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Whisper Small EN - erenozaltun-common1

This model is a fine-tuned version of openai/whisper-small on the Common Voice 1.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3868
  • Wer: 21.9771

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: 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: 2000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.1749 0.6588 500 0.3715 21.4957
0.0885 1.3175 1000 0.3665 21.5340
0.0905 1.9763 1500 0.3668 21.8322
0.0387 2.6350 2000 0.3868 21.9771

Framework versions

  • Transformers 4.42.3
  • Pytorch 2.1.2+cu121
  • Datasets 2.18.0
  • Tokenizers 0.19.1
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Dataset used to train erenozaltun/whisper-small-en-common1

Evaluation results