unet_segmentation: swap tree-crown base checkpoint for a building-pre… - #58
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unet_segmentation: swap tree-crown base checkpoint for a building-pre…#58nilshof01 wants to merge 1 commit into
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…trained base The shipped base (unet_resnet34_oam_rgb_tcd) is a tree-crown delineation model: zero-shot it scores building F1 0.00 on both held-out splits of hotosm/vhr-building-segmentation (n=7,237 val / 7,236 test chips), and fine-tuning from it reaches 50.0 pooled test F1 at 32 chips (6 regions x 5 folds) - below random decoder init (52.4). An identical-architecture base pretrained on hotosm/vhr-building-segmentation reaches 59.3 pooled (+9.3) with the unchanged fine-tune recipe, scores 0.40/0.51 building F1 zero-shot on the dataset val/test splits, and cuts fold variance. It is a raw smp state dict loading via the existing torch.load(weights_only=True) + load_state_dict(strict=False) path with 0 missing / 0 unexpected keys. The checkpoint asset is pinned to the upload revision; training provenance is documented in the model README and on the checkpoint's model card (hf.co/nilsho01/unet-resnet34-vhr-buildings). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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…trained base
The shipped base (unet_resnet34_oam_rgb_tcd) is a tree-crown delineation model: zero-shot it scores building F1 0.00 on both held-out splits of hotosm/vhr-building-segmentation (n=7,237 val / 7,236 test chips), and fine-tuning from it reaches 50.0 pooled test F1 at 32 chips (6 regions x 5 folds) - below random decoder init (52.4).
An identical-architecture base pretrained on
hotosm/vhr-building-segmentation reaches 59.3 pooled (+9.3) with the unchanged fine-tune recipe, scores 0.40/0.51 building F1 zero-shot on the dataset val/test splits, and cuts fold variance. It is a raw smp state dict loading via the existing torch.load(weights_only=True) + load_state_dict(strict=False) path with 0 missing / 0 unexpected keys.
The checkpoint asset is pinned to the upload revision; training provenance is documented in the model README and on the checkpoint's model card (hf.co/nilsho01/unet-resnet34-vhr-buildings.
For more insights into the study have a look here for more insights: https://huggingface.co/nilsho01/unet-resnet34-vhr-buildings