readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  - whisper-event
  metrics:
  - wer
  model-index:
  - name: whisper-small-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: 43.69
        name: WER
  ---
  
  <!-- 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-et
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) 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: 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_steps: 500
  - training_steps: 2000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 1.1285        | 1.03  | 200  | 1.0640          | 53.4934 |
  | 0.5163        | 2.05  | 400  | 0.6450          | 41.2428 |
  | 0.2005        | 4.01  | 600  | 0.5600          | 36.6797 |
  | 0.1188        | 5.03  | 800  | 0.5718          | 35.2847 |
  | 0.0487        | 6.06  | 1000 | 0.5999          | 34.7500 |
  | 0.0216        | 8.01  | 1200 | 0.6479          | 38.1906 |
  | 0.016         | 9.04  | 1400 | 0.6655          | 39.5034 |
  | 0.0085        | 10.06 | 1600 | 0.7027          | 33.9038 |
  | 0.0079        | 12.02 | 1800 | 0.7207          | 39.5723 |
  | 0.009         | 13.04 | 2000 | 0.7261          | 34.5973 |
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.12.1+rocm5.1.1
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  