mahdafr / distilhubert-finetuned-gtzan

huggingface.co
Total runs: 164
24-hour runs: 1
7-day runs: 3
30-day runs: 159
Model's Last Updated: Tháng bảy 29 2023
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: 0.4759
  • Accuracy: 0.87
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: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 10
Training results
Training Loss Epoch Step Validation Loss Accuracy
1.5864 1.0 112 1.4484 0.53
1.1517 2.0 225 1.0442 0.66
0.9177 3.0 337 0.8256 0.76
0.6564 4.0 450 0.6099 0.84
0.5938 5.0 562 0.6822 0.78
0.2182 6.0 675 0.5630 0.81
0.3178 7.0 787 0.4598 0.85
0.1181 8.0 900 0.4580 0.86
0.0377 9.0 1012 0.4716 0.88
0.034 9.96 1120 0.4759 0.87
Framework versions
  • Transformers 4.32.0.dev0
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.0
  • Tokenizers 0.13.3

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

164
Total runs
1
24-hour runs
2
3-day runs
3
7-day runs
159
30-day runs

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