Qwen3-0.6B-PsychSupport-Expert
This project performs full fine-tuning on the Qwen3-0.6B language model to enhance its psychological support reasoning and empathetic response capabilities. The model was optimized using the bfloat16 (bf16) data type.
Training Procedure
Dataset Preparation
- Dataset: Containing paired patient emotional context descriptions and step-by-step empathetic support responses.
Model Loading and Configuration
- Base model: Qwen3-0.6B, loaded with the
unsloth
library in bf16 precision. - Full fine-tuning (
full_finetuning=True
) applied to all layers to adapt the model for psychological support tasks.
- Base model: Qwen3-0.6B, loaded with the
Supervised Fine-Tuning (SFT)
Utilized the Hugging Face TRL library with the Supervised Fine-Tuning approach.
The model was trained to generate both intermediate empathetic reasoning steps and final supportive messages.
Training hyperparameters:
- Epochs: 2
- Learning rate: 2e-5
- Batch size: 8
Purpose and Outcome
- Enhanced the model’s ability to provide empathetic, context-aware psychological support to users.
Evaluation
Performance was measured on a held-out validation set with the following metric:
- Support Coherence: Rated 74.32% similarity to expert-generated responses.
License
This project is licensed under the Apache License 2.0. See the LICENSE file for details.
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