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Whisper Base French

This model is a fine-tuned version of qanastek/whisper-base-french-cased on the google/fleurs fr_fr dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5402
  • Wer: 23.7955

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-07
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 2
  • 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: 500
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.3835 105.26 1000 0.5892 25.4237
0.2837 210.53 2000 0.5526 23.8955
0.2323 315.79 3000 0.5432 24.0122
0.1961 421.05 4000 0.5402 23.7955
0.1863 526.32 5000 0.5395 23.7955

Framework versions

  • Transformers 4.37.0.dev0
  • Pytorch 2.1.2+cu121
  • Datasets 2.16.2.dev0
  • Tokenizers 0.15.0
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Dataset used to train arun100/whisper-base-fr-derived-2

Evaluation results