---
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: 0.6995
- Accuracy: 0.87

## 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: 0.0001
- 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: 0.2
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7415        | 1.0   | 113  | 1.8323          | 0.43     |
| 1.2237        | 2.0   | 226  | 1.2223          | 0.65     |
| 0.8856        | 3.0   | 339  | 0.8612          | 0.71     |
| 0.658         | 4.0   | 452  | 0.6679          | 0.8      |
| 0.2701        | 5.0   | 565  | 0.5787          | 0.81     |
| 0.1232        | 6.0   | 678  | 0.7164          | 0.81     |
| 0.0726        | 7.0   | 791  | 0.6973          | 0.84     |
| 0.0253        | 8.0   | 904  | 0.6665          | 0.86     |
| 0.0939        | 9.0   | 1017 | 0.6756          | 0.87     |
| 0.0112        | 10.0  | 1130 | 0.6995          | 0.87     |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3