Upload fair-rationales.py

fair-rationales.py

@@ -112,12 +112,9 @@ class FairRationales(datasets.GeneratorBasedBuilder):
             label_classes=SST2_LABELS,
             label_classes_original=["negative", "positive"],
             attributes=[
-                ("recruitment_ethnicity", ["Latino/Hispanic", "White/Causasian", "Black/African American"]),
+                ("recruitment_ethnicity", ["Black/African American", "White/Causasian", "Latino/Hispanic"]),
                 ("recruitment_age", [">=38", "<=35"]),
                 ("group_id", ["BO", "BY", "WO", "WY", "LO", "LY"]),
-                ("gender", ["Male", "Female"]),
-                ("english_proficiency", ["Not well", "Well", "Very well"]),    
-                ("attentioncheck", ["PASSED", "FAILED"]),
                 ("sst2_id", datasets.Value("int32")),
                 ("sst2_split", datasets.Value("string")),
             ],
@@ -158,12 +155,9 @@ class FairRationales(datasets.GeneratorBasedBuilder):
             label_classes=DYNASENT_LABELS,
             label_classes_original=["negative", "positive"],
             attributes=[
-                ("recruitment_ethnicity", ["Latino/Hispanic", "White/Causasian", "Black/African American"]),
+                ("recruitment_ethnicity", ["Black/African American", "White/Causasian", "Latino/Hispanic"]),
                 ("recruitment_age", [">=38", "<=35"]),
                 ("group_id", ["BO", "BY", "WO", "WY", "LO", "LY"]),
-                ("gender", ["Male", "Female", "Why do you conflate sex and gender?"]),
-                ("english_proficiency", ["Not well", "Well", "Very well"]),
-                ("attentioncheck", ["PASSED", "FAILED"]),
             ],
             data_url=os.path.join(MAIN_PATH, "dynasent.zip"),
             url="https://huggingface.co/datasets/dynabench/dynasent",
@@ -192,12 +186,9 @@ class FairRationales(datasets.GeneratorBasedBuilder):
             ),
             label_classes_original=["A", "B", "C", "D", "E"],
             attributes=[
-                ("recruitment_ethnicity", ["Latino/Hispanic", "White/Causasian", "Black/African American"]),
+                ("recruitment_ethnicity", ["Black/African American", "White/Causasian", "Latino/Hispanic"]),
                 ("recruitment_age", [">=38", "<=35"]),
                 ("group_id", ["BO", "BY", "WO", "WY", "LO", "LY"]),
-                ("gender", ["Male", "Female", "Curious ", "Non-binary/third gender"]),
-                ("english_proficiency", ["Not well", "Well", "Very well"]),
-                ("attentioncheck", ["PASSED", "FAILED"]),
             ],
             data_url=os.path.join(MAIN_PATH, "cose.zip"),
             url="https://huggingface.co/datasets/cos_e",
@@ -230,7 +221,10 @@ class FairRationales(datasets.GeneratorBasedBuilder):
                     "age": datasets.Value("int32"),
                     "ethnicity": datasets.Value("string"),
                     "originaldata_id": datasets.Value("string"),
-                    "annotator_ID": datasets.Value("int64")
+                    "annotator_ID": datasets.Value("int64"),
+                    "english_proficiency": datasets.Value("string"),
+                    "attentioncheck": datasets.Value("string"),
+                    "gender": datasets.Value("string")
                     }
         if self.config.name == "cose":
             features["label"] = datasets.Value("string")
@@ -280,7 +274,9 @@ class FairRationales(datasets.GeneratorBasedBuilder):
                     "ethnicity": data["ethnicity"],
                     "gender": data["gender"],
                     "originaldata_id": data["originaldata_id"],
-                    "annotator_ID": data["annotator_ID"]
+                    "annotator_ID": data["annotator_ID"],
+                    "english_proficiency": data["english_proficiency"],
+                    "attentioncheck": data["attentioncheck"]
                 }
                 for attribute_name, _ in self.config.attributes:
                     example[attribute_name] = data[attribute_name]