---
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: 0.7058
- Accuracy: 0.79

## 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
- gradient_accumulation_steps: 2
- 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7675        | 1.0   | 112  | 1.8184          | 0.42     |
| 1.2504        | 2.0   | 225  | 1.3015          | 0.62     |
| 1.0353        | 3.0   | 337  | 0.9890          | 0.72     |
| 0.8318        | 4.0   | 450  | 0.8237          | 0.8      |
| 0.4429        | 5.0   | 562  | 0.8123          | 0.78     |
| 0.4286        | 6.0   | 675  | 0.6820          | 0.8      |
| 0.2553        | 7.0   | 787  | 0.7826          | 0.78     |
| 0.3022        | 8.0   | 900  | 0.6811          | 0.77     |
| 0.1889        | 9.0   | 1012 | 0.6761          | 0.8      |
| 0.1073        | 9.96  | 1120 | 0.7058          | 0.79     |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3