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---
library_name: transformers
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- generated_from_trainer
datasets:
- gtzan
metrics:
- accuracy
model-index:
- name: hubert-test-model
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: gtzan
type: gtzan
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.785
---
<!-- 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-test-model
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: 1.5276
- Accuracy: 0.785
## 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
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 150 | 2.0494 | 0.29 |
| No log | 2.0 | 300 | 2.1993 | 0.19 |
| No log | 3.0 | 450 | 1.8439 | 0.44 |
| 1.9218 | 4.0 | 600 | 1.5277 | 0.48 |
| 1.9218 | 5.0 | 750 | 1.4164 | 0.475 |
| 1.9218 | 6.0 | 900 | 1.3641 | 0.63 |
| 1.2685 | 7.0 | 1050 | 1.1557 | 0.675 |
| 1.2685 | 8.0 | 1200 | 1.0935 | 0.72 |
| 1.2685 | 9.0 | 1350 | 1.0594 | 0.71 |
| 0.7151 | 10.0 | 1500 | 1.0119 | 0.735 |
| 0.7151 | 11.0 | 1650 | 1.0868 | 0.77 |
| 0.7151 | 12.0 | 1800 | 1.3736 | 0.75 |
| 0.7151 | 13.0 | 1950 | 1.2705 | 0.77 |
| 0.4135 | 14.0 | 2100 | 1.4052 | 0.76 |
| 0.4135 | 15.0 | 2250 | 1.3864 | 0.77 |
| 0.4135 | 16.0 | 2400 | 1.4296 | 0.785 |
| 0.2311 | 17.0 | 2550 | 1.5663 | 0.77 |
| 0.2311 | 18.0 | 2700 | 1.5310 | 0.78 |
| 0.2311 | 19.0 | 2850 | 1.4884 | 0.795 |
| 0.1408 | 20.0 | 3000 | 1.5276 | 0.785 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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