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 Tiny 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: 39.469591826496995
  ---
  
  <!-- 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 Tiny Pl
  
  This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6919
  - Wer: 39.4696
  
  ## 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: 64
  - 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     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.3647        | 1.05  | 500  | 0.6999          | 43.0430 |
  | 0.2752        | 3.04  | 1000 | 0.6002          | 39.3275 |
  | 0.2513        | 5.04  | 1500 | 0.5911          | 37.8643 |
  | 0.1661        | 7.04  | 2000 | 0.6381          | 37.6887 |
  | 0.154         | 9.03  | 2500 | 0.6157          | 37.9362 |
  | 0.1126        | 11.03 | 3000 | 0.6319          | 38.6402 |
  | 0.0763        | 13.02 | 3500 | 0.6539          | 38.9730 |
  | 0.0729        | 15.02 | 4000 | 0.6583          | 38.9362 |
  | 0.0778        | 17.02 | 4500 | 0.6653          | 39.6769 |
  | 0.0698        | 19.01 | 5000 | 0.6919          | 39.4696 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  