Fix splitting for generative tasks

src/lighteval/data.py

@@ -252,11 +252,11 @@ def init_split_limits(self, num_dataset_splits):
             )
 
         if len(self.sorted_data) > 0:
-            all_sorting_criterion = [self._sorting_criteria(self.sorted_data[0])[:2]]
+            all_sorting_criterion = [self._sorting_criteria(self.sorted_data[0])[:-1]]
         splits_indices = [[0, None]]
         for ix, req in enumerate(self.sorted_data):
             current_sorting_criteria = self._sorting_criteria(req)
-            current_key = current_sorting_criteria[:2]
+            current_key = current_sorting_criteria[:-1]
             if current_key not in all_sorting_criterion:
                 all_sorting_criterion.append(current_key)
                 splits_indices[-1][1] = ix
@@ -269,7 +269,7 @@ def init_split_limits(self, num_dataset_splits):
         splits_indices = [tuple(e) for e in splits_indices]
         return num_dataset_splits, splits_indices
 
-    def _sorting_criteria(self, request: GreedyUntilRequest) -> tuple[bool, bool, list, int]:
+    def _sorting_criteria(self, request: GreedyUntilRequest) -> tuple[bool, bool, list, int, int]:
         """
         Collate function for generating batches.
 
@@ -284,7 +284,13 @@ def _sorting_criteria(self, request: GreedyUntilRequest) -> tuple[bool, bool, li
         # The generative task has no limit except the model context
         if gen_length is None:
             gen_length = 0
-        return request.do_sample, request.use_logits, request.stop_sequence, -(len(toks) + gen_length)
+        return (
+            request.do_sample,
+            request.use_logits,
+            tuple(request.stop_sequence),
+            gen_length,
+            -(len(toks) + gen_length),
+        )
 
 
 class GenerativeTaskDatasetNanotron(GenerativeTaskDataset):