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.gitattributes

@@ -53,3 +53,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.jpg filter=lfs diff=lfs merge=lfs -text
 *.jpeg filter=lfs diff=lfs merge=lfs -text
 *.webp filter=lfs diff=lfs merge=lfs -text
+complete.csv filter=lfs diff=lfs merge=lfs -text
+polarity.csv filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+task_categories:
+- text-classification
+language:
+- en
+
+dataset_info:
+- config_name: full
+  features:
+  - name: text
+    dtype: string
+  - name: label
+    dtype:
+      class_label:
+        names:
+          '0': very negative
+          '1': negative
+          '2': neutral
+          '3': positive
+          '4': very positive
+- config_name: full
+  features:
+  - name: text
+    dtype: string
+  - name: label
+    dtype:
+      class_label:
+        names:
+          '0': negative
+          '1': positive
+
+configs:
+- config_name: full
+  data_files:
+  - split: complete
+    path: "complete.csv"
+  default: true
+- config_name: polarity
+  data_files:
+  - split: complete
+    path: "polarity.csv"
+  default: true
+---

complete.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:49358880eac8b8ca383d64fa36bb1c0fe1f81c0b53b68c33d1348a93df5ab27e
+size 124219344

convert.py

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+import csv
+import random
+
+import pandas as pd
+
+
+def remap_polarity(row):
+    if row["label"] < 2:
+        row["label"] = 0
+    else:
+        row["label"] = 1
+    return row
+
+
+def run():
+    rows = []
+
+    with open(
+        "training.1600000.processed.noemoticon.csv", "r", encoding="ISO-8859-1"
+    ) as file:
+        reader = csv.reader(file)
+        for row in reader:
+            rows.append({"label": int(row[0]), "text": row[5]})
+
+    df = pd.DataFrame(rows)
+    df.to_csv("complete.csv", index=False)
+
+    polarity_rows = [remap_polarity(row) for row in rows if row["label"] != 2]
+    positive_rows = [row for row in polarity_rows if row["label"] == 1]
+    negative_rows = [row for row in polarity_rows if row["label"] == 0]
+    min_size = min(len(positive_rows), len(negative_rows))
+    polarity_rows = positive_rows[:min_size] + negative_rows[:min_size]
+
+    random.shuffle(polarity_rows)
+
+    df = pd.DataFrame(polarity_rows)
+    df.to_csv("polarity.csv", index=False)
+
+
+if __name__ == "__main__":
+    run()

polarity.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:09f43f9e8a3ab5b6164301afea5c5f5acc2999b600040fca071f5a291ebd7767
+size 124219344