750
Epoch 10, Batch 401 -Loss: 154.8608 Validation Accuracy: 0.843750
Epoch 10, Batch 402 -Loss: 264.7904 Validation Accuracy: 0.843750
Epoch 10, Batch 403 -Loss: 309.5742 Validation Accuracy: 0.847656
Epoch 10, Batch 404 -Loss: 158.3135 Validation Accuracy: 0.843750
Epoch 10, Batch 405 -Loss: 309.2166 Validation Accuracy: 0.843750
Epoch 10, Batch 406 -Loss: 190.3871 Validation Accuracy: 0.843750
Epoch 10, Batch 407 -Loss: 246.1684 Validation Accuracy: 0.843750
Epoch 10, Batch 408 -Loss: 121.5727 Validation Accuracy: 0.843750
Epoch 10, Batch 409 -Loss: 241.9741 Validation Accuracy: 0.847656
Epoch 10, Batch 410 -Loss: 262.3614 Validation Accuracy: 0.843750
Epoch 10, Batch 411 -Loss: 96.0894 Validation Accuracy: 0.847656
Epoch 10, Batch 412 -Loss: 304.5662 Validation Accuracy: 0.839844
Epoch 10, Batch 413 -Loss: 186.0686 Validation Accuracy: 0.843750
Epoch 10, Batch 414 -Loss: 219.9587 Validation Accuracy: 0.839844
Epoch 10, Batch 415 -Loss: 146.1722 Validation Accuracy: 0.839844
Epoch 10, Batch 416 -Loss: 133.7537 Validation Accuracy: 0.839844
Epoch 10, Batch 417 -Loss: 114.7576 Validation Accuracy: 0.839844
Epoch 10, Batch 418 -Loss: 168.4944 Validation Accuracy: 0.839844
Epoch 10, Batch 419 -Loss: 253.2984 Validation Accuracy: 0.839844
Epoch 10, Batch 420 -Loss: 317.3074 Validation Accuracy: 0.839844
Epoch 10, Batch 421 -Loss: 293.6424 Validation Accuracy: 0.839844
Epoch 10, Batch 422 -Loss: 341.6960 Validation Accuracy: 0.839844
Epoch 10, Batch 423 -Loss: 124.5185 Validation Accuracy: 0.839844
Epoch 10, Batch 424 -Loss: 215.6124 Validation Accuracy: 0.839844
Epoch 10, Batch 425 -Loss: 409.5372 Validation Accuracy: 0.839844
Epoch 10, Batch 426 -Loss: 325.0568 Validation Accuracy: 0.839844
Epoch 10, Batch 427 -Loss: 435.9743 Validation Accuracy: 0.839844
Epoch 10, Batch 428 -Loss: 291.7277 Validation Accuracy: 0.839844
Epoch 10, Batch 429 -Loss: 230.9131 Validation Accuracy: 0.843750
Testing Accuracy: 0.83203125
In [ ]:
Content source: darienmt/intro-to-tensorflow
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