readme: ---
  language:
  - sv
  license: apache-2.0
  tags:
  - hf-asr-leaderboard
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: Whisper Small SV
    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 SV
  
  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: 0.3516
  - Wer: 23.0598
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - 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: 200
  - training_steps: 1000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.3274        | 0.86  | 200  | 0.3552          | 24.7469 |
  | 0.1395        | 1.72  | 400  | 0.3303          | 23.5038 |
  | 0.074         | 2.59  | 600  | 0.3349          | 22.6603 |
  | 0.0199        | 3.45  | 800  | 0.3451          | 22.7935 |
  | 0.0089        | 4.31  | 1000 | 0.3516          | 23.0598 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  