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metadata
license: apache-2.0
tags:
  - music
  - genre
  - classification
datasets:
  - marsyas/gtzan
metrics:
  - accuracy
model-index:
  - name: distilhubert-finetuned-gtzan_accuracy_93
    results: []
language:
  - en

distilhubert-finetuned-gtzan_accuracy_93

This model is a fine-tuned version of yuval6967/distilhubert-finetuned-gtzan on the GTZAN dataset.

It achieves the following results on the evaluation set:

  • Loss: 0.5121
  • Accuracy: 0.93

Model description

Intended uses & limitations

  • Model is built to identify the genre of music based on a ~30 sec clip

Training and evaluation data

More information needed

Training procedure

  • test_size = 0.20 was used for the split

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
0.0316 1.0 100 0.4338 0.895
0.0031 2.0 200 0.7039 0.86
0.0069 3.0 300 0.4526 0.925
0.1799 4.0 400 0.7071 0.88
0.1783 5.0 500 0.5923 0.92
0.0011 6.0 600 0.5498 0.92
0.0005 7.0 700 0.4927 0.925
0.0005 8.0 800 0.6172 0.915
0.0004 9.0 900 0.4988 0.925
0.0004 10.0 1000 0.5121 0.93

Framework versions

  • Transformers 4.30.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.13.1
  • Tokenizers 0.13.3