---
license: apache-2.0
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: 0.84
---

<!-- 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: 0.6527
- Accuracy: 0.84

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1249        | 1.0   | 112  | 1.9377          | 0.43     |
| 1.6556        | 2.0   | 225  | 1.5867          | 0.47     |
| 1.2564        | 3.0   | 337  | 1.2670          | 0.56     |
| 1.0786        | 4.0   | 450  | 1.1080          | 0.59     |
| 0.895         | 5.0   | 562  | 0.8518          | 0.75     |
| 0.7177        | 6.0   | 675  | 1.0047          | 0.7      |
| 0.964         | 7.0   | 787  | 0.7430          | 0.75     |
| 0.4107        | 8.0   | 900  | 1.0347          | 0.71     |
| 0.4166        | 9.0   | 1012 | 0.5399          | 0.85     |
| 0.1234        | 10.0  | 1125 | 0.6266          | 0.83     |
| 0.0902        | 11.0  | 1237 | 0.6292          | 0.84     |
| 0.1211        | 12.0  | 1350 | 0.7393          | 0.84     |
| 0.4082        | 13.0  | 1462 | 0.6524          | 0.85     |
| 0.3442        | 14.0  | 1575 | 0.5732          | 0.86     |
| 0.0913        | 14.93 | 1680 | 0.6527          | 0.84     |


### Framework versions

- Transformers 4.31.0.dev0
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.3