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Whisper Small Frisian 10h

This model is a fine-tuned version of openai/whisper-small on the Common Voice 6.1 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3402
  • Wer: 22.4274

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: 50
  • training_steps: 1500
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.0548 0.1070 100 1.0200 52.0620
0.6944 0.2139 200 0.7126 39.6222
0.6024 0.3209 300 0.6052 36.0791
0.4697 0.4278 400 0.5303 32.5040
0.4222 0.5348 500 0.4780 30.0766
0.4075 0.6417 600 0.4458 28.4691
0.374 0.7487 700 0.4151 26.9292
0.3381 0.8556 800 0.3949 25.4678
0.3235 0.9626 900 0.3764 24.8904
0.1861 1.0695 1000 0.3643 23.5716
0.1554 1.1765 1100 0.3608 23.4183
0.1639 1.2834 1200 0.3511 23.0298
0.1453 1.3904 1300 0.3449 22.6591
0.1531 1.4973 1400 0.3419 22.4452
0.1299 1.6043 1500 0.3402 22.4274

Framework versions

  • Transformers 4.40.1
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1
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