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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: 0.5036
  • Wer: 16.6019

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
0.7555 0.55 30 0.5180 28.4626
0.3756 1.09 60 0.4488 36.3749
0.2159 1.64 90 0.4497 19.5399
0.1656 2.18 120 0.4641 17.7056
0.1021 2.73 150 0.4502 17.1926
0.0774 3.27 180 0.4692 17.0527
0.0478 3.82 210 0.4712 18.7315
0.0264 4.36 240 0.4956 17.5657
0.016 4.91 270 0.5036 16.6019

Framework versions

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