smallsuper / distilhubert-finetuned-gtzan

huggingface.co
Total runs: 22
24-hour runs: 0
7-day runs: -35
30-day runs: -21
Model's Last Updated: December 02 2025
audio-classification

Introduction of distilhubert-finetuned-gtzan

Model Details of distilhubert-finetuned-gtzan

distilhubert-finetuned-gtzan

This model is a fine-tuned version of ntu-spml/distilhubert on the GTZAN dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6457
  • Accuracy: 0.82
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
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 10
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss Accuracy
1.9241 1.0 113 1.8301 0.51
1.1746 2.0 226 1.3230 0.62
1.0832 3.0 339 1.0935 0.72
0.686 4.0 452 0.8558 0.74
0.5173 5.0 565 0.7105 0.78
0.4431 6.0 678 0.6421 0.81
0.2764 7.0 791 0.6727 0.8
0.1549 8.0 904 0.6605 0.84
0.1832 9.0 1017 0.6764 0.82
0.1056 10.0 1130 0.6457 0.82
Framework versions
  • Transformers 4.57.2
  • Pytorch 2.9.0+cu126
  • Datasets 3.6.0
  • Tokenizers 0.22.1

Runs of smallsuper distilhubert-finetuned-gtzan on huggingface.co

22
Total runs
0
24-hour runs
-2
3-day runs
-35
7-day runs
-21
30-day runs

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