readme: ---
  language:
  - cy
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Small Welsh - Robust
    results:
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0 cy
        type: mozilla-foundation/common_voice_11_0
        config: cy
        split: test
        args: cy
      metrics:
      - type: wer
        value: 23.073562122656497
        name: Wer
      - type: wer
        value: 20.33
        name: WER
  ---
  
  <!-- 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 Small Welsh - Robust
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 cy dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4569
  - Wer: 23.0736
  
  ## 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: 5e-05
  - train_batch_size: 64
  - eval_batch_size: 32
  - 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     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.0597        | 6.1   | 1000 | 0.4690          | 29.4666 |
  | 0.0107        | 12.2  | 2000 | 0.4707          | 26.2671 |
  | 0.0026        | 18.29 | 3000 | 0.4643          | 24.6763 |
  | 0.0007        | 24.39 | 4000 | 0.4629          | 23.8024 |
  | 0.0004        | 30.49 | 5000 | 0.4610          | 23.0616 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu117
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  