global -> overall

user-friendly-metrics.py

@@ -113,13 +113,13 @@ class UserFriendlyMetrics(evaluate.Metric):
         debug: bool = False,
     ):
         """
-        Logs metrics to Weights and Biases (wandb) for tracking and visualization, including categorized bar charts for global metrics.
+        Logs metrics to Weights and Biases (wandb) for tracking and visualization, including categorized bar charts for overall metrics.
 
         Args:
-            results (dict): Results dictionary with 'global' and 'per_sequence' keys.
+            results (dict): Results dictionary with 'overall' and 'per_sequence' keys.
             wandb_section (str, optional): W&B section for metric grouping. Defaults to None.
             wandb_project (str, optional): The name of the wandb project. Defaults to 'user_friendly_metrics'.
-            log_plots (bool, optional): Generates categorized bar charts for global metrics. Defaults to True.
+            log_plots (bool, optional): Generates categorized bar charts for overall metrics. Defaults to True.
             debug (bool, optional): Logs detailed summaries and histories to the terminal console. Defaults to False.
         """
 
@@ -160,14 +160,14 @@ class UserFriendlyMetrics(evaluate.Metric):
 
         chart_data = {key: [] for key in categories.keys()}
 
-        # Log global metrics
-        if "global" in results:
-            for global_key, global_metrics in results["global"].items():
-                for metric, value in global_metrics["all"].items():
+        # Log overall metrics
+        if "overall" in results:
+            for overall_key, overall_metrics in results["overall"].items():
+                for metric, value in overall_metrics["all"].items():
                     log_key = (
-                        f"{wandb_section}/global/{global_key}/{metric}"
+                        f"{wandb_section}/overall/{overall_key}/{metric}"
                         if wandb_section
-                        else f"global/{global_key}/{metric}"
+                        else f"overall/{overall_key}/{metric}"
                     )
                     run.log({log_key: value})