I tried with 80/20 instead of 90/10 but didnt see much difference in loss curves.
As for shuffling across test and train sets,  I checked the number of samples per class for the 9 classes:

For test set:

{'0': 96,
 '1': 81,
 '2': 89,
 '3': 96,
 '4': 97,
 '5': 104,
 '6': 102,
 '7': 125,
 '8': 148}


For train set:

{'0': 406,
 '1': 319,
 '2': 316,
 '3': 352,
 '4': 443,
 '5': 408,
 '6': 516,
 '7': 454,
 '8': 512}

Seems appropriately shuffled to me, I am not sure if there are other things I should analyse.
P.S: The annotations count per class for the original un-augmented dataset:
4
79
81
30
68
53
41
57
32