readme: ---
  language:
  - sv
  license: apache-2.0
  tags:
  - hf-asr-leaderboard
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: Whisper Small - Swedish
    results: []
  ---
  
  <!-- 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 - Swedish
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3700
  - Wer: 20.2173
  
  ## 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: 4
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_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: 6000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.048         | 2.59  | 2000 | 0.2925          | 20.3893 |
  | 0.0045        | 5.18  | 4000 | 0.3258          | 19.6553 |
  | 0.0054        | 6.48  | 5000 | 0.3613          | 20.3087 |
  | 0.0028        | 7.77  | 6000 | 0.3700          | 20.2173 |
  
  
  ### Framework versions
  
  - Transformers 4.25.0.dev0
  - Pytorch 1.12.1
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  