kanchanchy / sentiment-analysis-bert-pytorch

Sentiment Analysis using BERT in PyTorch

This repository shows how to build a sentiment classification model using BERT pretrained model. BERT is a large-scale transformer-based Language Model that can be finetuned for a variety of tasks. From data loading to model training and classification, all the steps are described here.

In summary, this repository performs the following operations:

1. Importing SMILE Twitter Emotion dataset for the purpose of classifying emotions
2. Exploring the features of the dataset and performing necessary preprocessing
3. Loading tokenizer and encoding the dataset
4. Setting up BERT Pretrained Model
5. Configuring the model to be trained and defining accuracy metrics
6. Training and evaluating the model
7. Saving and loading the trained model