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pawmeow/wav2vec2-bn-checkpoints

sourceHugging Faceapache-2.0updated 10mo agoView on Hugging Face
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wav2vec2-bn-checkpoints

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 3.9099
  • Norm Lev Sim Mean: 0.0187
  • Wer: 1.0
  • Cer: 0.9812

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: 5e-05
  • trainbatchsize: 8
  • evalbatchsize: 8
  • seed: 42
  • gradientaccumulationsteps: 4
  • totaltrainbatch_size: 32
  • optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • lrschedulertype: cosine
  • lrschedulerwarmup_steps: 500
  • num_epochs: 15
  • mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepCerDecode ModeValidation LossNorm Lev Sim MeanWer
20.18271.0950.9775greedy26.99400.02301.0
18.57242.01901.0594greedy25.89650.02611.0
18.90313.02850.9740greedy23.99790.02651.0
14.64754.03800.9683greedy21.13890.03231.0
14.34934.997347017.54310.03211.00.9682
11.60666.056512.52540.02801.00.9725
7.51147.06608.12570.02541.00.9749
5.86018.07555.33550.02191.00.9780
4.33019.08504.21740.01871.00.9812
4.128810.09453.92230.01911.00.9808
3.741611.010403.90990.01881.00.9812
4.071212.011353.90990.01811.00.9818
3.730113.012303.90990.01851.00.9814
4.060514.013253.90980.01871.00.9812
4.170214.901914103.90990.01871.00.9812

Framework versions

  • Transformers 4.48.3
  • Pytorch 2.6.0+cu124
  • Datasets 3.6.0
  • Tokenizers 0.21.2