Downloads · 30 days
13
2% of all-time downloads
distilhubert-finetuned-gtzan
mlubos/distilhubert-finetuned-gtzan
distilhubert-finetuned-gtzan is a audio classification model from mlubos. 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
529
Public
Parameters
23.7M
9.6 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin94.8 MB · 50%
At a glance
- Task
- Audio Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- hubert
- Access
- Public
- Created
- Oct 24, 2023
- Updated
- Jan 17, 2024
- SHA
- d935b0cf
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: 0.7565
- 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.1839 | 1.0 | 113 | 2.0630 | 0.41 |
| 1.5052 | 2.0 | 226 | 1.4029 | 0.57 |
| 1.144 | 3.0 | 339 | 0.9807 | 0.77 |
| 0.9971 | 4.0 | 452 | 0.8701 | 0.75 |
| 0.6168 | 5.0 | 565 | 0.7094 | 0.76 |
| 0.4665 | 6.0 | 678 | 0.5940 | 0.83 |
| 0.58 | 7.0 | 791 | 0.4763 | 0.86 |
| 0.1009 | 8.0 | 904 | 0.4859 | 0.87 |
| 0.1817 | 9.0 | 1017 | 0.5313 | 0.88 |
| 0.0467 | 10.0 | 1130 | 0.6114 | 0.86 |
| 0.0201 | 11.0 | 1243 | 0.6677 | 0.85 |
| 0.1188 | 12.0 | 1356 | 0.6934 | 0.87 |
| 0.0055 | 13.0 | 1469 | 0.7070 | 0.89 |
| 0.0046 | 14.0 | 1582 | 0.7601 | 0.87 |
| 0.0043 | 15.0 | 1695 | 0.7584 | 0.87 |
| 0.0033 | 16.0 | 1808 | 0.7588 | 0.86 |
| 0.0696 | 17.0 | 1921 | 0.7495 | 0.88 |
| 0.0028 | 18.0 | 2034 | 0.7535 | 0.87 |
| 0.0027 | 19.0 | 2147 | 0.7571 | 0.87 |
| 0.0028 | 20.0 | 2260 | 0.7565 | 0.87 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
- Task
- Audio Classification
- Library
- transformers
- Type
- hubert
- License
- apache-2.0
- Created
- Oct 24, 2023
- Updated
- Jan 17, 2024