---
title: Automatic Machine Translation
emoji: 🌐
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 4.44.0
app_file: app.py
pinned: false
license: apache-2.0
short_description: Chinese ↔ English oral translation with Qwen3-0.6B + LoRA
---

# 🌐 口语化自动机器翻译 | Oral Machine Translation

基于 **Qwen3-0.6B + LoRA** 微调的中英双向口语翻译系统

A bilingual (Chinese ↔ English) oral translation system built with **Qwen3-0.6B** fine-tuned using **LoRA**.

## ✨ Features

- 🔄 **Bidirectional Translation**: Chinese → English and English → Chinese
- 💬 **Oral Style**: Optimized for conversational, natural language
- ⚡ **Lightweight**: Only 0.6B parameters, fast inference
- 🎯 **LoRA Fine-tuned**: Parameter-efficient training on OpenSubtitles dataset

## 📊 Performance

| Model | BLEU Score | Improvement |
|-------|------------|-------------|
| Baseline (Qwen3-0.6B) | 1.24 | - |
| **LoRA Fine-tuned** | **11.89** | **+858%** |

## 🛠️ Technical Details

- **Base Model**: [Qwen/Qwen3-0.6B](https://huggingface.co/Qwen/Qwen3-0.6B)
- **Fine-tuning Method**: LoRA (rank=16, alpha=32, dropout=0.05)
- **Training Data**: OpenSubtitles en-zh (5,000 samples)
- **Training Time**: ~6 minutes (dual GPU)
- **Framework**: Transformers + PEFT

## 🚀 Usage

Simply select the translation direction and enter your text. The model will generate a natural, conversational translation.

### Example Translations

**Chinese → English:**
- 输入: 你好呀
- 输出: Hi, how are you?

**English → Chinese:**
- 输入: See you later
- 输出: 回头见。

## 📝 Citation

If you use this model, please cite:

```bibtex
@misc{mt-qwen-oral,
  title={MT-Qwen-Oral: Bilingual Oral Translation with Qwen and LoRA},
  author={Hzzzzx0},
  year={2025},
  publisher={Hugging Face},
  howpublished={\url{https://huggingface.co/spaces/Hzzzzx0/Automatic_machine_translation}}
}
```

## 📄 License

Apache 2.0

## 🔗 Links

- [GitHub Repository](https://github.com/yourusername/mt-qwen-oral)
- [Model Weights](https://huggingface.co/Hzzzzx0/qwen3-0.6b-oral-lora)