Sorry if my question is at the wrong place, I'm new in this community.
So, I have dataset with total of 1 million images (augmented) that separated in 28 classes. I followed this tutorial https://www.tensorflow.org/hub/tutorials/image_retraining to do transfer learning using Inception V3 in Tensorflow to create my own model. But I have no strong background in ML or DL so I'm not sure how to tune the parameter correctly for training step.
This is the training source code that I'm using : https://github.com/tensorflow/hub/raw/master/examples/image_retraining/retrain.py
Using the default setting I was able to get 80~84% accuracy with 16.000 steps. I've tried to change the training, validation, test ratio, training_steps, batch. But, still the accuracy is below 90%. So, Im seeking for advice which parameter that should I change to achieve good accuracy.