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phi0108/audio_classification

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

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audio_classification

This model is a fine-tuned version of facebook/wav2vec2-base on the minds14 dataset. It achieves the following results on the evaluation set:

  • Loss: 2.6385
  • Accuracy: 0.0708

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: 3e-05
  • trainbatchsize: 32
  • evalbatchsize: 32
  • seed: 42
  • gradientaccumulationsteps: 4
  • totaltrainbatch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • lrschedulerwarmup_ratio: 0.1
  • num_epochs: 10

Training results

Training LossEpochStepValidation LossAccuracy
No log0.832.64400.0442
No log1.8772.65660.0531
2.64062.93112.65270.0354
2.64064.0152.65330.0619
2.64064.8182.65030.0796
2.64125.87222.64020.0885
2.64126.93262.63940.0619
2.63898.0302.63850.0708

Framework versions

  • Transformers 4.27.4
  • Pytorch 2.0.0
  • Datasets 2.11.0
  • Tokenizers 0.13.3