---
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)
```