- MNIST competition submission files
- Used Keras
- Model Architecture
Model | Description | Accuracy |
---|---|---|
VGG-like | VGGNet-like but smaller | 99.71% |
Resnet-like | ResNet-like but smaller | 99.60% |
VGG-like | VGGNet-like but even smaller than the first one | 99.63% |
Final | Ensemble 3 models + Voting | 99.80% |
python evaluation.py
python resnet.py 10 # 10 epochs & resnet
python vgg16.py 10 # 10 epochs & vgg
python vgg5.py 10 # 10 epochs & vgg
├── evaluation.py # evaluation.py
├── images # model architectures
│ ├── resnet.png
│ ├── vggnet5.png
│ └── vggnet.png
├── MNIST # mnist data (not included in this repo)
│ ├── t10k-images-idx3-ubyte.gz
│ ├── t10k-labels-idx1-ubyte.gz
│ ├── train-images-idx3-ubyte.gz
│ └── train-labels-idx1-ubyte.gz
├── model # model weights
│ ├── resnet.h5
│ ├── vggnet5.h5
│ └── vggnet.h5
├── model.py # base model interface
├── README.md
├── utils.py # helper functions
├── resnet.py
├── vgg16.py
└── vgg5.py