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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: 0.4064
  • Wer: 11.6270

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
0.6676 0.71 30 0.4010 19.5433
0.2705 1.43 60 0.3582 13.6441
0.1694 2.14 90 0.3648 11.8934
0.0793 2.86 120 0.3757 13.0542
0.0416 3.57 150 0.3965 13.3587
0.0245 4.29 180 0.3938 11.9125
0.012 5.0 210 0.4064 11.6270

Framework versions

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