Whisper Small Basque

This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_13_0 eu dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3485
  • Wer: 19.3516

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: 64
  • eval_batch_size: 32
  • 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: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.337 5.85 1000 0.3838 26.8815
0.1384 11.7 2000 0.3431 22.1544
0.0732 17.54 3000 0.3376 20.0447
0.0432 23.39 4000 0.3458 19.5349
0.0378 29.24 5000 0.3485 19.3516

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.2.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.1
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