MelloGPT
NOTE: This model should not be regarded as a replacement for professional mental health assistance. It is essential to seek support from qualified professionals for personalized and appropriate care.
A fine tuned version of Mistral-7B-Instruct-v0.1 on counsel-chat dataset for mental health counseling conversations.
Motivation
In an era where mental health support is of paramount importance, A large language model fine-tuned on mental health counseling conversations stands as a pioneering solution. Leveraging a diverse dataset of anonymized counseling sessions, the model has been trained to recognize and respond to a wide range of mental health concerns. The fine-tuning process incorporates ethical considerations, privacy concerns, and sensitivity to the nuances of mental health conversations. The resulting model will demonstrate an intricate understanding of mental health issues and provide empathetic and supportive responses.
Prompt Template
<s>[INST] {prompt} [/INST]
Quantized Model
The quantized model can be found here. Thanks to @TheBloke.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 57.59 |
AI2 Reasoning Challenge (25-Shot) | 53.84 |
HellaSwag (10-Shot) | 76.12 |
MMLU (5-Shot) | 55.99 |
TruthfulQA (0-shot) | 55.61 |
Winogrande (5-shot) | 73.88 |
GSM8k (5-shot) | 30.10 |
Contributions
This project is open for contributions. Feel free to use the community tab.
Inspiration
This project was inspired by the project(s) listed below:
companion_cube by @KnutJaegersberg
Credits
This is my first attempt at fine-tuning a large language model. It wouldn't be possible without Axolotl and Runpod. The axolotl config file can be found here.
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Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard53.840
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard76.120
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard55.990
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard55.610
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard73.880
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard30.100