Program code containing studies conducted as a part of thesis dedicated to aspect-based review summarization

This study is dedicated to aspect-based summarization. I fine-tuned LLMs ruBERT, mBERT and XLM-RoBERTa on reviews about restaurants and automobiles. There are two solutions to make summaries: use one of the model as a pair classificator or as a sequence tagger. Finally, there is clusterisation to obtain the result.

Jupyter Notebook, Python 3

• Jupyter Notebook, Python 3
• Each notebook contains installer for needed libraries

There are following notebooks:

• Preparation of laptop data
• Preparation of train data
• Fine-tuning of models
• Summarization pipelines

You can get laptop database from this link.

Yanina Khudina, currently enrolled in bachelor program "Fundamential and Computational Linguistics" at HSE University, Moscow.

• e-mail: [email protected]