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: 0.3679
  • Wer: 12.7848

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
0.7686 0.55 30 0.3602 18.3326
0.3835 1.09 60 0.3292 15.3107
0.22 1.64 90 0.3163 16.9069
0.1668 2.18 120 0.3356 16.5194
0.0955 2.73 150 0.3383 13.4356
0.0674 3.27 180 0.3632 11.9944
0.0376 3.82 210 0.3584 12.6143
0.0218 4.36 240 0.3645 12.9242
0.0136 4.91 270 0.3679 12.7848

Framework versions

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