Bert Implementation for Sentiment Analysis

BERT is currently being used at Google to optimize the interpretation of user search queries. BERT excels at several functions that make this possible, including:

Sequence-to-sequence based language generation tasks such as:

• Question answering
• Abstract summarization
• Sentence prediction
• Conversational response generation

Table Of Contents

1. About the Dataset
2. Data Import
3. Creating Training and Validation Set
4. Select Bert and Pre processing module
5. Passing Data to Preprocssing Module & Bert
6. Training and Evaluations
7. Saving and Re-Loading the Model
8. Predictions
9. Summary
10. References

1: About the Dataset

This notebook trains a sentiment analysis model to classify movie reviews as positive or negative, based on the text of the review.

The dataset contatins over 50,000 movie reviews collected from IMDB movie database