Downloads · 30 days
8
18% of all-time downloads
distilhubert-finetuned-gtzan
omthkkr/distilhubert-finetuned-gtzan
distilhubert-finetuned-gtzan is a audio classification model from omthkkr. 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
45
Public
Repo size
190 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin94.8 MB · 100%
At a glance
- Task
- Audio Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- hubert
- Access
- Public
- Created
- Sep 5, 2023
- Updated
- Sep 5, 2023
- SHA
- d9b1c95f
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: 0.6547
- Accuracy: 0.87
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.1837 | 1.0 | 113 | 2.0719 | 0.39 |
| 1.5697 | 2.0 | 226 | 1.5216 | 0.56 |
| 1.2341 | 3.0 | 339 | 1.0787 | 0.7 |
| 1.0559 | 4.0 | 452 | 0.9199 | 0.75 |
| 0.7576 | 5.0 | 565 | 0.8469 | 0.75 |
| 0.5683 | 6.0 | 678 | 0.7064 | 0.76 |
| 0.4652 | 7.0 | 791 | 0.5912 | 0.79 |
| 0.1398 | 8.0 | 904 | 0.5407 | 0.81 |
| 0.2012 | 9.0 | 1017 | 0.4836 | 0.87 |
| 0.0445 | 10.0 | 1130 | 0.4839 | 0.88 |
| 0.0145 | 11.0 | 1243 | 0.5439 | 0.88 |
| 0.0519 | 12.0 | 1356 | 0.6309 | 0.85 |
| 0.0068 | 13.0 | 1469 | 0.5626 | 0.88 |
| 0.0054 | 14.0 | 1582 | 0.5949 | 0.88 |
| 0.0054 | 15.0 | 1695 | 0.5889 | 0.88 |
| 0.0033 | 16.0 | 1808 | 0.6233 | 0.89 |
| 0.1396 | 17.0 | 1921 | 0.6340 | 0.88 |
| 0.0029 | 18.0 | 2034 | 0.6362 | 0.88 |
| 0.0026 | 19.0 | 2147 | 0.6441 | 0.88 |
| 0.0027 | 20.0 | 2260 | 0.6547 | 0.87 |
Framework versions
- Transformers 4.33.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
- Task
- Audio Classification
- Library
- transformers
- Type
- hubert
- License
- apache-2.0
- Created
- Sep 5, 2023
- Updated
- Sep 5, 2023