whisper-base-google-fleurs-pt-br

This model is a fine-tuned version of openai/whisper-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4987
  • Wer: 22.2974
  • Wer Normalized: 18.5291

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: 2.05e-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: reduce_lr_on_plateau
  • lr_scheduler_warmup_steps: 120
  • training_steps: 2400
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Wer Normalized
0.3716 1.01 400 0.3988 21.8039 17.8916
0.2003 2.02 800 0.4440 22.3350 18.6242
0.0571 3.02 1200 0.4960 22.5982 19.2284
0.03 4.03 1600 0.4987 22.2974 18.5291

Framework versions

  • Transformers 4.36.2
  • Pytorch 2.1.1
  • Datasets 2.16.1
  • Tokenizers 0.15.0
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