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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: 0.3247
  • Wer: 13.4709

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
0.5388 0.49 30 0.3297 12.2434
0.2858 0.98 60 0.2893 23.3419
0.143 1.48 90 0.2922 13.5327
0.1337 1.97 120 0.2838 10.7065
0.0606 2.46 150 0.2905 10.3765
0.0557 2.95 180 0.2915 10.0258
0.0265 3.44 210 0.3139 10.8613
0.0207 3.93 240 0.3094 10.0670
0.0098 4.43 270 0.3188 12.0578
0.0098 4.92 300 0.3247 13.4709

Framework versions

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