Datasets:

cardiffnlp
/

super_tweeteval

Tasks:

Text Classification

Token Classification

Question Answering

Modalities:

Formats:

Sub-tasks:

topic-classification

named-entity-recognition

Languages:

Size:

ArXiv:

Tags:

super_tweet_eval

natural language understanding

Libraries:

License:

Dataset card Viewer Files Files and versions Community

antypasd commited on Nov 8, 2023

Commit

77eafbc

•

1 Parent(s): 5779f15

fixed tweet_emoji labels

Files changed (1) hide show

super_tweeteval.py +2 -2

super_tweeteval.py CHANGED Viewed

@@ -2,7 +2,7 @@
 import json
 import datasets
-_VERSION = "0.1.7"
 _SUPER_TWEETEVAL_CITATION = """TBA"""
 _SUPER_TWEETEVAL_DESCRIPTION = """TBA"""
 _TWEET_TOPIC_DESCRIPTION = """
@@ -348,7 +348,7 @@ class SuperTweetEval(datasets.GeneratorBasedBuilder):
             label_classes = [x.strip('\n') for x in label_classes]
             features['gold_label'] = datasets.features.ClassLabel(
                 names=label_classes)
-            features['gold_label'] = datasets.Value("int32")
             features["text"] = datasets.Value("string")
             features['date'] = datasets.Value("string")
         if self.config.name == "tweet_sentiment":

 import json
 import datasets
+_VERSION = "0.1.71"
 _SUPER_TWEETEVAL_CITATION = """TBA"""
 _SUPER_TWEETEVAL_DESCRIPTION = """TBA"""
 _TWEET_TOPIC_DESCRIPTION = """
             label_classes = [x.strip('\n') for x in label_classes]
             features['gold_label'] = datasets.features.ClassLabel(
                 names=label_classes)
+            #features['gold_label'] = datasets.Value("int32")
             features["text"] = datasets.Value("string")
             features['date'] = datasets.Value("string")
         if self.config.name == "tweet_sentiment":