Can not achieve desired accuracy

I have been trying to complete TF1 C2W4 assignment and could never get the accuracy past 4%. I have gone through most of the posts and tweaked the submission as follows:

  1. Noted that the rescale doesn’t happen twice
  2. Noted that I’ve larger number of features as we go deeper in the NN (increased 32->64)
  3. Have Dense layer with 256 activation functions
  4. Use Adam optimizer with learning rate 0.001
  5. Use sparse_categorial_crossentropy loss function

Despite this, I still have accuracy of 4% as shown below

“loss: nan - accuracy: 0.0410 - val_loss: nan - val_accuracy: 0.0462”

Much appreciate any insight.

Feedback after reviewing your notebook:

Please read this:

Welcome to this assignment! In this exercise, you will get a chance to work on a multi-class classification problem. You will be using the Sign Language MNIST dataset, which contains 28x28 images of hands depicting the 26 letters of the english alphabet.

Your NN has 3 output units. Please fix this.

Thanks @balaji.ambresh somehow I went in autopilot mode thinking it was rock-paper-scissors problem (even the pictures shown in intermediate stages did not wake me up). Will try and mark this as solution (I’ve run out of free gpu time on colab)

Makarand