README.md

---
frameworks: PyTorch
license: apache-2.0
tags:
  - 向量检索
  - 中医
  - 医疗
tasks:
  - sentence-embedding
base_model:
  - BAAI/bge-m3
base_model_relation: finetune
---
# DeepPulse-Embedding Dense Retrieval Model Series

**DeepPulse (深度把脉)** is a member of 心语心言's open-source TCM series models. This project includes two dense retrieval (Embedding) models fine-tuned on different base models:

* **DeepPulse-Embedding-m3**: Fine-tuned based on `BGE-m3`.
* **DeepPulse-Embedding-0.6b**: Fine-tuned based on `Qwen3-0.6B`.

Both models are fine-tuned using a self-built medical dataset (especially TCM data) and are optimized for document chunk retrieval scenarios in the medical field.

# Self-Built Dataset Evaluation Metrics

The evaluation results on the self-built medical dataset are as follows. It can be seen that the DeepPulse series models outperform the original base models on all metrics.

| Model Name | MRR | NDCG@10 | Recall@1 | Recall@5 | Recall@10 |
| :--- | :--- | :--- | :--- | :--- | :--- |
| Qwen3-0.6B | 0.9458 | 0.9566 | 0.9157 | 0.9822 | 0.99 |
| bge-m3 | 0.9418 | 0.9519 | 0.9109 | 0.98 | 0.9831 |
| <font color="red">DeepPulse-Embedding-0.6b</font> | <font color="red">0.9693</font> | <font color="red">0.9751</font> | <font color="red">0.9513</font> | <font color="red">0.9891</font> | <font color="red">0.9935</font> |
| <font color="red">DeepPulse-Embedding-m3</font> | <font color="red">0.9729</font> | <font color="red">0.9781</font> | <font color="red">0.957</font> | <font color="red">0.9896</font> | <font color="red">0.9948</font> |

# Acknowledgement

DeepPulse-Embedding was trained by the algorithm team from 心语心言.

* [ChenCh2002](https://www.modelscope.cn/profile/ChenCh2002) completed the code implementation, model training, and evaluation work.
* [ChenCh2002](https://www.modelscope.cn/profile/ChenCh2002) and [Night-Quiet](https://huggingface.co/Night-Quiet) completed the data collection and organization work together.
* The project was led by [Night-Quiet](https://huggingface.co/Night-Quiet).