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preszzz/drone-audio-detection-05-17-trial-1

sourceHugging Facebsd-3-clauseupdated 1y agoView on Hugging Face
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Model Card

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drone-audio-detection-05-17-trial-1

This model is a fine-tuned version of MIT/ast-finetuned-audioset-10-10-0.4593 on an unknown dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.0601
  • —Accuracy: 0.9885
  • —Precision: 0.9949
  • —Recall: 0.9904
  • —F1: 0.9926

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: 0.000306026755687659
  • —trainbatchsize: 16
  • —evalbatchsize: 8
  • —seed: 42
  • —gradientaccumulationsteps: 4
  • —totaltrainbatch_size: 64
  • —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: polynomial
  • —lrschedulerwarmup_ratio: 0.04976531124812043
  • —num_epochs: 5
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossAccuracyPrecisionRecallF1
0.08061.01250.09230.96550.96920.98720.9781
0.07332.02500.05670.9820.99350.98340.9884
0.04183.03750.03960.98550.99290.98850.9907
0.02494.05000.05760.9830.98480.99360.9892
0.01095.06250.06010.98850.99490.99040.9926

Framework versions

  • —Transformers 4.51.3
  • —Pytorch 2.6.0+cu124
  • —Datasets 3.6.0
  • —Tokenizers 0.21.1