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---
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: hubert-base-ls960-finetuned-gtzan
results: []
---
<!-- 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](https://huggingface.co/facebook/hubert-base-ls960) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1107
- Accuracy: 0.85
## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 1.9975 | 1.0 | 225 | 0.47 | 1.8130 |
| 1.2415 | 2.0 | 450 | 0.57 | 1.3022 |
| 1.0225 | 3.0 | 675 | 0.645 | 1.1478 |
| 1.1012 | 4.0 | 900 | 0.755 | 0.8725 |
| 1.0753 | 5.0 | 1125 | 0.67 | 1.1645 |
| 0.5354 | 6.0 | 1350 | 0.66 | 1.3094 |
| 0.7805 | 7.0 | 1575 | 0.795 | 0.8406 |
| 0.3307 | 8.0 | 1800 | 0.795 | 0.9782 |
| 0.1861 | 9.0 | 2025 | 0.79 | 0.9140 |
| 0.2776 | 10.0 | 2250 | 0.795 | 1.1711 |
| 0.314 | 11.0 | 2475 | 0.825 | 0.9193 |
| 0.1785 | 12.0 | 2700 | 0.82 | 1.0272 |
| 0.1444 | 13.0 | 2925 | 0.845 | 0.9903 |
| 0.0122 | 14.0 | 3150 | 0.835 | 0.9974 |
| 0.0116 | 15.0 | 3375 | 0.85 | 0.9670 |
| 0.3403 | 31.0 | 3472 | 1.0085 | 0.85 |
| 0.3596 | 32.0 | 3585 | 1.3101 | 0.81 |
| 0.0242 | 33.0 | 3697 | 0.9612 | 0.86 |
| 0.1006 | 34.0 | 3810 | 1.1904 | 0.82 |
| 0.1034 | 35.0 | 3922 | 0.9582 | 0.86 |
| 0.195 | 36.0 | 4035 | 1.0223 | 0.84 |
| 0.0081 | 37.0 | 4147 | 1.2461 | 0.8 |
| 0.006 | 38.0 | 4260 | 0.9541 | 0.87 |
| 0.281 | 39.0 | 4372 | 0.9340 | 0.87 |
| 0.0491 | 40.0 | 4485 | 1.0942 | 0.85 |
| 0.0537 | 41.0 | 4597 | 1.1521 | 0.85 |
| 0.0017 | 42.0 | 4710 | 1.1738 | 0.85 |
| 0.0031 | 43.0 | 4822 | 1.1584 | 0.85 |
| 0.1107 | 44.0 | 4935 | 1.1503 | 0.86 |
| 0.0032 | 45.0 | 5047 | 1.0710 | 0.87 |
| 0.0027 | 46.0 | 5160 | 1.1310 | 0.86 |
| 0.0013 | 47.0 | 5272 | 1.1194 | 0.86 |
| 0.0023 | 48.0 | 5385 | 1.1173 | 0.85 |
| 0.0286 | 49.0 | 5497 | 1.1087 | 0.85 |
| 0.0133 | 49.91 | 5600 | 1.1107 | 0.85 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1
- Datasets 2.15.0
- Tokenizers 0.13.2
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