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hubert-base-ls960-finetuned-gtzan
ruisp/hubert-base-ls960-finetuned-gtzan
hubert-base-ls960-finetuned-gtzan is a audio classification model from ruisp. 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 20, 2023
- Updated
- Aug 20, 2023
- SHA
- bc6a2315
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-base-ls960-finetuned-gtzan
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: 0.7810
- 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: 4e-05
- train_batch_size: 2
- eval_batch_size: 2
- 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: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.9364 | 1.0 | 450 | 1.2781 | 0.61 |
| 1.0205 | 2.0 | 900 | 1.2654 | 0.63 |
| 0.7681 | 3.0 | 1350 | 1.6762 | 0.62 |
| 0.6968 | 4.0 | 1800 | 0.9113 | 0.78 |
| 0.0467 | 5.0 | 2250 | 1.0105 | 0.82 |
| 0.1238 | 6.0 | 2700 | 0.7810 | 0.87 |
Framework versions
- Transformers 4.31.0
- 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
- Aug 20, 2023
- Updated
- Aug 20, 2023