title: SSD-mobilenet object detection algorithm not converging
body: <p>Hi I am trying to train <strong>SSD -mobilenet</strong> in-order to detect 13 classes. I also trained a <strong>faster rcnn -resnet101</strong> . </p>
  
  <p>My training data images have resolution of 265 * 450 . (most of them) and each class had 400 images. </p>
  
  <p>Then this weird thing happened faster rcnn converged faster  with <strong>batch size of 1</strong> . </p>
  
  <p>But my SSD didn't . It's not converging at all . Here I will put the two graphs ,</p>
  
  <p>Purple - Faster Rcnn | resnet101
  Blue   - SSD | mobilenet </p>
  
  <p><a href="https://i.stack.imgur.com/jxti8.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/jxti8.png" alt="enter image description here"></a></p>
  
  <p>I have seen some have trained this for few classes and obtained good results . If anyone have obtained good results please answer following .</p>
  
  <p>You had only one class , so How fast it converged ? 
  What do you think , the network is suffering from vanishing gradents problem or local minima problem ? </p>
  
  <p>Editing - Here I will update the mAp for each category plot . </p>
  
  <p><a href="https://i.stack.imgur.com/ua7bp.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/ua7bp.png" alt="mAp score for each category when using ssd with mobilenet "></a></p>