Makerathian / distilhubert-finetuned-gtzan

huggingface.co
Total runs: 160
24-hour runs: 0
7-day runs: 159
30-day runs: 154
Model's Last Updated: 2023年8月21日
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: 0.5630
  • Accuracy: 0.85
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • 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
1.7667 1.0 113 1.8361 0.38
1.285 2.0 226 1.3397 0.58
1.109 3.0 339 1.0122 0.71
0.6605 4.0 452 0.7638 0.83
0.4847 5.0 565 0.6630 0.8
0.3533 6.0 678 0.5960 0.83
0.2344 7.0 791 0.5696 0.83
0.3147 8.0 904 0.5391 0.87
0.1588 9.0 1017 0.5477 0.88
0.1341 10.0 1130 0.5630 0.85
Framework versions
  • Transformers 4.28.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3

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

160
Total runs
0
24-hour runs
1
3-day runs
159
7-day runs
154
30-day runs

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