readme: ---
  language:
  - pl
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Small PL
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 11.0
        type: mozilla-foundation/common_voice_11_0
        config: pl
        split: test
        args: pl
      metrics:
      - name: Wer
        type: wer
        value: 8.820627727705968
  ---
  
  <!-- 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 PL
  
  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 11.0 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3739
  - Wer: 8.8206
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.121         | 0.1   | 500  | 0.2630          | 10.2804 |
  | 0.0474        | 1.1   | 1000 | 0.2561          | 9.5597  |
  | 0.0257        | 2.09  | 1500 | 0.2617          | 9.5681  |
  | 0.0119        | 3.09  | 2000 | 0.2901          | 9.1534  |
  | 0.0064        | 4.08  | 2500 | 0.3463          | 9.0280  |
  | 0.0045        | 5.08  | 3000 | 0.3151          | 9.0965  |
  | 0.0015        | 6.08  | 3500 | 0.3985          | 8.9611  |
  | 0.0007        | 7.07  | 4000 | 0.4218          | 8.8073  |
  | 0.0006        | 8.07  | 4500 | 0.4054          | 8.8156  |
  | 0.0005        | 9.07  | 5000 | 0.3739          | 8.8206  |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  