DIALOGUE GENERATIVE MODEL FOR MENTAL THERAPY

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dc.contributor.authorSametov, Askhat
dc.contributor.authorSovetova, Eldana
dc.contributor.authorBakytzhan, Makhabbat
dc.contributor.authorSuiunbekov, Daniiar
dc.date.accessioned2024-06-18T06:15:54Z
dc.date.available2024-06-18T06:15:54Z
dc.date.issued2024-04-20
dc.description.abstractThe increasing demand for accessible mental health re- sources has inspired the development of intelligent systems capable of offering immediate support. In this study, we present a mental health chatbot designed to provide empathetic and contextually relevant assistance to users. We initiated our approach by employing foundational NLP techniques, related to open-domain question answering methods, to establish a baseline understanding of conversational dynamics. Subse- quently, we explored the application of generative models to capture the nuanced and sensitive nature of mental health queries. Our methodology started with the full fine-tuning of smaller models, which provided initial insights into the training process of LLMs. Building upon this foundation, we leveraged the Low-Rank Adaptation (LoRA) [1] technique to fine-tune larger, more complex models, thus harnessing their superior generative capabilities without the computational expense of training from scratch. The success of our models can be attributed to the properly formatted and curated dataset, which was crucial in training the chatbot to understand and respond to a diverse range of mental health queries. The final chatbot demonstrates promising capabilities in delivering instant, reliable, and empathetic interaction, marking a signifi- cant step forward in digital mental health assistance. Our work not only showcases the potential of hybrid NLP applications in mental health scenarios but also paves the way for further innovations in therapeutic conversational agents.en_US
dc.identifier.citationSametov A., Sovetova E., Bakytzhan M., Suiunbekov D.(2024). Dialogue Generative Model for Mental Therapy. Nazarbayev University School of Engineering and Digital Sciencesen_US
dc.identifier.urihttp://nur.nu.edu.kz/handle/123456789/7874
dc.language.isoenen_US
dc.publisherNazarbayev University School of Engineering and Digital Sciencesen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subjectType of access: Open accessen_US
dc.subjectMental healthen_US
dc.subjectgenerative modelsen_US
dc.subjectcosine similarityen_US
dc.subjectopen-domain question-answeringen_US
dc.subjectgpt2en_US
dc.subjecttransformersen_US
dc.titleDIALOGUE GENERATIVE MODEL FOR MENTAL THERAPYen_US
dc.typeBachelor's thesisen_US
workflow.import.sourcescience

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