Minor fixes to Gradio and visualization scripts

scripts/demo_gradio.py

@@ -49,7 +49,8 @@ EVAL_REPORT_PATH = OUTPUTS_DIR / "evaluation_report.json"
 TRAINING_HISTORY_PATH = OUTPUTS_DIR / "training_history.json"
 
 # Emotion display - clean labels without emojis for research aesthetic
-EMOTION_LABELS = {\n    "joy": "Joy", "love": "Love", "anger": "Anger", "fear": "Fear",
+EMOTION_LABELS = {
+    "joy": "Joy", "love": "Love", "anger": "Anger", "fear": "Fear",
     "sadness": "Sadness", "surprise": "Surprise", "neutral": "Neutral",
     "admiration": "Admiration", "amusement": "Amusement", "annoyance": "Annoyance",
     "approval": "Approval", "caring": "Caring", "confusion": "Confusion",

scripts/visualize_training.py

@@ -410,7 +410,6 @@ def plot_learning_rate(run) -> None:
         # Estimate total steps from training loss history
         train_loss = client.get_metric_history(run.info.run_id, "train_total_loss")
         if train_loss:
-            epochs_completed = len(train_loss)
             # Estimate ~800 steps per epoch based on typical config
             estimated_steps_per_epoch = 800
             total_steps = max_epochs * estimated_steps_per_epoch
@@ -447,7 +446,7 @@ def plot_learning_rate(run) -> None:
                 transform=ax.transAxes, ha="right", va="bottom",
                 fontsize=9, color="gray", style="italic")
     else:
-        steps = [m.step for m in lr_metrics]
+        steps = np.array([m.step for m in lr_metrics])
         values = [m.value for m in lr_metrics]
 
         # Fill under curve for visual appeal