Upload evaluation/main_model_evaluation.py with huggingface_hub

evaluation/main_model_evaluation.py

@@ -1073,34 +1073,33 @@ class ColorHierarchyEvaluator:
         
         # Extract specialized hierarchy embeddings (dims 16-79)
         print("\n📝 Extracting specialized text hierarchy embeddings (dims 16-79)...")
-        text_hierarchy_embeddings_spec = text_full_embeddings[:, self.color_emb_dim:self.color_emb_dim+self.hierarchy_emb_dim]  # dims 16-79
+        text_hierarchy_embeddings_spec = text_full_embeddings[:, self.color_emb_dim:self.color_emb_dim+self.hierarchy_emb_dim] 
         print(f"   Specialized text hierarchy embeddings shape: {text_hierarchy_embeddings_spec.shape}")
         text_hierarchy_metrics = self.compute_similarity_metrics(text_hierarchy_embeddings_spec, text_hierarchies_full)
         # Use ensemble: combine specialized (64D) + full (512D)
         text_hierarchy_class = self.evaluate_classification_performance(
             text_hierarchy_embeddings_spec, text_hierarchies_full,
             "Text Hierarchy Embeddings (Ensemble)", "Hierarchy",
-            full_embeddings=text_full_embeddings, ensemble_weight=0.4
+            full_embeddings=text_full_embeddings, ensemble_weight=1
         )
         text_hierarchy_metrics.update(text_hierarchy_class)
         results['text_hierarchy'] = text_hierarchy_metrics
 
         # Image hierarchy embeddings with ensemble
         print("\n🖼️ Extracting specialized image hierarchy embeddings (dims 16-79)...")
-        image_hierarchy_embeddings_spec = image_full_embeddings[:, self.color_emb_dim:self.color_emb_dim+self.hierarchy_emb_dim]  # dims 16-79
+        image_hierarchy_embeddings_spec = image_full_embeddings[:, self.color_emb_dim:self.color_emb_dim+self.hierarchy_emb_dim] 
         print(f"   Specialized image hierarchy embeddings shape: {image_hierarchy_embeddings_spec.shape}")
         image_hierarchy_metrics = self.compute_similarity_metrics(image_hierarchy_embeddings_spec, image_hierarchies_full)
         image_hierarchy_class = self.evaluate_classification_performance(
             image_hierarchy_embeddings_spec, image_hierarchies_full,
             "Image Hierarchy Embeddings (Ensemble)", "Hierarchy",
-            full_embeddings=image_full_embeddings, ensemble_weight=0.4
+            full_embeddings=image_full_embeddings, ensemble_weight=1
         )
         image_hierarchy_metrics.update(image_hierarchy_class)
         results['image_hierarchy'] = image_hierarchy_metrics
 
         # Cleanup
         del text_full_embeddings, image_full_embeddings
-        del text_color_embeddings_spec, image_color_embeddings_spec
         del text_hierarchy_embeddings_spec, image_hierarchy_embeddings_spec
         torch.cuda.empty_cache() if torch.cuda.is_available() else None
 
@@ -1165,7 +1164,7 @@ class ColorHierarchyEvaluator:
         text_color_class = self.evaluate_classification_performance(
             text_color_embeddings_spec, text_colors_full, 
             "Text Color Embeddings (Ensemble)", "Color",
-            full_embeddings=text_full_embeddings, ensemble_weight=0.4  # 40% specialized, 60% full
+            full_embeddings=text_full_embeddings, ensemble_weight=1
         )
         text_color_metrics.update(text_color_class)
         results['text_color'] = text_color_metrics
@@ -1178,7 +1177,7 @@ class ColorHierarchyEvaluator:
         image_color_class = self.evaluate_classification_performance(
             image_color_embeddings_spec, image_colors_full,
             "Image Color Embeddings (Ensemble)", "Color",
-            full_embeddings=image_full_embeddings, ensemble_weight=0.4
+            full_embeddings=image_full_embeddings, ensemble_weight=1  # 40% specialized, 60% full
         )
         image_color_metrics.update(image_color_class)
         results['image_color'] = image_color_metrics