Merge pull request #999 from EleutherAI/port_master_squadv2

lm_eval/tasks/scrolls/README.md

@@ -28,4 +28,4 @@ Once the subset task class has been defined in this file, it can be used by addi
 to `lm_eval/tasks/__init__.py`.
 
 NOTE: GovReport may need `max_gen_toks` set larger for causal models.
-"""
+"""
\ No newline at end of file

lm_eval/tasks/squadv2/README.md

+# Task-name
+
+### Paper
+
+Title: `Know What You Don’t Know: Unanswerable Questions for SQuAD`
+Abstract: https://arxiv.org/abs/1806.03822
+
+Stanford Question Answering Dataset (SQuAD) is a reading comprehension dataset,
+consisting of questions posed by crowdworkers on a set of Wikipedia articles,
+where the answer to every question is a segment of text, or span, from the
+corresponding reading passage, or the question might be unanswerable.
+SQuAD2.0 combines the 100,000 questions in SQuAD1.1 with over 50,000 unanswerable
+questions written adversarially by crowdworkers to look similar to answerable ones.
+To do well on SQuAD2.0, systems must not only answer questions when possible, but
+also determine when no answer is supported by the paragraph and abstain from answering.
+
+Homepage: https://rajpurkar.github.io/SQuAD-explorer/
+
+
+### Citation
+
+```
+@misc{rajpurkar2018know,
+    title={Know What You Don't Know: Unanswerable Questions for SQuAD},
+    author={Pranav Rajpurkar and Robin Jia and Percy Liang},
+    year={2018},
+    eprint={1806.03822},
+    archivePrefix={arXiv},
+    primaryClass={cs.CL}
+}
+```
+
+### Groups and Tasks
+
+#### Groups
+
+* Not part of a group yet
+
+#### Tasks
+
+* `squadv2`: `Default squadv2 task`
+
+### Checklist
+
+For adding novel benchmarks/datasets to the library:
+* [ ] Is the task an existing benchmark in the literature?
+  * [ ] Have you referenced the original paper that introduced the task?
+  * [ ] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test?
+
+
+If other tasks on this dataset are already supported:
+* [ ] Is the "Main" variant of this task clearly denoted?
+* [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates?
+* [ ] Have you noted which, if any, published evaluation setups are matched by this variant?

lm_eval/tasks/squadv2/task.py

@@ -48,20 +48,6 @@ def _squad_agg(key, items):
     return _squad_metric(predictions=predictions, references=references).get(key, 0)
 
 
-def normalize_answer(s):
-    """Lower text and remove punctuation, articles and extra whitespace."""
-    def remove_articles(text):
-        regex = re.compile(r'\b(a|an|the)\b', re.UNICODE)
-        return re.sub(regex, ' ', text)
-    def white_space_fix(text):
-        return ' '.join(text.split())
-    def remove_punc(text):
-        exclude = set(string.punctuation)
-        return ''.join(ch for ch in text if ch not in exclude)
-    def lower(text):
-        return text.lower()
-    return white_space_fix(remove_articles(remove_punc(lower(s))))
-
 @register_task("squadv2")
 class SQuAD2(Task):
     VERSION = 1