Why test acuracy is 0%?

username: Mohammad_Islam
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username: ptrblck
cooked: <p>Based on the notebook it seems you are working on an assignment and don’t provide much information here.<br>
If you get stuck at a specific PyTorch-related problem, feel free to add some information to your post.</p>

username: Mohammad_Islam
cooked: <p>I’m working on a project which is a part of my Udacity ND…in the project at Ques./ step 3<br>
I have to build a NN from scratch and achieve test accuracy more than 10% but I am getting 0%…I also seeing that my Validation loss is increasing whereas test loss is decreasing…</p>
<p>then at step 4 I have to train my model using transfer learning and achieve test accuracy more than 60% where I could achieve 53% just about 20 epochs so I think increasing epoch can help or tuning learning rate  but here also It would be helpful if u suggest…</p>
<p>at last…in step 6 I am getting abnormal percentage in the output section<br>
<div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/6/b/6b5eac31d79f955d5fe99df881fc29b4f38dcc47.png" data-download-href="https://discuss.pytorch.org/uploads/default/6b5eac31d79f955d5fe99df881fc29b4f38dcc47" title="ddd"><img src="https://discuss.pytorch.org/uploads/default/original/3X/6/b/6b5eac31d79f955d5fe99df881fc29b4f38dcc47.png" alt="ddd" data-base62-sha1="fjPVjS0otVnjxYSulidnyNuaWVx" width="690" height="410" data-dominant-color="F3F3F3"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">ddd</span><span class="informations">905×539 21.9 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div><br>
<div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/6/d/6dc609a3aca41db1714d77818c40d10046402418.png" data-download-href="https://discuss.pytorch.org/uploads/default/6dc609a3aca41db1714d77818c40d10046402418" title="ddd"><img src="https://discuss.pytorch.org/uploads/default/optimized/3X/6/d/6dc609a3aca41db1714d77818c40d10046402418_2_510x500.png" alt="ddd" data-base62-sha1="fF6kXfJ1S6y29f9RRqtqZA13pB6" width="510" height="500" srcset="https://discuss.pytorch.org/uploads/default/optimized/3X/6/d/6dc609a3aca41db1714d77818c40d10046402418_2_510x500.png, https://discuss.pytorch.org/uploads/default/original/3X/6/d/6dc609a3aca41db1714d77818c40d10046402418.png 1.5x, https://discuss.pytorch.org/uploads/default/original/3X/6/d/6dc609a3aca41db1714d77818c40d10046402418.png 2x" data-dominant-color="D5D6D8"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">ddd</span><span class="informations">587×575 202 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div></p>

username: ptrblck
cooked: <p>I would recommend to scale down the problem and verify each step of your calculations.<br>
I.e. if your code predicts a 0% accuracy, check some output samples and compare them to the ground truth label. If some are right, your accuracy calculation seems to be wrong.</p>
<p>The same applies for your out of bounds probabilities: print each output separately, calculate the expected result manually and compare it to your formula.</p>
<p>I’m hesitant to help much further, as I believe that you would learn the most by digging into the code and debug it.</p>