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 medium 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: 42.07091581466174
      - name: Cer
        type: cer
        value: 22.368140081144567
  ---
  
  <!-- 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 nan-tw
  
  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_11_0 nan-tw dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9100
  - Wer: 42.0709
  - Cer: 22.3681
  
  ## 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: 8
  - eval_batch_size: 8
  - 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     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
  | 0.0568        | 5.0   | 1000 | 0.7769          | 48.2706 | 26.0890 |
  | 0.0057        | 10.0  | 2000 | 0.8438          | 44.0722 | 23.9270 |
  | 0.0041        | 15.01 | 3000 | 0.8740          | 42.8540 | 22.9554 |
  | 0.0001        | 20.01 | 4000 | 0.9041          | 42.1797 | 22.5496 |
  | 0.0001        | 25.01 | 5000 | 0.9100          | 42.0709 | 22.3681 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.1+cu117
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  