Update README.md

README.md

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 The dataset in this study is a Drug-Drug Interaction Event (DDIE) dataset obtained from DeepDDI 2. It includes detailed information on 2,386 drugs, each represented by a 50-dimensional Principal Components Analysis (PCA) feature vector, and the corresponding SMILES strings. Additionally, drug descriptions from DDInter and DrugBank have been integrated into the dataset.
 
-The DDIE dataset comprises 222,127 drug pairs, enabling the prediction of 113 different DDIE types. The interaction types are categorized within a set, with the specific interaction type between drug `i` and drug `j`.
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-Addressing few-shot scenarios is crucial due to the frequent occurrence of rare and poorly documented drug interactions in clinical settings, which present significant challenges.
+The DDIE dataset comprises 222,127 drug pairs, enabling the prediction of 113 different DDIE types. Addressing few-shot scenarios is crucial due to the frequent occurrence of rare and poorly documented drug interactions in clinical settings, which present significant challenges.
 
 ## Data Sample Distribution
 
 The following table shows the distribution of data samples across different interaction frequency categories in the training, validation, and test sets:
 
-| Freq   | Train | Valid | Test   |
-|--------|-------|-------|--------|
-| Common | 44,126| 44,113| 132,110|
-| Few    | 108   | 128   | 298    |
-| Rare   | 43    | 34    | 85     |
+| **Freq**  | **Train** | **Valid** | **Test**  |
+|:---------:|:---------:|:---------:|:---------:|
+| Common    | 44,126    | 44,113    | 132,110   |
+| Few       | 108       | 128       | 298       |
+| Rare      | 43        | 34        | 85        |
 
 
 This categorization into 'common', 'few', and 'rare' is based on the frequency of DDIE occurrences, which helps address the challenges posed by different frequency categories in real-world scenarios. Additionally, categories with fewer than two samples were removed, and the remaining samples were distributed into training, validation, and test sets at ratios of 2:2:6 to enhance the dataset's quality and reliability.