---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-gtzan-v2
  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-v2

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: 0.4006
- Accuracy: 0.89

## 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4786        | 1.0   | 225  | 1.3772          | 0.67     |
| 1.0539        | 2.0   | 450  | 0.8660          | 0.78     |
| 0.8426        | 3.0   | 675  | 0.7087          | 0.79     |
| 0.5203        | 4.0   | 900  | 0.6213          | 0.8      |
| 0.2969        | 5.0   | 1125 | 0.5474          | 0.8      |
| 0.2166        | 6.0   | 1350 | 0.5594          | 0.86     |
| 0.0563        | 7.0   | 1575 | 0.3808          | 0.91     |
| 0.1048        | 8.0   | 1800 | 0.4006          | 0.89     |


### Framework versions

- Transformers 4.30.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.0
- Tokenizers 0.13.3