Downloads · 30 days
5
1% of all-time downloads
distilhubert-finetuned-gtzan
magus4450/distilhubert-finetuned-gtzan
distilhubert-finetuned-gtzan is a audio classification model from magus4450. 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. --
All-time downloads
348
Public
Parameters
23.7M
2.8 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors94.8 MB · 100%
At a glance
- Task
- Audio Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- hubert
- Access
- Public
- Created
- Jan 8, 2024
- Updated
- Jan 29, 2024
- SHA
- 47960650
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: 0.9299
- Accuracy: 0.835
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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 |
|---|---|---|---|---|
| 2.1474 | 1.0 | 100 | 2.1098 | 0.47 |
| 1.5063 | 2.0 | 200 | 1.5695 | 0.575 |
| 1.2171 | 3.0 | 300 | 1.1629 | 0.685 |
| 0.9388 | 4.0 | 400 | 0.9617 | 0.7 |
| 0.6208 | 5.0 | 500 | 0.9273 | 0.685 |
| 0.6771 | 6.0 | 600 | 0.7753 | 0.785 |
| 0.5799 | 7.0 | 700 | 0.8492 | 0.695 |
| 0.1527 | 8.0 | 800 | 0.6581 | 0.805 |
| 0.0586 | 9.0 | 900 | 0.6788 | 0.82 |
| 0.0355 | 10.0 | 1000 | 0.7627 | 0.81 |
| 0.0186 | 11.0 | 1100 | 0.7585 | 0.82 |
| 0.0102 | 12.0 | 1200 | 0.8328 | 0.825 |
| 0.0074 | 13.0 | 1300 | 0.8543 | 0.835 |
| 0.0063 | 14.0 | 1400 | 0.8574 | 0.83 |
| 0.0271 | 15.0 | 1500 | 0.8889 | 0.835 |
| 0.0043 | 16.0 | 1600 | 0.9197 | 0.83 |
| 0.0045 | 17.0 | 1700 | 0.9130 | 0.835 |
| 0.0036 | 18.0 | 1800 | 0.9242 | 0.835 |
| 0.0042 | 19.0 | 1900 | 0.9279 | 0.835 |
| 0.0034 | 20.0 | 2000 | 0.9299 | 0.835 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.14.7
- Tokenizers 0.15.0
- Task
- Audio Classification
- Library
- transformers
- Type
- hubert
- License
- apache-2.0
- Created
- Jan 8, 2024
- Updated
- Jan 29, 2024