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whisper-small-minds14-enUS

This model is a fine-tuned version of openai/whisper-small on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5829
  • Wer Ortho: 27.8223
  • Wer: 28.1582

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
0.0003 17.86 500 0.5829 27.8223 28.1582

Framework versions

  • Transformers 4.34.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.14.0
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Finetuned from

Dataset used to train Terps/whisper-small-minds14-enUS

Evaluation results