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bola23/bert_audio_classification

sourceHugging Faceapache-2.0updated 1y agoView on Hugging Face
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Model Card

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bertaudioclassification

This model is a fine-tuned version of bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0517
  • Accuracy: 0.99
  • F1: 0.99
  • Precision: 0.99
  • Recall: 0.99

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: 2e-05
  • trainbatchsize: 32
  • evalbatchsize: 8
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • lrschedulertype: linear
  • num_epochs: 1

Training results

Training LossEpochStepValidation LossAccuracyF1PrecisionRecall
0.05931.01250.05170.990.990.990.99

Framework versions

  • Transformers 4.52.4
  • Pytorch 2.6.0+cu124
  • Datasets 3.6.0
  • Tokenizers 0.21.2