project_ceo

Step-by-step Instructions for Use

1. Clone this repository.

2. Open a terminal and navigate to the root directory (.../project_ceo).

3. Run the following: python train.py --dataset "MNIST" --optim "Adam"

   3a. The choice of optimizers at the moment include "Adam", "SGD", "Adamax", "RMSProp" "Adabelief", and "Adagrad". The optim argument is case sensitive. Additionally, the choice of "All" will train all of the optimizers at once.

   3b. The choice of datasets include "MNIST" and "CIFAR10". If time permits, a setting will be implemented such that if the dataset exists in torchvision.datasets, the code will run with the optimizers, though optimizer conditions or convergence will not be guaranteed.

Viewing Results

1. The training and validation accuracies are available in the /images directory.

The final paper generated for the project can be read here: 606_Project.pdf