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Whisper Large De - Krish Kalra

This model is a fine-tuned version of openai/whisper-large-v3-turbo on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2176
  • Wer: 9.2911

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: 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: 5
  • num_epochs: 5
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.1148 1.0 300 0.1876 10.6676
0.1281 2.0 600 0.2023 11.0805
0.032 3.0 900 0.2043 10.1170
0.0015 4.0 1200 0.2194 9.7729
0.0005 5.0 1500 0.2176 9.2911

Framework versions

  • Transformers 4.46.2
  • Pytorch 2.5.1+cu124
  • Datasets 3.1.0
  • Tokenizers 0.20.3
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