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src -> contains raw training and testing data files, preprocessed training and testing data files, separate files for data preprocessing, model fine-tuning and model evaluation


scoring.py -> Streamlit app/bot development


model.py -> preprocessing functions to be applied on the new data and prediction


dockerfile -> building docker image of streamlit app/bot


.github/workflows/deployment.yaml -> deployment of docker image to DockerHub through CI/CD pipeline

Classification Report of Best Model

class report

About

This is an automated scoring system that leverages a trained BERT model to predict sentence similarity. By comparing student responses to reference answers using BERT's deep understanding of semantic meaning, EvalBot provides efficient and objective evaluation, moving beyond simple keyword matching to assess the conceptual accuracy of text.

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