---
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: 0.82
---

<!-- 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: 0.9359
- Accuracy: 0.82

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2494        | 1.0   | 113  | 2.1568          | 0.36     |
| 1.7795        | 2.0   | 226  | 1.7904          | 0.38     |
| 1.5798        | 3.0   | 339  | 1.6144          | 0.5      |
| 1.6354        | 4.0   | 452  | 1.2584          | 0.66     |
| 0.9675        | 5.0   | 565  | 1.1453          | 0.64     |
| 0.995         | 6.0   | 678  | 0.9740          | 0.67     |
| 1.2052        | 7.0   | 791  | 1.0552          | 0.68     |
| 0.7028        | 8.0   | 904  | 0.8980          | 0.74     |
| 0.7472        | 9.0   | 1017 | 0.9431          | 0.72     |
| 0.3181        | 10.0  | 1130 | 0.8750          | 0.75     |
| 0.3948        | 11.0  | 1243 | 1.0047          | 0.73     |
| 0.3507        | 12.0  | 1356 | 0.8054          | 0.81     |
| 0.1785        | 13.0  | 1469 | 0.7866          | 0.84     |
| 0.2453        | 14.0  | 1582 | 0.8960          | 0.82     |
| 0.2832        | 15.0  | 1695 | 1.0770          | 0.81     |
| 0.2132        | 16.0  | 1808 | 0.9359          | 0.82     |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1