whisper-large-v3-turbo-augmented

This model is a fine-tuned version of openai/whisper-large-v3-turbo on the ntnu-smil/lttc-augmented-ft-1 dataset. It achieves the following results on the evaluation set:

  • Loss: 1.3566
  • Wer: 32.3600
  • Cer: 18.4747

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: 0.0005
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Wer Cer
0.0483 1.0 190 1.2801 35.8640 20.7045
0.0503 2.0 380 1.3510 32.5318 20.3283
0.0033 3.0 570 1.2776 39.3336 22.9891
0.0007 4.0 760 1.3057 32.6692 18.6594
0.0002 5.0 950 1.3566 32.3600 18.4747

Framework versions

  • PEFT 0.14.0
  • Transformers 4.47.0
  • Pytorch 2.2.0+cu121
  • Datasets 3.1.0
  • Tokenizers 0.21.0
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Dataset used to train ntnu-smil/whisper-large-v3-turbo-augmented-merged

Evaluation results