readme: ---
  language:
  - vi
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Medium VI - CV - Augmented
    results:
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: Common Voice 11.0
        type: mozilla-foundation/common_voice_11_0
        config: vi
        split: test
        args: vi
      metrics:
      - type: wer
        value: 18.030269796007897
        name: Wer
      - type: wer
        value: 17.98
        name: WER
      - type: cer
        value: 8.31
        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 - CV - Augmented
  
  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 11.0 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6613
  - Wer: 18.0303
  - Cer: 8.3095
  
  ## 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: 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    |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|
  | 0.0053        | 11.49 | 1000 | 0.5429          | 18.1290 | 8.4643 |
  | 0.0021        | 22.99 | 2000 | 0.5916          | 18.8857 | 8.6538 |
  | 0.0001        | 34.48 | 3000 | 0.6348          | 18.3374 | 8.4296 |
  | 0.0001        | 45.98 | 4000 | 0.6508          | 17.9754 | 8.3149 |
  | 0.0001        | 57.47 | 5000 | 0.6613          | 18.0303 | 8.3095 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  