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sajjadhadi/Mental-Disorder-Detection-DeepSeek-R1-Distill-Qwen-1.5B-v1

sourceHugging Facemitupdated 2y agoView on Hugging Face
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Mental-Disorder-Detection-DeepSeek-R1-Distill-Qwen-1.5B

Disclaimer

This mental disorder detection model is designed for research and educational purposes only. It is not intended for use in real-world medical environments or to detect actual mental health conditions. For any medical concerns, always consult a qualified healthcare professional. The developers assume no responsibility for misuse in clinical or real-life scenarios.

This model is a fine-tuned version of deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B.

Model description

This Large Language Model (LLM), based on DeepSeek R1 Distill Qwen with 1.5 billion parameters, is fine-tuned on a dataset of 48,000 records to classify five distinct mental health-related classes: depression, suicide, bipolar, anxiety, and expressing. The model leverages lightweight quantization techniques (4-bit) for efficient computation while maintaining accuracy. Though designed for experimental and research purposes, it demonstrates the potential to assist in identifying mental health patterns through text, offering valuable insights for educational and academic applications.

Metrics

ClassTop-1 AccuracyTop-1 CountTop-2 AccuracyTop-2 Count
Overall0.621526/24500.791946/2450
Depression0.56478/8610.87752/861
Suicide0.63294/4660.76352/466
Bipolar0.71248/3510.75264/351
Anxiety0.67277/4130.73303/413
Expressing0.64229/3590.77275/359

For more information about the usage and metrics you can check this Kaggle notebook.