Add HellaSwag dataset.

lm_eval/tasks/__init__.py

@@ -4,6 +4,7 @@ from . import arc
 from . import race
 from . import webqs
 from . import anli
+from . import hellaswag
 
 TASK_REGISTRY = {
     # GLUE
@@ -26,6 +27,7 @@ TASK_REGISTRY = {
     # Order by benchmark/genre?
     "arc_easy": arc.ARCEasy,
     "arc_challenge": arc.ARCChallenge,
+    "hellaswag": hellaswag.HellaSwag,
     "race": race.RACE,
     "webqs": webqs.WebQs,
     "anli_r1": anli.ANLIRound1,

lm_eval/tasks/hellaswag.py

+import numpy as np
+from scipy.stats import pearsonr, spearmanr
+from sklearn.metrics import f1_score, matthews_corrcoef
+from tqdm import auto as tqdm_lib
+from . common import HFTask, simple_accuracy_metric, yesno
+
+class HellaSwag(HFTask):
+    DATASET_PATH = "hellaswag"
+    DATASET_NAME = None
+
+    def has_training_docs(self):
+        return True
+
+    def has_validation_docs(self):
+        return True
+
+    def has_test_docs(self):
+        return True
+
+    def training_docs(self):
+        if self.has_training_docs():
+            return self.data["train"]
+
+    def validation_docs(self):
+        if self.has_validation_docs():
+            return self.data["validation"]
+
+    def test_docs(self):
+        if self.has_test_docs():
+            return self.data["test"]
+
+    def fewshot_description(self):
+        return "Label for the relevant action: Sentences describing the context, with an incomplete sentence trailing\nanswer that plausibly completes the situation."
+
+    def doc_to_text(self, doc, include_target=True):
+        text = doc['activity_label'] + ': ' + doc['ctx'] + '\n'
+        if include_target:
+            letter_answer = doc['label']
+            if letter_answer == '0':
+                index = 0
+            elif letter_answer == '1':
+                index = 1
+            elif letter_answer == '2':
+                index = 2
+            elif letter_answer == '3':
+                index = 3
+            else:
+                raise ValueError("HellaSwag from HF datasets contained an invalid answer key")
+            text += doc['endings'][index]
+        return text
+
+    def evaluate(self, docs, lm, provide_description, num_fewshot):
+        # TODO: Write evaluation function
+        raise NotImplementedError()