readme: ---
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: whisper-large-et-ERR2020-v2
    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: 17.4
        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-large-et-ERR2020-v2
  
  This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2915
  - Wer: 13.8640
  
  ## 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: 2
  - eval_batch_size: 1
  - seed: 42
  - gradient_accumulation_steps: 16
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1000
  - training_steps: 10000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
  | 0.2158        | 0.1   | 1000  | 0.3205          | 23.8154 |
  | 0.0897        | 0.2   | 2000  | 0.2961          | 18.3340 |
  | 0.0785        | 0.3   | 3000  | 0.2839          | 17.5230 |
  | 0.0653        | 0.4   | 4000  | 0.2847          | 17.8752 |
  | 0.0541        | 0.5   | 5000  | 0.2906          | 15.2645 |
  | 0.0566        | 0.6   | 6000  | 0.2845          | 15.2081 |
  | 0.051         | 0.7   | 7000  | 0.2888          | 14.4668 |
  | 0.049         | 1.03  | 8000  | 0.2927          | 15.3130 |
  | 0.044         | 1.13  | 9000  | 0.2915          | 13.8640 |
  | 0.0379        | 1.23  | 10000 | 0.2913          | 16.5773 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.12.1+rocm5.1.1
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  