Whisper Base Basque

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

  • Loss: 0.5071
  • Wer: 26.5933

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: 2.5e-05
  • train_batch_size: 128
  • eval_batch_size: 64
  • 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
0.3263 11.63 1000 0.5019 33.1701
0.1194 23.26 2000 0.4647 28.2859
0.0576 34.88 3000 0.4863 27.2401
0.0337 46.51 4000 0.5028 26.6135
0.0276 58.14 5000 0.5071 26.5933

Framework versions

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