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ap-QIBZtD7OwB1EdMtrY8z9uY

This model is a fine-tuned version of openai/whisper-large-v3-turbo on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4289
  • Model Preparation Time: 0.0073
  • Wer: 0.1482

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: 3e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 64
  • 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: 400
  • num_epochs: 24
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Model Preparation Time Wer
0.6535 0.9880 72 0.2314 0.0073 0.1507
0.164 1.9880 144 0.2551 0.0073 0.1633
0.1144 2.9880 216 0.2904 0.0073 0.1626
0.0931 3.9880 288 0.3181 0.0073 0.1752
0.0932 4.9880 360 0.3604 0.0073 0.2670
0.0849 5.9880 432 0.3761 0.0073 0.4850
0.0761 6.9880 504 0.4472 0.0073 0.2170
0.0693 7.9880 576 0.4621 0.0073 0.1937
0.0483 8.9880 648 0.4190 0.0073 0.1719
0.0382 9.9880 720 0.4299 0.0073 0.1719
0.0347 10.9880 792 0.4653 0.0073 0.1775
0.0295 11.9880 864 0.4408 0.0073 0.1749
0.0264 12.9880 936 0.4454 0.0073 0.1795
0.0137 13.9880 1008 0.4457 0.0073 0.1963
0.0134 14.9880 1080 0.4360 0.0073 0.2534
0.0108 15.9880 1152 0.4072 0.0073 0.1432
0.006 16.9880 1224 0.4071 0.0073 0.1660
0.0048 17.9880 1296 0.3858 0.0073 0.1481
0.0024 18.9880 1368 0.3916 0.0073 0.1570
0.0018 19.9880 1440 0.4183 0.0073 0.1621
0.0011 20.9880 1512 0.4246 0.0073 0.1500
0.0006 21.9880 1584 0.4246 0.0073 0.1484
0.0002 22.9880 1656 0.4142 0.0073 0.1479
0.0002 23.9880 1728 0.4289 0.0073 0.1482

Framework versions

  • Transformers 4.48.3
  • Pytorch 2.5.1+cu124
  • Datasets 3.2.0
  • Tokenizers 0.21.2
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