This GitHub repository provides a comprehensive implementation of sentiment analysis for Twitter data using the BERT (Bidirectional Encoder Representations from Transformers) model. The project includes pre-processing code to clean and tokenize the tweets, followed by fine-tuning the BERT model on a sentiment analysis dataset. The repository offers clear documentation and code organization, making it easy for users to understand and replicate the sentiment analysis process. The trained model can analyze tweets and classify them into angry, disgust, happy, npt-relevant, sad, surprise sentiments, demonstrating the power of BERT in natural language understanding and sentiment classification tasks. Whether you're new to sentiment analysis or an experienced practitioner, this repository offers a valuable resource to explore and enhance your understanding of BERT-based sentiment analysis on Twitter data.