Update README.md

README.md

@@ -33,7 +33,69 @@ size_categories:
 
 For a better dataset description, please visit: [LINK](https://klue-benchmark.com/) <br>
 <br>
-**This dataset was prepared by converting KLUENLI dataset** to use it for contrastive training (SimCSE).
+**This dataset was prepared by converting KLUENLI dataset** to use it for contrastive training (SimCSE). The code used to prepare the data is given below:
+
+```py
+import pandas as pd
+from datasets import load_dataset, concatenate_datasets, Dataset
+from torch.utils.data import random_split
+
+
+class PrepTriplets:
+    @staticmethod
+    def make_dataset():
+        train_dataset = load_dataset("klue", "nli", split="train")
+        val_dataset = load_dataset("klue", "nli", split="validation")
+        merged_dataset = concatenate_datasets([train_dataset, val_dataset])
+
+        triplets_dataset = PrepTriplets._get_triplets(merged_dataset)
+
+        # Split back into train and validation
+        train_size = int(0.9 * len(triplets_dataset))
+        val_size = len(triplets_dataset) - train_size
+        train_subset, val_subset = random_split(
+            triplets_dataset, [train_size, val_size]
+        )
+
+        # Convert Subset objects back to Dataset
+        train_dataset = triplets_dataset.select(train_subset.indices)
+        val_dataset = triplets_dataset.select(val_subset.indices)
+
+        return train_dataset, val_dataset
+
+    @staticmethod
+    def _get_triplets(dataset):
+        df = pd.DataFrame(dataset)
+
+        entailments = df[df["label"] == 0]
+        contradictions = df[df["label"] == 2]
+
+        triplets = []
+
+        for premise in df["premise"].unique():
+            entailment_hypothesis = entailments[entailments["premise"] == premise][
+                "hypothesis"
+            ].tolist()
+            contradiction_hypothesis = contradictions[
+                contradictions["premise"] == premise
+            ]["hypothesis"].tolist()
+
+            if entailment_hypothesis and contradiction_hypothesis:
+                triplets.append(
+                    {
+                        "premise": premise,
+                        "entailment": entailment_hypothesis[0],
+                        "contradiction": contradiction_hypothesis[0],
+                    }
+                )
+
+        triplets_dataset = Dataset.from_pandas(pd.DataFrame(triplets))
+
+        return triplets_dataset
+
+# Example usage:
+# PrepTriplets.make_dataset()
+```
 
 **How to download**