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dlantonia
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whisper-tiny-en

Automatic Speech Recognition
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Whisper tiny en - dlantonia

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

  • Loss: 0.6625
  • Wer Ortho: 22.5602
  • Wer: 22.6496

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 Wer
0.0012 17.8571 500 0.6625 22.5602 22.6496

Framework versions

  • Transformers 4.42.4
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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Base model

openai/whisper-small
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Dataset used to train dlantonia/whisper-tiny-en

Evaluation results