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distilhubert-finetuned-gtzan

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

  • Loss: 0.7322
  • Accuracy: 0.905

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
0.0002 1.0 100 0.5783 0.915
0.1984 2.0 200 0.7051 0.91
0.0518 3.0 300 1.0287 0.865
0.0039 4.0 400 0.7660 0.895
0.0001 5.0 500 0.7513 0.91
0.0001 6.0 600 0.7757 0.9
0.0002 7.0 700 0.9340 0.87
0.0001 8.0 800 0.7237 0.9
0.0001 9.0 900 0.7298 0.905
0.0001 10.0 1000 0.7322 0.905

Framework versions

  • Transformers 4.31.0.dev0
  • Pytorch 2.0.1+cu117
  • Datasets 2.13.1
  • Tokenizers 0.13.3
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Dataset used to train NemesisAlm/distilhubert-finetuned-gtzan

Evaluation results