---
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: 0.8078
- Accuracy: 0.81

## 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: 12
- eval_batch_size: 12
- 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1001        | 1.0   | 75   | 2.0810          | 0.45     |
| 1.563         | 2.0   | 150  | 1.5605          | 0.59     |
| 1.1348        | 3.0   | 225  | 1.1216          | 0.73     |
| 0.8687        | 4.0   | 300  | 0.9611          | 0.75     |
| 0.6107        | 5.0   | 375  | 0.9266          | 0.71     |
| 0.55          | 6.0   | 450  | 0.7138          | 0.81     |
| 0.3267        | 7.0   | 525  | 0.7121          | 0.84     |
| 0.3366        | 8.0   | 600  | 0.7213          | 0.81     |
| 0.2463        | 9.0   | 675  | 0.7768          | 0.79     |
| 0.1388        | 10.0  | 750  | 0.8165          | 0.79     |
| 0.1413        | 11.0  | 825  | 0.7713          | 0.82     |
| 0.0578        | 12.0  | 900  | 0.7860          | 0.8      |
| 0.0329        | 13.0  | 975  | 0.7821          | 0.82     |
| 0.0287        | 14.0  | 1050 | 0.8172          | 0.82     |
| 0.0277        | 15.0  | 1125 | 0.8078          | 0.81     |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3