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--- |
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license: apache-2.0 |
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datasets: |
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- jonathan-roberts1/Satellite-Images-of-Hurricane-Damage |
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tags: |
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- climate |
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--- |
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# Model Card for fluffypotato/flooding-classifier |
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<!-- Provide a quick summary of what the model is/does. --> |
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This model is trained on a subset of `jonathan-roberts1/Satellite-Images-of-Hurricane-Damage?` and performs binary classification on satellite images into either damaged or not damaged. |
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The model was trained using PyTorch on Intel Developer Cloud using ipex optimization. Here is the Neural Network architecture: |
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```python |
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model.fc = nn.Sequential( |
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nn.Linear(2048, 128), |
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nn.ReLU(inplace=True), |
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nn.Linear(128, 64), |
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nn.ReLU(inplace=True), |
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nn.Linear(64, 2)) |
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``` |
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## Uses |
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> |
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Some use cases include emergency response and disaster detection. |
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## Bias, Risks, and Limitations |
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This model is limited in use as it only performs binary classification. Further extensions include adding more classes to the model or more diverse data to the model. |
