Upload fedprox/latest/metadata.json with huggingface_hub

fedprox/latest/metadata.json

@@ -2,7 +2,7 @@
     "client_id": "hospital_NVIDIA",
     "client_repo": "ChisDong/Client_NVIDIA_IID",
     "scenario": "iid",
-    "round": 3,
+    "round": 4,
     "status": "completed",
     "method": "FedProx",
     "local_training_method": "FedProx",
@@ -13,21 +13,21 @@
     "val_samples": 384,
     "samples": 2283,
     "local_epochs": 1,
-    "base_global_model": "fedprox/global_model_round_3.safetensors",
-    "created_at": "2026-05-25T09:21:29.137139",
-    "train_loss": 0.9243819117546082,
-    "train_accuracy": 0.738939991239597,
-    "train_sensitivity_macro": 0.5283264089839086,
-    "train_specificity_macro": 0.9459210048607712,
-    "train_precision_macro": 0.6563178874172314,
-    "train_f1_macro": 0.52054655159183,
-    "train_auc_macro_ovr": 0.9352440812930974,
-    "val_loss": 0.6366434468266865,
-    "val_accuracy": 0.8046875,
-    "val_sensitivity_macro": 0.5659023906192389,
-    "val_specificity_macro": 0.9609339477964394,
-    "val_precision_macro": 0.49778317782976167,
-    "val_f1_macro": 0.5211958664143184,
-    "val_auc_macro_ovr": 0.9366624210167199,
-    "delta_file": "hospital_NVIDIA_round_3_delta.safetensors"
+    "base_global_model": "fedprox/global_model_round_4.safetensors",
+    "created_at": "2026-05-25T09:24:06.360982",
+    "train_loss": 0.8450007831884755,
+    "train_accuracy": 0.7472623740692071,
+    "train_sensitivity_macro": 0.5837681582626245,
+    "train_specificity_macro": 0.9472128848058804,
+    "train_precision_macro": 0.6543488923495612,
+    "train_f1_macro": 0.5708427645644215,
+    "train_auc_macro_ovr": 0.943034726890087,
+    "val_loss": 0.6255232601736983,
+    "val_accuracy": 0.7890625,
+    "val_sensitivity_macro": 0.5829594425128336,
+    "val_specificity_macro": 0.9603293827194349,
+    "val_precision_macro": 0.495996431359429,
+    "val_f1_macro": 0.5246452651357649,
+    "val_auc_macro_ovr": 0.9385901188667702,
+    "delta_file": "hospital_NVIDIA_round_4_delta.safetensors"
 }