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---
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: hubert-base-ls960-finetuned-gtzan
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: GTZAN
type: marsyas/gtzan
config: all
split: train
args: all
metrics:
- name: Accuracy
type: accuracy
value: 0.89
---
<!-- 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 GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4867
- 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: 20
- eval_batch_size: 20
- 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: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2324 | 1.0 | 45 | 2.1551 | 0.32 |
| 1.858 | 2.0 | 90 | 1.7637 | 0.43 |
| 1.6808 | 3.0 | 135 | 1.5373 | 0.5 |
| 1.4424 | 4.0 | 180 | 1.3738 | 0.59 |
| 1.2715 | 5.0 | 225 | 1.1840 | 0.61 |
| 1.1501 | 6.0 | 270 | 1.0517 | 0.63 |
| 1.0187 | 7.0 | 315 | 0.8796 | 0.72 |
| 0.9446 | 8.0 | 360 | 0.8616 | 0.66 |
| 0.9266 | 9.0 | 405 | 0.8598 | 0.68 |
| 0.7204 | 10.0 | 450 | 0.7464 | 0.72 |
| 0.5817 | 11.0 | 495 | 0.7511 | 0.79 |
| 0.6758 | 12.0 | 540 | 0.8287 | 0.75 |
| 0.5383 | 13.0 | 585 | 0.6391 | 0.8 |
| 0.659 | 14.0 | 630 | 0.5670 | 0.84 |
| 0.4272 | 15.0 | 675 | 0.6181 | 0.85 |
| 0.4661 | 16.0 | 720 | 0.4935 | 0.86 |
| 0.4798 | 17.0 | 765 | 0.5827 | 0.85 |
| 0.3895 | 18.0 | 810 | 0.4870 | 0.88 |
| 0.3039 | 19.0 | 855 | 0.4571 | 0.9 |
| 0.2401 | 20.0 | 900 | 0.4867 | 0.89 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.0.0+cu117
- Datasets 2.14.6
- Tokenizers 0.14.1
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