readme: ---
  language:
  - sv
  license: apache-2.0
  tags:
  - hf-asr-leaderboard
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Small Sv
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 11.0
        type: mozilla-foundation/common_voice_11_0
        config: sv
        split: test[:10%]
        args: 'config: sv, split: test'
      metrics:
      - name: Wer
        type: wer
        value: 19.76284584980237
  ---
  
  # Whisper Small Swedish
  This model is an adapted version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset in Swedish.
  It achieves the following results on the evaluation set:
  - Wer: 19.8166
  
  ## Model description & uses
  
  This model is the openai whisper small transformer adapted for Swedish audio to text transcription.
  The model is available through its [HuggingFace web app](https://huggingface.co/spaces/torileatherman/whisper_small_sv)
  
  ## Training and evaluation data
  
  Data used for training is the initial 10% of train and validation of [Swedish Common Voice](https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0/viewer/sv/train) 11.0 from Mozilla Foundation.
  The dataset used for evaluation is the initial 10% of test of Swedish Common Voice.
  The training data has been augmented with random noise, random pitching and change of the speed of the voice.
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 1e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - lr_scheduler_type: constant
  - lr_scheduler_warmup_steps: 500
  - training_steps: 4000
  - weight decay: 0
  
  ### Training results
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.1379        | 0.95  | 1000 | 0.295811        | 21.467|
  | 0.0245        | 2.86  | 3000 | 0.300059        | 20.160 |
  | 0.0060        | 3.82  | 4000 | 0.320301        | 19.762 |
  
  ### Framework versions
  - Transformers 4.26.0.dev0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  
        