Upload fedprox/rounds/round_18/hospital_NVIDIA_round_18_metadata.json with huggingface_hub

fedprox/rounds/round_18/hospital_NVIDIA_round_18_metadata.json

@@ -0,0 +1,33 @@
+{
+    "client_id": "hospital_NVIDIA",
+    "client_repo": "ChisDong/Client_NVIDIA_IID",
+    "scenario": "iid",
+    "round": 18,
+    "status": "completed",
+    "method": "FedProx",
+    "local_training_method": "FedProx",
+    "aggregation_method": "FedAvg",
+    "fedprox_mu": 0.01,
+    "experiment_folder": "fedprox",
+    "train_samples": 2283,
+    "val_samples": 384,
+    "samples": 2283,
+    "local_epochs": 1,
+    "base_global_model": "fedprox/global_model_round_18.safetensors",
+    "created_at": "2026-05-25T10:01:44.286841",
+    "train_loss": 0.42269920330080724,
+    "train_accuracy": 0.8580814717477004,
+    "train_sensitivity_macro": 0.8431685659783626,
+    "train_specificity_macro": 0.9715385937765975,
+    "train_precision_macro": 0.7964070658354699,
+    "train_f1_macro": 0.815965328583087,
+    "train_auc_macro_ovr": 0.9831590375270862,
+    "val_loss": 0.5791229752552075,
+    "val_accuracy": 0.828125,
+    "val_sensitivity_macro": 0.6172690888748728,
+    "val_specificity_macro": 0.9621390712139462,
+    "val_precision_macro": 0.6545236754989077,
+    "val_f1_macro": 0.6051974578793485,
+    "val_auc_macro_ovr": 0.9527929358221341,
+    "delta_file": "hospital_NVIDIA_round_18_delta.safetensors"
+}