---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: hubert-large-ls960-ft-finetuned-gtzan
  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-large-ls960-ft-finetuned-gtzan

This model is a fine-tuned version of [facebook/hubert-large-ls960-ft](https://huggingface.co/facebook/hubert-large-ls960-ft) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Accuracy: 0.86

## 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: 0.0001
- 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2625        | 1.0   | 56   | 2.2399          | 0.23     |
| 1.7887        | 1.99  | 112  | 1.7278          | 0.4      |
| 1.4728        | 2.99  | 168  | 1.4387          | 0.48     |
| 1.1536        | 4.0   | 225  | 1.3178          | 0.54     |
| 1.0758        | 5.0   | 281  | 1.1903          | 0.6      |
| 0.9742        | 5.99  | 337  | 0.8416          | 0.72     |
| 0.8285        | 6.99  | 393  | 0.5875          | 0.78     |
| 0.7953        | 8.0   | 450  | 0.7786          | 0.75     |
| 0.6224        | 9.0   | 506  | 0.6753          | 0.8      |
| 0.3806        | 9.99  | 562  | 0.5826          | 0.84     |
| 0.3121        | 10.99 | 618  | 0.7312          | 0.78     |
| 0.1729        | 12.0  | 675  | 0.6526          | 0.85     |
| 0.2958        | 13.0  | 731  | 0.7831          | 0.83     |
| 0.1496        | 13.99 | 787  | 0.8518          | 0.79     |
| 0.0659        | 14.99 | 843  | 0.8194          | 0.82     |
| 0.1208        | 16.0  | 900  | 0.8555          | 0.82     |
| 0.147         | 17.0  | 956  | 0.6768          | 0.86     |
| 0.0284        | 17.99 | 1012 | 0.7065          | 0.86     |
| 0.0295        | 18.99 | 1068 | 0.6942          | 0.87     |
| 0.0524        | 19.91 | 1120 | nan             | 0.86     |


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3