add arxiv link

data/tweet_qa/test.jsonl

@@ -1,3 +1,3 @@
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-oid sha256:57b3810c563f8a03f6d8f218fdf6843682e49be05bf8db20388cfe1b1d30fce4
-size 602000
+oid sha256:febf2fc5ae0ab149711709bf6a00ee5a96ccd0b5d00dac4dc50234a2621c0989
+size 322894

data/tweet_qa/train.jsonl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:fc2b6f57435863c1572867784338c03662bc9968e7d3f9e07b757db8a5691136
-size 4693013
+oid sha256:662ffee064429bd16dd0ca1a72d8e810066eb30ad864b99c700e3d289722748f
+size 2519331

data/tweet_qa/validation.jsonl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:14180a134e772a0463238df7edc51ea3b9574f02b5fdca89286e595132f7376c
-size 532805
+oid sha256:41478f2ae04546e6f6aa869fb947395a444e596c1923e9ddfc3312e6886bb412
+size 285505

process/tweet_qa.py

@@ -11,6 +11,8 @@ def process(tmp):
     for i in tmp:
         i['text'] = i.pop('paragraph_question')
         i['gold_label_str'] = i.pop('answer')
+        i.pop("paragraph")
+        i.pop("question")
     return tmp
 
 train = process(data["train"].to_pandas())

super_tweeteval.py

@@ -2,7 +2,7 @@
 import json
 import datasets
 
-_VERSION = "0.1.41"
+_VERSION = "0.1.42"
 _SUPER_TWEETEVAL_CITATION = """TBA"""
 _SUPER_TWEETEVAL_DESCRIPTION = """TBA"""
 _TWEET_TOPIC_DESCRIPTION = """
@@ -199,9 +199,16 @@ class SuperTweetEval(datasets.GeneratorBasedBuilder):
             name="tweet_qa",
             description=_TWEET_QA_DESCRIPTION,
             citation=_TWEET_QA_CITATION,
-            features=["text", "gold_label_str", "paragraph", "question"],
+            features=["text", "gold_label_str"],
             data_url="https://huggingface.co/datasets/cardiffnlp/super_tweet_eval/resolve/main/data/tweet_qa",
         ),
+        SuperTweetEvalConfig(
+            name="tweet_qg",
+            description=_TWEET_QA_DESCRIPTION,
+            citation=_TWEET_QA_CITATION,
+            features=["text", "gold_label_str"],
+            data_url="https://huggingface.co/datasets/cardiffnlp/super_tweet_eval/resolve/main/data/tweet_qg",
+        ),
         SuperTweetEvalConfig(
             name="tweet_intimacy",
             description=_TWEET_INTIMACY_DESCRIPTION,
@@ -284,7 +291,7 @@ class SuperTweetEval(datasets.GeneratorBasedBuilder):
             features['date_2'] = datasets.Value("string")
         if self.config.name == "tweet_hate":
             label_classes = [
-                    'hate_gender','hate_race', 'hate_sexuality', 'hate_religion','hate_origin', 'hate_disability',
+                    'hate_gender', 'hate_race', 'hate_sexuality', 'hate_religion','hate_origin', 'hate_disability',
                     'hate_age', 'not_hate']
             features['gold_label'] = datasets.features.ClassLabel(names=label_classes)
             features["text"] = datasets.Value("string")
@@ -310,7 +317,6 @@ class SuperTweetEval(datasets.GeneratorBasedBuilder):
             features["text"] = datasets.Value("string")
             features["target"] = datasets.Value("string")
 
-
         return datasets.DatasetInfo(
             description=_SUPER_TWEETEVAL_DESCRIPTION + "\n" + self.config.description,
             features=datasets.Features(features),