---
library_name: transformers
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: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7391304347826086
---

<!-- 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: 1.1234
- Accuracy: 0.7391

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.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: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4277        | 1.0   | 25   | 1.5627          | 0.4783   |
| 1.4946        | 2.0   | 50   | 1.4727          | 0.5217   |
| 1.051         | 3.0   | 75   | 1.3207          | 0.6087   |
| 1.0897        | 4.0   | 100  | 1.3614          | 0.6522   |
| 1.1461        | 5.0   | 125  | 1.3143          | 0.5652   |
| 0.6919        | 6.0   | 150  | 1.1131          | 0.6087   |
| 0.7273        | 7.0   | 175  | 1.4138          | 0.6522   |
| 0.5955        | 8.0   | 200  | 1.2106          | 0.6957   |
| 0.4823        | 9.0   | 225  | 1.1681          | 0.6087   |
| 0.5178        | 10.0  | 250  | 1.1616          | 0.6522   |
| 0.4635        | 11.0  | 275  | 0.9685          | 0.7826   |
| 0.4622        | 12.0  | 300  | 0.9625          | 0.7826   |
| 0.3048        | 13.0  | 325  | 1.0364          | 0.7391   |
| 0.1576        | 14.0  | 350  | 1.0571          | 0.7391   |
| 0.1876        | 15.0  | 375  | 1.1234          | 0.7391   |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.1
- Tokenizers 0.21.1