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bASILgIL/wav2vec2-large-960h-gs-xs-10epochs

sourceHugging Faceapache-2.0updated 1y agoView on Hugging Face
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wav2vec2-large-960h-gs-xs-10epochs

This model is a fine-tuned version of facebook/wav2vec2-large-960h on the gigaspeech dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.7753
  • —Wer: 0.2816

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: 1
  • —evalbatchsize: 1
  • —seed: 42
  • —gradientaccumulationsteps: 8
  • —totaltrainbatch_size: 8
  • —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 200
  • —num_epochs: 10
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossWer
0.61091.011740.87810.3144
0.53522.023480.77410.2966
0.48233.035220.78200.2921
0.4624.046960.80120.2871
0.41715.058700.77140.2881
0.41546.070440.79290.2854
0.41267.082180.77680.2855
0.38648.093920.77210.2831
0.37799.0105660.76860.2818
0.37669.9918117300.77530.2816

Framework versions

  • —Transformers 4.50.3
  • —Pytorch 2.6.0+cu124
  • —Datasets 3.5.0
  • —Tokenizers 0.21.1