Handle out-of-bound loss values from now-fixed code bugs.

app.py

@@ -235,8 +235,8 @@ def get_losses_over_time(wandb_runs: List) -> pd.DataFrame:
         best_loss = math.inf
         for _, uid_data in all_uid_data.items():
             loss = uid_data.get("average_loss", math.inf)
-            # Filter out the numbers from the exploit.
-            if loss < best_loss and (loss > 2.5 or timestamp > datetime.datetime(2024,2,8)):
+            # Filter out the numbers from the exploit and when validators lost the best model.
+            if loss < best_loss and (loss > 2.5 or timestamp > datetime.datetime(2024,2,12)) and (loss < 5 or timestamp > datetime.datetime(2024,3,27)):
                 best_loss = uid_data["average_loss"]
         if best_loss != math.inf:
             timestamps.append(timestamp)