Qwen-7B-Chat-Cantonese (通义千问·粤语)

Intro

Qwen-7B-Chat-Cantonese is a fine-tuned version based on Qwen-7B-Chat, trained on a substantial amount of Cantonese language data.

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。

ModelScope(魔搭社区)

Usage

Requirements

python 3.8 and above
pytorch 1.12 and above, 2.0 and above are recommended
CUDA 11.4 and above are recommended (this is for GPU users, flash-attention users, etc.)

Dependency

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.

pip install transformers==4.32.0 accelerate tiktoken einops scipy transformers_stream_generator==0.0.4 peft deepspeed

In addition, it is recommended to install the flash-attention library (we support flash attention 2 now.) for higher efficiency and lower memory usage.

git clone https://github.com/Dao-AILab/flash-attention
cd flash-attention && pip install .

Quickstart

Pls turn to QwenLM/Qwen - Quickstart

Training Parameters

Parameter	Description	Value
Learning Rate	AdamW optimizer learning rate	7e-5
Weight Decay	Regularization strength	0.8
Gamma	Learning rate decay factor	1.0
Batch Size	Number of samples per batch	1000
Precision	Floating point precision	fp16
Learning Policy	Learning rate adjustment policy	cosine
Warmup Steps	Initial steps without learning rate adjustment	0
Total Steps	Total training steps	1024
Gradient Accumulation Steps	Number of steps to accumulate gradients before updating	8