readme: ---
  language:
  - sv
  license: apache-2.0
  tags:
  - hf-asr-leaderboard
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  model-index:
  - name: whisper-small-se
    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-se
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
  ## Model description
  The model was initially trained on 680 000 hours of audio with corresponding transcripts from the internet, 65% of which was in english audio and 83 % of which had english transcripts.
  
  The model was then further trained for 4000 iterations, 500 of which as warm-up, on Swedish data from [Common_voice 11.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0). Achieving a WER of 19.865.
  
  ## 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: 16
  - eval_batch_size: 8
  - 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: 500
  - mixed_precision_training: Native AMP
  
  ### Training results
  ![Training table](whisper_finetune.png)
  ## Model Plot
  
  <details>
  <summary>View Training Plots</summary>
  
  ![Metrics](whisper_metrics.png)
  
  </details>
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2