Update README.md

README.md

@@ -21,10 +21,23 @@ You are provided with a large number of Wikipedia comments which have been label
 
 The original dataset can be found here: [jigsaw_toxic_classification](https://www.kaggle.com/competitions/jigsaw-toxic-comment-classification-challenge/data)
 
-Our training dataset is a version from the original dataset, <b>containing equal number of samples from each classes. </b><br>
-Number of samples in train_dataset: 25960<br>
-Number of samples in val_dataset: 6490<br>
-Number of samples in test_dataset: 153164<br>
+Our training dataset is a sampled version from the original dataset, <b>containing equal number of samples for both clean and toxic classes. </b><br>
+
+#### Dataset creation:
+<code><pre>data = pd.read_csv('train.csv') # train.csv from the original dataset
+column_names = ['toxic', 'severe_toxic', 'obscene', 'threat', 'insult', 'identity_hate']
+column_labels = data[column_names][2:-1]
+train_toxic = data[data[column_names].sum(axis=1) > 0]
+train_clean = data[data[column_names].sum(axis=1) == 0]
+train_clean_sampled = train_clean.sample(n=16225, random_state=42)
+
+dataframe = pd.concat([train_toxic, train_clean_sampled], axis=0)
+
+dataframe = dataframe.sample(frac=1, random_state=42)
+dataset = Dataset.from_pandas(dataframe)
+
+train_dataset = dataset.train_test_split(test_size=0.2)['train']
+val_dataset = dataset.train_test_split(test_size=0.2)['test']</pre></code>
 
 ### Caution:
 This dataset contains comments that are toxic in nature. Kindly use appropriately.