readme: ---
  language:
  - cs
  license: apache-2.0
  tags:
  - whisper-event
  - hf-asr-leaderboard
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Medium Czech CV11
    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
        split: test
        config: cs
      metrics:
      - name: Wer
        type: wer
        value: 11.689339690370561
  ---
  
  <!-- 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 Czech CV11
  
  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 cs dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2537
  - Wer: 11.6893
  
  ## 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: 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
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.0384        | 2.02  | 1000 | 0.2167          | 13.5467 |
  | 0.0061        | 4.03  | 2000 | 0.2373          | 12.9172 |
  | 0.0018        | 6.05  | 3000 | 0.2407          | 12.0409 |
  | 0.0007        | 8.07  | 4000 | 0.2463          | 11.7685 |
  | 0.0003        | 10.09 | 5000 | 0.2537          | 11.6893 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  