Update README.md

README.md

@@ -10,7 +10,10 @@ pipeline_tag: text-classification
 ---
 
 # Model Description
-This is a fine-tuned DistilBART model for sequence classification on CNN news articles for text classification. The model was fine-tuned using a batch size of 32, a learning rate of 6e-5, and for 1 epoch.
+This is a fine-tuned DistilBART model for sequence classification on CNN news articles for text classification.
+The model was fine-tuned using a batch size of 32,
+a learning rate of 6e-5,
+and for 1 epoch.
 
 ## Dataset
 The CNN News dataset was used for fine-tuning the model. The dataset consists of news articles from various categories such as sports, entertainment, politics, etc.
@@ -18,10 +21,10 @@ The CNN News dataset was used for fine-tuning the model. The dataset consists of
 ## Performance
 The following performance metrics were achieved after fine-tuning the model:
 
-Accuracy: 0.9597114707952147
-F1-score: 0.9589247895703302
-Recall: 0.9597114707952147
-Precision: 0.9589649408501851
+  - Accuracy: 0.9597114707952147
+  - F1-score: 0.9589247895703302
+  - Recall: 0.9597114707952147
+  - Precision: 0.9589649408501851
 
 ## Usage
 You can use this model to classify CNN news articles into different categories such as sports, entertainment, politics, etc. You can load the model using the Hugging Face Transformers library and use it to predict the class of a new news article.