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subatomicseer/wav2vec2-base-hyperVQ-timit-fine-tuned

sourceHugging Faceupdated 3y agoView on Hugging Face
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wav2vec2-base-hyperVQ-timit-fine-tuned

This model is a fine-tuned version of wav2vec2-pretrained-base-hyperVQ on the TIMIT_ASR - NA dataset. It achieves the following results on the evaluation set:

  • —Loss: 3.3628
  • —Wer: 0.9993

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: 0.0001
  • —trainbatchsize: 32
  • —evalbatchsize: 32
  • —seed: 42
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 1000
  • —num_epochs: 20.0

Training results

Training LossEpochStepValidation LossWer
3.272510.014503.46991.0006
3.168220.029003.36280.9993

Framework versions

  • —Transformers 4.36.2
  • —Pytorch 2.3.0.dev20231229+cu118
  • —Datasets 2.16.0
  • —Tokenizers 0.15.0