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hubert-base-ls960-finetuned-gtzan-efficient
derek-thomas/hubert-base-ls960-finetuned-gtzan-efficient
hubert-base-ls960-finetuned-gtzan-efficient is a audio classification model from derek-thomas. 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. --
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At a glance
- Task
- Audio Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- hubert
- Access
- Public
- Created
- Aug 27, 2023
- Updated
- Aug 28, 2023
- SHA
- 1eb0871f
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-base-ls960-finetuned-gtzan-efficient
This model is a fine-tuned version of facebook/hubert-base-ls960 on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 1.0959
- Accuracy: 0.89
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: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.1988 | 1.0 | 113 | 2.1353 | 0.36 |
| 1.6317 | 2.0 | 226 | 1.7387 | 0.39 |
| 1.4411 | 3.0 | 339 | 1.3925 | 0.46 |
| 0.8491 | 4.0 | 452 | 1.0834 | 0.65 |
| 2.1748 | 5.0 | 565 | 1.1530 | 0.64 |
| 1.4915 | 6.0 | 678 | 0.9865 | 0.69 |
| 0.4322 | 7.0 | 791 | 1.3910 | 0.6 |
| 0.6867 | 8.0 | 904 | 1.1252 | 0.7 |
| 0.0758 | 9.0 | 1017 | 0.7395 | 0.75 |
| 1.8782 | 10.0 | 1130 | 0.9792 | 0.77 |
| 1.0492 | 11.0 | 1243 | 0.8810 | 0.75 |
| 0.0376 | 12.0 | 1356 | 0.7031 | 0.81 |
| 0.0648 | 13.0 | 1469 | 0.7527 | 0.82 |
| 1.1951 | 14.0 | 1582 | 0.7731 | 0.84 |
| 0.0071 | 15.0 | 1695 | 0.9237 | 0.83 |
| 0.0095 | 16.0 | 1808 | 0.8471 | 0.85 |
| 0.0014 | 17.0 | 1921 | 1.0585 | 0.87 |
| 0.0007 | 18.0 | 2034 | 1.0959 | 0.89 |
| 0.0003 | 19.0 | 2147 | 1.3957 | 0.86 |
| 3.0069 | 20.0 | 2260 | 1.6382 | 0.84 |
| 0.0 | 21.0 | 2373 | 1.3385 | 0.88 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.1.0.dev20230627+cu121
- Datasets 2.13.1
- Tokenizers 0.13.3
- Task
- Audio Classification
- Library
- transformers
- Type
- hubert
- License
- apache-2.0
- Created
- Aug 27, 2023
- Updated
- Aug 28, 2023