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distilhubert-finetuned-gtzan
sanyam3/distilhubert-finetuned-gtzan
distilhubert-finetuned-gtzan is a audio classification model from sanyam3. 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
- Jan 26, 2026
- Updated
- Jan 26, 2026
- SHA
- 1b41dd20
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: 0.80
- Accuracy: 0.89
- Macro F1: 0.8957
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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 |
|---|---|---|---|---|---|
| 2.2641 | 1.0 | 450 | 2.2228 | 0.45 | 0.3545 |
| 1.8857 | 2.0 | 900 | 1.8527 | 0.56 | 0.4640 |
| 1.6008 | 3.0 | 1350 | 1.4108 | 0.68 | 0.6543 |
| 1.1742 | 4.0 | 1800 | 1.1191 | 0.72 | 0.6910 |
| 0.9257 | 5.0 | 2250 | 0.8738 | 0.81 | 0.8026 |
| 0.7766 | 6.0 | 2700 | 0.6843 | 0.82 | 0.8216 |
| 0.4557 | 7.0 | 3150 | 0.6263 | 0.82 | 0.8170 |
| 0.3278 | 8.0 | 3600 | 0.5555 | 0.84 | 0.8285 |
| 0.3262 | 9.0 | 4050 | 0.5471 | 0.87 | 0.8641 |
| 0.2547 | 10.0 | 4500 | 0.7685 | 0.81 | 0.8043 |
| 0.2713 | 11.0 | 4950 | 0.6107 | 0.89 | 0.8782 |
| 0.1555 | 12.0 | 5400 | 0.6796 | 0.88 | 0.8767 |
| 0.1983 | 13.0 | 5850 | 0.8251 | 0.86 | 0.8466 |
| 0.1146 | 14.0 | 6300 | 0.8332 | 0.85 | 0.8341 |
| 0.1164 | 15.0 | 6750 | 0.8060 | 0.89 | 0.8957 |
| 0.0103 | 16.0 | 7200 | 1.1965 | 0.84 | 0.8345 |
| 0.0247 | 17.0 | 7650 | 1.1232 | 0.86 | 0.8539 |
| 0.0037 | 18.0 | 8100 | 1.0172 | 0.87 | 0.8665 |
| 0.0021 | 19.0 | 8550 | 0.9868 | 0.88 | 0.8734 |
| 0.0594 | 20.0 | 9000 | 1.4043 | 0.86 | 0.8591 |
Framework versions
- Transformers 4.53.3
- Pytorch 2.9.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1
- Task
- Audio Classification
- Library
- transformers
- Type
- hubert
- License
- apache-2.0
- Created
- Jan 26, 2026
- Updated
- Jan 26, 2026