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Whisper small using Common Voice 16 (pt)

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

  • Loss: 0.2220
  • Wer: 16.0359
  • Wer Normalized: 10.3867

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: 5e-06
  • 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: 500
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Wer Normalized
0.2484 0.26 500 0.2712 19.2259 13.0929
0.2184 0.52 1000 0.2464 17.8895 11.9404
0.236 0.77 1500 0.2339 17.1348 11.3016
0.1401 1.03 2000 0.2285 16.7001 11.0432
0.1206 1.29 2500 0.2251 16.3235 10.6467
0.1199 1.55 3000 0.2236 16.1732 10.5424
0.1231 1.81 3500 0.2197 16.1587 10.5038
0.0935 2.06 4000 0.2220 16.0359 10.3867

Framework versions

  • Transformers 4.36.2
  • Pytorch 2.1.2
  • Datasets 2.16.1
  • Tokenizers 0.15.1
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Safetensors
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Finetuned from

Dataset used to train thiagobarbosa/whisper-small-common-voice-16-pt-v2

Evaluation results