Update README.md

README.md

@@ -41,22 +41,37 @@ These changes have been made in order to apply SimCSE method.
 from datasets import load_dataset
 from tqdm import tqdm
 import pandas as pd
+import numpy as np
 
 def create_trios(df, save_path):
     list_of_examples = []
     unique_premises = df.drop_duplicates("premise")["premise"]
     for premise in tqdm(unique_premises):
-        positive_example = df[(df["premise"] == premise) & (df["label"] == "entailment")]["hypothesis"].iloc[0]
-        negative_example = df[(df["premise"] == premise) & (df["label"] == "contradiction")]["hypothesis"].iloc[0]
-        list_of_examples.append((premise, positive_example, negative_example))
+        premise_dataset = df[(df["premise"] == premise)] 
+        positive_examples = premise_dataset[premise_dataset["label"] == "entailment"]["hypothesis"]
+        negative_examples = premise_dataset[premise_dataset["label"] == "contradiction"]["hypothesis"]
+        
+        if len(positive_examples) == 0 or len(negative_examples) == 0:
+            continue
+        
+        for positive_example in positive_examples:
+            for negative_example in negative_examples:
+                list_of_examples.append((premise, positive_example, negative_example))
+        
+        
     examples_df = pd.DataFrame(list_of_examples, columns=["premise", "entailment", "contradiction"])
-    examples_df.dropna(inplace=True)
     examples_df.to_csv(save_path)
 
-data = load_dataset("kor_nli", "snli")
-df = pd.DataFrame(data["train"])
-df["label"] = ["neutral" if label == 1 else "contradiction" if label == 2 else "entailment" for label in df["label"]]
-create_trios(df, save_path = #insert your path)
+
+if __name__ == "__main__":
+    dataset1 = load_dataset("kor_nli", "snli")["train"]
+    dataset2 = load_dataset("kor_nli", "multi_nli")["train"]
+    df_1 = pd.DataFrame(dataset1)
+    df_2 = pd.DataFrame(dataset2)
+    df_full = pd.concat([df_1, df_2])
+    df_full.dropna(inplace=True)
+    df_full["label"] = ["neutral" if label == 1 else "contradiction" if label == 2 else "entailment" for label in df_full["label"]]
+    create_trios(df_full, <insert your path>)
 ```
 
 **How to download**