Downloads · 30 days
8
10% of all-time downloads
hubert-large-ls960-ft-finetuned-gtzan
ORromu/hubert-large-ls960-ft-finetuned-gtzan
hubert-large-ls960-ft-finetuned-gtzan is a audio classification model from ORromu. 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
80
Public
Parameters
316M
29 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors1.3 GB · 100%
At a glance
- Task
- Audio Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- hubert
- Access
- Public
- Created
- Mar 10, 2025
- Updated
- Mar 12, 2025
- SHA
- a6d4ec60
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. -->
hubert-large-ls960-ft-finetuned-gtzan
This model is a fine-tuned version of facebook/hubert-large-ls960-ft on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 1.4835
- Accuracy: 0.76
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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 |
|---|---|---|---|---|
| 2.2311 | 1.0 | 100 | 2.2236 | 0.24 |
| 1.9497 | 2.0 | 200 | 1.7922 | 0.375 |
| 1.4897 | 3.0 | 300 | 1.5512 | 0.4 |
| 1.3977 | 4.0 | 400 | 1.5379 | 0.455 |
| 1.0858 | 5.0 | 500 | 1.4778 | 0.535 |
| 1.3193 | 6.0 | 600 | 1.1541 | 0.59 |
| 0.9246 | 7.0 | 700 | 1.3068 | 0.595 |
| 0.8115 | 8.0 | 800 | 1.0093 | 0.67 |
| 0.7293 | 9.0 | 900 | 1.1365 | 0.67 |
| 0.7645 | 10.0 | 1000 | 1.0879 | 0.69 |
| 0.6447 | 11.0 | 1100 | 1.1747 | 0.69 |
| 0.2322 | 12.0 | 1200 | 1.0627 | 0.73 |
| 0.2428 | 13.0 | 1300 | 0.9681 | 0.765 |
| 0.2777 | 14.0 | 1400 | 1.3665 | 0.72 |
| 0.2792 | 15.0 | 1500 | 1.3216 | 0.73 |
| 0.2509 | 16.0 | 1600 | 1.2809 | 0.755 |
| 0.7852 | 17.0 | 1700 | 1.3793 | 0.77 |
| 0.3948 | 18.0 | 1800 | 1.4736 | 0.765 |
| 0.3591 | 19.0 | 1900 | 1.5412 | 0.76 |
| 0.0059 | 20.0 | 2000 | 1.4835 | 0.76 |
Framework versions
- Transformers 4.50.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0
- Task
- Audio Classification
- Library
- transformers
- Type
- hubert
- License
- apache-2.0
- Created
- Mar 10, 2025
- Updated
- Mar 12, 2025