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transfer-learning-finetuned-gtzan-model
balamaniansp/transfer-learning-finetuned-gtzan-model
transfer-learning-finetuned-gtzan-model is a audio classification model from balamaniansp. 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
- Mar 28, 2026
- Updated
- Mar 28, 2026
- SHA
- dc4a3200
Base models
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. -->
transfer-learning-finetuned-gtzan-model
This model is a fine-tuned version of sanchit-gandhi/distilhubert-finetuned-gtzan on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3704
- Accuracy: 0.5565
- F1: 0.5318
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 15
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.05
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.9103 | 0.4735 | 500 | 1.9692 | 0.2823 | 0.2697 |
| 1.6753 | 0.9470 | 1000 | 1.7129 | 0.3992 | 0.3692 |
| 1.4613 | 1.4205 | 1500 | 1.6354 | 0.4240 | 0.3987 |
| 1.4226 | 1.8939 | 2000 | 1.5426 | 0.4504 | 0.4267 |
| 1.3909 | 2.3674 | 2500 | 1.5176 | 0.4702 | 0.4423 |
| 1.3919 | 2.8409 | 3000 | 1.4944 | 0.4855 | 0.4584 |
| 1.2577 | 3.3144 | 3500 | 1.4466 | 0.4955 | 0.4710 |
| 1.2455 | 3.7879 | 4000 | 1.4501 | 0.5050 | 0.4833 |
| 1.1261 | 4.2614 | 4500 | 1.4460 | 0.4945 | 0.4757 |
| 1.1117 | 4.7348 | 5000 | 1.4453 | 0.5087 | 0.4812 |
| 1.0591 | 5.2083 | 5500 | 1.4648 | 0.5032 | 0.4738 |
| 1.079 | 5.6818 | 6000 | 1.3912 | 0.5288 | 0.4998 |
| 1.0071 | 6.1553 | 6500 | 1.3956 | 0.5285 | 0.5012 |
| 0.976 | 6.6288 | 7000 | 1.4003 | 0.5309 | 0.5049 |
| 0.9517 | 7.1023 | 7500 | 1.4035 | 0.5343 | 0.5079 |
| 0.9873 | 7.5758 | 8000 | 1.3696 | 0.5383 | 0.5140 |
| 0.8671 | 8.0492 | 8500 | 1.3814 | 0.5446 | 0.5217 |
| 0.8546 | 8.5227 | 9000 | 1.3788 | 0.5446 | 0.5173 |
| 0.9945 | 8.9962 | 9500 | 1.3796 | 0.5454 | 0.5229 |
| 0.857 | 9.4697 | 10000 | 1.3667 | 0.5530 | 0.5293 |
| 0.8703 | 9.9432 | 10500 | 1.3439 | 0.5536 | 0.5292 |
| 0.8018 | 10.4167 | 11000 | 1.3654 | 0.5554 | 0.5296 |
| 0.8333 | 10.8902 | 11500 | 1.3696 | 0.5491 | 0.5235 |
| 0.8282 | 11.3636 | 12000 | 1.3825 | 0.5512 | 0.5245 |
| 0.7193 | 11.8371 | 12500 | 1.3758 | 0.5554 | 0.5296 |
| 0.7366 | 12.3106 | 13000 | 1.3582 | 0.5594 | 0.5326 |
| 0.792 | 12.7841 | 13500 | 1.3829 | 0.5512 | 0.5262 |
| 0.7758 | 13.2576 | 14000 | 1.3684 | 0.5588 | 0.5340 |
| 0.8631 | 13.7311 | 14500 | 1.3663 | 0.5580 | 0.5325 |
| 0.8261 | 14.2045 | 15000 | 1.3752 | 0.5562 | 0.5310 |
| 0.7624 | 14.6780 | 15500 | 1.3704 | 0.5565 | 0.5318 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.4.2
- Tokenizers 0.22.1
- Task
- Audio Classification
- Library
- transformers
- Type
- hubert
- License
- apache-2.0
- Created
- Mar 28, 2026
- Updated
- Mar 28, 2026