Why does discriminiator accuracy falls to 0%, and is there a fix around this?
I figured out my answer a while back. SO here it goes... 


Ensure that your training data is normalized. This was what causing the discriminator's accuracy to fall. 
You need to decrease your dropouts as it can cause heavy bias if done ineffectively.
Remove any unnecessary layers in your discriminator as they can cause overfitting.
Use batch normalization.
Introduce dropouts in your generator.