ydwen / opensphere

A hyperspherical face recognition library based on PyTorch
https://opensphere.world/
MIT License
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Overfitting Detection #22

Open akirs82 opened 1 year ago

akirs82 commented 1 year ago

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

ydwen commented 1 year ago

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.

akirs82 commented 1 year ago

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,

  1. Validation1 accuracy vs Iteration
  2. 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

sofpya commented 1 year ago

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.