Looking at the plot, it seems that the network “converged” after ~100 epochs. It’s nothing unusual, especially if you have smaller datasets like yours. From the plot, it really looks pretty normal to me. You can try different (e.g., adaptive learning rate) optimizers though to minimize fluctuations in the end – if that would help with generalization performance is a different issue though.