Whisper Base Portuguese

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

  • Loss: 0.3815
  • Wer: 19.2899

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-06
  • train_batch_size: 128
  • eval_batch_size: 64
  • 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
0.3261 7.04 1000 0.4097 20.6766
0.2632 14.08 2000 0.3884 19.5101
0.2241 21.13 3000 0.3827 19.4690
0.2048 28.17 4000 0.3815 19.2899
0.1956 35.21 5000 0.3815 19.4033

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.4
  • Tokenizers 0.15.1
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Dataset used to train zuazo/whisper-base-pt

Evaluation results