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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: 0.3901
  • Wer: 13.6657

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
0.6756 0.71 30 0.3774 15.0287
0.2704 1.43 60 0.3396 13.4864
0.1792 2.14 90 0.3453 12.6793
0.0815 2.86 120 0.3393 17.2704
0.0432 3.57 150 0.3639 14.2217
0.0249 4.29 180 0.3874 14.7418
0.0132 5.0 210 0.3901 13.6657

Framework versions

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