readme: ---
  language:
  - yue
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  model-index:
  - name: Whisper Large V2 - Cantonese - Augmented
    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: 6.213317142278891
        name: 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 - Augmented
  
  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 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1828
  - Cer: 6.2133
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  Training:
  - [mozilla-foundation/common_voice_11_0](https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0) (train+validation)
  
  Evaluation:
  - [mozilla-foundation/common_voice_11_0](https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0) (test)
  
  ## Training procedure
  
  Datasets were augmented on-the-fly using [audiomentations](https://github.com/iver56/audiomentations) via PitchShift and TimeStretch transformations at `p=0.3`.
  
  ### 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: 4
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 100
  - training_steps: 1000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Cer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.1126        | 1.21  | 200  | 0.1666          | 7.3103 |
  | 0.0467        | 2.42  | 400  | 0.1610          | 6.9419 |
  | 0.0217        | 3.63  | 600  | 0.1621          | 6.3874 |
  | 0.008         | 4.85  | 800  | 0.1699          | 6.3064 |
  | 0.0023        | 6.06  | 1000 | 0.1828          | 6.2133 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu117
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  