readme: ---
  language:
  - lv
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Small Latvian - Robust
    results:
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0 lv
        type: mozilla-foundation/common_voice_11_0
        config: lv
        split: test
        args: lv
      metrics:
      - type: wer
        value: 33.111954459203034
        name: Wer
      - type: wer
        value: 26.86
        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 Latvian - 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 lv dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5621
  - Wer: 33.1120
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.0219        | 16.67 | 1000 | 0.6129          | 41.1575 |
  | 0.0029        | 33.33 | 2000 | 0.5975          | 36.1480 |
  | 0.0003        | 50.0  | 3000 | 0.5626          | 33.6812 |
  | 0.0004        | 66.67 | 4000 | 0.5608          | 33.2827 |
  | 0.0001        | 83.33 | 5000 | 0.5715          | 33.8046 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu117
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  