whisper-tiny-fr

This model is a fine-tuned version of openai/whisper-tiny on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8198
  • Wer: 0.8502

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: 8
  • eval_batch_size: 8
  • 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: 6250

Training results

Training Loss Epoch Step Validation Loss Wer
0.6223 1.0 250 0.7567 0.7225
0.475 2.0 500 0.6213 0.5461
0.2938 3.0 750 0.5860 0.5383
0.1613 4.0 1000 0.5903 0.4384
0.1026 5.0 1250 0.5992 0.4451
0.0615 6.0 1500 0.6322 0.5383
0.0422 7.0 1750 0.6398 0.4373
0.019 8.0 2000 0.6682 0.5239
0.0125 9.0 2250 0.6980 0.6681
0.0069 10.0 2500 0.7335 0.8679
0.0039 11.0 2750 0.7354 0.6238
0.0026 12.0 3000 0.7458 0.6315
0.0021 13.0 3250 0.7599 0.6715
0.0018 14.0 3500 0.7682 0.7103
0.0015 15.0 3750 0.7750 0.7081
0.0013 16.0 4000 0.7846 0.7125
0.0012 17.0 4250 0.7897 0.7114
0.001 18.0 4500 0.7962 0.9345
0.0009 19.0 4750 0.8001 0.7170
0.0009 20.0 5000 0.8074 0.8335
0.0008 21.0 5250 0.8107 0.8424
0.0007 22.0 5500 0.8152 0.8402
0.0007 23.0 5750 0.8181 0.8446
0.0007 24.0 6000 0.8187 0.8479
0.0007 25.0 6250 0.8198 0.8502

Framework versions

  • Transformers 4.32.0.dev0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3
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