readme: ---
  framework: pytorch
  model: EfficientNet-B1
  dataset: CIFAR10 (restructured to have random upright and upside-down samples, with labels {0:'up', 1:'down'}
  imgSize: 224x224x3
  ---
  
  
  This repository contains model trained to predict orientation {0:'up', 1:'down'} of images.
  The model '.pkl' file contains a dictionary with the following keys:
  
  ```python:
  'optimizer': optimizer state dictionary
  'scheduler': scheduler state dictionary
  'model': model state dictionary
  'epoch': checkpoint epoch
  ```
  
  The image size is 3x224x224. The model can be initialized as:
  
  ```python:
  model = torchvision.models.efficientnet_b1(pretrained=True)
  
  in_features = model.classifier[1].in_features
  out_features = 2
  
  model.classifier[1] = nn.Linear(in_features, out_features, bias=True)
  ```