Update score calc

src/leaderboard/read_evals.py

@@ -124,22 +124,27 @@ class EvalResult:
         scores = {
             'naive_judge': self.results.get('naive_judge', 0),
             'human_eval_solidity_pass_1': self.results.get('human_eval_solidity_pass_1', 0),
-            'human_eval_solidity_pass_3': self.results.get('human_eval_solidity_pass_3', 0)
+            'human_eval_solidity_pass_3': self.results.get('human_eval_solidity_pass_3', 0),
         }
-    
-        soliditybench = 0
-        non_zero_scores = {k: v for k, v in scores.items() if v != 0}
-        if non_zero_scores:
+
+        # Set soliditybench score to 0 if HumanEval scores are not present
+        if (scores['human_eval_solidity_pass_1'] == 0 and 
+                scores['human_eval_solidity_pass_3'] == 0):
+            soliditybench = 0
+        else:
+            non_zero_scores = {k: v for k, v in scores.items() if v != 0}
             weights = {
                 'naive_judge': 0.1,
                 'human_eval_solidity_pass_1': 0.5,
-                'human_eval_solidity_pass_3': 0.4
+                'human_eval_solidity_pass_3': 0.4,
             }
             total_weight = sum(weights[k] for k in non_zero_scores)
-            soliditybench = sum(scores[k] * weights[k] / total_weight for k in non_zero_scores)
+            soliditybench = sum(
+                scores[k] * weights[k] / total_weight for k in non_zero_scores
+            )
 
         data_dict = {
-            "eval_name": self.eval_name,  # not a column, just a save name,
+            'eval_name': self.eval_name,  # not a column, just a save name
             AutoEvalColumn.precision.name: self.precision.value.name,
             AutoEvalColumn.model_type.name: self.model_type.value.name,
             AutoEvalColumn.model_type_symbol.name: self.model_type.value.symbol,