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: 0.3649
  • Wer: 11.9003

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
0.6619 0.71 30 0.3733 16.9978
0.2708 1.43 60 0.3423 15.2736
0.1655 2.14 90 0.3352 13.9055
0.0767 2.86 120 0.3321 12.6874
0.0416 3.57 150 0.3421 12.1439
0.0237 4.29 180 0.3498 12.2751
0.0114 5.0 210 0.3649 11.9003

Framework versions

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