Mukesh1729:

Do you think think the validation loss is bad from the output below?


It’s hard to tell, as you are trying to compare two different frameworks, so I don’t know if the validation loss is “good” in this isolated run. Since the models converge to a similar training loss, but give a different validation loss I think that something is still not right.
To check it further you could pass static inputs (e.g. torch.ones) to the model during validation and check, if both models would return approx. the same predictions.
If so, then the model itself seems to be alright and the data loading or preprocessing might be wrong.