readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  - whisper-event
  metrics:
  - wer
  model-index:
  - name: agnesluhtaru/whisper-medium-et
    results:
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0
        type: mozilla-foundation/common_voice_11_0
        config: et
        split: test
      metrics:
      - type: wer
        value: 28.6
        name: WER
  ---
  
  # whisper-medium-et
  
  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the following datasets: Common Voice 11, VoxPopuli and FLEURS.
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  Estonian data from Common Voice 11, VoxPopuli and FLEURS corpora as both training and validation sets. Tested on Common Voice 11 test set. 
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 1e-05
  - train_batch_size: 32
  - eval_batch_size: 16
  - 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: 5000
  - mixed_precision_training: Native AMP
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.12.1+rocm5.1.1
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2