Whisper medium v1.5 - 100h

This model is a fine-tuned version of openai/whisper-medium on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2555
  • Wer: 13.1072

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: 6.25e-06
  • train_batch_size: 32
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 800
  • training_steps: 4500
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.234 0.2 900 0.2541 13.2906
0.2239 0.4 1800 0.2514 13.5961
0.1413 1.1 2700 0.2544 13.3211
0.0899 1.3 3600 0.2585 13.1989
0.1138 1.5 4500 0.2555 13.1072

Framework versions

  • Transformers 4.51.2
  • Pytorch 2.6.0+cu124
  • Datasets 3.5.0
  • Tokenizers 0.21.1
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