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