Overfitting Detection
Opened this issue · 3 comments
Hello Ydwen,
I would like to know, from the training and validation logs how to check for overfitting or underfitting of the model capacity to the dataset ? My training loss is class_dataset type and my validation is pair_dataset type.
regards
akirs
Hi akirs82,
You can construct a validation set of pair_dataset type, where the images are from training set.
This is the solution that we are currently using. Will have a push in the near future.
Hello ydwen,
Thank you for the response. Just to summarize. I will split the dataset to training set (as class_dataset) and validation set 1(in the form of pair_dataset type - NON Overlapping with the data in training set). Now i will have validation accuracy and training loss - with this should i get the graphs as below,
- Validation1 accuracy vs Iteration
- Training loss vs Iteration.
(Any pointers how these graphs will explain overfitting - usually it is validation accuracy,training accuracy vs iteration or losses vs iteration)
So based on above graphs,
Is this Validation1 accuracy is like a proxy for the training accuracy ?
I also have another dataset which is not part of the training set. Can i use this as well or not for validation set or as a separate validation set 2 ?
regards
akirs
Hi, akir82.
I am training my own dataset. how to construct the validation dataset with pair dataset type. Because my original dataset is a classification type dataset.