title: can not detect the correct class when using Tensorflow object detection API
body: <p>I am using <strong>tensorflow</strong> object detection API to train and detect my dataset. This dataset has 5 classes(every class has 50 images), and it contains two very similar classes(red and black). After the train process, I detected the test images and found that, the model always detects a target of red class as a target of black class, the other classes is detected as correct class.</p>
  
  <p>I trained the model with <code>faster_rcnn_resnet101_breads.congfig</code>, and using <code>fine_tune_checkpoint.I</code> set the learning_rate to 0.003(the original is 0.0003).</p>
  
  <p>Can you tell me what is wrong with my model, and how much the learning_rate should I set? </p>
  
  <p>The compare result of my config file and samples config file:<a href="https://i.stack.imgur.com/0B9oi.png" rel="nofollow noreferrer">compare result</a></p>
  
  <p>train curves:<a href="https://i.stack.imgur.com/xoMsZ.png" rel="nofollow noreferrer">train curves</a></p>
  
  <pre><code>&gt; black class: https://i.stack.imgur.com/eWrlK.jpg
  &gt; red class: https://i.stack.imgur.com/TuRjg.jpg
  </code></pre>