diff --git a/evaluation/async_evaluate.py b/evaluation/async_evaluate.py
index ef4d088..396e4c4 100644
--- a/evaluation/async_evaluate.py
+++ b/evaluation/async_evaluate.py
@@ -53,7 +53,7 @@ def __init__(
 
         if not os.path.exists(self.model_config_path):
             raise FileNotFoundError(f"Model configuration for {model_name} not found in {model_configs_dir}")
-        
+
         with open(self.model_config_path, "r") as file:
             self.model_config = json.load(file)
 
@@ -84,11 +84,11 @@ def __init__(
 
         if not os.path.exists(haystack_path):
             raise FileNotFoundError(f"Haystack file not found at {haystack_path}")
-        
+
         self.haystack_path = haystack_path
 
         self.haystack = BookHaystack(self.haystack_path)
-        
+
         self.results_dir = results_dir
         os.makedirs(results_dir, exist_ok=True)
 
@@ -103,14 +103,14 @@ def __init__(
         self.seed = seed
         self.prevent_duplicate = prevent_duplicate
         self.distractor = distractor
-        
+
         self.log_placements = log_placements_dir != ""
         self.log_placements_dir = log_placements_dir
 
         self.test_name = test_name
         self.eval_name = f"{model_name}_book_{test_name}_{int(time.time())}" if test_name != "" else f"{model_name}_book_{int(time.time())}"
 
-    
+
     def _evaluate_response(self, response: str, gold_answers = None) -> int:
         if gold_answers is None:
             gold_answers = self.gold_answers
@@ -132,7 +132,7 @@ def get_hash(self, test_config: dict) -> str:
         del new_config["results"]
         del new_config["eval_name"]
         return hashlib.sha256(json.dumps(new_config, sort_keys=True).encode()).hexdigest()
-        
+
 
     def evaluate(self) -> None:
         np.random.seed(self.seed)
@@ -170,7 +170,7 @@ def evaluate(self) -> None:
             print(f"Results already exist at {results_path}")
             print("Skipping evaluation")
             return
-        
+
         if self.prevent_duplicate:
             for result_filename in os.listdir(self.results_dir):
                 with open(os.path.join(self.results_dir, result_filename), "r") as file:
@@ -180,7 +180,7 @@ def evaluate(self) -> None:
                     print(f"Duplicate test found with similar hash at {self.results_dir} -- TEST_HASH:", outputs["test_hash"])
                     print("Skipping evaluation")
                     return
-        
+
         async_tasks = []
         for i in tqdm(np.linspace(self.document_depth_percent_min, self.document_depth_percent_max, self.document_depth_percent_intervals)):
             needle_depth = i / 100
@@ -200,7 +200,7 @@ def evaluate(self) -> None:
                 retrieval_question = self.retrieval_question
 
             placement_output = self.haystack.generate_w_needle_placement(
-                needle=needle, 
+                needle=needle,
                 token_count_func=self.api_connector.token_count,
                 encoding_func=self.api_connector.encode,
                 decoding_func=self.api_connector.decode,
@@ -216,7 +216,7 @@ def evaluate(self) -> None:
             async_tasks.append(self.api_connector.generate_response(
                 system_prompt=self.system_prompt,
                 user_prompt=filled_template,
-                max_tokens=self.model_config["max_tokens"], 
+                max_tokens=self.model_config["max_tokens"],
                 temperature=self.model_config["temperature"],
                 top_p=self.model_config["top_p"]
             ))
@@ -238,14 +238,14 @@ def evaluate(self) -> None:
             outputs["results"][i]["metric"] = self._evaluate_response(responses[i]["response"], gold_answers=[outputs["results"][i]["selected_character"]]) if "{CHAR}" in self.needle else self._evaluate_response(responses[i]["response"])
             for k, v in responses[i].items():
                 outputs["results"][i][k] = v
-            
+
         # Save results by model name, haystack type, timestamp
         with open(results_path, "w") as file:
             json.dump(outputs, file, indent=4)
-        
+
         print(f"Results saved at {results_path}")
 
-    
+
 
 
 if __name__ == "__main__":
@@ -261,7 +261,6 @@ def evaluate(self) -> None:
     parser.add_argument("--system_prompt", type=str, help="System prompt for the model")
     parser.add_argument("--use_default_system_prompt", type=bool, default=False, help="Use default system prompt")
     parser.add_argument("--task_template", type=str, help="Task template for the model")
-    parser.add_argument("--system_prompt", type=str, help="System prompt for the model")
     parser.add_argument("--context_length", type=int, help="Context length for the needle placement")
     parser.add_argument("--document_depth_percent_min", type=int, default=0, help="Minimum document depth percentage")
     parser.add_argument("--document_depth_percent_max", type=int, default=100, help="Maximum document depth percentage")