This model is a fine-tuned version of unsloth/DeepSeek-R1-Distill-Llama-8B-unsloth-bnb-4bit, specifically tailored for mental health counseling tasks. It has been trained on the Amod/mental_health_counseling_conversations dataset for 10 epochs using two H100 GPUs.
Key Features
Base Model: Utilizes the DeepSeek-R1 architecture, known for its powerful reasoning capabilities13.
Distillation: Leverages knowledge distillation techniques to compress the larger DeepSeek-R1 model into a more efficient 8B parameter Llama-based version13.
Quantization: Employs Unsloth's dynamic 4-bit quantization for reduced memory footprint and faster inference59.
Domain Specialization: Fine-tuned on a dataset of mental health counseling conversations, enhancing its ability to understand and respond to mental health-related queries68.
Training Details
Dataset: Amod/mental_health_counseling_conversations, containing 3,512 Q&A pairs from counseling platforms68.
Training Duration: 10 epochs
Hardware: Two H100 GPUs
Potential Applications
This model could be particularly useful for:
Prototyping mental health chatbots
Assisting in mental health research
Providing initial screening or support in mental health contexts
Limitations and Ethical Considerations
While this model has been trained on mental health counseling data, it's crucial to note:
It should not replace professional mental health care or diagnosis.
The model may have biases or limitations based on its training data.
Ethical use and privacy considerations are paramount when dealing with sensitive mental health information.
