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Whisper Small for Common Accent

This model is a fine-tuned version of openai/whisper-small on the Common Accent dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3213
  • Wer Ortho: 16.2560
  • Wer: 11.5126

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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_steps: 50
  • training_steps: 500

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
0.1011 1.14 500 0.3213 16.2560 11.5126

Framework versions

  • Transformers 4.33.0.dev0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3
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Dataset used to train Wishwa98/ASRCOMMONACCENT_LessEpoch

Evaluation results