bug fix: hate

process/tweet_hate.py

@@ -7,7 +7,7 @@ import urllib
 HATE = 1
 NOT_HATE = 0
 
-# class mapping for the multiclass
+# class mapping for the multi-class
 class_mapping = {
     'target_gender_aggregated': 0,
     'target_race_aggregated': 1,
@@ -38,7 +38,7 @@ def clean_text(text):
     for t in text.split():
         # MAKE SURE to check lowercase
         t = '@user' if t.startswith('@') and len(t) > 1 and t.replace('@','').lower() not in verified_users else t
-        t = '\{URL\}' if t.startswith('http') else t
+        t = '{URL}' if (t.startswith('http') or t.startswith('URL')) else t
         new_text.append(t)
     
     return ' '.join(new_text)

super_tweet_eval.py

@@ -2,7 +2,7 @@
 import json
 import datasets
 
-_VERSION = "0.1.35"
+_VERSION = "0.1.37"
 _SUPER_TWEET_EVAL_CITATION = """TBA"""
 _SUPER_TWEET_EVAL_DESCRIPTION = """TBA"""
 _TWEET_TOPIC_DESCRIPTION = """
@@ -286,7 +286,7 @@ class SuperTweetEval(datasets.GeneratorBasedBuilder):
             label_classes = [
                     'hate_gender','hate_race', 'hate_sexuality', 'hate_religion','hate_origin', 'hate_disability',
                     'target_age', 'not_hate']
-            features['gold_label'] = datasets.features.ClassLabel(names=self.config.label_classes)
+            features['gold_label'] = datasets.features.ClassLabel(names=label_classes)
             #features["gold_label"] = datasets.Value("int32")
             features["text"] = datasets.Value("string")
         if self.config.name == "tweet_nerd":