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rossevine/Model_G_2

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face
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Model Card

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ModelG2

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the common_voice dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3710
  • Wer: 0.2513
  • Cer: 0.0631

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: 0.0003
  • trainbatchsize: 16
  • evalbatchsize: 8
  • seed: 42
  • gradientaccumulationsteps: 2
  • totaltrainbatch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • lrschedulerwarmup_steps: 500
  • num_epochs: 30

Training results

Training LossEpochStepValidation LossWerCer
3.74843.234000.57060.56980.1477
0.34196.458000.41200.37580.0924
0.17969.6812000.36910.32950.0843
0.12512.916000.38210.30970.0782
0.098416.1320000.40850.29470.0742
0.082719.3524000.38590.27810.0711
0.066622.5828000.38130.26630.0684
0.055825.8132000.36810.25450.0644
0.046629.0336000.37100.25130.0631

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu117
  • Datasets 1.18.3
  • Tokenizers 0.13.3