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README.md

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 license: mit
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 ## BERT-based Text Classification Model
-This model is a fine-tuned version of the bert-base-uncased model, specifically adapted for text classification across a diverse set of categories. The model has been trained on a rich dataset collected from multiple sources, including the News Category Dataset on Kaggle and various other websites.
+This model is a fine-tuned version of the bert-base-uncased model, specifically adapted for text classification across a diverse set of categories. The model has been trained on a dataset collected from multiple sources, including the News Category Dataset on Kaggle and various other websites.
 
 The model classifies text into one of the following 12 categories:
 
-Food
-Videogames & Shows
-Kids and fun
-Homestyle
-Travel
-Health
-Charity
-Electronics & Technology
-Sports
-Cultural & Music
-Education
-Convenience
+* Food
+* Videogames & Shows
+* Kids and fun
+* Homestyle
+* Travel
+* Health
+* Charity
+* Electronics & Technology
+* Sports
+* Cultural & Music
+* Education
+* Convenience
 The model has demonstrated robust performance with an accuracy of 0.721459, F1 score of 0.659451, precision of 0.707620, and recall of 0.635155.
 
 ## Model Architecture