API tools faq
paste
Advertisement
ZdenekM

tensorflow_ros - no images in the category testing

ZdenekM
Jan 13th, 2017
197
0
Never
Add comment
Not a member of Pastebin yet? Sign Up, it unlocks many cool features!
text 87.46 KB | None | 0 0
raw download clone embed print report
  1. imaterna@pcspanel3:~/catkin_ed_ws$ rosrun tensorflow_ros_rqt train_gui
  2. Starting TensorBoard 39 on port 6006
  3. (You can navigate to http://127.0.1.1:6006)
  4. Looking for images in 'profile'
  5. Looking for images in 'small_bracket'
  6. Looking for images in 'screw'
  7. Looking for images in 'big_bracket'
  8. Looking for images in 'cover'
  9. 100 bottleneck files created.
  10. WARNING:tensorflow:From /home/imaterna/catkin_ed_ws/src/image_recognition/tensorflow_ros/src/tensorflow_ros/tf_retrain.py:711 in variable_summaries.: scalar_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
  11. Instructions for updating:
  12. Please switch to tf.summary.scalar. Note that tf.summary.scalar uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on the scope they are created in. Also, passing a tensor or list of tags to a scalar summary op is no longer supported.
  13. WARNING:tensorflow:From /home/imaterna/catkin_ed_ws/src/image_recognition/tensorflow_ros/src/tensorflow_ros/tf_retrain.py:714 in variable_summaries.: scalar_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
  14. Instructions for updating:
  15. Please switch to tf.summary.scalar. Note that tf.summary.scalar uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on the scope they are created in. Also, passing a tensor or list of tags to a scalar summary op is no longer supported.
  16. WARNING:tensorflow:From /home/imaterna/catkin_ed_ws/src/image_recognition/tensorflow_ros/src/tensorflow_ros/tf_retrain.py:715 in variable_summaries.: scalar_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
  17. Instructions for updating:
  18. Please switch to tf.summary.scalar. Note that tf.summary.scalar uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on the scope they are created in. Also, passing a tensor or list of tags to a scalar summary op is no longer supported.
  19. WARNING:tensorflow:From /home/imaterna/catkin_ed_ws/src/image_recognition/tensorflow_ros/src/tensorflow_ros/tf_retrain.py:716 in variable_summaries.: scalar_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
  20. Instructions for updating:
  21. Please switch to tf.summary.scalar. Note that tf.summary.scalar uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on the scope they are created in. Also, passing a tensor or list of tags to a scalar summary op is no longer supported.
  22. WARNING:tensorflow:From /home/imaterna/catkin_ed_ws/src/image_recognition/tensorflow_ros/src/tensorflow_ros/tf_retrain.py:717 in variable_summaries.: histogram_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
  23. Instructions for updating:
  24. Please switch to tf.summary.histogram. Note that tf.summary.histogram uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on their scope.
  25. WARNING:tensorflow:From /home/imaterna/catkin_ed_ws/src/image_recognition/tensorflow_ros/src/tensorflow_ros/tf_retrain.py:711 in variable_summaries.: scalar_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
  26. Instructions for updating:
  27. Please switch to tf.summary.scalar. Note that tf.summary.scalar uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on the scope they are created in. Also, passing a tensor or list of tags to a scalar summary op is no longer supported.
  28. WARNING:tensorflow:From /home/imaterna/catkin_ed_ws/src/image_recognition/tensorflow_ros/src/tensorflow_ros/tf_retrain.py:714 in variable_summaries.: scalar_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
  29. Instructions for updating:
  30. Please switch to tf.summary.scalar. Note that tf.summary.scalar uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on the scope they are created in. Also, passing a tensor or list of tags to a scalar summary op is no longer supported.
  31. WARNING:tensorflow:From /home/imaterna/catkin_ed_ws/src/image_recognition/tensorflow_ros/src/tensorflow_ros/tf_retrain.py:715 in variable_summaries.: scalar_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
  32. Instructions for updating:
  33. Please switch to tf.summary.scalar. Note that tf.summary.scalar uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on the scope they are created in. Also, passing a tensor or list of tags to a scalar summary op is no longer supported.
  34. WARNING:tensorflow:From /home/imaterna/catkin_ed_ws/src/image_recognition/tensorflow_ros/src/tensorflow_ros/tf_retrain.py:716 in variable_summaries.: scalar_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
  35. Instructions for updating:
  36. Please switch to tf.summary.scalar. Note that tf.summary.scalar uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on the scope they are created in. Also, passing a tensor or list of tags to a scalar summary op is no longer supported.
  37. WARNING:tensorflow:From /home/imaterna/catkin_ed_ws/src/image_recognition/tensorflow_ros/src/tensorflow_ros/tf_retrain.py:717 in variable_summaries.: histogram_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
  38. Instructions for updating:
  39. Please switch to tf.summary.histogram. Note that tf.summary.histogram uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on their scope.
  40. WARNING:tensorflow:From /home/imaterna/catkin_ed_ws/src/image_recognition/tensorflow_ros/src/tensorflow_ros/tf_retrain.py:761 in add_final_training_ops.: histogram_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
  41. Instructions for updating:
  42. Please switch to tf.summary.histogram. Note that tf.summary.histogram uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on their scope.
  43. WARNING:tensorflow:From /home/imaterna/catkin_ed_ws/src/image_recognition/tensorflow_ros/src/tensorflow_ros/tf_retrain.py:764 in add_final_training_ops.: histogram_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
  44. Instructions for updating:
  45. Please switch to tf.summary.histogram. Note that tf.summary.histogram uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on their scope.
  46. WARNING:tensorflow:From /home/imaterna/catkin_ed_ws/src/image_recognition/tensorflow_ros/src/tensorflow_ros/tf_retrain.py:771 in add_final_training_ops.: scalar_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
  47. Instructions for updating:
  48. Please switch to tf.summary.scalar. Note that tf.summary.scalar uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on the scope they are created in. Also, passing a tensor or list of tags to a scalar summary op is no longer supported.
  49. WARNING:tensorflow:From /home/imaterna/catkin_ed_ws/src/image_recognition/tensorflow_ros/src/tensorflow_ros/tf_retrain.py:798 in add_evaluation_step.: scalar_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
  50. Instructions for updating:
  51. Please switch to tf.summary.scalar. Note that tf.summary.scalar uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on the scope they are created in. Also, passing a tensor or list of tags to a scalar summary op is no longer supported.
  52. WARNING:tensorflow:From /home/imaterna/catkin_ed_ws/src/image_recognition/tensorflow_ros/src/tensorflow_ros/tf_retrain.py:852 in main.: merge_all_summaries (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
  53. Instructions for updating:
  54. Please switch to tf.summary.merge_all.
  55. WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/logging_ops.py:264 in merge_all_summaries.: merge_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
  56. Instructions for updating:
  57. Please switch to tf.summary.merge.
  58. WARNING:tensorflow:From /home/imaterna/catkin_ed_ws/src/image_recognition/tensorflow_ros/src/tensorflow_ros/tf_retrain.py:854 in main.: __init__ (from tensorflow.python.training.summary_io) is deprecated and will be removed after 2016-11-30.
  59. Instructions for updating:
  60. Please switch to tf.summary.FileWriter. The interface and behavior is the same; this is just a rename.
  61. WARNING:tensorflow:From /home/imaterna/catkin_ed_ws/src/image_recognition/tensorflow_ros/src/tensorflow_ros/tf_retrain.py:855 in main.: __init__ (from tensorflow.python.training.summary_io) is deprecated and will be removed after 2016-11-30.
  62. Instructions for updating:
  63. Please switch to tf.summary.FileWriter. The interface and behavior is the same; this is just a rename.
  64. WARNING:tensorflow:From /home/imaterna/catkin_ed_ws/src/image_recognition/tensorflow_ros/src/tensorflow_ros/tf_retrain.py:858 in main.: initialize_all_variables (from tensorflow.python.ops.variables) is deprecated and will be removed after 2017-03-02.
  65. Instructions for updating:
  66. Use `tf.global_variables_initializer` instead.
  67. 2017-01-13 08:58:26.417535: Step 0: Train accuracy = 69.0%
  68. 2017-01-13 08:58:26.417622: Step 0: Cross entropy = 1.502139
  69. 2017-01-13 08:58:26.489079: Step 0: Validation accuracy = 75.0%
  70. 2017-01-13 08:58:27.160932: Step 10: Train accuracy = 99.0%
  71. 2017-01-13 08:58:27.160997: Step 10: Cross entropy = 0.901265
  72. 2017-01-13 08:58:27.223131: Step 10: Validation accuracy = 100.0%
  73. 2017-01-13 08:58:27.893188: Step 20: Train accuracy = 99.0%
  74. 2017-01-13 08:58:27.893260: Step 20: Cross entropy = 0.624344
  75. 2017-01-13 08:58:27.955774: Step 20: Validation accuracy = 100.0%
  76. 2017-01-13 08:58:28.614513: Step 30: Train accuracy = 100.0%
  77. 2017-01-13 08:58:28.614597: Step 30: Cross entropy = 0.435087
  78. 2017-01-13 08:58:28.676991: Step 30: Validation accuracy = 100.0%
  79. 2017-01-13 08:58:29.343643: Step 40: Train accuracy = 99.0%
  80. 2017-01-13 08:58:29.343761: Step 40: Cross entropy = 0.369204
  81. 2017-01-13 08:58:29.405670: Step 40: Validation accuracy = 100.0%
  82. 2017-01-13 08:58:30.072931: Step 50: Train accuracy = 100.0%
  83. 2017-01-13 08:58:30.073022: Step 50: Cross entropy = 0.308133
  84. 2017-01-13 08:58:30.135304: Step 50: Validation accuracy = 100.0%
  85. 2017-01-13 08:58:30.782920: Step 60: Train accuracy = 100.0%
  86. 2017-01-13 08:58:30.783143: Step 60: Cross entropy = 0.261100
  87. 2017-01-13 08:58:30.846139: Step 60: Validation accuracy = 100.0%
  88. 2017-01-13 08:58:31.499432: Step 70: Train accuracy = 100.0%
  89. 2017-01-13 08:58:31.499514: Step 70: Cross entropy = 0.225515
  90. 2017-01-13 08:58:31.558806: Step 70: Validation accuracy = 100.0%
  91. 2017-01-13 08:58:32.224622: Step 80: Train accuracy = 100.0%
  92. 2017-01-13 08:58:32.224826: Step 80: Cross entropy = 0.201154
  93. 2017-01-13 08:58:32.288589: Step 80: Validation accuracy = 100.0%
  94. 2017-01-13 08:58:32.959702: Step 90: Train accuracy = 100.0%
  95. 2017-01-13 08:58:32.959834: Step 90: Cross entropy = 0.177564
  96. 2017-01-13 08:58:33.021757: Step 90: Validation accuracy = 100.0%
  97. 2017-01-13 08:58:33.682048: Step 100: Train accuracy = 100.0%
  98. 2017-01-13 08:58:33.682139: Step 100: Cross entropy = 0.151484
  99. 2017-01-13 08:58:33.743100: Step 100: Validation accuracy = 100.0%
  100. 2017-01-13 08:58:34.389634: Step 110: Train accuracy = 100.0%
  101. 2017-01-13 08:58:34.389812: Step 110: Cross entropy = 0.132569
  102. 2017-01-13 08:58:34.451849: Step 110: Validation accuracy = 100.0%
  103. 2017-01-13 08:58:35.127664: Step 120: Train accuracy = 100.0%
  104. 2017-01-13 08:58:35.127778: Step 120: Cross entropy = 0.141525
  105. 2017-01-13 08:58:35.188890: Step 120: Validation accuracy = 100.0%
  106. 2017-01-13 08:58:35.868276: Step 130: Train accuracy = 100.0%
  107. 2017-01-13 08:58:35.868358: Step 130: Cross entropy = 0.127561
  108. 2017-01-13 08:58:35.931595: Step 130: Validation accuracy = 100.0%
  109. 2017-01-13 08:58:36.583340: Step 140: Train accuracy = 100.0%
  110. 2017-01-13 08:58:36.583432: Step 140: Cross entropy = 0.115266
  111. 2017-01-13 08:58:36.645873: Step 140: Validation accuracy = 100.0%
  112. 2017-01-13 08:58:37.289061: Step 150: Train accuracy = 100.0%
  113. 2017-01-13 08:58:37.289168: Step 150: Cross entropy = 0.098158
  114. 2017-01-13 08:58:37.350283: Step 150: Validation accuracy = 100.0%
  115. 2017-01-13 08:58:38.013078: Step 160: Train accuracy = 100.0%
  116. 2017-01-13 08:58:38.013161: Step 160: Cross entropy = 0.098014
  117. 2017-01-13 08:58:38.075730: Step 160: Validation accuracy = 100.0%
  118. 2017-01-13 08:58:38.721989: Step 170: Train accuracy = 100.0%
  119. 2017-01-13 08:58:38.722176: Step 170: Cross entropy = 0.088031
  120. 2017-01-13 08:58:38.787918: Step 170: Validation accuracy = 100.0%
  121. 2017-01-13 08:58:39.449006: Step 180: Train accuracy = 100.0%
  122. 2017-01-13 08:58:39.449125: Step 180: Cross entropy = 0.096300
  123. 2017-01-13 08:58:39.509563: Step 180: Validation accuracy = 100.0%
  124. 2017-01-13 08:58:40.158432: Step 190: Train accuracy = 100.0%
  125. 2017-01-13 08:58:40.158514: Step 190: Cross entropy = 0.093560
  126. 2017-01-13 08:58:40.220206: Step 190: Validation accuracy = 100.0%
  127. 2017-01-13 08:58:40.885950: Step 200: Train accuracy = 100.0%
  128. 2017-01-13 08:58:40.886177: Step 200: Cross entropy = 0.072826
  129. 2017-01-13 08:58:40.948142: Step 200: Validation accuracy = 100.0%
  130. 2017-01-13 08:58:41.605006: Step 210: Train accuracy = 100.0%
  131. 2017-01-13 08:58:41.605182: Step 210: Cross entropy = 0.075436
  132. 2017-01-13 08:58:41.668129: Step 210: Validation accuracy = 100.0%
  133. 2017-01-13 08:58:42.315327: Step 220: Train accuracy = 100.0%
  134. 2017-01-13 08:58:42.315416: Step 220: Cross entropy = 0.079677
  135. 2017-01-13 08:58:42.376605: Step 220: Validation accuracy = 100.0%
  136. 2017-01-13 08:58:43.028134: Step 230: Train accuracy = 100.0%
  137. 2017-01-13 08:58:43.028302: Step 230: Cross entropy = 0.069014
  138. 2017-01-13 08:58:43.092669: Step 230: Validation accuracy = 100.0%
  139. 2017-01-13 08:58:43.759343: Step 240: Train accuracy = 100.0%
  140. 2017-01-13 08:58:43.759481: Step 240: Cross entropy = 0.067829
  141. 2017-01-13 08:58:43.821353: Step 240: Validation accuracy = 100.0%
  142. 2017-01-13 08:58:44.487771: Step 250: Train accuracy = 100.0%
  143. 2017-01-13 08:58:44.487859: Step 250: Cross entropy = 0.059771
  144. 2017-01-13 08:58:44.551133: Step 250: Validation accuracy = 100.0%
  145. 2017-01-13 08:58:45.211901: Step 260: Train accuracy = 100.0%
  146. 2017-01-13 08:58:45.211986: Step 260: Cross entropy = 0.067287
  147. 2017-01-13 08:58:45.272816: Step 260: Validation accuracy = 100.0%
  148. 2017-01-13 08:58:45.928640: Step 270: Train accuracy = 100.0%
  149. 2017-01-13 08:58:45.928780: Step 270: Cross entropy = 0.058999
  150. 2017-01-13 08:58:45.988761: Step 270: Validation accuracy = 100.0%
  151. 2017-01-13 08:58:46.632183: Step 280: Train accuracy = 100.0%
  152. 2017-01-13 08:58:46.633409: Step 280: Cross entropy = 0.057394
  153. 2017-01-13 08:58:46.694152: Step 280: Validation accuracy = 100.0%
  154. 2017-01-13 08:58:47.349410: Step 290: Train accuracy = 100.0%
  155. 2017-01-13 08:58:47.349494: Step 290: Cross entropy = 0.050713
  156. 2017-01-13 08:58:47.411270: Step 290: Validation accuracy = 100.0%
  157. 2017-01-13 08:58:48.075813: Step 300: Train accuracy = 100.0%
  158. 2017-01-13 08:58:48.075911: Step 300: Cross entropy = 0.052190
  159. 2017-01-13 08:58:48.138730: Step 300: Validation accuracy = 100.0%
  160. 2017-01-13 08:58:48.804634: Step 310: Train accuracy = 100.0%
  161. 2017-01-13 08:58:48.804806: Step 310: Cross entropy = 0.060916
  162. 2017-01-13 08:58:48.866428: Step 310: Validation accuracy = 100.0%
  163. 2017-01-13 08:58:49.533093: Step 320: Train accuracy = 100.0%
  164. 2017-01-13 08:58:49.533189: Step 320: Cross entropy = 0.054555
  165. 2017-01-13 08:58:49.596211: Step 320: Validation accuracy = 100.0%
  166. 2017-01-13 08:58:50.263440: Step 330: Train accuracy = 100.0%
  167. 2017-01-13 08:58:50.263595: Step 330: Cross entropy = 0.046449
  168. 2017-01-13 08:58:50.324855: Step 330: Validation accuracy = 100.0%
  169. 2017-01-13 08:58:50.987724: Step 340: Train accuracy = 100.0%
  170. 2017-01-13 08:58:50.987811: Step 340: Cross entropy = 0.044644
  171. 2017-01-13 08:58:51.050040: Step 340: Validation accuracy = 100.0%
  172. 2017-01-13 08:58:51.717682: Step 350: Train accuracy = 100.0%
  173. 2017-01-13 08:58:51.717764: Step 350: Cross entropy = 0.044836
  174. 2017-01-13 08:58:51.779555: Step 350: Validation accuracy = 100.0%
  175. 2017-01-13 08:58:52.447890: Step 360: Train accuracy = 100.0%
  176. 2017-01-13 08:58:52.448011: Step 360: Cross entropy = 0.048856
  177. 2017-01-13 08:58:52.512517: Step 360: Validation accuracy = 100.0%
  178. 2017-01-13 08:58:53.169727: Step 370: Train accuracy = 100.0%
  179. 2017-01-13 08:58:53.169815: Step 370: Cross entropy = 0.039329
  180. 2017-01-13 08:58:53.230024: Step 370: Validation accuracy = 100.0%
  181. 2017-01-13 08:58:53.891454: Step 380: Train accuracy = 100.0%
  182. 2017-01-13 08:58:53.891527: Step 380: Cross entropy = 0.037947
  183. 2017-01-13 08:58:53.952747: Step 380: Validation accuracy = 100.0%
  184. 2017-01-13 08:58:54.609823: Step 390: Train accuracy = 100.0%
  185. 2017-01-13 08:58:54.609962: Step 390: Cross entropy = 0.037724
  186. 2017-01-13 08:58:54.673026: Step 390: Validation accuracy = 100.0%
  187. 2017-01-13 08:58:55.351055: Step 400: Train accuracy = 100.0%
  188. 2017-01-13 08:58:55.351247: Step 400: Cross entropy = 0.037738
  189. 2017-01-13 08:58:55.415879: Step 400: Validation accuracy = 100.0%
  190. 2017-01-13 08:58:56.116590: Step 410: Train accuracy = 100.0%
  191. 2017-01-13 08:58:56.116660: Step 410: Cross entropy = 0.032751
  192. 2017-01-13 08:58:56.184538: Step 410: Validation accuracy = 100.0%
  193. 2017-01-13 08:58:56.857690: Step 420: Train accuracy = 100.0%
  194. 2017-01-13 08:58:56.857760: Step 420: Cross entropy = 0.039656
  195. 2017-01-13 08:58:56.921129: Step 420: Validation accuracy = 100.0%
  196. 2017-01-13 08:58:57.604167: Step 430: Train accuracy = 100.0%
  197. 2017-01-13 08:58:57.604253: Step 430: Cross entropy = 0.040224
  198. 2017-01-13 08:58:57.671958: Step 430: Validation accuracy = 100.0%
  199. 2017-01-13 08:58:58.399117: Step 440: Train accuracy = 100.0%
  200. 2017-01-13 08:58:58.399195: Step 440: Cross entropy = 0.036639
  201. 2017-01-13 08:58:58.463296: Step 440: Validation accuracy = 100.0%
  202. 2017-01-13 08:58:59.128186: Step 450: Train accuracy = 100.0%
  203. 2017-01-13 08:58:59.128285: Step 450: Cross entropy = 0.035036
  204. 2017-01-13 08:58:59.190321: Step 450: Validation accuracy = 100.0%
  205. 2017-01-13 08:58:59.844982: Step 460: Train accuracy = 100.0%
  206. 2017-01-13 08:58:59.845067: Step 460: Cross entropy = 0.029682
  207. 2017-01-13 08:58:59.907359: Step 460: Validation accuracy = 100.0%
  208. 2017-01-13 08:59:00.567706: Step 470: Train accuracy = 100.0%
  209. 2017-01-13 08:59:00.567846: Step 470: Cross entropy = 0.034150
  210. 2017-01-13 08:59:00.630050: Step 470: Validation accuracy = 100.0%
  211. 2017-01-13 08:59:01.296282: Step 480: Train accuracy = 100.0%
  212. 2017-01-13 08:59:01.296392: Step 480: Cross entropy = 0.029710
  213. 2017-01-13 08:59:01.362117: Step 480: Validation accuracy = 100.0%
  214. 2017-01-13 08:59:02.031286: Step 490: Train accuracy = 100.0%
  215. 2017-01-13 08:59:02.031419: Step 490: Cross entropy = 0.031497
  216. 2017-01-13 08:59:02.091570: Step 490: Validation accuracy = 100.0%
  217. 2017-01-13 08:59:02.759624: Step 500: Train accuracy = 100.0%
  218. 2017-01-13 08:59:02.759695: Step 500: Cross entropy = 0.031908
  219. 2017-01-13 08:59:02.824013: Step 500: Validation accuracy = 100.0%
  220. 2017-01-13 08:59:03.492287: Step 510: Train accuracy = 100.0%
  221. 2017-01-13 08:59:03.492365: Step 510: Cross entropy = 0.026839
  222. 2017-01-13 08:59:03.554670: Step 510: Validation accuracy = 100.0%
  223. 2017-01-13 08:59:04.219310: Step 520: Train accuracy = 100.0%
  224. 2017-01-13 08:59:04.219388: Step 520: Cross entropy = 0.029128
  225. 2017-01-13 08:59:04.282274: Step 520: Validation accuracy = 100.0%
  226. 2017-01-13 08:59:04.962177: Step 530: Train accuracy = 100.0%
  227. 2017-01-13 08:59:04.962266: Step 530: Cross entropy = 0.028153
  228. 2017-01-13 08:59:05.033002: Step 530: Validation accuracy = 100.0%
  229. 2017-01-13 08:59:05.692025: Step 540: Train accuracy = 100.0%
  230. 2017-01-13 08:59:05.692103: Step 540: Cross entropy = 0.025002
  231. 2017-01-13 08:59:05.753194: Step 540: Validation accuracy = 100.0%
  232. 2017-01-13 08:59:06.432846: Step 550: Train accuracy = 100.0%
  233. 2017-01-13 08:59:06.432935: Step 550: Cross entropy = 0.025564
  234. 2017-01-13 08:59:06.497580: Step 550: Validation accuracy = 100.0%
  235. 2017-01-13 08:59:07.165344: Step 560: Train accuracy = 100.0%
  236. 2017-01-13 08:59:07.165445: Step 560: Cross entropy = 0.028792
  237. 2017-01-13 08:59:07.228258: Step 560: Validation accuracy = 100.0%
  238. 2017-01-13 08:59:07.895477: Step 570: Train accuracy = 100.0%
  239. 2017-01-13 08:59:07.895563: Step 570: Cross entropy = 0.022815
  240. 2017-01-13 08:59:07.958770: Step 570: Validation accuracy = 100.0%
  241. 2017-01-13 08:59:08.618687: Step 580: Train accuracy = 100.0%
  242. 2017-01-13 08:59:08.618784: Step 580: Cross entropy = 0.025089
  243. 2017-01-13 08:59:08.687366: Step 580: Validation accuracy = 100.0%
  244. 2017-01-13 08:59:09.366382: Step 590: Train accuracy = 100.0%
  245. 2017-01-13 08:59:09.366592: Step 590: Cross entropy = 0.027070
  246. 2017-01-13 08:59:09.428985: Step 590: Validation accuracy = 100.0%
  247. 2017-01-13 08:59:10.087715: Step 600: Train accuracy = 100.0%
  248. 2017-01-13 08:59:10.087798: Step 600: Cross entropy = 0.026673
  249. 2017-01-13 08:59:10.151081: Step 600: Validation accuracy = 100.0%
  250. 2017-01-13 08:59:10.832387: Step 610: Train accuracy = 100.0%
  251. 2017-01-13 08:59:10.832485: Step 610: Cross entropy = 0.023013
  252. 2017-01-13 08:59:10.899093: Step 610: Validation accuracy = 100.0%
  253. 2017-01-13 08:59:11.579199: Step 620: Train accuracy = 100.0%
  254. 2017-01-13 08:59:11.579386: Step 620: Cross entropy = 0.020226
  255. 2017-01-13 08:59:11.638915: Step 620: Validation accuracy = 100.0%
  256. 2017-01-13 08:59:12.298345: Step 630: Train accuracy = 100.0%
  257. 2017-01-13 08:59:12.298462: Step 630: Cross entropy = 0.021408
  258. 2017-01-13 08:59:12.359862: Step 630: Validation accuracy = 100.0%
  259. 2017-01-13 08:59:13.026480: Step 640: Train accuracy = 100.0%
  260. 2017-01-13 08:59:13.026748: Step 640: Cross entropy = 0.024321
  261. 2017-01-13 08:59:13.087502: Step 640: Validation accuracy = 100.0%
  262. 2017-01-13 08:59:13.763118: Step 650: Train accuracy = 100.0%
  263. 2017-01-13 08:59:13.763191: Step 650: Cross entropy = 0.026428
  264. 2017-01-13 08:59:13.824656: Step 650: Validation accuracy = 100.0%
  265. 2017-01-13 08:59:14.472831: Step 660: Train accuracy = 100.0%
  266. 2017-01-13 08:59:14.472961: Step 660: Cross entropy = 0.023120
  267. 2017-01-13 08:59:14.532645: Step 660: Validation accuracy = 100.0%
  268. 2017-01-13 08:59:15.207608: Step 670: Train accuracy = 100.0%
  269. 2017-01-13 08:59:15.207695: Step 670: Cross entropy = 0.025212
  270. 2017-01-13 08:59:15.272789: Step 670: Validation accuracy = 100.0%
  271. 2017-01-13 08:59:15.961714: Step 680: Train accuracy = 100.0%
  272. 2017-01-13 08:59:15.961789: Step 680: Cross entropy = 0.024553
  273. 2017-01-13 08:59:16.020548: Step 680: Validation accuracy = 100.0%
  274. ERROR:tensorflow:Unable to get size of /tmp/retrain_logs/train/events.out.tfevents.1484294271.pcspanel3: /tmp/retrain_logs/train/events.out.tfevents.1484294271.pcspanel3
  275. WARNING:tensorflow:Found more than one graph event per run, or there was a metagraph containing a graph_def, as well as one or more graph events. Overwriting the graph with the newest event.
  276. 2017-01-13 08:59:16.698891: Step 690: Train accuracy = 100.0%
  277. 2017-01-13 08:59:16.698960: Step 690: Cross entropy = 0.021666
  278. 2017-01-13 08:59:16.761684: Step 690: Validation accuracy = 100.0%
  279. WARNING:tensorflow:Found more than one metagraph event per run. Overwriting the metagraph with the newest event.
  280. 2017-01-13 08:59:17.463775: Step 700: Train accuracy = 100.0%
  281. 2017-01-13 08:59:17.463968: Step 700: Cross entropy = 0.021261
  282. 2017-01-13 08:59:17.524768: Step 700: Validation accuracy = 100.0%
  283. 2017-01-13 08:59:18.290325: Step 710: Train accuracy = 100.0%
  284. 2017-01-13 08:59:18.290500: Step 710: Cross entropy = 0.019721
  285. 2017-01-13 08:59:18.386138: Step 710: Validation accuracy = 100.0%
  286. 2017-01-13 08:59:19.235029: Step 720: Train accuracy = 100.0%
  287. 2017-01-13 08:59:19.235144: Step 720: Cross entropy = 0.022338
  288. 2017-01-13 08:59:19.300410: Step 720: Validation accuracy = 100.0%
  289. 2017-01-13 08:59:19.993934: Step 730: Train accuracy = 100.0%
  290. 2017-01-13 08:59:19.994105: Step 730: Cross entropy = 0.023157
  291. 2017-01-13 08:59:20.056816: Step 730: Validation accuracy = 100.0%
  292. 2017-01-13 08:59:20.716806: Step 740: Train accuracy = 100.0%
  293. 2017-01-13 08:59:20.716933: Step 740: Cross entropy = 0.018947
  294. 2017-01-13 08:59:20.788582: Step 740: Validation accuracy = 100.0%
  295. 2017-01-13 08:59:21.457269: Step 750: Train accuracy = 100.0%
  296. 2017-01-13 08:59:21.457479: Step 750: Cross entropy = 0.019566
  297. 2017-01-13 08:59:21.520623: Step 750: Validation accuracy = 100.0%
  298. 2017-01-13 08:59:22.192091: Step 760: Train accuracy = 100.0%
  299. 2017-01-13 08:59:22.192190: Step 760: Cross entropy = 0.019478
  300. 2017-01-13 08:59:22.255567: Step 760: Validation accuracy = 100.0%
  301. 2017-01-13 08:59:22.929909: Step 770: Train accuracy = 100.0%
  302. 2017-01-13 08:59:22.929967: Step 770: Cross entropy = 0.016753
  303. 2017-01-13 08:59:22.994072: Step 770: Validation accuracy = 100.0%
  304. 2017-01-13 08:59:23.662558: Step 780: Train accuracy = 100.0%
  305. 2017-01-13 08:59:23.662657: Step 780: Cross entropy = 0.018416
  306. 2017-01-13 08:59:23.722629: Step 780: Validation accuracy = 100.0%
  307. 2017-01-13 08:59:24.393251: Step 790: Train accuracy = 100.0%
  308. 2017-01-13 08:59:24.393714: Step 790: Cross entropy = 0.018063
  309. 2017-01-13 08:59:24.455290: Step 790: Validation accuracy = 100.0%
  310. 2017-01-13 08:59:25.136898: Step 800: Train accuracy = 100.0%
  311. 2017-01-13 08:59:25.137030: Step 800: Cross entropy = 0.018527
  312. 2017-01-13 08:59:25.197177: Step 800: Validation accuracy = 100.0%
  313. 2017-01-13 08:59:25.868033: Step 810: Train accuracy = 100.0%
  314. 2017-01-13 08:59:25.868125: Step 810: Cross entropy = 0.020857
  315. 2017-01-13 08:59:25.927894: Step 810: Validation accuracy = 100.0%
  316. 2017-01-13 08:59:26.606256: Step 820: Train accuracy = 100.0%
  317. 2017-01-13 08:59:26.606412: Step 820: Cross entropy = 0.021491
  318. 2017-01-13 08:59:26.681773: Step 820: Validation accuracy = 100.0%
  319. 2017-01-13 08:59:27.357202: Step 830: Train accuracy = 100.0%
  320. 2017-01-13 08:59:27.357385: Step 830: Cross entropy = 0.018286
  321. 2017-01-13 08:59:27.419751: Step 830: Validation accuracy = 100.0%
  322. 2017-01-13 08:59:28.093694: Step 840: Train accuracy = 100.0%
  323. 2017-01-13 08:59:28.093880: Step 840: Cross entropy = 0.017246
  324. 2017-01-13 08:59:28.153499: Step 840: Validation accuracy = 100.0%
  325. 2017-01-13 08:59:28.829148: Step 850: Train accuracy = 100.0%
  326. 2017-01-13 08:59:28.829261: Step 850: Cross entropy = 0.015820
  327. 2017-01-13 08:59:28.890914: Step 850: Validation accuracy = 100.0%
  328. 2017-01-13 08:59:29.555605: Step 860: Train accuracy = 100.0%
  329. 2017-01-13 08:59:29.555692: Step 860: Cross entropy = 0.017505
  330. 2017-01-13 08:59:29.619643: Step 860: Validation accuracy = 100.0%
  331. 2017-01-13 08:59:30.285517: Step 870: Train accuracy = 100.0%
  332. 2017-01-13 08:59:30.285587: Step 870: Cross entropy = 0.017158
  333. 2017-01-13 08:59:30.348143: Step 870: Validation accuracy = 100.0%
  334. 2017-01-13 08:59:31.009567: Step 880: Train accuracy = 100.0%
  335. 2017-01-13 08:59:31.009685: Step 880: Cross entropy = 0.017033
  336. 2017-01-13 08:59:31.072836: Step 880: Validation accuracy = 100.0%
  337. 2017-01-13 08:59:31.754423: Step 890: Train accuracy = 100.0%
  338. 2017-01-13 08:59:31.754612: Step 890: Cross entropy = 0.018299
  339. 2017-01-13 08:59:31.817679: Step 890: Validation accuracy = 100.0%
  340. 2017-01-13 08:59:32.482426: Step 900: Train accuracy = 100.0%
  341. 2017-01-13 08:59:32.482510: Step 900: Cross entropy = 0.017649
  342. 2017-01-13 08:59:32.545621: Step 900: Validation accuracy = 100.0%
  343. 2017-01-13 08:59:33.211310: Step 910: Train accuracy = 100.0%
  344. 2017-01-13 08:59:33.211403: Step 910: Cross entropy = 0.017328
  345. 2017-01-13 08:59:33.273260: Step 910: Validation accuracy = 100.0%
  346. 2017-01-13 08:59:33.956826: Step 920: Train accuracy = 100.0%
  347. 2017-01-13 08:59:33.956888: Step 920: Cross entropy = 0.016161
  348. 2017-01-13 08:59:34.022463: Step 920: Validation accuracy = 100.0%
  349. 2017-01-13 08:59:34.695592: Step 930: Train accuracy = 100.0%
  350. 2017-01-13 08:59:34.695696: Step 930: Cross entropy = 0.016593
  351. 2017-01-13 08:59:34.756741: Step 930: Validation accuracy = 100.0%
  352. 2017-01-13 08:59:35.423727: Step 940: Train accuracy = 100.0%
  353. 2017-01-13 08:59:35.423791: Step 940: Cross entropy = 0.014505
  354. 2017-01-13 08:59:35.486718: Step 940: Validation accuracy = 100.0%
  355. 2017-01-13 08:59:36.154564: Step 950: Train accuracy = 100.0%
  356. 2017-01-13 08:59:36.154634: Step 950: Cross entropy = 0.014995
  357. 2017-01-13 08:59:36.217181: Step 950: Validation accuracy = 100.0%
  358. 2017-01-13 08:59:36.881070: Step 960: Train accuracy = 100.0%
  359. 2017-01-13 08:59:36.881269: Step 960: Cross entropy = 0.018089
  360. 2017-01-13 08:59:36.944165: Step 960: Validation accuracy = 100.0%
  361. 2017-01-13 08:59:37.597606: Step 970: Train accuracy = 100.0%
  362. 2017-01-13 08:59:37.597758: Step 970: Cross entropy = 0.016222
  363. 2017-01-13 08:59:37.663671: Step 970: Validation accuracy = 100.0%
  364. 2017-01-13 08:59:38.334057: Step 980: Train accuracy = 100.0%
  365. 2017-01-13 08:59:38.334212: Step 980: Cross entropy = 0.014878
  366. 2017-01-13 08:59:38.398361: Step 980: Validation accuracy = 100.0%
  367. 2017-01-13 08:59:39.058848: Step 990: Train accuracy = 100.0%
  368. 2017-01-13 08:59:39.058994: Step 990: Cross entropy = 0.015773
  369. 2017-01-13 08:59:39.121985: Step 990: Validation accuracy = 100.0%
  370. 2017-01-13 08:59:39.807935: Step 1000: Train accuracy = 100.0%
  371. 2017-01-13 08:59:39.808121: Step 1000: Cross entropy = 0.017089
  372. 2017-01-13 08:59:39.869256: Step 1000: Validation accuracy = 100.0%
  373. 2017-01-13 08:59:40.533131: Step 1010: Train accuracy = 100.0%
  374. 2017-01-13 08:59:40.533235: Step 1010: Cross entropy = 0.012550
  375. 2017-01-13 08:59:40.593210: Step 1010: Validation accuracy = 100.0%
  376. 2017-01-13 08:59:41.265682: Step 1020: Train accuracy = 100.0%
  377. 2017-01-13 08:59:41.265806: Step 1020: Cross entropy = 0.017224
  378. 2017-01-13 08:59:41.328460: Step 1020: Validation accuracy = 100.0%
  379. 2017-01-13 08:59:41.996266: Step 1030: Train accuracy = 100.0%
  380. 2017-01-13 08:59:41.996454: Step 1030: Cross entropy = 0.014103
  381. 2017-01-13 08:59:42.061565: Step 1030: Validation accuracy = 100.0%
  382. 2017-01-13 08:59:42.742441: Step 1040: Train accuracy = 100.0%
  383. 2017-01-13 08:59:42.742552: Step 1040: Cross entropy = 0.015650
  384. 2017-01-13 08:59:42.808237: Step 1040: Validation accuracy = 100.0%
  385. 2017-01-13 08:59:43.480370: Step 1050: Train accuracy = 100.0%
  386. 2017-01-13 08:59:43.480453: Step 1050: Cross entropy = 0.013404
  387. 2017-01-13 08:59:43.543988: Step 1050: Validation accuracy = 100.0%
  388. 2017-01-13 08:59:44.227516: Step 1060: Train accuracy = 100.0%
  389. 2017-01-13 08:59:44.227589: Step 1060: Cross entropy = 0.014748
  390. 2017-01-13 08:59:44.290712: Step 1060: Validation accuracy = 100.0%
  391. 2017-01-13 08:59:44.969122: Step 1070: Train accuracy = 100.0%
  392. 2017-01-13 08:59:44.969213: Step 1070: Cross entropy = 0.016019
  393. 2017-01-13 08:59:45.030585: Step 1070: Validation accuracy = 100.0%
  394. 2017-01-13 08:59:45.733856: Step 1080: Train accuracy = 100.0%
  395. 2017-01-13 08:59:45.734034: Step 1080: Cross entropy = 0.012873
  396. 2017-01-13 08:59:45.794502: Step 1080: Validation accuracy = 100.0%
  397. 2017-01-13 08:59:46.457325: Step 1090: Train accuracy = 100.0%
  398. 2017-01-13 08:59:46.457399: Step 1090: Cross entropy = 0.012032
  399. 2017-01-13 08:59:46.521332: Step 1090: Validation accuracy = 100.0%
  400. 2017-01-13 08:59:47.200390: Step 1100: Train accuracy = 100.0%
  401. 2017-01-13 08:59:47.200480: Step 1100: Cross entropy = 0.012793
  402. 2017-01-13 08:59:47.260678: Step 1100: Validation accuracy = 100.0%
  403. 2017-01-13 08:59:47.934972: Step 1110: Train accuracy = 100.0%
  404. 2017-01-13 08:59:47.935043: Step 1110: Cross entropy = 0.012000
  405. 2017-01-13 08:59:48.001310: Step 1110: Validation accuracy = 100.0%
  406. 2017-01-13 08:59:48.667299: Step 1120: Train accuracy = 100.0%
  407. 2017-01-13 08:59:48.667478: Step 1120: Cross entropy = 0.013763
  408. 2017-01-13 08:59:48.730129: Step 1120: Validation accuracy = 100.0%
  409. 2017-01-13 08:59:49.403847: Step 1130: Train accuracy = 100.0%
  410. 2017-01-13 08:59:49.403925: Step 1130: Cross entropy = 0.012725
  411. 2017-01-13 08:59:49.465075: Step 1130: Validation accuracy = 100.0%
  412. 2017-01-13 08:59:50.137641: Step 1140: Train accuracy = 100.0%
  413. 2017-01-13 08:59:50.137823: Step 1140: Cross entropy = 0.014381
  414. 2017-01-13 08:59:50.201199: Step 1140: Validation accuracy = 100.0%
  415. 2017-01-13 08:59:50.858362: Step 1150: Train accuracy = 100.0%
  416. 2017-01-13 08:59:50.858461: Step 1150: Cross entropy = 0.013471
  417. 2017-01-13 08:59:50.921471: Step 1150: Validation accuracy = 100.0%
  418. 2017-01-13 08:59:51.581274: Step 1160: Train accuracy = 100.0%
  419. 2017-01-13 08:59:51.581371: Step 1160: Cross entropy = 0.014905
  420. 2017-01-13 08:59:51.643342: Step 1160: Validation accuracy = 100.0%
  421. 2017-01-13 08:59:52.307753: Step 1170: Train accuracy = 100.0%
  422. 2017-01-13 08:59:52.307850: Step 1170: Cross entropy = 0.012984
  423. 2017-01-13 08:59:52.372549: Step 1170: Validation accuracy = 100.0%
  424. 2017-01-13 08:59:53.056524: Step 1180: Train accuracy = 100.0%
  425. 2017-01-13 08:59:53.056602: Step 1180: Cross entropy = 0.011987
  426. 2017-01-13 08:59:53.124951: Step 1180: Validation accuracy = 100.0%
  427. 2017-01-13 08:59:53.797751: Step 1190: Train accuracy = 100.0%
  428. 2017-01-13 08:59:53.797841: Step 1190: Cross entropy = 0.013448
  429. 2017-01-13 08:59:53.859893: Step 1190: Validation accuracy = 100.0%
  430. 2017-01-13 08:59:54.532601: Step 1200: Train accuracy = 100.0%
  431. 2017-01-13 08:59:54.533767: Step 1200: Cross entropy = 0.013009
  432. 2017-01-13 08:59:54.596546: Step 1200: Validation accuracy = 100.0%
  433. 2017-01-13 08:59:55.263273: Step 1210: Train accuracy = 100.0%
  434. 2017-01-13 08:59:55.263417: Step 1210: Cross entropy = 0.011226
  435. 2017-01-13 08:59:55.326526: Step 1210: Validation accuracy = 100.0%
  436. 2017-01-13 08:59:56.003308: Step 1220: Train accuracy = 100.0%
  437. 2017-01-13 08:59:56.003401: Step 1220: Cross entropy = 0.010912
  438. 2017-01-13 08:59:56.063800: Step 1220: Validation accuracy = 100.0%
  439. 2017-01-13 08:59:56.722099: Step 1230: Train accuracy = 100.0%
  440. 2017-01-13 08:59:56.722188: Step 1230: Cross entropy = 0.009362
  441. 2017-01-13 08:59:56.785077: Step 1230: Validation accuracy = 100.0%
  442. 2017-01-13 08:59:57.447152: Step 1240: Train accuracy = 100.0%
  443. 2017-01-13 08:59:57.447229: Step 1240: Cross entropy = 0.012603
  444. 2017-01-13 08:59:57.510400: Step 1240: Validation accuracy = 100.0%
  445. 2017-01-13 08:59:58.173766: Step 1250: Train accuracy = 100.0%
  446. 2017-01-13 08:59:58.173900: Step 1250: Cross entropy = 0.011712
  447. 2017-01-13 08:59:58.237438: Step 1250: Validation accuracy = 100.0%
  448. 2017-01-13 08:59:58.894117: Step 1260: Train accuracy = 100.0%
  449. 2017-01-13 08:59:58.894290: Step 1260: Cross entropy = 0.015204
  450. 2017-01-13 08:59:58.971523: Step 1260: Validation accuracy = 100.0%
  451. 2017-01-13 08:59:59.631345: Step 1270: Train accuracy = 100.0%
  452. 2017-01-13 08:59:59.631443: Step 1270: Cross entropy = 0.013511
  453. 2017-01-13 08:59:59.690254: Step 1270: Validation accuracy = 100.0%
  454. 2017-01-13 09:00:00.359327: Step 1280: Train accuracy = 100.0%
  455. 2017-01-13 09:00:00.359418: Step 1280: Cross entropy = 0.012836
  456. 2017-01-13 09:00:00.422107: Step 1280: Validation accuracy = 100.0%
  457. 2017-01-13 09:00:01.100665: Step 1290: Train accuracy = 100.0%
  458. 2017-01-13 09:00:01.100784: Step 1290: Cross entropy = 0.011261
  459. 2017-01-13 09:00:01.162829: Step 1290: Validation accuracy = 100.0%
  460. 2017-01-13 09:00:01.845663: Step 1300: Train accuracy = 100.0%
  461. 2017-01-13 09:00:01.845765: Step 1300: Cross entropy = 0.011654
  462. 2017-01-13 09:00:01.904716: Step 1300: Validation accuracy = 100.0%
  463. 2017-01-13 09:00:02.567687: Step 1310: Train accuracy = 100.0%
  464. 2017-01-13 09:00:02.567796: Step 1310: Cross entropy = 0.010698
  465. 2017-01-13 09:00:02.631103: Step 1310: Validation accuracy = 100.0%
  466. 2017-01-13 09:00:03.333530: Step 1320: Train accuracy = 100.0%
  467. 2017-01-13 09:00:03.333627: Step 1320: Cross entropy = 0.010799
  468. 2017-01-13 09:00:03.397543: Step 1320: Validation accuracy = 100.0%
  469. 2017-01-13 09:00:04.072543: Step 1330: Train accuracy = 100.0%
  470. 2017-01-13 09:00:04.072689: Step 1330: Cross entropy = 0.012468
  471. 2017-01-13 09:00:04.134532: Step 1330: Validation accuracy = 100.0%
  472. 2017-01-13 09:00:04.818595: Step 1340: Train accuracy = 100.0%
  473. 2017-01-13 09:00:04.818791: Step 1340: Cross entropy = 0.010502
  474. 2017-01-13 09:00:04.883080: Step 1340: Validation accuracy = 100.0%
  475. 2017-01-13 09:00:05.580378: Step 1350: Train accuracy = 100.0%
  476. 2017-01-13 09:00:05.580469: Step 1350: Cross entropy = 0.012850
  477. 2017-01-13 09:00:05.642370: Step 1350: Validation accuracy = 100.0%
  478. 2017-01-13 09:00:06.324157: Step 1360: Train accuracy = 100.0%
  479. 2017-01-13 09:00:06.324306: Step 1360: Cross entropy = 0.010147
  480. 2017-01-13 09:00:06.388235: Step 1360: Validation accuracy = 100.0%
  481. 2017-01-13 09:00:07.068779: Step 1370: Train accuracy = 100.0%
  482. 2017-01-13 09:00:07.068845: Step 1370: Cross entropy = 0.009990
  483. 2017-01-13 09:00:07.139213: Step 1370: Validation accuracy = 100.0%
  484. 2017-01-13 09:00:07.813634: Step 1380: Train accuracy = 100.0%
  485. 2017-01-13 09:00:07.813719: Step 1380: Cross entropy = 0.011032
  486. 2017-01-13 09:00:07.876890: Step 1380: Validation accuracy = 100.0%
  487. 2017-01-13 09:00:08.535927: Step 1390: Train accuracy = 100.0%
  488. 2017-01-13 09:00:08.536150: Step 1390: Cross entropy = 0.010467
  489. 2017-01-13 09:00:08.598880: Step 1390: Validation accuracy = 100.0%
  490. 2017-01-13 09:00:09.273909: Step 1400: Train accuracy = 100.0%
  491. 2017-01-13 09:00:09.274015: Step 1400: Cross entropy = 0.011224
  492. 2017-01-13 09:00:09.342926: Step 1400: Validation accuracy = 100.0%
  493. 2017-01-13 09:00:10.021310: Step 1410: Train accuracy = 100.0%
  494. 2017-01-13 09:00:10.021396: Step 1410: Cross entropy = 0.010985
  495. 2017-01-13 09:00:10.085858: Step 1410: Validation accuracy = 100.0%
  496. 2017-01-13 09:00:10.758297: Step 1420: Train accuracy = 100.0%
  497. 2017-01-13 09:00:10.758367: Step 1420: Cross entropy = 0.011982
  498. 2017-01-13 09:00:10.822169: Step 1420: Validation accuracy = 100.0%
  499. 2017-01-13 09:00:11.494022: Step 1430: Train accuracy = 100.0%
  500. 2017-01-13 09:00:11.494104: Step 1430: Cross entropy = 0.012210
  501. 2017-01-13 09:00:11.558966: Step 1430: Validation accuracy = 100.0%
  502. 2017-01-13 09:00:12.226620: Step 1440: Train accuracy = 100.0%
  503. 2017-01-13 09:00:12.226716: Step 1440: Cross entropy = 0.009919
  504. 2017-01-13 09:00:12.288708: Step 1440: Validation accuracy = 100.0%
  505. 2017-01-13 09:00:12.963323: Step 1450: Train accuracy = 100.0%
  506. 2017-01-13 09:00:12.963475: Step 1450: Cross entropy = 0.010543
  507. 2017-01-13 09:00:13.026255: Step 1450: Validation accuracy = 100.0%
  508. 2017-01-13 09:00:13.686014: Step 1460: Train accuracy = 100.0%
  509. 2017-01-13 09:00:13.686096: Step 1460: Cross entropy = 0.010096
  510. 2017-01-13 09:00:13.750860: Step 1460: Validation accuracy = 100.0%
  511. 2017-01-13 09:00:14.432567: Step 1470: Train accuracy = 100.0%
  512. 2017-01-13 09:00:14.432650: Step 1470: Cross entropy = 0.009775
  513. 2017-01-13 09:00:14.497305: Step 1470: Validation accuracy = 100.0%
  514. 2017-01-13 09:00:15.168011: Step 1480: Train accuracy = 100.0%
  515. 2017-01-13 09:00:15.168174: Step 1480: Cross entropy = 0.009399
  516. 2017-01-13 09:00:15.230651: Step 1480: Validation accuracy = 100.0%
  517. 2017-01-13 09:00:15.920143: Step 1490: Train accuracy = 100.0%
  518. 2017-01-13 09:00:15.920245: Step 1490: Cross entropy = 0.009840
  519. 2017-01-13 09:00:15.984968: Step 1490: Validation accuracy = 100.0%
  520. 2017-01-13 09:00:16.656425: Step 1500: Train accuracy = 100.0%
  521. 2017-01-13 09:00:16.656520: Step 1500: Cross entropy = 0.009984
  522. 2017-01-13 09:00:16.719726: Step 1500: Validation accuracy = 100.0%
  523. 2017-01-13 09:00:17.387504: Step 1510: Train accuracy = 100.0%
  524. 2017-01-13 09:00:17.387615: Step 1510: Cross entropy = 0.010937
  525. 2017-01-13 09:00:17.451385: Step 1510: Validation accuracy = 100.0%
  526. 2017-01-13 09:00:18.141550: Step 1520: Train accuracy = 100.0%
  527. 2017-01-13 09:00:18.141629: Step 1520: Cross entropy = 0.008123
  528. 2017-01-13 09:00:18.207792: Step 1520: Validation accuracy = 100.0%
  529. 2017-01-13 09:00:18.895713: Step 1530: Train accuracy = 100.0%
  530. 2017-01-13 09:00:18.895896: Step 1530: Cross entropy = 0.009272
  531. 2017-01-13 09:00:18.962309: Step 1530: Validation accuracy = 100.0%
  532. 2017-01-13 09:00:19.691421: Step 1540: Train accuracy = 100.0%
  533. 2017-01-13 09:00:19.691502: Step 1540: Cross entropy = 0.011060
  534. 2017-01-13 09:00:19.794178: Step 1540: Validation accuracy = 100.0%
  535. 2017-01-13 09:00:20.506688: Step 1550: Train accuracy = 100.0%
  536. 2017-01-13 09:00:20.506812: Step 1550: Cross entropy = 0.010102
  537. 2017-01-13 09:00:20.570320: Step 1550: Validation accuracy = 100.0%
  538. 2017-01-13 09:00:21.245888: Step 1560: Train accuracy = 100.0%
  539. 2017-01-13 09:00:21.245963: Step 1560: Cross entropy = 0.007845
  540. 2017-01-13 09:00:21.309291: Step 1560: Validation accuracy = 100.0%
  541. 2017-01-13 09:00:21.988325: Step 1570: Train accuracy = 100.0%
  542. 2017-01-13 09:00:21.988420: Step 1570: Cross entropy = 0.009031
  543. 2017-01-13 09:00:22.049434: Step 1570: Validation accuracy = 100.0%
  544. 2017-01-13 09:00:22.719877: Step 1580: Train accuracy = 100.0%
  545. 2017-01-13 09:00:22.719991: Step 1580: Cross entropy = 0.008994
  546. 2017-01-13 09:00:22.782647: Step 1580: Validation accuracy = 100.0%
  547. 2017-01-13 09:00:23.455340: Step 1590: Train accuracy = 100.0%
  548. 2017-01-13 09:00:23.455448: Step 1590: Cross entropy = 0.010205
  549. 2017-01-13 09:00:23.526414: Step 1590: Validation accuracy = 100.0%
  550. 2017-01-13 09:00:24.193242: Step 1600: Train accuracy = 100.0%
  551. 2017-01-13 09:00:24.193418: Step 1600: Cross entropy = 0.009448
  552. 2017-01-13 09:00:24.257919: Step 1600: Validation accuracy = 100.0%
  553. 2017-01-13 09:00:24.938647: Step 1610: Train accuracy = 100.0%
  554. 2017-01-13 09:00:24.938734: Step 1610: Cross entropy = 0.008248
  555. 2017-01-13 09:00:25.001890: Step 1610: Validation accuracy = 100.0%
  556. 2017-01-13 09:00:25.673821: Step 1620: Train accuracy = 100.0%
  557. 2017-01-13 09:00:25.673913: Step 1620: Cross entropy = 0.009193
  558. 2017-01-13 09:00:25.749562: Step 1620: Validation accuracy = 100.0%
  559. 2017-01-13 09:00:26.429044: Step 1630: Train accuracy = 100.0%
  560. 2017-01-13 09:00:26.429211: Step 1630: Cross entropy = 0.008756
  561. 2017-01-13 09:00:26.491409: Step 1630: Validation accuracy = 100.0%
  562. 2017-01-13 09:00:27.160412: Step 1640: Train accuracy = 100.0%
  563. 2017-01-13 09:00:27.160505: Step 1640: Cross entropy = 0.008128
  564. 2017-01-13 09:00:27.222233: Step 1640: Validation accuracy = 100.0%
  565. 2017-01-13 09:00:27.891718: Step 1650: Train accuracy = 100.0%
  566. 2017-01-13 09:00:27.891800: Step 1650: Cross entropy = 0.008505
  567. 2017-01-13 09:00:27.955638: Step 1650: Validation accuracy = 100.0%
  568. 2017-01-13 09:00:28.626521: Step 1660: Train accuracy = 100.0%
  569. 2017-01-13 09:00:28.626596: Step 1660: Cross entropy = 0.008762
  570. 2017-01-13 09:00:28.689494: Step 1660: Validation accuracy = 100.0%
  571. 2017-01-13 09:00:29.359624: Step 1670: Train accuracy = 100.0%
  572. 2017-01-13 09:00:29.359709: Step 1670: Cross entropy = 0.010086
  573. 2017-01-13 09:00:29.424790: Step 1670: Validation accuracy = 100.0%
  574. 2017-01-13 09:00:30.093300: Step 1680: Train accuracy = 100.0%
  575. 2017-01-13 09:00:30.093367: Step 1680: Cross entropy = 0.009734
  576. 2017-01-13 09:00:30.157547: Step 1680: Validation accuracy = 100.0%
  577. 2017-01-13 09:00:30.845129: Step 1690: Train accuracy = 100.0%
  578. 2017-01-13 09:00:30.845252: Step 1690: Cross entropy = 0.008531
  579. 2017-01-13 09:00:30.909255: Step 1690: Validation accuracy = 100.0%
  580. 2017-01-13 09:00:31.575469: Step 1700: Train accuracy = 100.0%
  581. 2017-01-13 09:00:31.575586: Step 1700: Cross entropy = 0.008270
  582. 2017-01-13 09:00:31.639846: Step 1700: Validation accuracy = 100.0%
  583. 2017-01-13 09:00:32.317390: Step 1710: Train accuracy = 100.0%
  584. 2017-01-13 09:00:32.317543: Step 1710: Cross entropy = 0.007851
  585. 2017-01-13 09:00:32.382201: Step 1710: Validation accuracy = 100.0%
  586. 2017-01-13 09:00:33.050690: Step 1720: Train accuracy = 100.0%
  587. 2017-01-13 09:00:33.050765: Step 1720: Cross entropy = 0.010243
  588. 2017-01-13 09:00:33.111493: Step 1720: Validation accuracy = 100.0%
  589. 2017-01-13 09:00:33.799148: Step 1730: Train accuracy = 100.0%
  590. 2017-01-13 09:00:33.799303: Step 1730: Cross entropy = 0.009741
  591. 2017-01-13 09:00:33.865242: Step 1730: Validation accuracy = 100.0%
  592. 2017-01-13 09:00:34.537476: Step 1740: Train accuracy = 100.0%
  593. 2017-01-13 09:00:34.537563: Step 1740: Cross entropy = 0.008424
  594. 2017-01-13 09:00:34.601245: Step 1740: Validation accuracy = 100.0%
  595. 2017-01-13 09:00:35.259188: Step 1750: Train accuracy = 100.0%
  596. 2017-01-13 09:00:35.259322: Step 1750: Cross entropy = 0.008943
  597. 2017-01-13 09:00:35.321211: Step 1750: Validation accuracy = 100.0%
  598. 2017-01-13 09:00:36.003400: Step 1760: Train accuracy = 100.0%
  599. 2017-01-13 09:00:36.003473: Step 1760: Cross entropy = 0.009426
  600. 2017-01-13 09:00:36.065684: Step 1760: Validation accuracy = 100.0%
  601. 2017-01-13 09:00:36.729579: Step 1770: Train accuracy = 100.0%
  602. 2017-01-13 09:00:36.729668: Step 1770: Cross entropy = 0.006596
  603. 2017-01-13 09:00:36.794635: Step 1770: Validation accuracy = 100.0%
  604. 2017-01-13 09:00:37.464288: Step 1780: Train accuracy = 100.0%
  605. 2017-01-13 09:00:37.464434: Step 1780: Cross entropy = 0.008938
  606. 2017-01-13 09:00:37.524458: Step 1780: Validation accuracy = 100.0%
  607. 2017-01-13 09:00:38.205061: Step 1790: Train accuracy = 100.0%
  608. 2017-01-13 09:00:38.205153: Step 1790: Cross entropy = 0.007827
  609. 2017-01-13 09:00:38.275169: Step 1790: Validation accuracy = 100.0%
  610. 2017-01-13 09:00:38.952382: Step 1800: Train accuracy = 100.0%
  611. 2017-01-13 09:00:38.952447: Step 1800: Cross entropy = 0.007868
  612. 2017-01-13 09:00:39.016805: Step 1800: Validation accuracy = 100.0%
  613. 2017-01-13 09:00:39.688492: Step 1810: Train accuracy = 100.0%
  614. 2017-01-13 09:00:39.688701: Step 1810: Cross entropy = 0.007774
  615. 2017-01-13 09:00:39.759275: Step 1810: Validation accuracy = 100.0%
  616. 2017-01-13 09:00:40.463671: Step 1820: Train accuracy = 100.0%
  617. 2017-01-13 09:00:40.463810: Step 1820: Cross entropy = 0.007588
  618. 2017-01-13 09:00:40.531560: Step 1820: Validation accuracy = 100.0%
  619. 2017-01-13 09:00:41.199394: Step 1830: Train accuracy = 100.0%
  620. 2017-01-13 09:00:41.199552: Step 1830: Cross entropy = 0.008255
  621. 2017-01-13 09:00:41.263083: Step 1830: Validation accuracy = 100.0%
  622. 2017-01-13 09:00:41.936008: Step 1840: Train accuracy = 100.0%
  623. 2017-01-13 09:00:41.936141: Step 1840: Cross entropy = 0.009301
  624. 2017-01-13 09:00:41.999718: Step 1840: Validation accuracy = 100.0%
  625. 2017-01-13 09:00:42.690769: Step 1850: Train accuracy = 100.0%
  626. 2017-01-13 09:00:42.690862: Step 1850: Cross entropy = 0.008957
  627. 2017-01-13 09:00:42.753727: Step 1850: Validation accuracy = 100.0%
  628. 2017-01-13 09:00:43.426724: Step 1860: Train accuracy = 100.0%
  629. 2017-01-13 09:00:43.426809: Step 1860: Cross entropy = 0.009299
  630. 2017-01-13 09:00:43.492177: Step 1860: Validation accuracy = 100.0%
  631. 2017-01-13 09:00:44.164960: Step 1870: Train accuracy = 100.0%
  632. 2017-01-13 09:00:44.165057: Step 1870: Cross entropy = 0.008134
  633. 2017-01-13 09:00:44.228832: Step 1870: Validation accuracy = 100.0%
  634. 2017-01-13 09:00:44.890252: Step 1880: Train accuracy = 100.0%
  635. 2017-01-13 09:00:44.890325: Step 1880: Cross entropy = 0.009809
  636. 2017-01-13 09:00:44.954595: Step 1880: Validation accuracy = 100.0%
  637. 2017-01-13 09:00:45.639054: Step 1890: Train accuracy = 100.0%
  638. 2017-01-13 09:00:45.639159: Step 1890: Cross entropy = 0.008217
  639. 2017-01-13 09:00:45.700110: Step 1890: Validation accuracy = 100.0%
  640. 2017-01-13 09:00:46.371217: Step 1900: Train accuracy = 100.0%
  641. 2017-01-13 09:00:46.371329: Step 1900: Cross entropy = 0.008671
  642. 2017-01-13 09:00:46.435185: Step 1900: Validation accuracy = 100.0%
  643. 2017-01-13 09:00:47.098402: Step 1910: Train accuracy = 100.0%
  644. 2017-01-13 09:00:47.098561: Step 1910: Cross entropy = 0.008667
  645. 2017-01-13 09:00:47.163595: Step 1910: Validation accuracy = 100.0%
  646. 2017-01-13 09:00:47.874660: Step 1920: Train accuracy = 100.0%
  647. 2017-01-13 09:00:47.874767: Step 1920: Cross entropy = 0.007931
  648. 2017-01-13 09:00:47.937965: Step 1920: Validation accuracy = 100.0%
  649. 2017-01-13 09:00:48.618228: Step 1930: Train accuracy = 100.0%
  650. 2017-01-13 09:00:48.618331: Step 1930: Cross entropy = 0.007807
  651. 2017-01-13 09:00:48.684362: Step 1930: Validation accuracy = 100.0%
  652. 2017-01-13 09:00:49.367671: Step 1940: Train accuracy = 100.0%
  653. 2017-01-13 09:00:49.367798: Step 1940: Cross entropy = 0.006500
  654. 2017-01-13 09:00:49.429874: Step 1940: Validation accuracy = 100.0%
  655. 2017-01-13 09:00:50.102515: Step 1950: Train accuracy = 100.0%
  656. 2017-01-13 09:00:50.102890: Step 1950: Cross entropy = 0.007967
  657. 2017-01-13 09:00:50.166650: Step 1950: Validation accuracy = 100.0%
  658. 2017-01-13 09:00:50.862126: Step 1960: Train accuracy = 100.0%
  659. 2017-01-13 09:00:50.862223: Step 1960: Cross entropy = 0.006237
  660. 2017-01-13 09:00:50.922482: Step 1960: Validation accuracy = 100.0%
  661. 2017-01-13 09:00:51.611273: Step 1970: Train accuracy = 100.0%
  662. 2017-01-13 09:00:51.611565: Step 1970: Cross entropy = 0.008957
  663. 2017-01-13 09:00:51.676377: Step 1970: Validation accuracy = 100.0%
  664. 2017-01-13 09:00:52.364669: Step 1980: Train accuracy = 100.0%
  665. 2017-01-13 09:00:52.364757: Step 1980: Cross entropy = 0.007180
  666. 2017-01-13 09:00:52.428802: Step 1980: Validation accuracy = 100.0%
  667. 2017-01-13 09:00:53.096651: Step 1990: Train accuracy = 100.0%
  668. 2017-01-13 09:00:53.096724: Step 1990: Cross entropy = 0.007547
  669. 2017-01-13 09:00:53.162425: Step 1990: Validation accuracy = 100.0%
  670. 2017-01-13 09:00:53.833667: Step 2000: Train accuracy = 100.0%
  671. 2017-01-13 09:00:53.833764: Step 2000: Cross entropy = 0.008201
  672. 2017-01-13 09:00:53.898544: Step 2000: Validation accuracy = 100.0%
  673. 2017-01-13 09:00:54.576581: Step 2010: Train accuracy = 100.0%
  674. 2017-01-13 09:00:54.576720: Step 2010: Cross entropy = 0.008129
  675. 2017-01-13 09:00:54.643740: Step 2010: Validation accuracy = 100.0%
  676. 2017-01-13 09:00:55.307551: Step 2020: Train accuracy = 100.0%
  677. 2017-01-13 09:00:55.307639: Step 2020: Cross entropy = 0.006841
  678. 2017-01-13 09:00:55.370479: Step 2020: Validation accuracy = 100.0%
  679. 2017-01-13 09:00:56.035549: Step 2030: Train accuracy = 100.0%
  680. 2017-01-13 09:00:56.035891: Step 2030: Cross entropy = 0.007374
  681. 2017-01-13 09:00:56.098632: Step 2030: Validation accuracy = 100.0%
  682. 2017-01-13 09:00:56.771909: Step 2040: Train accuracy = 100.0%
  683. 2017-01-13 09:00:56.771981: Step 2040: Cross entropy = 0.006014
  684. 2017-01-13 09:00:56.835931: Step 2040: Validation accuracy = 100.0%
  685. 2017-01-13 09:00:57.501404: Step 2050: Train accuracy = 100.0%
  686. 2017-01-13 09:00:57.501733: Step 2050: Cross entropy = 0.007416
  687. 2017-01-13 09:00:57.573693: Step 2050: Validation accuracy = 100.0%
  688. 2017-01-13 09:00:58.242124: Step 2060: Train accuracy = 100.0%
  689. 2017-01-13 09:00:58.242210: Step 2060: Cross entropy = 0.007300
  690. 2017-01-13 09:00:58.304121: Step 2060: Validation accuracy = 100.0%
  691. 2017-01-13 09:00:58.985061: Step 2070: Train accuracy = 100.0%
  692. 2017-01-13 09:00:58.985134: Step 2070: Cross entropy = 0.007516
  693. 2017-01-13 09:00:59.050476: Step 2070: Validation accuracy = 100.0%
  694. 2017-01-13 09:00:59.726170: Step 2080: Train accuracy = 100.0%
  695. 2017-01-13 09:00:59.726236: Step 2080: Cross entropy = 0.007075
  696. 2017-01-13 09:00:59.789673: Step 2080: Validation accuracy = 100.0%
  697. 2017-01-13 09:01:00.462665: Step 2090: Train accuracy = 100.0%
  698. 2017-01-13 09:01:00.462766: Step 2090: Cross entropy = 0.008601
  699. 2017-01-13 09:01:00.524937: Step 2090: Validation accuracy = 100.0%
  700. 2017-01-13 09:01:01.197131: Step 2100: Train accuracy = 100.0%
  701. 2017-01-13 09:01:01.197328: Step 2100: Cross entropy = 0.006872
  702. 2017-01-13 09:01:01.257979: Step 2100: Validation accuracy = 100.0%
  703. 2017-01-13 09:01:01.930965: Step 2110: Train accuracy = 100.0%
  704. 2017-01-13 09:01:01.931102: Step 2110: Cross entropy = 0.007448
  705. 2017-01-13 09:01:01.992622: Step 2110: Validation accuracy = 100.0%
  706. 2017-01-13 09:01:02.666253: Step 2120: Train accuracy = 100.0%
  707. 2017-01-13 09:01:02.666398: Step 2120: Cross entropy = 0.007031
  708. 2017-01-13 09:01:02.727989: Step 2120: Validation accuracy = 100.0%
  709. 2017-01-13 09:01:03.398933: Step 2130: Train accuracy = 100.0%
  710. 2017-01-13 09:01:03.399041: Step 2130: Cross entropy = 0.007537
  711. 2017-01-13 09:01:03.465471: Step 2130: Validation accuracy = 100.0%
  712. 2017-01-13 09:01:04.140950: Step 2140: Train accuracy = 100.0%
  713. 2017-01-13 09:01:04.141041: Step 2140: Cross entropy = 0.006399
  714. 2017-01-13 09:01:04.203733: Step 2140: Validation accuracy = 100.0%
  715. 2017-01-13 09:01:04.889159: Step 2150: Train accuracy = 100.0%
  716. 2017-01-13 09:01:04.889550: Step 2150: Cross entropy = 0.006471
  717. 2017-01-13 09:01:04.957720: Step 2150: Validation accuracy = 100.0%
  718. 2017-01-13 09:01:05.635358: Step 2160: Train accuracy = 100.0%
  719. 2017-01-13 09:01:05.635540: Step 2160: Cross entropy = 0.005667
  720. 2017-01-13 09:01:05.698988: Step 2160: Validation accuracy = 100.0%
  721. 2017-01-13 09:01:06.376399: Step 2170: Train accuracy = 100.0%
  722. 2017-01-13 09:01:06.376506: Step 2170: Cross entropy = 0.006969
  723. 2017-01-13 09:01:06.439725: Step 2170: Validation accuracy = 100.0%
  724. 2017-01-13 09:01:07.131346: Step 2180: Train accuracy = 100.0%
  725. 2017-01-13 09:01:07.131447: Step 2180: Cross entropy = 0.006943
  726. 2017-01-13 09:01:07.195401: Step 2180: Validation accuracy = 100.0%
  727. 2017-01-13 09:01:07.863909: Step 2190: Train accuracy = 100.0%
  728. 2017-01-13 09:01:07.863987: Step 2190: Cross entropy = 0.006699
  729. 2017-01-13 09:01:07.945023: Step 2190: Validation accuracy = 100.0%
  730. 2017-01-13 09:01:08.645312: Step 2200: Train accuracy = 100.0%
  731. 2017-01-13 09:01:08.645388: Step 2200: Cross entropy = 0.006455
  732. 2017-01-13 09:01:08.709383: Step 2200: Validation accuracy = 100.0%
  733. 2017-01-13 09:01:09.378121: Step 2210: Train accuracy = 100.0%
  734. 2017-01-13 09:01:09.378192: Step 2210: Cross entropy = 0.006328
  735. 2017-01-13 09:01:09.445833: Step 2210: Validation accuracy = 100.0%
  736. 2017-01-13 09:01:10.163657: Step 2220: Train accuracy = 100.0%
  737. 2017-01-13 09:01:10.163742: Step 2220: Cross entropy = 0.006401
  738. 2017-01-13 09:01:10.232205: Step 2220: Validation accuracy = 100.0%
  739. 2017-01-13 09:01:10.921238: Step 2230: Train accuracy = 100.0%
  740. 2017-01-13 09:01:10.921323: Step 2230: Cross entropy = 0.008168
  741. 2017-01-13 09:01:10.986222: Step 2230: Validation accuracy = 100.0%
  742. 2017-01-13 09:01:11.673234: Step 2240: Train accuracy = 100.0%
  743. 2017-01-13 09:01:11.673432: Step 2240: Cross entropy = 0.007219
  744. 2017-01-13 09:01:11.745570: Step 2240: Validation accuracy = 100.0%
  745. 2017-01-13 09:01:12.430616: Step 2250: Train accuracy = 100.0%
  746. 2017-01-13 09:01:12.430731: Step 2250: Cross entropy = 0.006817
  747. 2017-01-13 09:01:12.490985: Step 2250: Validation accuracy = 100.0%
  748. 2017-01-13 09:01:13.164614: Step 2260: Train accuracy = 100.0%
  749. 2017-01-13 09:01:13.164796: Step 2260: Cross entropy = 0.007992
  750. 2017-01-13 09:01:13.230186: Step 2260: Validation accuracy = 100.0%
  751. 2017-01-13 09:01:13.898040: Step 2270: Train accuracy = 100.0%
  752. 2017-01-13 09:01:13.898112: Step 2270: Cross entropy = 0.005722
  753. 2017-01-13 09:01:13.966052: Step 2270: Validation accuracy = 100.0%
  754. 2017-01-13 09:01:14.648636: Step 2280: Train accuracy = 100.0%
  755. 2017-01-13 09:01:14.648823: Step 2280: Cross entropy = 0.006757
  756. 2017-01-13 09:01:14.714608: Step 2280: Validation accuracy = 100.0%
  757. 2017-01-13 09:01:15.383913: Step 2290: Train accuracy = 100.0%
  758. 2017-01-13 09:01:15.383986: Step 2290: Cross entropy = 0.006814
  759. 2017-01-13 09:01:15.447223: Step 2290: Validation accuracy = 100.0%
  760. 2017-01-13 09:01:16.134920: Step 2300: Train accuracy = 100.0%
  761. 2017-01-13 09:01:16.135088: Step 2300: Cross entropy = 0.006035
  762. 2017-01-13 09:01:16.197638: Step 2300: Validation accuracy = 100.0%
  763. 2017-01-13 09:01:16.869557: Step 2310: Train accuracy = 100.0%
  764. 2017-01-13 09:01:16.869635: Step 2310: Cross entropy = 0.006766
  765. 2017-01-13 09:01:16.931209: Step 2310: Validation accuracy = 100.0%
  766. 2017-01-13 09:01:17.612222: Step 2320: Train accuracy = 100.0%
  767. 2017-01-13 09:01:17.612304: Step 2320: Cross entropy = 0.006178
  768. 2017-01-13 09:01:17.677017: Step 2320: Validation accuracy = 100.0%
  769. 2017-01-13 09:01:18.351402: Step 2330: Train accuracy = 100.0%
  770. 2017-01-13 09:01:18.351470: Step 2330: Cross entropy = 0.005817
  771. 2017-01-13 09:01:18.416972: Step 2330: Validation accuracy = 100.0%
  772. 2017-01-13 09:01:19.098502: Step 2340: Train accuracy = 100.0%
  773. 2017-01-13 09:01:19.098574: Step 2340: Cross entropy = 0.005615
  774. 2017-01-13 09:01:19.160965: Step 2340: Validation accuracy = 100.0%
  775. 2017-01-13 09:01:19.828259: Step 2350: Train accuracy = 100.0%
  776. 2017-01-13 09:01:19.828367: Step 2350: Cross entropy = 0.006245
  777. 2017-01-13 09:01:19.890994: Step 2350: Validation accuracy = 100.0%
  778. 2017-01-13 09:01:20.563424: Step 2360: Train accuracy = 100.0%
  779. 2017-01-13 09:01:20.563563: Step 2360: Cross entropy = 0.006356
  780. 2017-01-13 09:01:20.625396: Step 2360: Validation accuracy = 100.0%
  781. 2017-01-13 09:01:21.300594: Step 2370: Train accuracy = 100.0%
  782. 2017-01-13 09:01:21.300731: Step 2370: Cross entropy = 0.006156
  783. 2017-01-13 09:01:21.360811: Step 2370: Validation accuracy = 100.0%
  784. 2017-01-13 09:01:22.069815: Step 2380: Train accuracy = 100.0%
  785. 2017-01-13 09:01:22.069898: Step 2380: Cross entropy = 0.005325
  786. 2017-01-13 09:01:22.131050: Step 2380: Validation accuracy = 100.0%
  787. 2017-01-13 09:01:22.801865: Step 2390: Train accuracy = 100.0%
  788. 2017-01-13 09:01:22.801943: Step 2390: Cross entropy = 0.007181
  789. 2017-01-13 09:01:22.862227: Step 2390: Validation accuracy = 100.0%
  790. 2017-01-13 09:01:23.608558: Step 2400: Train accuracy = 100.0%
  791. 2017-01-13 09:01:23.608647: Step 2400: Cross entropy = 0.006645
  792. 2017-01-13 09:01:23.676111: Step 2400: Validation accuracy = 100.0%
  793. 2017-01-13 09:01:24.372115: Step 2410: Train accuracy = 100.0%
  794. 2017-01-13 09:01:24.372205: Step 2410: Cross entropy = 0.006631
  795. 2017-01-13 09:01:24.441188: Step 2410: Validation accuracy = 100.0%
  796. 2017-01-13 09:01:25.129965: Step 2420: Train accuracy = 100.0%
  797. 2017-01-13 09:01:25.130034: Step 2420: Cross entropy = 0.007443
  798. 2017-01-13 09:01:25.199543: Step 2420: Validation accuracy = 100.0%
  799. 2017-01-13 09:01:25.872236: Step 2430: Train accuracy = 100.0%
  800. 2017-01-13 09:01:25.872315: Step 2430: Cross entropy = 0.005819
  801. 2017-01-13 09:01:25.933522: Step 2430: Validation accuracy = 100.0%
  802. 2017-01-13 09:01:26.614789: Step 2440: Train accuracy = 100.0%
  803. 2017-01-13 09:01:26.614869: Step 2440: Cross entropy = 0.006263
  804. 2017-01-13 09:01:26.679629: Step 2440: Validation accuracy = 100.0%
  805. 2017-01-13 09:01:27.361498: Step 2450: Train accuracy = 100.0%
  806. 2017-01-13 09:01:27.361568: Step 2450: Cross entropy = 0.006485
  807. 2017-01-13 09:01:27.429228: Step 2450: Validation accuracy = 100.0%
  808. 2017-01-13 09:01:28.108617: Step 2460: Train accuracy = 100.0%
  809. 2017-01-13 09:01:28.108697: Step 2460: Cross entropy = 0.005776
  810. 2017-01-13 09:01:28.172695: Step 2460: Validation accuracy = 100.0%
  811. 2017-01-13 09:01:28.862137: Step 2470: Train accuracy = 100.0%
  812. 2017-01-13 09:01:28.862251: Step 2470: Cross entropy = 0.005977
  813. 2017-01-13 09:01:28.928092: Step 2470: Validation accuracy = 100.0%
  814. 2017-01-13 09:01:29.611347: Step 2480: Train accuracy = 100.0%
  815. 2017-01-13 09:01:29.611432: Step 2480: Cross entropy = 0.006360
  816. 2017-01-13 09:01:29.675880: Step 2480: Validation accuracy = 100.0%
  817. 2017-01-13 09:01:30.366349: Step 2490: Train accuracy = 100.0%
  818. 2017-01-13 09:01:30.366438: Step 2490: Cross entropy = 0.006232
  819. 2017-01-13 09:01:30.427989: Step 2490: Validation accuracy = 100.0%
  820. 2017-01-13 09:01:31.104361: Step 2500: Train accuracy = 100.0%
  821. 2017-01-13 09:01:31.104430: Step 2500: Cross entropy = 0.006190
  822. 2017-01-13 09:01:31.169424: Step 2500: Validation accuracy = 100.0%
  823. 2017-01-13 09:01:31.865220: Step 2510: Train accuracy = 100.0%
  824. 2017-01-13 09:01:31.865318: Step 2510: Cross entropy = 0.006033
  825. 2017-01-13 09:01:31.926172: Step 2510: Validation accuracy = 100.0%
  826. 2017-01-13 09:01:32.606274: Step 2520: Train accuracy = 100.0%
  827. 2017-01-13 09:01:32.606367: Step 2520: Cross entropy = 0.005884
  828. 2017-01-13 09:01:32.670540: Step 2520: Validation accuracy = 100.0%
  829. 2017-01-13 09:01:33.354757: Step 2530: Train accuracy = 100.0%
  830. 2017-01-13 09:01:33.354855: Step 2530: Cross entropy = 0.005774
  831. 2017-01-13 09:01:33.417804: Step 2530: Validation accuracy = 100.0%
  832. 2017-01-13 09:01:34.092176: Step 2540: Train accuracy = 100.0%
  833. 2017-01-13 09:01:34.092320: Step 2540: Cross entropy = 0.007226
  834. 2017-01-13 09:01:34.154557: Step 2540: Validation accuracy = 100.0%
  835. 2017-01-13 09:01:34.827887: Step 2550: Train accuracy = 100.0%
  836. 2017-01-13 09:01:34.827993: Step 2550: Cross entropy = 0.004925
  837. 2017-01-13 09:01:34.893580: Step 2550: Validation accuracy = 100.0%
  838. 2017-01-13 09:01:35.580759: Step 2560: Train accuracy = 100.0%
  839. 2017-01-13 09:01:35.580948: Step 2560: Cross entropy = 0.006068
  840. 2017-01-13 09:01:35.644675: Step 2560: Validation accuracy = 100.0%
  841. 2017-01-13 09:01:36.319158: Step 2570: Train accuracy = 100.0%
  842. 2017-01-13 09:01:36.319274: Step 2570: Cross entropy = 0.005545
  843. 2017-01-13 09:01:36.382717: Step 2570: Validation accuracy = 100.0%
  844. 2017-01-13 09:01:37.064228: Step 2580: Train accuracy = 100.0%
  845. 2017-01-13 09:01:37.064397: Step 2580: Cross entropy = 0.005757
  846. 2017-01-13 09:01:37.128938: Step 2580: Validation accuracy = 100.0%
  847. 2017-01-13 09:01:37.794264: Step 2590: Train accuracy = 100.0%
  848. 2017-01-13 09:01:37.794369: Step 2590: Cross entropy = 0.006953
  849. 2017-01-13 09:01:37.858338: Step 2590: Validation accuracy = 100.0%
  850. 2017-01-13 09:01:38.533749: Step 2600: Train accuracy = 100.0%
  851. 2017-01-13 09:01:38.533882: Step 2600: Cross entropy = 0.005821
  852. 2017-01-13 09:01:38.601283: Step 2600: Validation accuracy = 100.0%
  853. 2017-01-13 09:01:39.288139: Step 2610: Train accuracy = 100.0%
  854. 2017-01-13 09:01:39.288235: Step 2610: Cross entropy = 0.005706
  855. 2017-01-13 09:01:39.353593: Step 2610: Validation accuracy = 100.0%
  856. 2017-01-13 09:01:40.028487: Step 2620: Train accuracy = 100.0%
  857. 2017-01-13 09:01:40.028622: Step 2620: Cross entropy = 0.005237
  858. 2017-01-13 09:01:40.091574: Step 2620: Validation accuracy = 100.0%
  859. 2017-01-13 09:01:40.766852: Step 2630: Train accuracy = 100.0%
  860. 2017-01-13 09:01:40.766968: Step 2630: Cross entropy = 0.005690
  861. 2017-01-13 09:01:40.829552: Step 2630: Validation accuracy = 100.0%
  862. 2017-01-13 09:01:41.498927: Step 2640: Train accuracy = 100.0%
  863. 2017-01-13 09:01:41.500321: Step 2640: Cross entropy = 0.005116
  864. 2017-01-13 09:01:41.561380: Step 2640: Validation accuracy = 100.0%
  865. 2017-01-13 09:01:42.245113: Step 2650: Train accuracy = 100.0%
  866. 2017-01-13 09:01:42.245205: Step 2650: Cross entropy = 0.005927
  867. 2017-01-13 09:01:42.311502: Step 2650: Validation accuracy = 100.0%
  868. 2017-01-13 09:01:42.985726: Step 2660: Train accuracy = 100.0%
  869. 2017-01-13 09:01:42.985793: Step 2660: Cross entropy = 0.006260
  870. 2017-01-13 09:01:43.049180: Step 2660: Validation accuracy = 100.0%
  871. 2017-01-13 09:01:43.728193: Step 2670: Train accuracy = 100.0%
  872. 2017-01-13 09:01:43.728346: Step 2670: Cross entropy = 0.005633
  873. 2017-01-13 09:01:43.792405: Step 2670: Validation accuracy = 100.0%
  874. 2017-01-13 09:01:44.464958: Step 2680: Train accuracy = 100.0%
  875. 2017-01-13 09:01:44.465080: Step 2680: Cross entropy = 0.006202
  876. 2017-01-13 09:01:44.531573: Step 2680: Validation accuracy = 100.0%
  877. 2017-01-13 09:01:45.213920: Step 2690: Train accuracy = 100.0%
  878. 2017-01-13 09:01:45.213999: Step 2690: Cross entropy = 0.005721
  879. 2017-01-13 09:01:45.278487: Step 2690: Validation accuracy = 100.0%
  880. 2017-01-13 09:01:45.959276: Step 2700: Train accuracy = 100.0%
  881. 2017-01-13 09:01:45.959346: Step 2700: Cross entropy = 0.005896
  882. 2017-01-13 09:01:46.025140: Step 2700: Validation accuracy = 100.0%
  883. 2017-01-13 09:01:46.702928: Step 2710: Train accuracy = 100.0%
  884. 2017-01-13 09:01:46.703035: Step 2710: Cross entropy = 0.005142
  885. 2017-01-13 09:01:46.764791: Step 2710: Validation accuracy = 100.0%
  886. 2017-01-13 09:01:47.496112: Step 2720: Train accuracy = 100.0%
  887. 2017-01-13 09:01:47.496190: Step 2720: Cross entropy = 0.005406
  888. 2017-01-13 09:01:47.560551: Step 2720: Validation accuracy = 100.0%
  889. 2017-01-13 09:01:48.251785: Step 2730: Train accuracy = 100.0%
  890. 2017-01-13 09:01:48.251872: Step 2730: Cross entropy = 0.004990
  891. 2017-01-13 09:01:48.316537: Step 2730: Validation accuracy = 100.0%
  892. 2017-01-13 09:01:49.009245: Step 2740: Train accuracy = 100.0%
  893. 2017-01-13 09:01:49.009326: Step 2740: Cross entropy = 0.005666
  894. 2017-01-13 09:01:49.073134: Step 2740: Validation accuracy = 100.0%
  895. 2017-01-13 09:01:49.777926: Step 2750: Train accuracy = 100.0%
  896. 2017-01-13 09:01:49.778152: Step 2750: Cross entropy = 0.005514
  897. 2017-01-13 09:01:49.842201: Step 2750: Validation accuracy = 100.0%
  898. 2017-01-13 09:01:50.521646: Step 2760: Train accuracy = 100.0%
  899. 2017-01-13 09:01:50.521736: Step 2760: Cross entropy = 0.005179
  900. 2017-01-13 09:01:50.586123: Step 2760: Validation accuracy = 100.0%
  901. 2017-01-13 09:01:51.268110: Step 2770: Train accuracy = 100.0%
  902. 2017-01-13 09:01:51.268917: Step 2770: Cross entropy = 0.006167
  903. 2017-01-13 09:01:51.335329: Step 2770: Validation accuracy = 100.0%
  904. 2017-01-13 09:01:52.036994: Step 2780: Train accuracy = 100.0%
  905. 2017-01-13 09:01:52.037100: Step 2780: Cross entropy = 0.005406
  906. 2017-01-13 09:01:52.107433: Step 2780: Validation accuracy = 100.0%
  907. 2017-01-13 09:01:52.781468: Step 2790: Train accuracy = 100.0%
  908. 2017-01-13 09:01:52.781546: Step 2790: Cross entropy = 0.005117
  909. 2017-01-13 09:01:52.845316: Step 2790: Validation accuracy = 100.0%
  910. 2017-01-13 09:01:53.530699: Step 2800: Train accuracy = 100.0%
  911. 2017-01-13 09:01:53.530862: Step 2800: Cross entropy = 0.006272
  912. 2017-01-13 09:01:53.592866: Step 2800: Validation accuracy = 100.0%
  913. 2017-01-13 09:01:54.275879: Step 2810: Train accuracy = 100.0%
  914. 2017-01-13 09:01:54.275976: Step 2810: Cross entropy = 0.004816
  915. 2017-01-13 09:01:54.339444: Step 2810: Validation accuracy = 100.0%
  916. 2017-01-13 09:01:55.018245: Step 2820: Train accuracy = 100.0%
  917. 2017-01-13 09:01:55.018314: Step 2820: Cross entropy = 0.005903
  918. 2017-01-13 09:01:55.083105: Step 2820: Validation accuracy = 100.0%
  919. 2017-01-13 09:01:55.766951: Step 2830: Train accuracy = 100.0%
  920. 2017-01-13 09:01:55.767139: Step 2830: Cross entropy = 0.004851
  921. 2017-01-13 09:01:55.835660: Step 2830: Validation accuracy = 100.0%
  922. 2017-01-13 09:01:56.522518: Step 2840: Train accuracy = 100.0%
  923. 2017-01-13 09:01:56.522600: Step 2840: Cross entropy = 0.004720
  924. 2017-01-13 09:01:56.587915: Step 2840: Validation accuracy = 100.0%
  925. 2017-01-13 09:01:57.265702: Step 2850: Train accuracy = 100.0%
  926. 2017-01-13 09:01:57.265813: Step 2850: Cross entropy = 0.006003
  927. 2017-01-13 09:01:57.333874: Step 2850: Validation accuracy = 100.0%
  928. 2017-01-13 09:01:58.021140: Step 2860: Train accuracy = 100.0%
  929. 2017-01-13 09:01:58.021225: Step 2860: Cross entropy = 0.005681
  930. 2017-01-13 09:01:58.087208: Step 2860: Validation accuracy = 100.0%
  931. 2017-01-13 09:01:58.786452: Step 2870: Train accuracy = 100.0%
  932. 2017-01-13 09:01:58.786542: Step 2870: Cross entropy = 0.006137
  933. 2017-01-13 09:01:58.849982: Step 2870: Validation accuracy = 100.0%
  934. 2017-01-13 09:01:59.532423: Step 2880: Train accuracy = 100.0%
  935. 2017-01-13 09:01:59.532544: Step 2880: Cross entropy = 0.004401
  936. 2017-01-13 09:01:59.594567: Step 2880: Validation accuracy = 100.0%
  937. 2017-01-13 09:02:00.279631: Step 2890: Train accuracy = 100.0%
  938. 2017-01-13 09:02:00.279707: Step 2890: Cross entropy = 0.004995
  939. 2017-01-13 09:02:00.345743: Step 2890: Validation accuracy = 100.0%
  940. 2017-01-13 09:02:01.040829: Step 2900: Train accuracy = 100.0%
  941. 2017-01-13 09:02:01.040920: Step 2900: Cross entropy = 0.005506
  942. 2017-01-13 09:02:01.104470: Step 2900: Validation accuracy = 100.0%
  943. 2017-01-13 09:02:01.786574: Step 2910: Train accuracy = 100.0%
  944. 2017-01-13 09:02:01.786736: Step 2910: Cross entropy = 0.005571
  945. 2017-01-13 09:02:01.850425: Step 2910: Validation accuracy = 100.0%
  946. 2017-01-13 09:02:02.527355: Step 2920: Train accuracy = 100.0%
  947. 2017-01-13 09:02:02.527613: Step 2920: Cross entropy = 0.004870
  948. 2017-01-13 09:02:02.590606: Step 2920: Validation accuracy = 100.0%
  949. 2017-01-13 09:02:03.303949: Step 2930: Train accuracy = 100.0%
  950. 2017-01-13 09:02:03.304040: Step 2930: Cross entropy = 0.004462
  951. 2017-01-13 09:02:03.367642: Step 2930: Validation accuracy = 100.0%
  952. 2017-01-13 09:02:04.042884: Step 2940: Train accuracy = 100.0%
  953. 2017-01-13 09:02:04.042976: Step 2940: Cross entropy = 0.005252
  954. 2017-01-13 09:02:04.110000: Step 2940: Validation accuracy = 100.0%
  955. 2017-01-13 09:02:04.786623: Step 2950: Train accuracy = 100.0%
  956. 2017-01-13 09:02:04.786698: Step 2950: Cross entropy = 0.006063
  957. 2017-01-13 09:02:04.852766: Step 2950: Validation accuracy = 100.0%
  958. 2017-01-13 09:02:05.529275: Step 2960: Train accuracy = 100.0%
  959. 2017-01-13 09:02:05.529370: Step 2960: Cross entropy = 0.004569
  960. 2017-01-13 09:02:05.594659: Step 2960: Validation accuracy = 100.0%
  961. 2017-01-13 09:02:06.282709: Step 2970: Train accuracy = 100.0%
  962. 2017-01-13 09:02:06.282786: Step 2970: Cross entropy = 0.004819
  963. 2017-01-13 09:02:06.350577: Step 2970: Validation accuracy = 100.0%
  964. 2017-01-13 09:02:07.065156: Step 2980: Train accuracy = 100.0%
  965. 2017-01-13 09:02:07.065270: Step 2980: Cross entropy = 0.005281
  966. 2017-01-13 09:02:07.130563: Step 2980: Validation accuracy = 100.0%
  967. 2017-01-13 09:02:07.819774: Step 2990: Train accuracy = 100.0%
  968. 2017-01-13 09:02:07.821592: Step 2990: Cross entropy = 0.004962
  969. 2017-01-13 09:02:07.887305: Step 2990: Validation accuracy = 100.0%
  970. 2017-01-13 09:02:08.572398: Step 3000: Train accuracy = 100.0%
  971. 2017-01-13 09:02:08.572475: Step 3000: Cross entropy = 0.004716
  972. 2017-01-13 09:02:08.635534: Step 3000: Validation accuracy = 100.0%
  973. 2017-01-13 09:02:09.329165: Step 3010: Train accuracy = 100.0%
  974. 2017-01-13 09:02:09.329276: Step 3010: Cross entropy = 0.004780
  975. 2017-01-13 09:02:09.393293: Step 3010: Validation accuracy = 100.0%
  976. 2017-01-13 09:02:10.069169: Step 3020: Train accuracy = 100.0%
  977. 2017-01-13 09:02:10.069278: Step 3020: Cross entropy = 0.005233
  978. 2017-01-13 09:02:10.132859: Step 3020: Validation accuracy = 100.0%
  979. 2017-01-13 09:02:10.820481: Step 3030: Train accuracy = 100.0%
  980. 2017-01-13 09:02:10.820568: Step 3030: Cross entropy = 0.005131
  981. 2017-01-13 09:02:10.889380: Step 3030: Validation accuracy = 100.0%
  982. 2017-01-13 09:02:11.561614: Step 3040: Train accuracy = 100.0%
  983. 2017-01-13 09:02:11.561686: Step 3040: Cross entropy = 0.004665
  984. 2017-01-13 09:02:11.632283: Step 3040: Validation accuracy = 100.0%
  985. 2017-01-13 09:02:12.308248: Step 3050: Train accuracy = 100.0%
  986. 2017-01-13 09:02:12.308332: Step 3050: Cross entropy = 0.004328
  987. 2017-01-13 09:02:12.373918: Step 3050: Validation accuracy = 100.0%
  988. 2017-01-13 09:02:13.065464: Step 3060: Train accuracy = 100.0%
  989. 2017-01-13 09:02:13.065577: Step 3060: Cross entropy = 0.004506
  990. 2017-01-13 09:02:13.126793: Step 3060: Validation accuracy = 100.0%
  991. 2017-01-13 09:02:13.822820: Step 3070: Train accuracy = 100.0%
  992. 2017-01-13 09:02:13.822898: Step 3070: Cross entropy = 0.005248
  993. 2017-01-13 09:02:13.890235: Step 3070: Validation accuracy = 100.0%
  994. 2017-01-13 09:02:14.585436: Step 3080: Train accuracy = 100.0%
  995. 2017-01-13 09:02:14.585508: Step 3080: Cross entropy = 0.004334
  996. 2017-01-13 09:02:14.650382: Step 3080: Validation accuracy = 100.0%
  997. 2017-01-13 09:02:15.324092: Step 3090: Train accuracy = 100.0%
  998. 2017-01-13 09:02:15.324157: Step 3090: Cross entropy = 0.004713
  999. 2017-01-13 09:02:15.388219: Step 3090: Validation accuracy = 100.0%
  1000. 2017-01-13 09:02:16.057585: Step 3100: Train accuracy = 100.0%
  1001. 2017-01-13 09:02:16.057666: Step 3100: Cross entropy = 0.005041
  1002. 2017-01-13 09:02:16.122941: Step 3100: Validation accuracy = 100.0%
  1003. 2017-01-13 09:02:16.790210: Step 3110: Train accuracy = 100.0%
  1004. 2017-01-13 09:02:16.790287: Step 3110: Cross entropy = 0.004952
  1005. 2017-01-13 09:02:16.855144: Step 3110: Validation accuracy = 100.0%
  1006. 2017-01-13 09:02:17.548440: Step 3120: Train accuracy = 100.0%
  1007. 2017-01-13 09:02:17.548519: Step 3120: Cross entropy = 0.005192
  1008. 2017-01-13 09:02:17.611581: Step 3120: Validation accuracy = 100.0%
  1009. 2017-01-13 09:02:18.301643: Step 3130: Train accuracy = 100.0%
  1010. 2017-01-13 09:02:18.301727: Step 3130: Cross entropy = 0.004639
  1011. 2017-01-13 09:02:18.366715: Step 3130: Validation accuracy = 100.0%
  1012. 2017-01-13 09:02:19.061048: Step 3140: Train accuracy = 100.0%
  1013. 2017-01-13 09:02:19.061271: Step 3140: Cross entropy = 0.004341
  1014. 2017-01-13 09:02:19.125925: Step 3140: Validation accuracy = 100.0%
  1015. 2017-01-13 09:02:19.796994: Step 3150: Train accuracy = 100.0%
  1016. 2017-01-13 09:02:19.797088: Step 3150: Cross entropy = 0.004711
  1017. 2017-01-13 09:02:19.857229: Step 3150: Validation accuracy = 100.0%
  1018. 2017-01-13 09:02:20.543324: Step 3160: Train accuracy = 100.0%
  1019. 2017-01-13 09:02:20.543468: Step 3160: Cross entropy = 0.005117
  1020. 2017-01-13 09:02:20.609684: Step 3160: Validation accuracy = 100.0%
  1021. 2017-01-13 09:02:21.299594: Step 3170: Train accuracy = 100.0%
  1022. 2017-01-13 09:02:21.299731: Step 3170: Cross entropy = 0.005219
  1023. 2017-01-13 09:02:21.363810: Step 3170: Validation accuracy = 100.0%
  1024. 2017-01-13 09:02:22.053160: Step 3180: Train accuracy = 100.0%
  1025. 2017-01-13 09:02:22.053254: Step 3180: Cross entropy = 0.005546
  1026. 2017-01-13 09:02:22.120038: Step 3180: Validation accuracy = 100.0%
  1027. 2017-01-13 09:02:22.814459: Step 3190: Train accuracy = 100.0%
  1028. 2017-01-13 09:02:22.814555: Step 3190: Cross entropy = 0.004761
  1029. 2017-01-13 09:02:22.877061: Step 3190: Validation accuracy = 100.0%
  1030. 2017-01-13 09:02:23.569571: Step 3200: Train accuracy = 100.0%
  1031. 2017-01-13 09:02:23.569653: Step 3200: Cross entropy = 0.004524
  1032. 2017-01-13 09:02:23.640986: Step 3200: Validation accuracy = 100.0%
  1033. 2017-01-13 09:02:24.488869: Step 3210: Train accuracy = 100.0%
  1034. 2017-01-13 09:02:24.489111: Step 3210: Cross entropy = 0.004706
  1035. 2017-01-13 09:02:24.560709: Step 3210: Validation accuracy = 100.0%
  1036. 2017-01-13 09:02:25.325993: Step 3220: Train accuracy = 100.0%
  1037. 2017-01-13 09:02:25.326150: Step 3220: Cross entropy = 0.005124
  1038. 2017-01-13 09:02:25.385207: Step 3220: Validation accuracy = 100.0%
  1039. 2017-01-13 09:02:26.092604: Step 3230: Train accuracy = 100.0%
  1040. 2017-01-13 09:02:26.092774: Step 3230: Cross entropy = 0.004151
  1041. 2017-01-13 09:02:26.157203: Step 3230: Validation accuracy = 100.0%
  1042. 2017-01-13 09:02:26.834779: Step 3240: Train accuracy = 100.0%
  1043. 2017-01-13 09:02:26.834869: Step 3240: Cross entropy = 0.004194
  1044. 2017-01-13 09:02:26.899596: Step 3240: Validation accuracy = 100.0%
  1045. 2017-01-13 09:02:27.585646: Step 3250: Train accuracy = 100.0%
  1046. 2017-01-13 09:02:27.585750: Step 3250: Cross entropy = 0.004682
  1047. 2017-01-13 09:02:27.649703: Step 3250: Validation accuracy = 100.0%
  1048. 2017-01-13 09:02:28.351560: Step 3260: Train accuracy = 100.0%
  1049. 2017-01-13 09:02:28.351629: Step 3260: Cross entropy = 0.004347
  1050. 2017-01-13 09:02:28.418960: Step 3260: Validation accuracy = 100.0%
  1051. 2017-01-13 09:02:29.100201: Step 3270: Train accuracy = 100.0%
  1052. 2017-01-13 09:02:29.100283: Step 3270: Cross entropy = 0.004429
  1053. 2017-01-13 09:02:29.162172: Step 3270: Validation accuracy = 100.0%
  1054. 2017-01-13 09:02:29.863264: Step 3280: Train accuracy = 100.0%
  1055. 2017-01-13 09:02:29.863583: Step 3280: Cross entropy = 0.004637
  1056. 2017-01-13 09:02:29.928235: Step 3280: Validation accuracy = 100.0%
  1057. 2017-01-13 09:02:30.612968: Step 3290: Train accuracy = 100.0%
  1058. 2017-01-13 09:02:30.613152: Step 3290: Cross entropy = 0.004404
  1059. 2017-01-13 09:02:30.680980: Step 3290: Validation accuracy = 100.0%
  1060. 2017-01-13 09:02:31.361488: Step 3300: Train accuracy = 100.0%
  1061. 2017-01-13 09:02:31.361590: Step 3300: Cross entropy = 0.005445
  1062. 2017-01-13 09:02:31.426354: Step 3300: Validation accuracy = 100.0%
  1063. 2017-01-13 09:02:32.134519: Step 3310: Train accuracy = 100.0%
  1064. 2017-01-13 09:02:32.134740: Step 3310: Cross entropy = 0.004400
  1065. 2017-01-13 09:02:32.198943: Step 3310: Validation accuracy = 100.0%
  1066. 2017-01-13 09:02:32.871033: Step 3320: Train accuracy = 100.0%
  1067. 2017-01-13 09:02:32.871122: Step 3320: Cross entropy = 0.004634
  1068. 2017-01-13 09:02:32.939935: Step 3320: Validation accuracy = 100.0%
  1069. 2017-01-13 09:02:33.641365: Step 3330: Train accuracy = 100.0%
  1070. 2017-01-13 09:02:33.641466: Step 3330: Cross entropy = 0.004753
  1071. 2017-01-13 09:02:33.708739: Step 3330: Validation accuracy = 100.0%
  1072. 2017-01-13 09:02:34.400632: Step 3340: Train accuracy = 100.0%
  1073. 2017-01-13 09:02:34.400740: Step 3340: Cross entropy = 0.004876
  1074. 2017-01-13 09:02:34.463988: Step 3340: Validation accuracy = 100.0%
  1075. 2017-01-13 09:02:35.152436: Step 3350: Train accuracy = 100.0%
  1076. 2017-01-13 09:02:35.152524: Step 3350: Cross entropy = 0.004135
  1077. 2017-01-13 09:02:35.218113: Step 3350: Validation accuracy = 100.0%
  1078. 2017-01-13 09:02:35.903853: Step 3360: Train accuracy = 100.0%
  1079. 2017-01-13 09:02:35.903966: Step 3360: Cross entropy = 0.004489
  1080. 2017-01-13 09:02:35.967455: Step 3360: Validation accuracy = 100.0%
  1081. 2017-01-13 09:02:36.668561: Step 3370: Train accuracy = 100.0%
  1082. 2017-01-13 09:02:36.668700: Step 3370: Cross entropy = 0.004332
  1083. 2017-01-13 09:02:36.733635: Step 3370: Validation accuracy = 100.0%
  1084. 2017-01-13 09:02:37.424883: Step 3380: Train accuracy = 100.0%
  1085. 2017-01-13 09:02:37.424981: Step 3380: Cross entropy = 0.004266
  1086. 2017-01-13 09:02:37.490342: Step 3380: Validation accuracy = 100.0%
  1087. 2017-01-13 09:02:38.199001: Step 3390: Train accuracy = 100.0%
  1088. 2017-01-13 09:02:38.199119: Step 3390: Cross entropy = 0.005225
  1089. 2017-01-13 09:02:38.267353: Step 3390: Validation accuracy = 100.0%
  1090. 2017-01-13 09:02:38.957384: Step 3400: Train accuracy = 100.0%
  1091. 2017-01-13 09:02:38.957477: Step 3400: Cross entropy = 0.004544
  1092. 2017-01-13 09:02:39.020476: Step 3400: Validation accuracy = 100.0%
  1093. 2017-01-13 09:02:39.703880: Step 3410: Train accuracy = 100.0%
  1094. 2017-01-13 09:02:39.704056: Step 3410: Cross entropy = 0.004278
  1095. 2017-01-13 09:02:39.771144: Step 3410: Validation accuracy = 100.0%
  1096. 2017-01-13 09:02:40.460574: Step 3420: Train accuracy = 100.0%
  1097. 2017-01-13 09:02:40.460654: Step 3420: Cross entropy = 0.003860
  1098. 2017-01-13 09:02:40.530723: Step 3420: Validation accuracy = 100.0%
  1099. 2017-01-13 09:02:41.230946: Step 3430: Train accuracy = 100.0%
  1100. 2017-01-13 09:02:41.231039: Step 3430: Cross entropy = 0.004833
  1101. 2017-01-13 09:02:41.298889: Step 3430: Validation accuracy = 100.0%
  1102. 2017-01-13 09:02:42.001107: Step 3440: Train accuracy = 100.0%
  1103. 2017-01-13 09:02:42.001186: Step 3440: Cross entropy = 0.004012
  1104. 2017-01-13 09:02:42.064766: Step 3440: Validation accuracy = 100.0%
  1105. 2017-01-13 09:02:42.751853: Step 3450: Train accuracy = 100.0%
  1106. 2017-01-13 09:02:42.751935: Step 3450: Cross entropy = 0.004248
  1107. 2017-01-13 09:02:42.817467: Step 3450: Validation accuracy = 100.0%
  1108. 2017-01-13 09:02:43.501312: Step 3460: Train accuracy = 100.0%
  1109. 2017-01-13 09:02:43.501488: Step 3460: Cross entropy = 0.004102
  1110. 2017-01-13 09:02:43.568600: Step 3460: Validation accuracy = 100.0%
  1111. 2017-01-13 09:02:44.251324: Step 3470: Train accuracy = 100.0%
  1112. 2017-01-13 09:02:44.251395: Step 3470: Cross entropy = 0.005223
  1113. 2017-01-13 09:02:44.315505: Step 3470: Validation accuracy = 100.0%
  1114. 2017-01-13 09:02:45.007585: Step 3480: Train accuracy = 100.0%
  1115. 2017-01-13 09:02:45.007662: Step 3480: Cross entropy = 0.004377
  1116. 2017-01-13 09:02:45.072626: Step 3480: Validation accuracy = 100.0%
  1117. 2017-01-13 09:02:45.764889: Step 3490: Train accuracy = 100.0%
  1118. 2017-01-13 09:02:45.765054: Step 3490: Cross entropy = 0.003974
  1119. 2017-01-13 09:02:45.827010: Step 3490: Validation accuracy = 100.0%
  1120. 2017-01-13 09:02:46.517014: Step 3500: Train accuracy = 100.0%
  1121. 2017-01-13 09:02:46.517086: Step 3500: Cross entropy = 0.004282
  1122. 2017-01-13 09:02:46.583947: Step 3500: Validation accuracy = 100.0%
  1123. 2017-01-13 09:02:47.268669: Step 3510: Train accuracy = 100.0%
  1124. 2017-01-13 09:02:47.268776: Step 3510: Cross entropy = 0.004819
  1125. 2017-01-13 09:02:47.331816: Step 3510: Validation accuracy = 100.0%
  1126. 2017-01-13 09:02:48.025955: Step 3520: Train accuracy = 100.0%
  1127. 2017-01-13 09:02:48.026037: Step 3520: Cross entropy = 0.004948
  1128. 2017-01-13 09:02:48.091473: Step 3520: Validation accuracy = 100.0%
  1129. 2017-01-13 09:02:48.793271: Step 3530: Train accuracy = 100.0%
  1130. 2017-01-13 09:02:48.793355: Step 3530: Cross entropy = 0.003565
  1131. 2017-01-13 09:02:48.859134: Step 3530: Validation accuracy = 100.0%
  1132. 2017-01-13 09:02:49.546150: Step 3540: Train accuracy = 100.0%
  1133. 2017-01-13 09:02:49.546259: Step 3540: Cross entropy = 0.004142
  1134. 2017-01-13 09:02:49.614494: Step 3540: Validation accuracy = 100.0%
  1135. 2017-01-13 09:02:50.302393: Step 3550: Train accuracy = 100.0%
  1136. 2017-01-13 09:02:50.302548: Step 3550: Cross entropy = 0.003646
  1137. 2017-01-13 09:02:50.370324: Step 3550: Validation accuracy = 100.0%
  1138. 2017-01-13 09:02:51.058662: Step 3560: Train accuracy = 100.0%
  1139. 2017-01-13 09:02:51.058750: Step 3560: Cross entropy = 0.004612
  1140. 2017-01-13 09:02:51.124733: Step 3560: Validation accuracy = 100.0%
  1141. 2017-01-13 09:02:51.801808: Step 3570: Train accuracy = 100.0%
  1142. 2017-01-13 09:02:51.801881: Step 3570: Cross entropy = 0.003608
  1143. 2017-01-13 09:02:51.864280: Step 3570: Validation accuracy = 100.0%
  1144. 2017-01-13 09:02:52.536981: Step 3580: Train accuracy = 100.0%
  1145. 2017-01-13 09:02:52.537068: Step 3580: Cross entropy = 0.003832
  1146. 2017-01-13 09:02:52.601148: Step 3580: Validation accuracy = 100.0%
  1147. 2017-01-13 09:02:53.299880: Step 3590: Train accuracy = 100.0%
  1148. 2017-01-13 09:02:53.300027: Step 3590: Cross entropy = 0.004520
  1149. 2017-01-13 09:02:53.366035: Step 3590: Validation accuracy = 100.0%
  1150. 2017-01-13 09:02:54.054179: Step 3600: Train accuracy = 100.0%
  1151. 2017-01-13 09:02:54.054271: Step 3600: Cross entropy = 0.004329
  1152. 2017-01-13 09:02:54.120047: Step 3600: Validation accuracy = 100.0%
  1153. 2017-01-13 09:02:54.797094: Step 3610: Train accuracy = 100.0%
  1154. 2017-01-13 09:02:54.797180: Step 3610: Cross entropy = 0.003937
  1155. 2017-01-13 09:02:54.860358: Step 3610: Validation accuracy = 100.0%
  1156. 2017-01-13 09:02:55.550652: Step 3620: Train accuracy = 100.0%
  1157. 2017-01-13 09:02:55.550733: Step 3620: Cross entropy = 0.003465
  1158. 2017-01-13 09:02:55.616002: Step 3620: Validation accuracy = 100.0%
  1159. 2017-01-13 09:02:56.325584: Step 3630: Train accuracy = 100.0%
  1160. 2017-01-13 09:02:56.325659: Step 3630: Cross entropy = 0.004290
  1161. 2017-01-13 09:02:56.391579: Step 3630: Validation accuracy = 100.0%
  1162. 2017-01-13 09:02:57.064491: Step 3640: Train accuracy = 100.0%
  1163. 2017-01-13 09:02:57.064665: Step 3640: Cross entropy = 0.003573
  1164. 2017-01-13 09:02:57.129091: Step 3640: Validation accuracy = 100.0%
  1165. 2017-01-13 09:02:57.819981: Step 3650: Train accuracy = 100.0%
  1166. 2017-01-13 09:02:57.820057: Step 3650: Cross entropy = 0.004555
  1167. 2017-01-13 09:02:57.885142: Step 3650: Validation accuracy = 100.0%
  1168. 2017-01-13 09:02:58.572235: Step 3660: Train accuracy = 100.0%
  1169. 2017-01-13 09:02:58.572358: Step 3660: Cross entropy = 0.004464
  1170. 2017-01-13 09:02:58.631885: Step 3660: Validation accuracy = 100.0%
  1171. 2017-01-13 09:02:59.340826: Step 3670: Train accuracy = 100.0%
  1172. 2017-01-13 09:02:59.340917: Step 3670: Cross entropy = 0.004248
  1173. 2017-01-13 09:02:59.407364: Step 3670: Validation accuracy = 100.0%
  1174. 2017-01-13 09:03:00.101220: Step 3680: Train accuracy = 100.0%
  1175. 2017-01-13 09:03:00.101358: Step 3680: Cross entropy = 0.004258
  1176. 2017-01-13 09:03:00.167414: Step 3680: Validation accuracy = 100.0%
  1177. 2017-01-13 09:03:00.860466: Step 3690: Train accuracy = 100.0%
  1178. 2017-01-13 09:03:00.860590: Step 3690: Cross entropy = 0.004053
  1179. 2017-01-13 09:03:00.926234: Step 3690: Validation accuracy = 100.0%
  1180. 2017-01-13 09:03:01.605630: Step 3700: Train accuracy = 100.0%
  1181. 2017-01-13 09:03:01.605733: Step 3700: Cross entropy = 0.003975
  1182. 2017-01-13 09:03:01.671380: Step 3700: Validation accuracy = 100.0%
  1183. 2017-01-13 09:03:02.392770: Step 3710: Train accuracy = 100.0%
  1184. 2017-01-13 09:03:02.392847: Step 3710: Cross entropy = 0.004482
  1185. 2017-01-13 09:03:02.458732: Step 3710: Validation accuracy = 100.0%
  1186. 2017-01-13 09:03:03.163592: Step 3720: Train accuracy = 100.0%
  1187. 2017-01-13 09:03:03.163755: Step 3720: Cross entropy = 0.004104
  1188. 2017-01-13 09:03:03.227246: Step 3720: Validation accuracy = 100.0%
  1189. 2017-01-13 09:03:03.913971: Step 3730: Train accuracy = 100.0%
  1190. 2017-01-13 09:03:03.914049: Step 3730: Cross entropy = 0.004929
  1191. 2017-01-13 09:03:03.979018: Step 3730: Validation accuracy = 100.0%
  1192. 2017-01-13 09:03:04.670672: Step 3740: Train accuracy = 100.0%
  1193. 2017-01-13 09:03:04.670745: Step 3740: Cross entropy = 0.003639
  1194. 2017-01-13 09:03:04.736584: Step 3740: Validation accuracy = 100.0%
  1195. 2017-01-13 09:03:05.431160: Step 3750: Train accuracy = 100.0%
  1196. 2017-01-13 09:03:05.431317: Step 3750: Cross entropy = 0.003457
  1197. 2017-01-13 09:03:05.500283: Step 3750: Validation accuracy = 100.0%
  1198. 2017-01-13 09:03:06.188068: Step 3760: Train accuracy = 100.0%
  1199. 2017-01-13 09:03:06.188176: Step 3760: Cross entropy = 0.003475
  1200. 2017-01-13 09:03:06.256659: Step 3760: Validation accuracy = 100.0%
  1201. 2017-01-13 09:03:06.950917: Step 3770: Train accuracy = 100.0%
  1202. 2017-01-13 09:03:06.951101: Step 3770: Cross entropy = 0.003844
  1203. 2017-01-13 09:03:07.020483: Step 3770: Validation accuracy = 100.0%
  1204. 2017-01-13 09:03:07.700869: Step 3780: Train accuracy = 100.0%
  1205. 2017-01-13 09:03:07.701014: Step 3780: Cross entropy = 0.003553
  1206. 2017-01-13 09:03:07.762915: Step 3780: Validation accuracy = 100.0%
  1207. 2017-01-13 09:03:08.462410: Step 3790: Train accuracy = 100.0%
  1208. 2017-01-13 09:03:08.462955: Step 3790: Cross entropy = 0.003511
  1209. 2017-01-13 09:03:08.528164: Step 3790: Validation accuracy = 100.0%
  1210. 2017-01-13 09:03:09.226110: Step 3800: Train accuracy = 100.0%
  1211. 2017-01-13 09:03:09.226183: Step 3800: Cross entropy = 0.004085
  1212. 2017-01-13 09:03:09.295195: Step 3800: Validation accuracy = 100.0%
  1213. 2017-01-13 09:03:09.981218: Step 3810: Train accuracy = 100.0%
  1214. 2017-01-13 09:03:09.981426: Step 3810: Cross entropy = 0.004122
  1215. 2017-01-13 09:03:10.048527: Step 3810: Validation accuracy = 100.0%
  1216. 2017-01-13 09:03:10.736079: Step 3820: Train accuracy = 100.0%
  1217. 2017-01-13 09:03:10.736278: Step 3820: Cross entropy = 0.003962
  1218. 2017-01-13 09:03:10.803825: Step 3820: Validation accuracy = 100.0%
  1219. 2017-01-13 09:03:11.501729: Step 3830: Train accuracy = 100.0%
  1220. 2017-01-13 09:03:11.501832: Step 3830: Cross entropy = 0.003787
  1221. 2017-01-13 09:03:11.566539: Step 3830: Validation accuracy = 100.0%
  1222. 2017-01-13 09:03:12.248027: Step 3840: Train accuracy = 100.0%
  1223. 2017-01-13 09:03:12.248122: Step 3840: Cross entropy = 0.004049
  1224. 2017-01-13 09:03:12.315570: Step 3840: Validation accuracy = 100.0%
  1225. 2017-01-13 09:03:12.993139: Step 3850: Train accuracy = 100.0%
  1226. 2017-01-13 09:03:12.993324: Step 3850: Cross entropy = 0.004102
  1227. 2017-01-13 09:03:13.055892: Step 3850: Validation accuracy = 100.0%
  1228. 2017-01-13 09:03:13.737499: Step 3860: Train accuracy = 100.0%
  1229. 2017-01-13 09:03:13.737701: Step 3860: Cross entropy = 0.004231
  1230. 2017-01-13 09:03:13.803872: Step 3860: Validation accuracy = 100.0%
  1231. 2017-01-13 09:03:14.488426: Step 3870: Train accuracy = 100.0%
  1232. 2017-01-13 09:03:14.488503: Step 3870: Cross entropy = 0.003302
  1233. 2017-01-13 09:03:14.552870: Step 3870: Validation accuracy = 100.0%
  1234. 2017-01-13 09:03:15.260997: Step 3880: Train accuracy = 100.0%
  1235. 2017-01-13 09:03:15.261165: Step 3880: Cross entropy = 0.003945
  1236. 2017-01-13 09:03:15.329539: Step 3880: Validation accuracy = 100.0%
  1237. 2017-01-13 09:03:16.033643: Step 3890: Train accuracy = 100.0%
  1238. 2017-01-13 09:03:16.033766: Step 3890: Cross entropy = 0.004119
  1239. 2017-01-13 09:03:16.095538: Step 3890: Validation accuracy = 100.0%
  1240. 2017-01-13 09:03:16.801368: Step 3900: Train accuracy = 100.0%
  1241. 2017-01-13 09:03:16.801449: Step 3900: Cross entropy = 0.003834
  1242. 2017-01-13 09:03:16.868646: Step 3900: Validation accuracy = 100.0%
  1243. 2017-01-13 09:03:17.553833: Step 3910: Train accuracy = 100.0%
  1244. 2017-01-13 09:03:17.553922: Step 3910: Cross entropy = 0.004162
  1245. 2017-01-13 09:03:17.618802: Step 3910: Validation accuracy = 100.0%
  1246. 2017-01-13 09:03:18.333691: Step 3920: Train accuracy = 100.0%
  1247. 2017-01-13 09:03:18.335154: Step 3920: Cross entropy = 0.003786
  1248. 2017-01-13 09:03:18.404548: Step 3920: Validation accuracy = 100.0%
  1249. 2017-01-13 09:03:19.099781: Step 3930: Train accuracy = 100.0%
  1250. 2017-01-13 09:03:19.099889: Step 3930: Cross entropy = 0.004219
  1251. 2017-01-13 09:03:19.160142: Step 3930: Validation accuracy = 100.0%
  1252. 2017-01-13 09:03:19.858362: Step 3940: Train accuracy = 100.0%
  1253. 2017-01-13 09:03:19.858513: Step 3940: Cross entropy = 0.004068
  1254. 2017-01-13 09:03:19.923234: Step 3940: Validation accuracy = 100.0%
  1255. 2017-01-13 09:03:20.619357: Step 3950: Train accuracy = 100.0%
  1256. 2017-01-13 09:03:20.619465: Step 3950: Cross entropy = 0.003294
  1257. 2017-01-13 09:03:20.683728: Step 3950: Validation accuracy = 100.0%
  1258. 2017-01-13 09:03:21.362124: Step 3960: Train accuracy = 100.0%
  1259. 2017-01-13 09:03:21.362224: Step 3960: Cross entropy = 0.003749
  1260. 2017-01-13 09:03:21.425749: Step 3960: Validation accuracy = 100.0%
  1261. 2017-01-13 09:03:22.117165: Step 3970: Train accuracy = 100.0%
  1262. 2017-01-13 09:03:22.117245: Step 3970: Cross entropy = 0.003662
  1263. 2017-01-13 09:03:22.182718: Step 3970: Validation accuracy = 100.0%
  1264. 2017-01-13 09:03:22.865505: Step 3980: Train accuracy = 100.0%
  1265. 2017-01-13 09:03:22.865580: Step 3980: Cross entropy = 0.003771
  1266. 2017-01-13 09:03:22.927317: Step 3980: Validation accuracy = 100.0%
  1267. 2017-01-13 09:03:23.618296: Step 3990: Train accuracy = 100.0%
  1268. 2017-01-13 09:03:23.618396: Step 3990: Cross entropy = 0.003498
  1269. 2017-01-13 09:03:23.682354: Step 3990: Validation accuracy = 100.0%
  1270. 2017-01-13 09:03:24.302884: Step 3999: Train accuracy = 100.0%
  1271. 2017-01-13 09:03:24.302989: Step 3999: Cross entropy = 0.003753
  1272. 2017-01-13 09:03:24.369273: Step 3999: Validation accuracy = 100.0%
  1273. CRITICAL:tensorflow:Label profile has no images in the category testing.
Advertisement
Add Comment
Please, Sign In to add comment
Advertisement
Public Pastes
Advertisement
We use cookies for various purposes including analytics. By continuing to use Pastebin, you agree to our use of cookies as described in the Cookies Policy.  OK, I Understand
Not a member of Pastebin yet?
Sign Up, it unlocks many cool features!