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neuronbit/speech-synth-large-finetune

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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speech-synth-large-finetune

This model is a fine-tuned version of openai/whisper-large-v3 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4259
  • Wer: 16.8396

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
  • trainbatchsize: 8
  • evalbatchsize: 8
  • seed: 42
  • gradientaccumulationsteps: 2
  • totaltrainbatch_size: 16
  • optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • lrschedulertype: linear
  • lrschedulerwarmup_steps: 500
  • training_steps: 5000
  • mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossWer
0.13130.78002500.495330.7145
0.05311.55855000.464728.1055
0.02692.33707500.444819.9526
0.01013.115410000.439223.0062
0.00643.895512500.405322.2947
0.00574.673915000.414819.3003
0.00445.452417500.402817.9958
0.00476.230920000.412519.0631
0.0037.009422500.397917.7883
0.00387.789425000.392320.5455
0.08.567927500.407717.6401
0.00029.346330000.405017.3733
0.000910.124832500.410117.0471
0.000510.904835000.422717.1954
0.011.683337500.421717.2250
0.000212.461840000.424117.0471
0.013.240242500.423916.9582
0.000514.018745000.425016.6617
0.014.798847500.425416.8396
0.000115.577250000.425916.8396

Framework versions

  • Transformers 4.47.0
  • Pytorch 2.5.1+cu124
  • Datasets 3.2.0
  • Tokenizers 0.21.0