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dinov2_vitb14dinov2_vitb14 features to measure what those features carry.1import visbench
2from visbench.hub import load_probe_from_hub
3
4backbone = visbench.get_backbone("dinov2_vitb14")
5probe = load_probe_from_hub("turhancan97/visbench-semantic_segmentation-dinov2_vitb14", backbone=backbone)dinov2_vitb14, taken with
pooling=mean and feature_mode=dense_only. Loading them against
anything else is refused, because the failure is otherwise silent: a head fitted
on one pooling and fed another has the right shapes and produces a plausible,
wrong number.| backbone | dinov2_vitb14 |
| backbone key | dinov2/dinov2_vitb14/224/7764ea0f912e |
| task | semantic_segmentation (high_level) |
| pooling | mean (requested mean) |
| feature mode | dense_only |
| layers | None |
| metric | value |
|---|---|
mean_acc | 0.8403 |
miou | 0.7533 |
miou_per_image | 0.7161 |
pixel_acc | 0.9316 |
batch_size: 8epochs: 10head: linearhidden_dim: 512ignore_index: -1layers: Noneloss: cross_entropylr: 0.0005miou_reduction: dataset_and_per_imagenum_classes: 21optimizer: adamwprotocol: visbench_semantic_segwarmup_epochs: 1.5weight_decay: 0.0001