readme: ---
  language:
    - vi
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: openai/whisper-large-v2
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0 vi
        type: mozilla-foundation/common_voice_11_0
        config: vi
        split: test
        args: vi
      metrics:
      - name: Wer
        type: wer
        value: 15.7710
      - name: Cer
        type: cer
        value: 7.6691
  ---
  
  <!-- 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. -->
  
  # openai/whisper-large-v2
  
  This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4041
  - Wer: 15.7710
  - Cer: 7.6691
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  Training data: 
  * [mozilla-foundation/common_voice_11_0](https://huggingface.co/openai/whisper-large-v2)
  * [google/fleurs](https://huggingface.co/datasets/google/fleurs)
  
  Evaluation data:
  * [mozilla-foundation/common_voice_11_0](https://huggingface.co/openai/whisper-large-v2)
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 1e-07
  - train_batch_size: 8
  - eval_batch_size: 4
  - seed: 42
  - gradient_accumulation_steps: 3
  - total_train_batch_size: 24
  - 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 | Wer     | Cer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
  | 0.3983        | 0.1   | 500  | 0.5338          | 19.5876 | 10.6391 |
  | 0.2277        | 1.08  | 1000 | 0.4134          | 16.5826 | 8.2668  |
  | 0.172         | 2.05  | 1500 | 0.3968          | 16.3084 | 7.9787  |
  | 0.1823        | 3.03  | 2000 | 0.3956          | 16.1768 | 7.8159  |
  | 0.1445        | 4.0   | 2500 | 0.3955          | 16.0342 | 7.7438  |
  | 0.147         | 4.1   | 3000 | 0.3965          | 15.8807 | 7.7145  |
  | 0.1292        | 5.08  | 3500 | 0.4000          | 15.8587 | 7.7065  |
  | 0.1187        | 6.05  | 4000 | 0.4029          | 15.7491 | 7.6398  |
  | 0.1368        | 7.03  | 4500 | 0.4041          | 15.7600 | 7.6558  |
  | 0.1231        | 8.0   | 5000 | 0.4041          | 15.7710 | 7.6691  |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  