Update README.md

README.md

@@ -3,4 +3,6 @@ license: mit
 language:
 - en
 pipeline_tag: image-classification
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+---
+Our approach is to design a visual recognition model that considers both the target object and its surrounding environment. To further enhance prediction consistency, we apply a custom loss function that reflects the hierarchical structure of the target categories.
+While we employed standard classification accuracy for training, the primary evaluation metric was hierarchical distance, defined by the number of hops between the predicted label and the ground truth in the taxonomy tree. The final model attained a public distance score of 1.62 and a private distance score of 1.45 on the official evaluation leaderboard.