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distilhubert-finetuned-gtzan

This model is a fine-tuned version of MariaK/distilhubert-finetuned-gtzan-v2 on the GTZAN dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4905
  • Accuracy: 0.89

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: 0.01

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.0742 0.02 2 0.4905 0.89

Framework versions

  • Transformers 4.30.2
  • Pytorch 2.0.1+cu117
  • Datasets 2.13.1
  • Tokenizers 0.13.3
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Dataset used to train mcamara/distilhubert-finetuned-gtzan