readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - fleurs
  metrics:
  - wer
  model-index:
  - name: openai/whisper-tiny
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: fleurs
        type: fleurs
        config: sv_se
        split: validation
        args: sv_se
      metrics:
      - name: Wer
        type: wer
        value: 168.6092926712438
  ---
  
  <!-- 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. -->
  
  # openai/whisper-tiny
  
  This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the fleurs dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.0456
  - Wer: 168.6093
  
  ## 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
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.2
  - training_steps: 112
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer      |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 1.5299        | 0.1   | 11   | 1.5622          | 219.6711 |
  | 1.1908        | 0.2   | 22   | 1.3652          | 192.2401 |
  | 1.1161        | 0.29  | 33   | 1.1921          | 200.2395 |
  | 0.9216        | 1.05  | 44   | 1.1263          | 186.5240 |
  | 0.8441        | 1.15  | 55   | 1.0946          | 179.3230 |
  | 0.8505        | 1.25  | 66   | 1.0748          | 159.6839 |
  | 0.7844        | 2.01  | 77   | 1.0585          | 163.2924 |
  | 0.7208        | 2.11  | 88   | 1.0491          | 158.1031 |
  | 0.6481        | 2.21  | 99   | 1.0468          | 158.5183 |
  | 0.7912        | 2.3   | 110  | 1.0456          | 168.6093 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  