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

# distilhubert-finetuned-gtzan

This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9006
- Accuracy: 0.8

## 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: 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1981        | 1.0   | 57   | 2.1804          | 0.37     |
| 1.7932        | 2.0   | 114  | 1.7160          | 0.62     |
| 1.3257        | 3.0   | 171  | 1.2539          | 0.67     |
| 1.1239        | 4.0   | 228  | 1.1187          | 0.68     |
| 0.7457        | 5.0   | 285  | 0.9367          | 0.73     |
| 0.6922        | 6.0   | 342  | 0.7564          | 0.81     |
| 0.5718        | 7.0   | 399  | 0.8179          | 0.78     |
| 0.3729        | 8.0   | 456  | 0.7299          | 0.79     |
| 0.2667        | 9.0   | 513  | 0.6415          | 0.82     |
| 0.4672        | 10.0  | 570  | 0.8068          | 0.78     |
| 0.1392        | 11.0  | 627  | 0.7228          | 0.81     |
| 0.1069        | 12.0  | 684  | 0.7787          | 0.79     |
| 0.0659        | 13.0  | 741  | 0.7720          | 0.8      |
| 0.0291        | 14.0  | 798  | 0.7609          | 0.79     |
| 0.0263        | 15.0  | 855  | 0.8363          | 0.8      |
| 0.0177        | 16.0  | 912  | 0.8796          | 0.78     |
| 0.0166        | 17.0  | 969  | 0.8844          | 0.79     |
| 0.0139        | 18.0  | 1026 | 0.8909          | 0.8      |
| 0.0132        | 19.0  | 1083 | 0.9017          | 0.8      |
| 0.0131        | 20.0  | 1140 | 0.9006          | 0.8      |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3