My learning curves are giving fluctuations for a 3 class classification problem. I am training using Resnet 50 with

class 1 of 899 images

class 2 of 899 images

class 3 of 690 images.

My model gave a

train accuracy of 99.5%

validation accuracy 93%

test accuracy of 88%

with Epochs = 300, Batch size 32 and learning rate 0.1.

i tried tuning my parameters to epochs 50, 100, 200, 300, batch size 16,32, and learning rate 0.1,0.01,0.001,0.0001, still the spikes are present. Is the problem with my model or dataset? How can i actually know that my model is actually learning?