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Yoruba_asr_whisper

Automatic Speech Recognition
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Yoruba
whisper
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Whisper-yoruba - Harcuracy

This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9734
  • Wer: 78.3558

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: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • training_steps: 500
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.9978 0.2173 500 0.9734 78.3558

Framework versions

  • Transformers 4.46.3
  • Pytorch 2.5.1+cu121
  • Datasets 3.1.0
  • Tokenizers 0.20.3
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Model tree for harcuracy619/Yoruba_asr_whisper

Base model

openai/whisper-small
Finetuned
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this model

Dataset used to train harcuracy619/Yoruba_asr_whisper

Evaluation results