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MHaurel
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whisper-tiny-english

Automatic Speech Recognition
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Whisper Tiny en - MHaurel

This model is a fine-tuned version of openai/whisper-tiny on the Minds14 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6628
  • Wer Ortho Percentage: 32.5108
  • Wer: 0.3253
  • Wer Percentage: 32.5266

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
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Percentage Wer Wer Percentage
0.0006 17.8571 500 0.6628 32.5108 0.3253 32.5266

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.19.1
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Dataset used to train MHaurel/whisper-tiny-english

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