readme: ---
  language:
  - zh
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  - cer
  model-index:
  - name: whisper_medium_zh_tw
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0 zh-tw
        type: mozilla-foundation/common_voice_11_0
        config: zh-tw
        split: train
        args: zh-tw
      metrics:
      - name: Wer
        type: wer
        value: 34.45240532241556
  ---
  
  <!-- 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_zh_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 zh-TW dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2039
  - Wer: 34.4524
  - Cer: 7.6293
  
  ## 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    |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|
  | 0.0895        | 1.04  | 1000 | 0.1806          | 37.6049 | 8.5312 |
  | 0.0259        | 2.07  | 2000 | 0.2031          | 36.1924 | 8.3641 |
  | 0.0117        | 3.11  | 3000 | 0.1966          | 35.9672 | 7.9476 |
  | 0.0015        | 4.14  | 4000 | 0.2032          | 34.8414 | 7.6478 |
  | 0.0003        | 6.01  | 5000 | 0.2039          | 34.4524 | 7.6293 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.1+cu117
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  