Downloads · 30 days
47
3% of all-time downloads
distilhubert-finetuned-gtzan
sfedar/distilhubert-finetuned-gtzan
distilhubert-finetuned-gtzan is a audio classification model from sfedar. Use it for the audio classification task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
All-time downloads
1.7K
Public
Parameters
23.7M
46 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors94.8 MB · 98%
At a glance
- Task
- Audio Classification
- License
- apache-2.0
- Model type
- hubert
- Access
- Public
- Created
- Sep 4, 2024
- Updated
- Sep 29, 2024
- SHA
- 4f9aa259
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: 1.2162
- Accuracy: 0.84
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: 6e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.2216 | 1.0 | 57 | 2.1520 | 0.45 |
| 1.704 | 2.0 | 114 | 1.6254 | 0.59 |
| 1.1885 | 3.0 | 171 | 1.1741 | 0.7 |
| 0.8575 | 4.0 | 228 | 0.9653 | 0.7 |
| 0.6822 | 5.0 | 285 | 0.8219 | 0.81 |
| 0.5103 | 6.0 | 342 | 0.7254 | 0.8 |
| 0.4386 | 7.0 | 399 | 0.6772 | 0.84 |
| 0.2862 | 8.0 | 456 | 0.7047 | 0.8 |
| 0.1639 | 9.0 | 513 | 0.7126 | 0.8 |
| 0.0998 | 10.0 | 570 | 0.8339 | 0.77 |
| 0.0585 | 11.0 | 627 | 0.7380 | 0.8 |
| 0.0256 | 12.0 | 684 | 0.7606 | 0.84 |
| 0.0201 | 13.0 | 741 | 0.8292 | 0.83 |
| 0.0058 | 14.0 | 798 | 0.9495 | 0.83 |
| 0.0029 | 15.0 | 855 | 1.1009 | 0.82 |
| 0.0016 | 16.0 | 912 | 1.1451 | 0.82 |
| 0.001 | 17.0 | 969 | 1.1886 | 0.84 |
| 0.0071 | 18.0 | 1026 | 1.1731 | 0.84 |
| 0.0004 | 19.0 | 1083 | 1.2255 | 0.84 |
| 0.0003 | 20.0 | 1140 | 1.2162 | 0.84 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.19.1
- Task
- Audio Classification
- Type
- hubert
- License
- apache-2.0
- Created
- Sep 4, 2024
- Updated
- Sep 29, 2024