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airg/unet-efficientnet-b7-ltfl-mmgab-150ep-2window-ftw
unet-efficientnet-b7-ltfl-mmgab-150ep-2window-ftw is a machine learning model from airg. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
U-Net generally conforming to the current FTW baseline 3-class model settings, trained on the Fields of the World full dataset, using both time points (Window A, Window B) for 150 epochs. The model is the same as the…
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Updated Apr 14, 2026
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From the Hugging Face model README
U-Net generally conforming to the current FTW baseline 3-class model settings, trained on the Fields of the World full dataset, using both time points (Window A, Window B) for 150 epochs. The model is the same as the current FTW PRUE variant with EfficientNet-b7 backbone, but was trained using a locally-weighted Tversky Focal Loss rather Logcoshdice, and using global min-max across band normalization using the 1st and 99th percentile image values. See here for code and configuration.
Performance metrics on the validation split (calculated across samples from countries listed below):
<table> <thead> <tr> <th></th> <th colspan="4">pixel level</th> <th colspan="3">object level</th> </tr> <tr> <th>iou</th> <th>precision</th> <th>recall</th> <th>f1</th> <th>precision</th> <th>recall</th> <th>f1</th> </tr> </thead> <tbody> <tr> <td>0.824</td> <td>0.913</td> <td>0.893</td> <td>0.903</td> <td>0.488</td> <td>0.373</td> <td>0.422</td> </tr> </tbody> </table>Data included in validation set: