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Whisper Tiny PT

This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6077
  • Wer: 29.9844

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-05
  • train_batch_size: 64
  • 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
0.4143 1.04 500 0.5325 32.7399
0.2693 3.03 1000 0.4718 29.4867
0.1724 5.01 1500 0.4758 28.7218
0.0849 7.0 2000 0.5070 29.2211
0.0659 8.04 2500 0.5223 29.3169
0.0539 10.03 3000 0.5402 30.1458
0.0376 12.02 3500 0.5755 29.9995
0.0217 14.0 4000 0.6067 29.6565
0.0168 15.04 4500 0.6082 29.8162
0.0205 17.03 5000 0.6077 29.9844

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0+cu116
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2
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Dataset used to train dominguesm/whisper-tiny-pt

Evaluation results