whisper-tiny-pl / README.md
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metadata
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

Whisper Tiny Pl

This model is a fine-tuned version of 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