---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-gtzan-1
  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-1

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: 0.5778
- Accuracy: 0.82

## 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: 3e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- 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: 14

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.103         | 1.0   | 112  | 2.1288          | 0.42     |
| 1.5948        | 2.0   | 225  | 1.6203          | 0.55     |
| 1.3883        | 3.0   | 337  | 1.2437          | 0.69     |
| 1.1032        | 4.0   | 450  | 1.0490          | 0.73     |
| 0.7595        | 5.0   | 562  | 0.8857          | 0.79     |
| 0.812         | 6.0   | 675  | 0.7776          | 0.8      |
| 0.4903        | 7.0   | 787  | 0.7682          | 0.78     |
| 0.5568        | 8.0   | 900  | 0.7100          | 0.79     |
| 0.405         | 9.0   | 1012 | 0.6279          | 0.84     |
| 0.5888        | 10.0  | 1125 | 0.6944          | 0.8      |
| 0.2576        | 11.0  | 1237 | 0.6027          | 0.83     |
| 0.2123        | 12.0  | 1350 | 0.5891          | 0.83     |
| 0.2008        | 13.0  | 1462 | 0.5659          | 0.83     |
| 0.1343        | 13.94 | 1568 | 0.5778          | 0.82     |


### Framework versions

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