readme: ---
  language:
  - zh
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper large-v2 nan-tw
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0 nan-tw
        type: mozilla-foundation/common_voice_11_0
        config: nan-tw
        split: train
        args: nan-tw
      metrics:
      - name: Wer
        type: wer
        value: 42.592995431803345
      - name: Cer
        type: cer
        value: 23.297031817211188   
  ---
  
  <!-- 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 nan-tw
  
  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 nan-tw dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7525
  - Wer: 42.5930
  - Cer: 23.2970
  
  ## 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: 2
  - eval_batch_size: 2
  - 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     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
  | 0.4781        | 1.04  | 1000 | 0.7256          | 52.4690 | 28.7583 |
  | 0.1881        | 2.08  | 2000 | 0.7346          | 50.2067 | 26.6389 |
  | 0.0429        | 3.13  | 3000 | 0.7094          | 45.3557 | 24.7811 |
  | 0.0112        | 5.01  | 4000 | 0.7416          | 44.4203 | 24.6850 |
  | 0.0011        | 6.05  | 5000 | 0.7525          | 42.5930 | 23.2970 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.1+cu117
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  