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Model: BELLE-2/Belle-whisper-large-v3-turbo-zh
Source: Original Platform

.gitattributes

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README.md

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+---
+license: apache-2.0
+metrics:
+- cer
+base_model:
+- openai/whisper-large-v3-turbo
+pipeline_tag: automatic-speech-recognition
+library_name: transformers
+---
+
+## 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-turbo-zh
+Fine tune whisper-large-v3-turbo-zh to enhance Chinese speech recognition capabilities,
+Belle-whisper-large-v3-turbo-zh demonstrates a **24-64%** relative improvement in performance to whisper-large-v3-turbo on Chinese ASR benchmarks, including AISHELL1, AISHELL2, WENETSPEECH, and HKUST.
+
+Same to Belle-whisper-large-v3-zh-punct, the punctuation marks 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 are added to the training datasets.
+
+## Usage
+```python
+
+from transformers import pipeline
+
+transcriber = pipeline(
+  "automatic-speech-recognition", 
+  model="BELLE-2/Belle-whisper-large-v3-turbo-zh"
+)
+
+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-turbo-zh | 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)  |   [full fine-tuning](https://github.com/shuaijiang/Whisper-Finetune)   |    
+
+
+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 |
+| whisper-large-v3-turbo | Chinese |  8.639 | 6.014  |  13.507   |  20.313 | 37.324 |
+| Belle-whisper-large-v3-turbo-zh | Chinese |   3.070    | 4.114  |   10.230    | 13.357 | 18.944 |
+
+It is worth mentioning that compared to whisper-large-v3 and whisper-large-v3-turbo, Belle-whisper-large-v3-turbo-zh has a significant improvement.
+
+
+## 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}},
+}
+```

config.json

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+{
+  "_name_or_path": "/raid/yoach/tmp_whisper_turbo",
+  "activation_dropout": 0.0,
+  "activation_function": "gelu",
+  "apply_spec_augment": false,
+  "architectures": [
+    "WhisperForConditionalGeneration"
+  ],
+  "attention_dropout": 0.0,
+  "begin_suppress_tokens": [
+    220,
+    50256
+  ],
+  "bos_token_id": 50257,
+  "classifier_proj_size": 256,
+  "d_model": 1280,
+  "decoder_attention_heads": 20,
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+  "decoder_layerdrop": 0.0,
+  "decoder_layers": 4,
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+  "dropout": 0.0,
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+  "init_std": 0.02,
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+  "mask_feature_min_masks": 0,
+  "mask_feature_prob": 0.0,
+  "mask_time_length": 10,
+  "mask_time_min_masks": 2,
+  "mask_time_prob": 0.05,
+  "max_source_positions": 1500,
+  "max_target_positions": 448,
+  "median_filter_width": 7,
+  "model_type": "whisper",
+  "num_hidden_layers": 32,
+  "num_mel_bins": 128,
+  "pad_token_id": 50257,
+  "scale_embedding": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.46.0.dev0",
+  "use_cache": true,
+  "use_weighted_layer_sum": false,
+  "vocab_size": 51866
+}

generation_config.json

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