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Whisper Base using Common Voice 16 (pt)

This model is a fine-tuned version of openai/whisper-base on the Mozilla Common Voices - 16.0 - Portuguese dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3552
  • Wer: 25.4363
  • Wer Normalized: 19.4668

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: 2e-05
  • train_batch_size: 16
  • 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: 400
  • training_steps: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Wer Normalized
0.6085 0.19 500 0.4465 32.1833 25.3383
0.4624 0.37 1000 0.4131 28.9867 22.8488
0.4375 0.56 1500 0.3936 27.8135 21.3817
0.4372 0.74 2000 0.3784 27.5695 21.7171
0.4704 0.93 2500 0.3630 26.1167 20.5133
0.2013 1.11 3000 0.3600 25.5462 19.7750
0.2261 1.3 3500 0.3570 25.5010 19.5181
0.2118 1.48 4000 0.3552 25.4363 19.4668

Framework versions

  • Transformers 4.36.2
  • Pytorch 2.1.1
  • Datasets 2.16.1
  • Tokenizers 0.15.0
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Dataset used to train thiagobarbosa/whisper-base-common-voice-16-pt-v6

Evaluation results