hubert-test-model

This model is a fine-tuned version of facebook/hubert-base-ls960 on the gtzan dataset. It achieves the following results on the evaluation set:

  • Loss: 1.5276
  • Accuracy: 0.785

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: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Use adamw_torch 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: 20
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 150 2.0494 0.29
No log 2.0 300 2.1993 0.19
No log 3.0 450 1.8439 0.44
1.9218 4.0 600 1.5277 0.48
1.9218 5.0 750 1.4164 0.475
1.9218 6.0 900 1.3641 0.63
1.2685 7.0 1050 1.1557 0.675
1.2685 8.0 1200 1.0935 0.72
1.2685 9.0 1350 1.0594 0.71
0.7151 10.0 1500 1.0119 0.735
0.7151 11.0 1650 1.0868 0.77
0.7151 12.0 1800 1.3736 0.75
0.7151 13.0 1950 1.2705 0.77
0.4135 14.0 2100 1.4052 0.76
0.4135 15.0 2250 1.3864 0.77
0.4135 16.0 2400 1.4296 0.785
0.2311 17.0 2550 1.5663 0.77
0.2311 18.0 2700 1.5310 0.78
0.2311 19.0 2850 1.4884 0.795
0.1408 20.0 3000 1.5276 0.785

Framework versions

  • Transformers 4.46.2
  • Pytorch 2.5.1+cu121
  • Datasets 3.1.0
  • Tokenizers 0.20.3
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Evaluation results