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openai/whisper-base

This model is a fine-tuned version of openai/whisper-base on the /nas/data/lowband_telephone/wav/training/D01/J01/S000001 dataset. It achieves the following results on the evaluation set:

  • Loss: 1.3994
  • Cer: 18.3333

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: 1e-05
  • train_batch_size: 64
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 4000

Training results

Training Loss Epoch Step Validation Loss Cer
0.0 1000.0 1000 1.2835 17.5
0.0 2000.0 2000 1.3486 18.3333
0.0 3000.0 3000 1.3850 18.3333
0.0 4000.0 4000 1.3994 18.3333

Framework versions

  • Transformers 4.36.0.dev0
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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