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Whisper Small French

This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 fr dataset. It achieves the following results on the evaluation set:

  • Loss: 0.00
  • WER on mozilla-foundation/common_voice_11_0 FR (with normalization): 15.38 %
  • WER on facebook/voxpopuli FR (with normalization): 16.29 %
  • WER on google/fleurs fr_fr (with normalization): 13.98 %

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: 32
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.11.0+cu102
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2
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Dataset used to train qanastek/whisper-small-french-uncased

Evaluation results