Bolakubus / distilhubert-finetuned-gtzan

huggingface.co
Total runs: 161
24-hour runs: 0
7-day runs: 158
30-day runs: 153
Model's Last Updated: September 11 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: 0.6073
  • Accuracy: 0.84
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
Training results
Training Loss Epoch Step Validation Loss Accuracy
1.9996 1.0 113 1.7954 0.57
1.3157 2.0 226 1.2129 0.67
0.9375 3.0 339 0.9223 0.76
0.817 4.0 452 0.8372 0.73
0.5425 5.0 565 0.7206 0.74
0.4381 6.0 678 0.6317 0.78
0.5359 7.0 791 0.5468 0.84
0.2037 8.0 904 0.5492 0.84
0.3028 9.0 1017 0.5550 0.8
0.1674 10.0 1130 0.6073 0.84
Framework versions
  • Transformers 4.34.0.dev0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3

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

161
Total runs
0
24-hour runs
0
3-day runs
158
7-day runs
153
30-day runs

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