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 Large v2 PL
    results:
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: Common Voice 11.0
        type: mozilla-foundation/common_voice_11_0
        config: pl
        split: test
        args: pl
      metrics:
      - type: wer
        value: 6.89
        name: WER
      - type: wer_without_norm
        value: 19.79
        name: WER unnormalized
      - type: cer
        value: 1.88
        name: CER
      - type: mer
        value: 6.84
        name: MER
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: facebook/voxpopuli
        type: facebook/voxpopuli
        config: pl
        split: test
      metrics:
      - type: wer
        value: 9.26
        name: WER
      - type: wer_without_norm
        value: 30.25
        name: WER unnormalized
      - type: cer
        value: 5.32
        name: CER
      - type: mer
        value: 9.1
        name: MER
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: google/fleurs
        type: google/fleurs
        config: pl_pl
        split: test
      metrics:
      - type: wer
        value: 9.88
        name: WER
      - type: wer_without_norm
        value: 29.53
        name: WER unnormalized
      - type: cer
        value: 5.09
        name: CER
      - type: mer
        value: 9.73
        name: MER
  ---
  
  <!-- 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 v2 PL
  
  This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the Common Voice 11.0 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4222
  - Wer: 6.9125
  
  ## 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: 8
  - eval_batch_size: 4
  - seed: 42
  - gradient_accumulation_steps: 8
  - total_train_batch_size: 64
  - 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.1144        | 1.93  | 500  | 0.2016          | 7.4749 |
  | 0.0441        | 3.86  | 1000 | 0.2193          | 7.3154 |
  | 0.0099        | 5.79  | 1500 | 0.2983          | 7.0804 |
  | 0.0048        | 7.72  | 2000 | 0.3514          | 7.0988 |
  | 0.0017        | 9.65  | 2500 | 0.3614          | 7.0485 |
  | 0.0014        | 11.58 | 3000 | 0.3814          | 7.1240 |
  | 0.001         | 13.51 | 3500 | 0.3773          | 6.9931 |
  | 0.0005        | 15.44 | 4000 | 0.4085          | 6.9662 |
  | 0.0004        | 17.37 | 4500 | 0.4195          | 6.9192 |
  | 0.0004        | 19.3  | 5000 | 0.4222          | 6.9125 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  