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README.md

@@ -37,6 +37,7 @@ MaskDistill learns visual representations by distilling knowledge from a frozen
 | Evaluation | Result |
 |-----------|--------|
 | k-NN (k=10) | **75.6%** top-1 |
+| Linear Probe | **76.3%** top-1 |
 | Sem. Seg. (ADE20K, UPerNet) | **52.6** mIoU |
 | Obj. Det. (COCO, Mask R-CNN) | **44.4** bbox mAP |
 | Inst. Seg. (COCO, Mask R-CNN) | **40.1** segm mAP |
@@ -46,6 +47,7 @@ MaskDistill learns visual representations by distilling knowledge from a frozen
 | File | Description |
 |------|------------|
 | `pretrain_vit_base_ep290.pth` | Pretrained ViT-Base (300 epochs) |
+| `linprobe_vit_base_ep90.pth.tar` | Linear probe (90 epochs, 76.3% top-1) |
 | `semseg_upernet_ade20k_160k.pth` | UPerNet on ADE20K (52.6 mIoU) |
 | `detection_maskrcnn_coco_12ep.pth` | Mask R-CNN on COCO (44.4 mAP) |