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distilhubert-finetuned-gtzan
eljandoubi/distilhubert-finetuned-gtzan
distilhubert-finetuned-gtzan is a audio classification model from eljandoubi. 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
- Nov 12, 2023
- Updated
- Nov 12, 2023
- SHA
- a3b49735
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: 0.5086
- 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: 4e-05
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 7
- total_train_batch_size: 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: 25
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.2912 | 0.98 | 21 | 2.2667 | 0.19 |
| 2.2263 | 1.96 | 42 | 2.1460 | 0.48 |
| 1.9552 | 2.99 | 64 | 1.8067 | 0.44 |
| 1.5982 | 3.97 | 85 | 1.5912 | 0.54 |
| 1.5182 | 4.99 | 107 | 1.4077 | 0.61 |
| 1.2855 | 5.97 | 128 | 1.2654 | 0.69 |
| 1.1649 | 7.0 | 150 | 1.1915 | 0.69 |
| 1.0742 | 7.98 | 171 | 1.0769 | 0.75 |
| 1.0495 | 8.96 | 192 | 1.0011 | 0.77 |
| 0.8827 | 9.99 | 214 | 0.9062 | 0.79 |
| 0.7886 | 10.97 | 235 | 0.8333 | 0.83 |
| 0.7019 | 11.99 | 257 | 0.7801 | 0.83 |
| 0.6642 | 12.97 | 278 | 0.7691 | 0.79 |
| 0.5982 | 14.0 | 300 | 0.6984 | 0.82 |
| 0.5002 | 14.98 | 321 | 0.6526 | 0.84 |
| 0.4789 | 15.96 | 342 | 0.5980 | 0.88 |
| 0.3908 | 16.99 | 364 | 0.5874 | 0.86 |
| 0.3892 | 17.97 | 385 | 0.5570 | 0.86 |
| 0.3675 | 18.99 | 407 | 0.5634 | 0.87 |
| 0.303 | 19.97 | 428 | 0.5387 | 0.87 |
| 0.3017 | 21.0 | 450 | 0.5086 | 0.89 |
| 0.2469 | 21.98 | 471 | 0.4969 | 0.89 |
| 0.2542 | 22.96 | 492 | 0.4972 | 0.88 |
| 0.2651 | 23.99 | 514 | 0.4947 | 0.89 |
| 0.2591 | 24.5 | 525 | 0.4929 | 0.89 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1
- Task
- Audio Classification
- Library
- transformers
- Type
- hubert
- License
- apache-2.0
- Created
- Nov 12, 2023
- Updated
- Nov 12, 2023