Training MNIST benchmark with PyTorch
This notebook reproduces a simple benchmark experiment that trains a convolutional neural network based on the MNIST dataset. In particular, the neural network is built and trained with PyTorch.
MNIST is a database with 60,000 training images and 10,000 testing images that contains hand-written digits. Please see http://yann.lecun.com/exdb/mnist/ for more details.
Digital Object Identifier (DOI)
10.5281/zenodo.4344415 (2020-09-09T01:36UTC)
Launch on Chameleon
Launching this artifact will open it within Chameleon’s shared Jupyter experiment environment, which is accessible to all Chameleon users with an active allocation.
Download ArchiveDownload an archive containing the files of this artifact.