Hi @ashi,
This behaviour of ML models is expected. You can notice that even though there is a gap between the validation loss and train loss, the general trend in both is of decrease. The graph of validation loss will be noisier than that of the train loss.
Possible steps to tackle the problem.

Train for more epochs, gives model more time in searching for global minimums before settling for some local minimums.
Increase model capacity, Over parameterization as discussed here 115 may help in achieving lower validation loss.
Hope this helps!