From 0eb5a0c0e58367d3a763272c218d9c8fe9de2289 Mon Sep 17 00:00:00 2001 From: Victor Hall Date: Wed, 8 Feb 2023 16:11:09 -0500 Subject: [PATCH] validation docs --- README.md | 2 ++ doc/VALIDATION.md | 6 +++++- 2 files changed, 7 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index fda7e97..4ede281 100644 --- a/README.md +++ b/README.md @@ -41,6 +41,8 @@ Make sure to check out the [tools repo](https://github.com/victorchall/EveryDrea [Data Balancing](doc/BALANCING.md) - Includes my small treatise on model preservation with ground truth data +[Validation](doc/VALIDATION.md) - Use a validation split on your data to see when you are overfitting and tune hyperparameters + ## Cloud [Free tier Google Colab notebook](https://colab.research.google.com/github/victorchall/EveryDream2trainer/blob/main/Train_Colab.ipynb) diff --git a/doc/VALIDATION.md b/doc/VALIDATION.md index 0468d0c..7d007bd 100644 --- a/doc/VALIDATION.md +++ b/doc/VALIDATION.md @@ -1,9 +1,13 @@ # Validation -Validation allows you to split data for evaluating your training progress. +*This documentation is incomplete. Please feel free to contribute to it.* + +Validation allows you to use a split of your data for evaluating your training progress. When training a specific class, setting aside a portion of the data for validation will allow you to see trend lines you cannot see when purely looking at loss of the training itself. +While loss on your training data should trend downward, if you set aside a validation set, you can see when your validation loss starts to trend upward. This is a sign that you are overfitting. You can then adjust your hyperparameters to reduce overfitting, such as reducing LR or reducing training epochs. + ## How to use validation The `validation_config` option is a pointer to a JSON config file with settings for use in validation. There is a default validation file `validation_default.json` in the repo root, but it is not used unless you specify it.