optimize code

dan/predict/prediction.py

@@ -350,7 +350,7 @@ def run(
         index = [pos for pos, char in enumerate(text) if char in ["ⓝ", "ⓟ", "ⓓ", "ⓡ"]]
 
         # calculates scores by token
-        score_by_token = [
+        result["confidences"]["by ner token"] = [
             {
                 "text": f"{text[current: next_token-1]}",
                 "confidence_ner": f"{np.around(np.mean(char_confidences[current : next_token-1]), 2)}",
@@ -359,9 +359,6 @@ def run(
         ]
 
         result["confidences"]["total"] = np.around(np.mean(char_confidences), 2)
-        result["confidences"]["by ner token"] = []
-        for entity in score_by_token:
-            result["confidences"]["by ner token"].append(entity)
 
         for level in confidence_score_levels:
             result["confidences"][level] = []