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Whisper Base French

This model is a fine-tuned version of qanastek/whisper-small-french-uncased on the mozilla-foundation/common_voice_16_0 fr dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8014
  • Wer: 15.1845

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: 5e-07
  • train_batch_size: 16
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • training_steps: 1000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.9295 0.2 100 0.8014 15.1845
0.2976 0.4 200 0.4207 16.0289
0.2699 0.59 300 0.3999 15.8267
0.2773 0.79 400 0.3910 15.7267
0.2631 0.99 500 0.3863 15.5972
0.2487 1.19 600 0.3834 15.5907
0.2477 1.39 700 0.3814 15.6156
0.2428 1.59 800 0.3801 15.4902
0.2492 1.78 900 0.3794 15.4672
0.2471 1.98 1000 0.3791 15.4707

Framework versions

  • Transformers 4.38.0.dev0
  • Pytorch 2.1.2+cu121
  • Datasets 2.16.2.dev0
  • Tokenizers 0.15.0
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Finetuned from

Dataset used to train arun100/whisper-small-fr-derived-1

Evaluation results