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Whisper Small Stutter - Ariel Cerda

This model is a fine-tuned version of openai/whisper-small on the Libristutter 4.7k dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4843
  • Wer: 31.7028

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: 16
  • eval_batch_size: 8
  • 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
0.0595 3.7453 1000 0.3199 17.1830
0.0046 7.4906 2000 0.4093 18.1542
0.0008 11.2360 3000 0.4562 24.3625
0.0006 14.9813 4000 0.4754 33.2340
0.0005 18.7266 5000 0.4843 31.7028

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.19.1
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Evaluation results