readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  - whisper-event
  - hf-asr-leaderboard
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: openai/whisper-medium
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: common_voice_11_0
        type: common_voice_11_0
        config: ba
        split: test
        args: ba
      metrics:
      - name: Wer
        type: wer
        value: 19.56338265908963
  ---
  
  <!-- 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. -->
  
  # openai/whisper-small
  
  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: 0.2195
  - Wer: 19.56
  
  ## 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: 1
  - 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: 10000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Epoch | Step | Wer     |
  |:-------------:|:-----:|:----:|
  | 0.1   | 1000 | 43.61 |
  | 0.2   | 2000 | 36.79 |
  | 0.3   | 3000 | 33.05 |
  | 0.4   | 4000 | 29.53 |
  | 0.5   | 5000 | 26.01 |
  | 0.6   | 6000 | 23.44 |
  | 0.7   | 7000 | 22.22 |
  | 0.8   | 8000 | 21.88 |
  | 0.9   | 9000 | 20.53 |
  | 1.0   | 10000 | 19.56 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2