---
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: 0.6925
- Accuracy: 0.83

## 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: 0.0001115511981046745
- 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: 9

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 1.278         | 1.0   | 112  | 0.57     | 1.3298          |
| 0.8315        | 2.0   | 225  | 0.73     | 0.9432          |
| 0.7709        | 3.0   | 337  | 0.72     | 0.9310          |
| 0.5427        | 4.0   | 450  | 0.72     | 0.8738          |
| 0.2645        | 4.98  | 560  | 0.79     | 0.6648          |
| 0.245         | 6.0   | 672  | 0.83     | 0.6147          |
| 0.1331        | 6.99  | 784  | 0.83     | 0.6305          |
| 0.1863        | 8.0   | 896  | 0.6356   | 0.84            |
| 0.0843        | 8.99  | 1008 | 0.6925   | 0.83            |


### Framework versions

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