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Whisper Medium Basque

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

  • Loss: 0.4119
  • Wer: 14.1196

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: 10000

Training results

Training Loss Epoch Step Validation Loss Wer
0.0206 4.02 1000 0.2998 16.9995
0.0036 9.01 2000 0.3235 15.5211
0.0018 14.01 3000 0.3454 14.9905
0.0013 19.01 4000 0.3538 14.9439
0.0013 24.01 5000 0.3587 14.8568
0.0002 29.0 6000 0.3799 14.4153
0.0001 33.02 7000 0.3937 14.2067
0.0001 38.02 8000 0.4050 14.1946
0.0001 43.01 9000 0.4119 14.1196
0.0001 48.01 10000 0.4150 14.1358

Framework versions

  • Transformers 4.33.0.dev0
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.4
  • Tokenizers 0.13.3
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