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genre-recognizer-finetuned-gtzan_dset

Audio Classification Transformers PyTorch
hubert generated_from_trainer Eval Results License: apache-2.0
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music-genre-detector-finetuned-gtzan_dset

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: 0.3892
  • Accuracy: 0.8972
  • Precision: 0.8989
  • Recall: 0.8972
  • F1: 0.8974

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: 9e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 7

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
2.2319 0.98 49 1.5808 0.5263 0.5682 0.5263 0.4767
1.2682 1.98 99 0.9750 0.7556 0.7524 0.7556 0.7510
0.9462 2.99 149 0.7403 0.7945 0.7964 0.7945 0.7921
0.5946 3.99 199 0.5921 0.8233 0.8281 0.8233 0.8214
0.4095 4.99 249 0.4772 0.8634 0.8663 0.8634 0.8638
0.3349 5.99 299 0.4167 0.8835 0.8866 0.8835 0.8841
0.2427 6.88 343 0.3892 0.8972 0.8989 0.8972 0.8974

Framework versions

  • Transformers 4.33.1
  • Pytorch 1.10.2+cu111
  • Datasets 2.14.5
  • Tokenizers 0.13.3
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Evaluation results

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