| # EfficientNet Model | |
| ## Model Class | |
| ```python | |
| model = efficientnet_b0(weights='IMAGENET1K_V1') | |
| in_features = model.classifier[1].in_features | |
| model.classifier[1] = nn.Linear(in_features, 2) | |
| device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') | |
| model.to(device) | |
| criterion = nn.MSELoss() | |
| optimizer = optim.Adam(model.parameters(), lr=1e-4) | |
| ``` | |
| ## How to Run | |
| In the notebook Run_EfficientNet.ipynb, replace the line: | |
| ```python | |
| dataset_test = load_dataset("gydou/released_img") | |
| ``` | |
| with the proper location of the testing dataset. | |
| ## Training Dataset Statistics | |
| ```python | |
| lat_std = 0.0006914493505038013 | |
| lon_std = 0.0006539239061573955 | |
| lat_mean = 39.9517411499467 | |
| lon_mean = -75.19143213125122 | |
| ``` |