readme: ---
  language:
  - da
  license: apache-2.0
  tags:
  - generated_from_trainer
  - hf-asr-leaderboard
  - whisper-event
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Medium Danish (CV11 + FLEAURS)
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0
        type: mozilla-foundation/common_voice_11_0
        config: da
        split: test
      metrics:
      - name: Wer
        type: wer
        value: 13.708574434508153
  ---
  
  <!-- 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 Danish (CV11 + FLEAURS)
  
  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_11_0,google/fleurs da,da_dk dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5814
  - Wer: 13.7086
  
  ## 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: 8e-06
  - train_batch_size: 32
  - 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: 500
  - training_steps: 10000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
  | 0.0265        | 3.14  | 1000  | 0.3690          | 14.7607 |
  | 0.0063        | 6.29  | 2000  | 0.4342          | 14.0926 |
  | 0.0016        | 9.43  | 3000  | 0.4847          | 14.3609 |
  | 0.002         | 12.58 | 4000  | 0.4919          | 14.1715 |
  | 0.0013        | 15.72 | 5000  | 0.5114          | 14.2294 |
  | 0.0014        | 18.87 | 6000  | 0.5197          | 13.9137 |
  | 0.0003        | 22.01 | 7000  | 0.5422          | 14.1978 |
  | 0.0001        | 25.16 | 8000  | 0.5659          | 13.8716 |
  | 0.0001        | 28.3  | 9000  | 0.5772          | 13.7296 |
  | 0.0001        | 31.45 | 10000 | 0.5814          | 13.7086 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  