---
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: 0.9570
- 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1586        | 1.0   | 112  | 2.0855          | 0.45     |
| 1.4771        | 2.0   | 225  | 1.3396          | 0.72     |
| 1.181         | 3.0   | 337  | 0.9735          | 0.76     |
| 0.8133        | 4.0   | 450  | 0.8692          | 0.76     |
| 0.5397        | 5.0   | 562  | 0.7118          | 0.81     |
| 0.3424        | 6.0   | 675  | 0.6237          | 0.81     |
| 0.2717        | 7.0   | 787  | 0.6551          | 0.83     |
| 0.2653        | 8.0   | 900  | 0.6707          | 0.83     |
| 0.0503        | 9.0   | 1012 | 0.7025          | 0.84     |
| 0.0168        | 10.0  | 1125 | 0.7643          | 0.87     |
| 0.1125        | 11.0  | 1237 | 0.8550          | 0.86     |
| 0.155         | 12.0  | 1350 | 0.9796          | 0.82     |
| 0.005         | 13.0  | 1462 | 0.9539          | 0.86     |
| 0.0038        | 14.0  | 1575 | 0.9206          | 0.86     |
| 0.0035        | 15.0  | 1687 | 0.8725          | 0.88     |
| 0.051         | 16.0  | 1800 | 0.9980          | 0.86     |
| 0.003         | 17.0  | 1912 | 0.9579          | 0.86     |
| 0.0025        | 18.0  | 2025 | 0.9735          | 0.86     |
| 0.0023        | 19.0  | 2137 | 0.9589          | 0.86     |
| 0.0022        | 19.91 | 2240 | 0.9570          | 0.86     |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.0
- Datasets 2.13.1
- Tokenizers 0.13.3