readme: ---
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - babelbox/babelbox_voice
  metrics:
  - wer
  model-index:
  - name: Whisper medium Swedish
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: babelbox/babelbox_voice nst
        type: babelbox/babelbox_voice
        config: default
        split: train
        args: default
      metrics:
      - name: Wer
        type: wer
        value: 10.523062036340178
  ---
  
  <!-- 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 medium Swedish
  
  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the babelbox/babelbox_voice nst dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3042
  - Wer: 10.5231
  
  ## 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: 64
  - eval_batch_size: 32
  - seed: 42
  - distributed_type: multi-GPU
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 128
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - training_steps: 10000
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
  | 0.0999        | 0.1   | 1000  | 0.2781          | 12.8158 |
  | 0.0852        | 0.2   | 2000  | 0.2661          | 12.0202 |
  | 0.065         | 1.08  | 3000  | 0.2783          | 11.6332 |
  | 0.0678        | 1.18  | 4000  | 0.2744          | 11.7299 |
  | 0.0447        | 2.07  | 5000  | 0.2893          | 11.0606 |
  | 0.0425        | 2.17  | 6000  | 0.2795          | 10.8107 |
  | 0.0395        | 3.05  | 7000  | 0.2861          | 10.7462 |
  | 0.0369        | 3.15  | 8000  | 0.2910          | 10.7596 |
  | 0.0338        | 4.04  | 9000  | 0.3037          | 11.1708 |
  | 0.0271        | 4.14  | 10000 | 0.3042          | 10.5231 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu117
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  