I was running my gated recurrent unit (GRU) model. I wanted to get an opinion if my loss and validation loss graph is good or not, since I'm new to this and don't really know if that is considered underfitting or not
When ever you are buliding a ML Model don't take accuracy seriously(Mistake done by Netflix that cost them alot), you should try to get the hit scores as they will help you to know how many times your model worked on real world users.However, if your model must have to measure the accuracy try it with the RMSE score as it will penalise you more for being more out of the Line. Here is the link for more information on it RMSE Its hard to predict if its overfitting or underfitting as your graph is vague(for example what does graph lines representing). However, you can solve underfitting by following steps: 1) Increase the size or number of parameters in the ML model. 2) Increase the complexity or type of the model. 3) Increasing the training time until cost function in ML is minimised.
For overfitting you can try Regularization methods like weight decay provide an easy way to control overfitting for large neural network models. A modern recommendation for regularization is to use early stopping with dropout and a weight constraint.
You should at least crop the plots and add a legend. Maybe also provide some scores (accuracy, auc, whatever you're using). Anyway, it doesn't look your model is underfitting, if it was you should have high error at both, training and test phase and the lines would not cross.