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distilhubert-finetuned-gtzan
ParitKansal/distilhubert-finetuned-gtzan
distilhubert-finetuned-gtzan is a audio classification model from ParitKansal. Use it for the audio classification task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Audio Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- hubert
- Access
- Public
- Created
- Jun 18, 2025
- Updated
- Jun 21, 2025
- SHA
- 268701af
Base models
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
distilhubert-finetuned-gtzan
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: 0.4772
- 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.1579 | 1.0 | 113 | 2.0599 | 0.49 |
| 1.414 | 2.0 | 226 | 1.4245 | 0.66 |
| 1.1784 | 3.0 | 339 | 1.1034 | 0.65 |
| 0.7209 | 4.0 | 452 | 0.7965 | 0.78 |
| 0.5967 | 5.0 | 565 | 0.7356 | 0.78 |
| 0.3644 | 6.0 | 678 | 0.5675 | 0.82 |
| 0.2092 | 7.0 | 791 | 0.5001 | 0.86 |
| 0.0647 | 8.0 | 904 | 0.6535 | 0.83 |
| 0.1354 | 9.0 | 1017 | 0.4772 | 0.88 |
| 0.0525 | 10.0 | 1130 | 0.6393 | 0.86 |
| 0.0127 | 11.0 | 1243 | 0.6587 | 0.87 |
| 0.0059 | 12.0 | 1356 | 0.6669 | 0.84 |
| 0.0052 | 13.0 | 1469 | 0.6354 | 0.86 |
| 0.0044 | 14.0 | 1582 | 0.7918 | 0.82 |
| 0.0035 | 15.0 | 1695 | 0.7577 | 0.83 |
| 0.0035 | 16.0 | 1808 | 0.7344 | 0.82 |
| 0.0033 | 17.0 | 1921 | 0.7079 | 0.84 |
| 0.0031 | 18.0 | 2034 | 0.7367 | 0.84 |
| 0.0032 | 19.0 | 2147 | 0.7150 | 0.84 |
| 0.0034 | 20.0 | 2260 | 0.7144 | 0.84 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
- Task
- Audio Classification
- Library
- transformers
- Type
- hubert
- License
- apache-2.0
- Created
- Jun 18, 2025
- Updated
- Jun 21, 2025