Update README.md

README.md

@@ -52,32 +52,29 @@ Rules:
 - For Track 3, only the Google training split may be used for training.
 
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-
 ## Results
 
 Models evaluated on the official test split (spatial holdout by French department — see dataset card for details).
 
 ### Segmentation (DeepLabV3-ResNet101)
 
-| Provider | IoU | F1 |
-|----------|-----|----|
-| Google | TBD | TBD |
-| IGN | TBD | TBD |
+| Train | Test | IoU | F1 | n (test) |
+|-------|------|-----|----|----------|
+| Google | Google | 0.884 | 0.937 | 1,935 |
+| IGN | IGN | 0.735 | 0.844 | 1,239 |
+| Google | IGN | 0.561 | 0.709 | 1,239 |
+| IGN | Google | 0.657 | 0.786 | 1,935 |
 
 ### Classification (InceptionV3)
 
-| Provider | Accuracy | F1 |
-|----------|----------|----|
-| Google | TBD | TBD |
-| IGN | TBD | TBD |
-
-### Distribution shift benchmark
-
-Train on Google, evaluate on IGN — the intended cross-provider protocol:
+| Train | Test | Accuracy | Precision | Recall | F1 | n (test) |
+|-------|------|----------|-----------|--------|----|----------|
+| Google | Google | 0.952 | 0.990 | 0.912 | 0.949 | 3,884 |
+| IGN | IGN | 0.640 | 0.831 | 0.309 | 0.451 | 2,593 |
+| Google | IGN | 0.592 | 0.815 | 0.188 | 0.306 | 2,593 |
+| IGN | Google | 0.543 | 1.000 | 0.083 | 0.153 | 3,884 |
 
-| Model | Train | Test | IoU |
-|-------|-------|------|-----|
-| DeepLabV3-ResNet101 | Google | IGN | TBD |
+**Note on classification cross-provider results:** the IGN-trained model collapses on Google imagery (Recall=0.08, Precision=1.0), indicating the model rarely predicts positives — a degenerate operating point. This illustrates the severity of the distribution shift documented in [Kasmi et al. (2025)](https://doi.org/10.1017/eds.2025.13).
 
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