---
license: apache-2.0
base_model: Sandiago21/distilhubert-finetuned-gtzan
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: distilhubert-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. -->

# distilhubert-finetuned-gtzan

This model is a fine-tuned version of [Sandiago21/distilhubert-finetuned-gtzan](https://huggingface.co/Sandiago21/distilhubert-finetuned-gtzan) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9951
- 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- 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: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0951        | 1.0   | 57   | 0.5566          | 0.87     |
| 0.0629        | 2.0   | 114  | 0.6819          | 0.83     |
| 0.0231        | 3.0   | 171  | 0.6118          | 0.86     |
| 0.0159        | 4.0   | 228  | 0.9208          | 0.83     |
| 0.0374        | 5.0   | 285  | 0.8746          | 0.85     |
| 0.1714        | 6.0   | 342  | 0.6671          | 0.87     |
| 0.2148        | 7.0   | 399  | 1.1850          | 0.79     |
| 0.0147        | 8.0   | 456  | 1.0551          | 0.79     |
| 0.0788        | 9.0   | 513  | 1.5179          | 0.79     |
| 0.0015        | 10.0  | 570  | 1.3290          | 0.8      |
| 0.0049        | 11.0  | 627  | 1.0943          | 0.85     |
| 0.0012        | 12.0  | 684  | 1.0667          | 0.85     |
| 0.0043        | 13.0  | 741  | 1.1816          | 0.82     |
| 0.0015        | 14.0  | 798  | 0.9108          | 0.88     |
| 0.0011        | 15.0  | 855  | 1.0289          | 0.87     |
| 0.001         | 16.0  | 912  | 0.7696          | 0.87     |
| 0.0006        | 17.0  | 969  | 0.8539          | 0.87     |
| 0.1001        | 18.0  | 1026 | 1.1917          | 0.78     |
| 0.0017        | 19.0  | 1083 | 1.0016          | 0.83     |
| 0.0525        | 20.0  | 1140 | 0.9513          | 0.88     |
| 0.0004        | 21.0  | 1197 | 0.9268          | 0.86     |
| 0.0003        | 22.0  | 1254 | 1.1209          | 0.82     |
| 0.0003        | 23.0  | 1311 | 0.9270          | 0.87     |
| 0.0003        | 24.0  | 1368 | 1.1148          | 0.84     |
| 0.0003        | 25.0  | 1425 | 1.0507          | 0.85     |
| 0.0002        | 26.0  | 1482 | 1.0156          | 0.86     |
| 0.0002        | 27.0  | 1539 | 1.0062          | 0.87     |
| 0.0002        | 28.0  | 1596 | 1.0124          | 0.87     |
| 0.0002        | 29.0  | 1653 | 1.0154          | 0.87     |
| 0.0002        | 30.0  | 1710 | 1.0092          | 0.88     |
| 0.0002        | 31.0  | 1767 | 1.0123          | 0.88     |
| 0.0175        | 32.0  | 1824 | 0.9928          | 0.88     |
| 0.0002        | 33.0  | 1881 | 1.0014          | 0.88     |
| 0.0115        | 34.0  | 1938 | 0.9989          | 0.88     |
| 0.0001        | 35.0  | 1995 | 0.9871          | 0.88     |
| 0.0001        | 36.0  | 2052 | 0.9920          | 0.88     |
| 0.0002        | 37.0  | 2109 | 0.9974          | 0.88     |
| 0.0002        | 38.0  | 2166 | 0.9950          | 0.88     |
| 0.0001        | 39.0  | 2223 | 0.9997          | 0.88     |
| 0.0001        | 40.0  | 2280 | 0.9951          | 0.88     |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3