title: Tensorflow - loss not decreasing
body: <p>Lately, I have been trying to replicate the results of <a href="https://medium.com/@tuennermann/convolutional-neural-networks-to-find-cars-43cbc4fb713" rel="nofollow noreferrer">this post</a>, but using TensorFlow instead of Keras. However, my model loss is not converging as <a href="https://github.com/HTuennermann/Vehicle-Detection-and-Tracking" rel="nofollow noreferrer">in the code provided</a>. I took care to use the same parameters used by the author, even those not explicitly shown. My complete code can be seen <a href="https://gist.github.com/arnaldog12/2f6e8910f56a73e95be682143193682e" rel="nofollow noreferrer">here</a>.</p>
  
  <p>I have already tried different learning rates, optimizers, and batch sizes, but these did not affect the result very much as well. </p>
  
  <p>I found a bunch of other questions related to this problem here in StackOverflow and StackExchange, but most of them had no answer at all. The questions with answers, however, did not help.</p>
  
  <p>I'm using TensorFlow 1.1.0,  Python 3.6 and Windows 10. </p>
  
  <p>The most weird thing is that we have the same database and the same model, but just different frameworks. Thus, it was not supposed to give completely different behaviours. Does anyone have suggestions about what should I try to solve this problem, please?</p>