---
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: 0.88
---

<!-- 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: 0.7650
- Accuracy: 0.88

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2258        | 1.0   | 225  | 1.9240          | 0.28     |
| 1.6083        | 2.0   | 450  | 1.4887          | 0.39     |
| 1.3983        | 3.0   | 675  | 1.3524          | 0.56     |
| 0.7368        | 4.0   | 900  | 1.3110          | 0.56     |
| 0.6121        | 5.0   | 1125 | 0.9572          | 0.72     |
| 0.1772        | 6.0   | 1350 | 0.8775          | 0.73     |
| 1.8666        | 7.0   | 1575 | 0.6078          | 0.82     |
| 0.091         | 8.0   | 1800 | 0.9999          | 0.76     |
| 0.0458        | 9.0   | 2025 | 0.7169          | 0.83     |
| 0.6817        | 10.0  | 2250 | 0.7614          | 0.86     |
| 0.7023        | 11.0  | 2475 | 0.9348          | 0.84     |
| 0.0047        | 12.0  | 2700 | 0.7222          | 0.88     |
| 0.0363        | 13.0  | 2925 | 0.7027          | 0.89     |
| 0.0073        | 14.0  | 3150 | 0.7440          | 0.88     |
| 0.0055        | 15.0  | 3375 | 0.7650          | 0.88     |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0