---
language:
- yue
license: apache-2.0
tags:
- whisper-event
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- cer
base_model: openai/whisper-large-v2
model-index:
- name: Whisper Large V2 Cantonese
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0
      type: mozilla-foundation/common_voice_11_0
      config: yue
      split: test
    metrics:
    - type: cer
      value: 6.7274
      name: Cer
  - task:
      type: automatic-speech-recognition
      name: Speech Recognition
    dataset:
      name: Common Voice zh-HK
      type: common_voice
      args: zh-HK
    metrics:
    - type: cer
      value: 6.7274
      name: Test CER
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# Whisper Large V2 Cantonese

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the mozilla-foundation/common_voice_11_0 yue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2807
- Cer: 6.7274

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0032        | 13.01 | 1000 | 0.2318          | 6.8569 |
| 0.002         | 26.01 | 2000 | 0.2404          | 7.1524 |
| 0.0001        | 39.02 | 3000 | 0.2807          | 6.7274 |
| 0.0001        | 53.01 | 4000 | 0.2912          | 6.7517 |
| 0.0           | 66.01 | 5000 | 0.2957          | 6.7638 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2