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: 0.4312
  - Wer: 19.0503
  
  ## 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: 18000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
  | 0.0887        | 1.71  | 2000  | 0.2817          | 21.0831 |
  | 0.0168        | 3.41  | 4000  | 0.3108          | 19.6338 |
  | 0.0027        | 5.12  | 6000  | 0.3421          | 19.8731 |
  | 0.0012        | 6.83  | 8000  | 0.3713          | 19.1229 |
  | 0.0005        | 8.53  | 10000 | 0.3844          | 19.2036 |
  | 0.0004        | 10.24 | 12000 | 0.3900          | 19.0369 |
  | 0.0008        | 11.94 | 14000 | 0.4161          | 19.9511 |
  | 0.0002        | 13.65 | 16000 | 0.4201          | 19.1283 |
  | 0.0001        | 15.36 | 18000 | 0.4312          | 19.0503 |
  
  
  ### Framework versions
  
  - Transformers 4.25.0.dev0
  - Pytorch 1.12.1
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  