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--- |
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license: agpl-3.0 |
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datasets: |
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- stvlynn/Cantonese-Dialogue |
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language: |
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- zh |
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pipeline_tag: text-generation |
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tags: |
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- Cantonese |
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- 廣東話 |
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- 粤语 |
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base_model: Qwen/Qwen-7B-Chat |
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--- |
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# Qwen-7B-Chat-Cantonese (通义千问·粤语) |
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## Intro |
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Qwen-7B-Chat-Cantonese is a fine-tuned version based on Qwen-7B-Chat, trained on a substantial amount of Cantonese language data. |
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Qwen-7B-Chat-Cantonese係基於Qwen-7B-Chat嘅微調版本，基於大量粵語數據進行訓練。 |
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[ModelScope(魔搭社区)](https://www.modelscope.cn/models/stvlynn/Qwen-7B-Chat-Cantonese) |
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## Usage |
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### Requirements |
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* python 3.8 and above |
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* pytorch 1.12 and above, 2.0 and above are recommended |
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* CUDA 11.4 and above are recommended (this is for GPU users, flash-attention users, etc.) |
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### Dependency |
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To run Qwen-7B-Chat-Cantonese, please make sure you meet the above requirements, and then execute the following pip commands to install the dependent libraries. |
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```bash |
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pip install transformers==4.32.0 accelerate tiktoken einops scipy transformers_stream_generator==0.0.4 peft deepspeed |
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``` |
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In addition, it is recommended to install the `flash-attention` library (**we support flash attention 2 now.**) for higher efficiency and lower memory usage. |
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```bash |
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git clone https://github.com/Dao-AILab/flash-attention |
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cd flash-attention && pip install . |
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``` |
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### Quickstart |
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Pls turn to QwenLM/Qwen - [Quickstart](https://github.com/QwenLM/Qwen?tab=readme-ov-file#quickstart) |
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## Training Parameters |
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| Parameter | Description | Value | |
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|-----------------|----------------------------------------|--------| |
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| Learning Rate | AdamW optimizer learning rate | 7e-5 | |
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| Weight Decay | Regularization strength | 0.8 | |
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| Gamma | Learning rate decay factor | 1.0 | |
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| Batch Size | Number of samples per batch | 1000 | |
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| Precision | Floating point precision | fp16 | |
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| Learning Policy | Learning rate adjustment policy | cosine | |
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| Warmup Steps | Initial steps without learning rate adjustment | 0 | |
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| Total Steps | Total training steps | 1024 | |
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| Gradient Accumulation Steps | Number of steps to accumulate gradients before updating | 8 | |
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## Demo |
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## Special Note |
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This is my first fine-tuning LLM project. Pls forgive me if there's anything wrong. |
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If you have any questions or suggestions, feel free to contact me. |
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[Twitter @stv_lynn](https://x.com/stv_lynn) |
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[Telegram @stvlynn](https://t.me/stvlynn) |
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[email [email protected]](mailto://[email protected]) |
