In this project, we aim to classify sentences based on whether they sound more like Homer or Bart from "The Simpsons". Our approach involves fine-tuning a pre-trained BERT model on a dataset manually curated composed of TheSimpsons dialogs collected online BERT (Bidirectional Encoder Representations from Transformers) is a transformer-based architecture that's pre-trained on a vast amount of text. Fine-tuning it allows us to leverage the pre-trained weights and adapt them to our specific task, which, in this case, is classifying sentences based on their speaker.
