When I try to train a simple model with a simple dataset, as instructed here, I get weird result as below.
The accuracy varies a lot when I rerun the same code again and again. Why would this happen? If the variation is narrow, I do not bother, but it widely goes from 70% to 95%, rendering the model totally unreliable. Kindly help.
With only one epoch of training, the model is not close to converging, so you will see a wide variation in results. Longer training could help you achieve more consistency.
