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Whisper Medium Breton

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

  • Loss: 0.8486
  • Wer: 41.6117

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: 4e-06
  • train_batch_size: 32
  • eval_batch_size: 16
  • seed: 42
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 400
  • training_steps: 5000

Training results

Training Loss Epoch Step Validation Loss Wer
0.0602 5.03 1000 0.7324 43.6957
0.0036 10.05 2000 0.8486 41.6117
0.001 15.08 3000 0.9033 42.0458
0.0004 20.1 4000 0.9351 41.6811
0.0003 25.13 5000 0.9468 41.7853

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.1+cu117
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2
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Dataset used to train BlueRaccoon/whisper-medium-br

Evaluation results