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Common Voice 16 - Guarani

This model is a fine-tuned version of openai/whisper-base on the Common Voice 16 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4522
  • Wer: 53.9363

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: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_steps: 3000
  • training_steps: 3000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
2.9797 0.4955 500 1.0523 91.7365
1.1502 0.9911 1000 0.6757 87.2138
0.717 1.4866 1500 0.5718 63.4841
0.5485 1.9822 2000 0.5059 58.3473
0.3345 2.4777 2500 0.4828 56.7281
0.2748 2.9732 3000 0.4522 53.9363

Framework versions

  • Transformers 4.44.0
  • Pytorch 2.3.1+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1
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