---
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: 0.7339
- 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9233        | 1.0   | 225  | 1.7014          | 0.49     |
| 0.8822        | 2.0   | 450  | 1.0546          | 0.68     |
| 0.676         | 3.0   | 675  | 0.7165          | 0.78     |
| 0.8326        | 4.0   | 900  | 0.5948          | 0.79     |
| 0.3184        | 5.0   | 1125 | 0.5484          | 0.81     |
| 0.6154        | 6.0   | 1350 | 0.5977          | 0.83     |
| 0.0305        | 7.0   | 1575 | 0.6213          | 0.81     |
| 0.0154        | 8.0   | 1800 | 0.7479          | 0.79     |
| 0.086         | 9.0   | 2025 | 0.6926          | 0.84     |
| 0.0103        | 10.0  | 2250 | 0.7339          | 0.82     |


### Framework versions

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