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distilhubert-finetuned-finetuned-gtzan

This model is a fine-tuned version of weiren119/distilhubert-finetuned-gtzan on the GTZAN dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8658
  • Accuracy: 0.88

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: 0.0001
  • train_batch_size: 16
  • eval_batch_size: 16
  • 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
0.1441 1.0 57 0.5206 0.86
0.0992 2.0 114 0.6685 0.84
0.0881 3.0 171 0.8925 0.76
0.0792 4.0 228 1.0064 0.78
0.0045 5.0 285 0.8283 0.83
0.0695 6.0 342 0.7731 0.86
0.0303 7.0 399 1.0389 0.82
0.0026 8.0 456 0.9661 0.83
0.0014 9.0 513 0.8917 0.87
0.0012 10.0 570 0.8658 0.88

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.0
  • Tokenizers 0.13.3
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Finetuned from

Dataset used to train weiren119/distilhubert-finetuned-finetuned-gtzan

Evaluation results