readme: ---
  language:
  - pl
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  - google/fleurs
  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: 7.280175959972464
        name: WER
      - type: wer
        value: 7.31
        name: WER
      - type: wer_without_norm
        value: 20.18
        name: WER unnormalized
      - type: cer
        value: 2.08
        name: CER
      - type: mer
        value: 7.27
        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: 9.61
        name: WER
      - type: wer_without_norm
        value: 30.33
        name: WER unnormalized
      - type: cer
        value: 5.5
        name: CER
      - type: mer
        value: 9.45
        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: 8.68
        name: WER
      - type: wer_without_norm
        value: 29.33
        name: WER unnormalized
      - type: cer
        value: 3.63
        name: CER
      - type: mer
        value: 8.62
        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 [bardsai/whisper-large-v2-pl](https://huggingface.co/bardsai/whisper-large-v2-pl) on the Common Voice 11.0 and the FLEURS datasets.
  It achieves the following results on the evaluation set:
  - Loss: 0.3684
  - Wer: 7.2802
  
  ## 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: 2100
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.0047        | 1.35  | 700  | 0.3428          | 8.5562 |
  | 0.0011        | 2.7   | 1400 | 0.3605          | 7.5505 |
  | 0.0003        | 4.05  | 2100 | 0.3684          | 7.2802 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  