---
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