Update toxic_comments.py

toxic_comments.py

@@ -9,12 +9,10 @@ from datasets.tasks import TextClassification
 import sys
 csv.field_size_limit(sys.maxsize)
 
-_DESCRIPTION = """\
-This data collection contains all the data used in our learning question classification experiments(see [1]), which has question class definitions, the training and testing question sets, examples of preprocessing the questions, feature definition scripts and examples of semantically related word features. 
-This work has been done by Xin Li and Dan Roth and supported by [2].
+_DESCRIPTION = """
 """
 
-_CITATION = """"""
+_CITATION = """jigsaw_toxicity_pred"""
 
 _TRAIN_DOWNLOAD_URL = "https://huggingface.co/datasets/vmalperovich/toxic_comments/raw/main/train.csv"
 _TEST_DOWNLOAD_URL = "https://huggingface.co/datasets/vmalperovich/toxic_comments/raw/main/test.csv"
@@ -24,7 +22,7 @@ _VALID_DOWNLOAD_URL = "https://huggingface.co/datasets/vmalperovich/toxic_commen
 CATEGORY_MAPPING = ['neutral', 'toxic', 'severe_toxic', 'obscene', 'threat', 'insult', 'identity_hate']
 
 class NG(datasets.GeneratorBasedBuilder):
-    """20ng  classification dataset."""
+    """toxic_comments  classification dataset."""
 
     def _info(self):
         return datasets.DatasetInfo(
@@ -37,7 +35,7 @@ class NG(datasets.GeneratorBasedBuilder):
             ),
             homepage="",
             citation=_CITATION,
-            task_templates=[TextClassification(text_column="text", label_column="label")],
+            # task_templates=[TextClassification(text_column="text", label_column="label")],
         )
 
     def _split_generators(self, dl_manager):