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Whisper Large V2

This model is a fine-tuned version of openai/whisper-large-v2 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4660
  • Wer: 14.5440

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: 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: 20
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Wer
0.7649 0.55 30 0.4569 21.4116
0.3718 1.09 60 0.4107 14.9247
0.2053 1.64 90 0.3970 17.1451
0.1836 2.18 120 0.4242 14.0523
0.092 2.73 150 0.4120 14.4330
0.0648 3.27 180 0.4352 15.5115
0.0359 3.82 210 0.4290 15.0991
0.0205 4.36 240 0.4587 14.6392
0.0132 4.91 270 0.4660 14.5440

Framework versions

  • Transformers 4.38.0.dev0
  • Pytorch 2.1.0+cu121
  • Datasets 2.14.6
  • Tokenizers 0.15.0
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