Difference between revisions of "Tutorial: Binary Matcher with TensorFlow"

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0 cost = 4.06461 Accuracy on training data = 7.78% Accuracy on test data = 0.00%
 +
100 cost = 0.0568146 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
 +
200 cost = 0.0249612 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
 +
300 cost = 0.0156735 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
 +
400 cost = 0.0113394 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
 +
500 cost = 0.00885047 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
 +
600 cost = 0.00724066 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
 +
700 cost = 0.00611609 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
 +
800 cost = 0.00528698 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
 +
900 cost = 0.00465089 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
 +
1000 cost = 0.00414775 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
 +
1100 cost = 0.00374 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
 +
1200 cost = 0.00340309 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
 +
1300 cost = 0.00312006 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
 +
1400 cost = 0.00287907 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
 +
1500 cost = 0.00267149 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
 +
1600 cost = 0.00249079 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
 +
1700 cost = 0.00233219 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
 +
1800 cost = 0.00219193 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
 +
1900 cost = 0.00206695 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
 +
2000 cost = 0.00195495 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
  
 
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Revision as of 14:32, 19 March 2017

--D. Thiebaut (talk) 15:26, 19 March 2017 (EDT)

Source


This tutorial is in the form of a Jupyter Notebook, and made available here in various forms:


Output


0 cost = 4.06461 Accuracy on training data = 7.78% Accuracy on test data = 0.00%
100 cost = 0.0568146 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
200 cost = 0.0249612 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
300 cost = 0.0156735 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
400 cost = 0.0113394 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
500 cost = 0.00885047 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
600 cost = 0.00724066 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
700 cost = 0.00611609 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
800 cost = 0.00528698 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
900 cost = 0.00465089 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
1000 cost = 0.00414775 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
1100 cost = 0.00374 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
1200 cost = 0.00340309 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
1300 cost = 0.00312006 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
1400 cost = 0.00287907 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
1500 cost = 0.00267149 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
1600 cost = 0.00249079 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
1700 cost = 0.00233219 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
1800 cost = 0.00219193 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
1900 cost = 0.00206695 Accuracy on training data = 100.00% Accuracy on test data = 90.00%
2000 cost = 0.00195495 Accuracy on training data = 100.00% Accuracy on test data = 90.00%














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