---
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: 0.7031
- 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2612        | 1.0   | 57   | 2.2511          | 0.26     |
| 2.1275        | 2.0   | 114  | 2.0384          | 0.36     |
| 1.8071        | 3.0   | 171  | 1.7399          | 0.52     |
| 1.6381        | 4.0   | 228  | 1.5693          | 0.61     |
| 1.4188        | 5.0   | 285  | 1.3573          | 0.61     |
| 1.2974        | 6.0   | 342  | 1.2103          | 0.72     |
| 1.2146        | 7.0   | 399  | 1.1800          | 0.69     |
| 1.0725        | 8.0   | 456  | 1.0126          | 0.77     |
| 1.0492        | 9.0   | 513  | 0.9821          | 0.74     |
| 1.0529        | 10.0  | 570  | 0.9347          | 0.77     |
| 0.895         | 11.0  | 627  | 0.8520          | 0.79     |
| 0.7692        | 12.0  | 684  | 0.8451          | 0.8      |
| 0.6566        | 13.0  | 741  | 0.7763          | 0.82     |
| 0.5885        | 14.0  | 798  | 0.7852          | 0.8      |
| 0.619         | 15.0  | 855  | 0.7443          | 0.8      |
| 0.5572        | 16.0  | 912  | 0.7444          | 0.79     |
| 0.6493        | 17.0  | 969  | 0.7024          | 0.83     |
| 0.5499        | 18.0  | 1026 | 0.7137          | 0.81     |
| 0.5923        | 19.0  | 1083 | 0.7059          | 0.81     |
| 0.5556        | 20.0  | 1140 | 0.7031          | 0.82     |


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3