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wav2vec 2.0 XLSR-53 Model

This is the wav2vec 2.0 XLSR-53 model fine-tuned on the Common Voice 8.0 datasets for Bahasa Indonesia using the train, validation, and other splits (~32.000 sound samples). This model was used for research purposes to complete my Undergraduate Thesis.


  1. Removal of symbols from transcript
  2. Convert numbers (0, 1, ..., 9) to word forms (satu, dua, ..., sembilan)
  3. Convert all characters to lowercase
  4. Resample the audio data to 16kHz.
  5. Uses data collator from this example

Hyperparameters used

  • Learning rate = 1e-4
  • Maximum Epochs = 30
  • Batch size = 4 (limitations of compute resource)
  • Early stopping = Stop when WER doesn't improve for 2 validations
  • Other parameters use the defaults from this config


The results are an average of 5 runs using the test split from the Common Voice datasets for Bahasa Indonesia.

Test Result: 15,6% WER


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Dataset used to train m-salman-a/wav2vec2-xlsr-53-common-voice-indonesian