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whisper-small-npsc

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

  • Loss: 0.2028
  • Wer: 12.9254

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: 6000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.3922 0.18 500 0.3975 24.2055
0.2893 0.36 1000 0.3139 20.1507
0.2471 0.54 1500 0.2733 17.4449
0.2159 0.72 2000 0.2488 16.2681
0.2195 0.89 2500 0.2304 15.0577
0.1178 1.07 3000 0.2245 14.5968
0.1099 1.25 3500 0.2183 14.1118
0.1059 1.43 4000 0.2136 13.7914
0.1156 1.61 4500 0.2072 13.7491
0.1025 1.79 5000 0.2034 13.1515
0.1123 1.97 5500 0.2006 13.0284
0.0734 2.15 6000 0.2028 12.9254

Framework versions

  • Transformers 4.25.0.dev0
  • Pytorch 1.12.1+cu113
  • Datasets 2.6.1
  • Tokenizers 0.13.1
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Dataset used to train pere/whisper-small-npsc

Evaluation results