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Whisper Small Frisian 1h

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: 0.7909
  • Wer: 38.7382

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: 600
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.9012 1.1236 100 1.0076 50.6327
0.2217 2.2472 200 0.8082 42.3311
0.0728 3.3708 300 0.7689 39.8467
0.0228 4.4944 400 0.7767 38.6526
0.0099 5.6180 500 0.7866 38.7738
0.0061 6.7416 600 0.7909 38.7382

Framework versions

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