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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: 0.4000
  • Wer: 10.8918

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
0.2263 0.49 30 0.3524 16.2639
0.2192 0.98 60 0.3412 16.1689
0.104 1.48 90 0.3537 12.4644
0.0967 1.97 120 0.3511 11.5567
0.0467 2.46 150 0.3665 13.7098
0.0409 2.95 180 0.3717 11.5884
0.0213 3.44 210 0.3875 11.2718
0.0156 3.93 240 0.3891 11.6834
0.0097 4.43 270 0.3946 10.7018
0.0064 4.92 300 0.4000 10.8918

Framework versions

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