add accuracy and macro f1 score in kobest task

lm_eval/tasks/kobest.py

@@ -21,7 +21,7 @@ Homepage: https://huggingface.co/datasets/skt/kobest_v1
 
 import numpy as np
 from lm_eval.base import MultipleChoiceTask, rf, Task
-from lm_eval.metrics import f1_score, macro_f1_score
+from lm_eval.metrics import f1_score, macro_f1_score, mean
 
 
 class BoolQ(Task):
@@ -65,17 +65,23 @@ class BoolQ(Task):
         pred = np.argmax(results)
         gold = doc["label"]
         return {
-            "f1": (gold, pred)
+            "f1": (gold, pred),
+            "acc": pred == gold,
+            "macro_f1": (gold, pred)
         }
 
     def higher_is_better(self):
         return {
-            "f1": True
+            "f1": True,
+            "acc": True,
+            "macro_f1": True
         }
 
     def aggregation(self):
         return {
-            "f1": f1_score
+            "f1": f1_score,
+            "acc": mean,
+            "macro_f1": macro_f1_score
         }
 
 
@@ -131,17 +137,24 @@ class COPA(Task):
         pred = np.argmax(results)
         gold = doc["label"]
         return {
-            "f1": (gold, pred)
+            "f1": (gold, pred),
+            "acc": pred == gold,
+            "macro_f1": (gold, pred)
         }
 
     def higher_is_better(self):
         return {
-            "f1": True
+            "f1": True,
+            "acc": True,
+            "macro_f1": True
         }
 
+
     def aggregation(self):
         return {
-            "f1": f1_score
+            "f1": f1_score,
+            "acc": mean,
+            "macro_f1": macro_f1_score
         }
 
 class WiC(Task):
@@ -185,17 +198,23 @@ class WiC(Task):
         pred = np.argmax(results)
         gold = doc["label"]
         return {
-            "f1": (gold, pred)
+            "f1": (gold, pred),
+            "acc": pred == gold,
+            "macro_f1": (gold, pred)
         }
 
     def higher_is_better(self):
         return {
-            "f1": True
+            "f1": True,
+            "acc": True,
+            "macro_f1": True
         }
 
     def aggregation(self):
         return {
-            "f1": f1_score
+            "f1": f1_score,
+            "acc": mean,
+            "macro_f1": macro_f1_score
         }
 
 
@@ -239,17 +258,20 @@ class HellaSwag(MultipleChoiceTask):
         pred = np.argmax(results)
         gold = doc["gold"]
         return {
-            "f1": (gold, pred)
+            "acc": pred == gold,
+            "macro_f1": (gold, pred)
         }
 
     def higher_is_better(self):
         return {
-            "f1": True
+            "acc": True,
+            "macro_f1": True
         }
 
     def aggregation(self):
         return {
-            "f1": macro_f1_score
+            "acc": mean,
+            "macro_f1": macro_f1_score
         }
 
 
@@ -294,15 +316,21 @@ class SentiNeg(Task):
         pred = np.argmax(results)
         gold = doc["label"]
         return {
-            "f1": (gold, pred)
+            "f1": (gold, pred),
+            "acc": pred == gold,
+            "macro_f1": (gold, pred)
         }
 
     def higher_is_better(self):
         return {
-            "f1": True
+            "f1": True,
+            "acc": True,
+            "macro_f1": True
         }
 
     def aggregation(self):
         return {
-            "f1": f1_score
+            "f1": f1_score,
+            "acc": mean,
+            "macro_f1": macro_f1_score
         }