---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: hubert-base-ls960-finetuned-gtzan-efficient
  results: []
---

<!-- 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-efficient

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: 1.0959
- Accuracy: 0.89

## 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1988        | 1.0   | 113  | 2.1353          | 0.36     |
| 1.6317        | 2.0   | 226  | 1.7387          | 0.39     |
| 1.4411        | 3.0   | 339  | 1.3925          | 0.46     |
| 0.8491        | 4.0   | 452  | 1.0834          | 0.65     |
| 2.1748        | 5.0   | 565  | 1.1530          | 0.64     |
| 1.4915        | 6.0   | 678  | 0.9865          | 0.69     |
| 0.4322        | 7.0   | 791  | 1.3910          | 0.6      |
| 0.6867        | 8.0   | 904  | 1.1252          | 0.7      |
| 0.0758        | 9.0   | 1017 | 0.7395          | 0.75     |
| 1.8782        | 10.0  | 1130 | 0.9792          | 0.77     |
| 1.0492        | 11.0  | 1243 | 0.8810          | 0.75     |
| 0.0376        | 12.0  | 1356 | 0.7031          | 0.81     |
| 0.0648        | 13.0  | 1469 | 0.7527          | 0.82     |
| 1.1951        | 14.0  | 1582 | 0.7731          | 0.84     |
| 0.0071        | 15.0  | 1695 | 0.9237          | 0.83     |
| 0.0095        | 16.0  | 1808 | 0.8471          | 0.85     |
| 0.0014        | 17.0  | 1921 | 1.0585          | 0.87     |
| 0.0007        | 18.0  | 2034 | 1.0959          | 0.89     |
| 0.0003        | 19.0  | 2147 | 1.3957          | 0.86     |
| 3.0069        | 20.0  | 2260 | 1.6382          | 0.84     |
| 0.0           | 21.0  | 2373 | 1.3385          | 0.88     |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.1.0.dev20230627+cu121
- Datasets 2.13.1
- Tokenizers 0.13.3