Binary Text Classification using FineTuned BERT Transformer Model

• Objective : To perform Text Classification on Movies Review Dataset and Classify Review as Positive or Negative Sentiment.

• Dataset : Large Movie Review Dataset From Stanford

• Methodology: Using a pretrained BERT transformers model and fine-tune it on a classification task.

• Implementation Framework: PyTorch

Dataset Information

• For this Text Classification task we are using wellknown Large Movie Datset from Stanford.
• This is a dataset for binary sentiment classification containing a set of 25,000 highly polar movie reviews for training, and 25,000 for testing.
• There is additional unlabeled data for use as well. Raw text and already processed bag of words formats are provided.

Result : Confusion Matrix