readme: ---
  language:
  - nl
  license: apache-2.0
  tags:
  - hf-asr-leaderboard
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: FIFA_WC22_WINNER_LANGUAGE_MODEL
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 11.0
        type: mozilla-foundation/common_voice_11_0
        config: 'null'
        split: None
        args: 'config: nl, split: test'
      metrics:
      - name: Wer
        type: wer
        value: 14.261890699371158
  ---
  
  
  # whisper-lt-finetune
  
  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: 0.2588
  - Wer: 14.2619
  
  ### 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: 250
  - training_steps: 4000
  - mixed_precision_training: Native AMP
  ### Training results
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.0783        | 1.3   | 1000 | 0.2478          | 15.5647 |
  | 0.0287        | 2.6   | 2000 | 0.2441          | 14.3765 |
  | 0.0087        | 3.9   | 3000 | 0.2516          | 14.3349 |
  | 0.0021        | 5.19  | 4000 | 0.2588          | 14.2619 |
  
  ### Framework versions
  - Transformers 4.26.0.dev0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  