Update README.md

README.md

@@ -1,3 +1,68 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+metrics:
+- cer
+---
+## Welcome
+If you find this model helpful, please *like* this model and star us on https://github.com/LianjiaTech/BELLE  and https://github.com/shuaijiang/Whisper-Finetune
+
+# Belle-whisper-large-v3-zh-punct
+Fine tune whisper-large-v3-zh to enhance Chinese punctuation mark capabilities, 
+Belle-whisper-large-v3-zh-punct demonstrates similar performance to Belle-whisper-large-v3-zh on Chinese ASR benchmarks, including AISHELL1, AISHELL2, WENETSPEECH, and HKUST.
+
+The punctuation mark come from model [punc_ct-transformer_cn-en-common-vocab471067-large](https://www.modelscope.cn/models/iic/punc_ct-transformer_cn-en-common-vocab471067-large/),
+and was added to the training datasets.
+
+## Usage
+```python
+
+from transformers import pipeline
+
+transcriber = pipeline(
+  "automatic-speech-recognition", 
+  model="BELLE-2/Belle-whisper-large-v3-zh-punct"
+)
+
+transcriber.model.config.forced_decoder_ids = (
+  transcriber.tokenizer.get_decoder_prompt_ids(
+    language="zh", 
+    task="transcribe"
+  )
+)
+
+transcription = transcriber("my_audio.wav") 
+
+```
+
+## Fine-tuning
+|       Model      |  (Re)Sample Rate   |                      Train Datasets         | Fine-tuning (full or peft) | 
+|:----------------:|:-------:|:----------------------------------------------------------:|:-----------:|
+| Belle-whisper-large-v3-zh-punct | 16KHz | [AISHELL-1](https://openslr.magicdatatech.com/resources/33/) [AISHELL-2](https://www.aishelltech.com/aishell_2) [WenetSpeech](https://wenet.org.cn/WenetSpeech/) [HKUST](https://catalog.ldc.upenn.edu/LDC2005S15)  |   [lora fine-tuning](https://github.com/shuaijiang/Whisper-Finetune)   |    
+
+To incorporate punctuation marks without compromising performance, Lora fine-tuning was employed.
+If you want to fine-thuning the model on your datasets, please reference to the [github repo](https://github.com/shuaijiang/Whisper-Finetune)
+
+    
+## CER(%) ↓ 
+|      Model       |  Language Tag   | aishell_1_test(↓) |aishell_2_test(↓)| wenetspeech_net(↓) | wenetspeech_meeting(↓) | HKUST_dev(↓)|   
+|:----------------:|:-------:|:-----------:|:-----------:|:--------:|:-----------:|:-------:|
+| whisper-large-v3 | Chinese |  8.085 | 5.475  |  11.72   |  20.15 | 28.597 |
+| Belle-whisper-large-v3-zh | Chinese |   2.781    | 3.786  |   8.865    | 11.246 | 16.440 |
+| Belle-whisper-large-v3-zh-punct | Chinese |   2.945    | 3.0  |   8.0    | 11.0 | 16.0 |
+
+It is worth mentioning that compared to Belle-whisper-large-v3-zh, Belle-whisper-large-v3-zh-punct has a smilar performance.
+
+## Citation
+
+Please cite our paper and github when using our code, data or model.
+
+```
+@misc{BELLE,
+  author = {BELLEGroup},
+  title = {BELLE: Be Everyone's Large Language model Engine},
+  year = {2023},
+  publisher = {GitHub},
+  journal = {GitHub repository},
+  howpublished = {\url{https://github.com/LianjiaTech/BELLE}},
+}
+```