readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: whisper-large-v2-zh-hk-2gpu
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0 zh-HK
        type: mozilla-foundation/common_voice_11_0
        config: None
        split: None
        args: zh-HK
      metrics:
      - name: Wer
        type: wer
        value: 0.45734639358860196
  ---
  
  <!-- 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-zh-hk-2gpu
  
  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-HK dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2237
  - Wer: 0.4573
  
  ## 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
  - distributed_type: multi-GPU
  - num_devices: 2
  - total_train_batch_size: 16
  - total_eval_batch_size: 16
  - 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.1544        | 1.14  | 1000 | 0.2260          | 0.5485 |
  | 0.0745        | 2.28  | 2000 | 0.2132          | 0.4967 |
  | 0.0213        | 3.42  | 3000 | 0.2114          | 0.4718 |
  | 0.0117        | 4.57  | 4000 | 0.2196          | 0.4643 |
  | 0.0014        | 5.71  | 5000 | 0.2237          | 0.4573 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  