---
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: 0.6645
- 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2685        | 1.0   | 56   | 2.2069          | 0.44     |
| 2.0208        | 1.99  | 112  | 1.8352          | 0.46     |
| 1.7603        | 2.99  | 168  | 1.5275          | 0.49     |
| 1.4843        | 4.0   | 225  | 1.4296          | 0.52     |
| 1.347         | 5.0   | 281  | 1.2222          | 0.52     |
| 1.2364        | 5.99  | 337  | 1.1477          | 0.62     |
| 1.2082        | 6.99  | 393  | 1.0181          | 0.67     |
| 0.9861        | 8.0   | 450  | 0.9598          | 0.71     |
| 0.752         | 9.0   | 506  | 0.7499          | 0.77     |
| 1.006         | 9.99  | 562  | 0.8190          | 0.79     |
| 0.6725        | 10.99 | 618  | 0.8798          | 0.75     |
| 0.7457        | 12.0  | 675  | 0.6276          | 0.81     |
| 0.4605        | 13.0  | 731  | 0.6086          | 0.85     |
| 0.5751        | 13.99 | 787  | 0.6894          | 0.75     |
| 0.4886        | 14.99 | 843  | 0.6109          | 0.83     |
| 0.2429        | 16.0  | 900  | 0.6076          | 0.85     |
| 0.3084        | 17.0  | 956  | 0.4646          | 0.86     |
| 0.3762        | 17.99 | 1012 | 0.8349          | 0.81     |
| 0.2897        | 18.99 | 1068 | 0.4509          | 0.89     |
| 0.1296        | 20.0  | 1125 | 0.6791          | 0.86     |
| 0.1291        | 21.0  | 1181 | 0.6466          | 0.85     |
| 0.3784        | 21.99 | 1237 | 0.6272          | 0.88     |
| 0.1156        | 22.99 | 1293 | 0.7916          | 0.85     |
| 0.2093        | 24.0  | 1350 | 0.6536          | 0.85     |
| 0.2167        | 25.0  | 1406 | 0.7050          | 0.87     |
| 0.1095        | 25.99 | 1462 | 0.6128          | 0.88     |
| 0.1004        | 26.99 | 1518 | 0.6092          | 0.89     |
| 0.0897        | 28.0  | 1575 | 0.6730          | 0.88     |
| 0.083         | 29.0  | 1631 | 0.6396          | 0.89     |
| 0.0343        | 29.87 | 1680 | 0.6645          | 0.88     |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.14.1
- Tokenizers 0.13.3