diff --git a/main.py b/main.py
index ed9ca39..258cb70 100644
--- a/main.py
+++ b/main.py
@@ -335,7 +335,8 @@ async def scores(ctx):
     }
 
     normalized_scores = {
-        model: summed_scores[model] / len(all_hashes) for model in summed_scores
+        model: round(summed_scores[model] / len(all_hashes), 10)
+        for model in summed_scores
     }
 
     print("scores are [worst...best]")
@@ -346,29 +347,29 @@ async def scores(ctx):
         reverse=True,
     ):
         print(model, normalized_scores[model])
+        if os.getenv("SHOWOFF", "0") == "1":
+            print("[", end="")
 
-        print("[", end="")
+            for bad_md5_hash in sorted(
+                model_scores[model].keys(),
+                key=lambda md5_hash: model_scores[model][md5_hash]["score"],
+            )[:4]:
+                data = model_scores[model][bad_md5_hash]
+                if os.getenv("DEBUG", "0") == "1":
+                    print(md5_hash, data["score"], " ".join(data["incorrect_tags"]))
+                else:
+                    print(data["score"], end=",")
+            print("...", end="")
 
-        for bad_md5_hash in sorted(
-            model_scores[model].keys(),
-            key=lambda md5_hash: model_scores[model][md5_hash]["score"],
-        )[:4]:
-            data = model_scores[model][bad_md5_hash]
-            if os.getenv("DEBUG", "0") == "1":
-                print(md5_hash, data["score"], " ".join(data["incorrect_tags"]))
-            else:
+            for good_md5_hash in sorted(
+                model_scores[model].keys(),
+                key=lambda md5_hash: model_scores[model][md5_hash]["score"],
+                reverse=True,
+            )[:4]:
+                data = model_scores[model][good_md5_hash]
                 print(data["score"], end=",")
-        print("...", end="")
 
-        for good_md5_hash in sorted(
-            model_scores[model].keys(),
-            key=lambda md5_hash: model_scores[model][md5_hash]["score"],
-            reverse=True,
-        )[:4]:
-            data = model_scores[model][good_md5_hash]
-            print(data["score"], end=",")
-
-        print("]")
+            print("]")
         print("most incorrect tags", incorrect_tags_counters[model].most_common(5))