Update

opencompass/configs/datasets/korbench/korbench_single_0shot_cascade_eval_gen_56cf43.py

@@ -1,14 +1,24 @@
+"""
+Summary: A config for KoR-Bench Evaluation.
+Setting:
+    Shot: 0-shot
+    Evaluator:
+        - CascadeEvaluator
+            - korbenchEvaluator
+            - GenericLLMEvaluator
+    Repeat: 1
+Avaliable Models:
+    - Instruct/Chat Models
+"""
 from opencompass.datasets.korbench.korbench import korbenchDataset, korbenchEvaluator
 from opencompass.openicl.icl_inferencer import GenInferencer
 from opencompass.openicl.icl_prompt_template import PromptTemplate
 from opencompass.openicl.icl_retriever import ZeroRetriever
-from opencompass.evaluator import GenericLLMEvaluator
+from opencompass.evaluator import GenericLLMEvaluator, CascadeEvaluator
 from opencompass.datasets import generic_llmjudge_postprocess
-from opencompass.utils import xml_tag_postprocessor
 
 categories = ['cipher', 'counterfactual', 'logic', 'operation', 'puzzle']
 
-
 GRADER_TEMPLATE = """
     Please as a grading expert, judge whether the final answers given by the candidates below are consistent with the standard answers, that is, whether the candidates answered correctly. 
 
@@ -50,7 +60,7 @@ for category in categories:
             round=[
                 dict(
                     role='HUMAN',
-                    prompt='{prompt}' # f-string
+                    prompt='{prompt}'  # f-string
                 )
             ]
         )
@@ -66,41 +76,45 @@ for category in categories:
     infer_cfg = dict(
         prompt_template=prompt_template,
         retriever=dict(type=ZeroRetriever),
-        inferencer=dict(type=GenInferencer, max_out_len=1024),
+        inferencer=dict(type=GenInferencer),
     )
 
     # Evaluation configuration
     eval_cfg = dict(
         evaluator=dict(
-            type=GenericLLMEvaluator,
-            prompt_template=dict(
-                type=PromptTemplate,
-                template=dict(
-                begin=[
-                    dict(
-                        role='SYSTEM',
-                        fallback_role='HUMAN',
-                        prompt="You are a helpful assistant who evaluates the correctness and quality of models' outputs.")
-                ],
-                    round=[
-                    dict(
-                        role='HUMAN',
-                        prompt = GRADER_TEMPLATE
-                    ),
-                ]),
+            type=CascadeEvaluator,
+            rule_evaluator=dict(
+                type=korbenchEvaluator,
             ),
-            dataset_cfg=dict(
-                type=korbenchDataset,
-                path='opencompass/korbench',
-                prompt_mode='0_shot',
-                category=category,
-                reader_cfg=reader_cfg,
+            llm_evaluator=dict(
+                type=GenericLLMEvaluator,
+                prompt_template=dict(
+                    type=PromptTemplate,
+                    template=dict(
+                        begin=[
+                            dict(
+                                role='SYSTEM',
+                                fallback_role='HUMAN',
+                                prompt="You are a helpful assistant who evaluates the correctness and quality of models' outputs.")
+                        ],
+                        round=[
+                            dict(
+                                role='HUMAN',
+                                prompt=GRADER_TEMPLATE
+                            ),
+                        ]),
+                ),
+                dataset_cfg=dict(
+                    type=korbenchDataset,
+                    path='opencompass/korbench',
+                    prompt_mode='0_shot',
+                    category=category,
+                    reader_cfg=reader_cfg,
+                ),
+                judge_cfg=dict(),
+                dict_postprocessor=dict(type=generic_llmjudge_postprocess),
             ),
-            judge_cfg=dict(),
-            dict_postprocessor=dict(type=generic_llmjudge_postprocess),
-            pred_postprocessor=dict(type=xml_tag_postprocessor, tag='<conclude>'),
-        ),
-        pred_role='BOT',
+        )
     )
 
     # Dataset
@@ -113,7 +127,7 @@ for category in categories:
         reader_cfg=reader_cfg,
         infer_cfg=infer_cfg,
         eval_cfg=eval_cfg,
-        mode='singlescore',
+        n=1,
     )
 
     korbench_0shot_single_datasets.append(korbench_dataset)

opencompass/configs/datasets/livereasonbench/livereasonbench_llmverify_20250428_gen_0484cb.py

@@ -4,7 +4,6 @@ from opencompass.openicl.icl_inferencer import GenInferencer
 
 from opencompass.evaluator import GenericLLMEvaluator
 from opencompass.datasets import LiveReasonBenchDataset, livereasonbench_postprocess
-from opencompass.utils import xml_tag_postprocessor
 
 
 GRADER_TEMPLATE = """
@@ -97,7 +96,7 @@ livereasonbench_infer_cfg = dict(
             ],
         )),
     retriever=dict(type=ZeroRetriever),
-    inferencer=dict(type=GenInferencer, max_out_len=16384))
+    inferencer=dict(type=GenInferencer))
 
 livereasonbench_eval_cfg = dict(
     evaluator=dict(
@@ -122,23 +121,22 @@ livereasonbench_eval_cfg = dict(
             type=LiveReasonBenchDataset,
             path='opencompass/LiveReasonBench',
             reader_cfg=livereasonbench_reader_cfg,
+            version='livereasonbench-20250428',
         ),
         judge_cfg=dict(),
         dict_postprocessor=dict(type=livereasonbench_postprocess),
-        pred_postprocessor=dict(type=xml_tag_postprocessor, tag='<conclude>'),
     ),
-    pred_role='BOT',
 )
 
 livereasonbench_datasets = [
     dict(
-        abbr='LiveReasonBench-20241202',
+        abbr='LiveReasonBench-20250428',
         type=LiveReasonBenchDataset,
         path='opencompass/LiveReasonBench',
         reader_cfg=livereasonbench_reader_cfg,
         infer_cfg=livereasonbench_infer_cfg,
         eval_cfg=livereasonbench_eval_cfg,
-        version='livereasonbench-20241202',
-        mode='singlescore',
+        version='livereasonbench-20250428',
+        n=1
   )
 ]