Early Stopping for PyTorch

Early stopping is a form of regularization used to avoid overfitting on the training dataset. Early stopping keeps track of the validation loss, if the loss stops decreasing for several epochs in a row the training stops. The EarlyStopping class in early_stopping_pytorch/early_stopping.py is used to create an object to keep track of the validation loss while training a PyTorch model. It will save a checkpoint of the model each time the validation loss decrease. We set the patience argument in the EarlyStopping class to how many epochs we want to wait after the last time the validation loss improved before breaking the training loop. There is a simple example of how to use the EarlyStopping class in the MNIST_Early_Stopping_example notebook.

Underneath is a plot from the example notebook, which shows the last checkpoint made by the EarlyStopping object, right before the model started to overfit. It had patience set to 20.

Installation

Option 1: Install from PyPI (Recommended)

pip install early-stopping-pytorch

Option 2: Install from Source

For development or if you want the latest unreleased changes:

1. Clone the Repository

git clone https://github.com/your_username/early-stopping-pytorch.git
cd early-stopping-pytorch

2. Set Up the Virtual Environment

Run the setup script to create a virtual environment and install all necessary dependencies.

./setup_dev_env.sh

3. Activate the Virtual Environment

Activate the virtual environment:

source dev-venv/bin/activate

4. Install the Package in Editable Mode

Install the package locally in editable mode so you can use it immediately:

pip install -e .

Usage

from early_stopping_pytorch import EarlyStopping

# Initialize early stopping object
early_stopping = EarlyStopping(patience=7, verbose=True)

# In your training loop:
for epoch in range(num_epochs):
    # ... training code ...
    val_loss = ... # calculate validation loss

    # Early stopping call
    early_stopping(val_loss, model)
    if early_stopping.early_stop:
        print("Early stopping triggered")
        break

For a complete example, see the MNIST Early Stopping Example Notebook.

Citation

If you find this package useful in your research, please consider citing it as:

@misc{early_stopping_pytorch,
  author = {Bjarte Mehus Sunde},
  title = {early-stopping-pytorch: A PyTorch utility package for Early Stopping},
  year = {2024},
  url = {https://github.com/Bjarten/early-stopping-pytorch},
}

References

The EarlyStopping class in early_stopping_pytorch/early_stopping.py is inspired by the ignite EarlyStopping class.