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segformer-b0-kaggle-ktm-dataset-block-fold0
Pranilllllll/segformer-b0-kaggle-ktm-dataset-block-fold0
segformer-b0-kaggle-ktm-dataset-block-fold0 is a machine learning model from Pranilllllll. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
Kathmandu Valley land-use segmentation, 6 classes, ignoreindex=255.
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Updated Aug 17, 2026
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.pt74.7 MB · 96%
At a glance
- Library
- transformers
- Access
- Public
- Created
- Aug 17, 2026
- Updated
- Aug 17, 2026
- SHA
- 9b95af20
Model card
From the Hugging Face model README
GeoNUSAF - SegFormer-B0 - block split, fold 0
Kathmandu Valley land-use segmentation, 6 classes, ignore_index=255.
| field | value |
|---|---|
| architecture | SegformerForSemanticSegmentation, nvidia/segformer-b0-finetuned-ade-512-512 |
| split mode | block |
| fold | 0 of 3 |
| seed | 42 |
| input | 512x512, ImageNet norm, effective GSD 0.586 m/px |
| classes | Residential, Road, River, Forest, UnusedLand, Agricultural |
| lr (head/encoder) | 6e-05 / 6e-06 |
| regularization | wd 0.01, drop_path 0.1, smooth 0.05, EMA True |
| best epoch | 13 |
| val mIoU | 0.2877 |
| val mF1 | 0.4127 |
| val OA | 0.5704 |
| val kappa | 0.4385 |
Per-class (validation)
| class | IoU | F1 |
|---|---|---|
| Residential | 0.4619 | 0.6319 |
| Road | 0.1215 | 0.2166 |
| River | 0.0084 | 0.0167 |
| Forest | 0.5420 | 0.7030 |
| UnusedLand | 0.2381 | 0.3847 |
| Agricultural | 0.3542 | 0.5231 |
Checkpoint best.pt holds model_state (EMA weights when EMA is on), the run cfg, the full HF model_config, and metrics.
- Library
- transformers
- Created
- Aug 17, 2026
- Updated
- Aug 17, 2026