whisper-medium-en-cv-4.9

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

  • Loss: 0.3508
  • Wer: 11.3793

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: 6e-06
  • train_batch_size: 48
  • eval_batch_size: 4
  • 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: 150
  • training_steps: 1500
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
No log 0 0 1.5197 12.4138
0.2355 0.2 300 0.3713 11.3793
0.3136 0.4 600 0.3537 11.2069
0.1076 1.1 900 0.3551 11.8103
0.1079 1.3 1200 0.3570 11.3793
0.1715 1.5 1500 0.3508 11.3793

Framework versions

  • Transformers 4.51.3
  • Pytorch 2.6.0+cu124
  • Datasets 3.5.1
  • Tokenizers 0.21.1
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Dataset used to train xbilek25/whisper-medium-en-cv-4.9

Evaluation results