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Whisper Small PL

This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 and the FLEURS datasets. It achieves the following results on the evaluation set:

  • eval_loss: 0.3571
  • eval_wer: 14.8004
  • eval_runtime: 2233.4204
  • eval_samples_per_second: 3.714
  • eval_steps_per_second: 0.232
  • epoch: 4.03
  • step: 3000

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: 24
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 48
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 8000
  • mixed_precision_training: Native AMP

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0+cu117
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2
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Datasets used to train bardsai/whisper-small-pl

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Evaluation results