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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: 0.3157
  • Wer: 10.7746

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
0.5562 0.49 30 0.3054 11.4500
0.2771 0.98 60 0.2629 11.3656
0.1427 1.48 90 0.2726 13.1173
0.1369 1.97 120 0.2639 10.9751
0.0638 2.46 150 0.2741 11.9038
0.0541 2.95 180 0.2833 10.0992
0.0289 3.44 210 0.3024 10.7851
0.0198 3.93 240 0.3073 10.6902
0.0103 4.43 270 0.3177 10.4158
0.0089 4.92 300 0.3157 10.7746

Framework versions

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