readme: ---
  language:
  - vi
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  - google/fleurs
  - vivos
  metrics:
  - wer
  model-index:
  - name: Whisper Medium VI - Multi - 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: vi
        split: test
      metrics:
      - type: wer
        value: 16.63
        name: WER
      - type: cer
        value: 7.74
        name: CER
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: google/fleurs
        type: google/fleurs
        config: vi_vn
        split: test
      metrics:
      - type: wer
        value: 9.04
        name: WER
      - type: cer
        value: 4.81
        name: CER
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: vivos
        type: vivos
        split: test
      metrics:
      - type: wer
        value: 8.53
        name: WER
      - type: cer
        value: 3.67
        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 Medium VI - Multi - Augmented
  
  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the following datasets:
  - [mozilla-foundation/common_voice_11_0](https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0)
  - [google/fleurs](https://huggingface.co/datasets/google/fleurs)
  - [vivos](https://huggingface.co/datasets/vivos)
  
  It achieves the following results on the evaluation set:
  - Loss: 0.3696
  - Wer: 16.6594
  - Cer: 7.7625
  
  ## 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)
  - [google/fleurs](https://huggingface.co/datasets/google/fleurs) (train+validation)
  - [vivos](https://huggingface.co/datasets/vivos) (train)
  
  Evaluation:
  - [mozilla-foundation/common_voice_11_0](https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0) (test)
  - [google/fleurs](https://huggingface.co/datasets/google/fleurs) (test)
  - [vivos](https://huggingface.co/datasets/vivos) (test)
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 1e-05
  - train_batch_size: 32
  - eval_batch_size: 16
  - seed: 42
  - 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    |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|
  | 0.1992        | 1.8   | 1000 | 0.2726          | 17.4929 | 8.2562 |
  | 0.0402        | 3.6   | 2000 | 0.3317          | 17.4929 | 8.2588 |
  | 0.0073        | 5.4   | 3000 | 0.3429          | 17.6793 | 8.8913 |
  | 0.0014        | 7.19  | 4000 | 0.3599          | 19.0283 | 9.5103 |
  | 0.0006        | 8.99  | 5000 | 0.3696          | 16.6594 | 7.7625 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  