---
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: 0.6869
- Accuracy: 0.7889

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9903        | 1.0   | 102  | 1.9462          | 0.5333   |
| 1.4477        | 2.0   | 204  | 1.3659          | 0.5111   |
| 1.082         | 3.0   | 306  | 1.1169          | 0.6444   |
| 0.967         | 4.0   | 408  | 0.8758          | 0.8111   |
| 0.4794        | 5.0   | 510  | 0.7574          | 0.8      |
| 0.4756        | 6.0   | 612  | 0.7637          | 0.7667   |
| 0.2381        | 7.0   | 714  | 0.7337          | 0.7889   |
| 0.2841        | 8.0   | 816  | 0.6546          | 0.8111   |
| 0.098         | 9.0   | 918  | 0.6680          | 0.8111   |
| 0.1294        | 10.0  | 1020 | 0.6869          | 0.7889   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3