---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-gtzan-3
  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-3

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: 0.5578
- 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: 0.0001
- 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.8069        | 1.0   | 57   | 1.7158          | 0.51     |
| 1.3469        | 2.0   | 114  | 1.2925          | 0.64     |
| 0.8341        | 3.0   | 171  | 0.8796          | 0.77     |
| 0.682         | 4.0   | 228  | 0.8847          | 0.69     |
| 0.3931        | 5.0   | 285  | 0.6189          | 0.84     |
| 0.26          | 6.0   | 342  | 0.5124          | 0.85     |
| 0.1744        | 7.0   | 399  | 0.6412          | 0.81     |
| 0.1053        | 8.0   | 456  | 0.6281          | 0.86     |
| 0.0655        | 9.0   | 513  | 0.5340          | 0.89     |
| 0.2067        | 10.0  | 570  | 0.5578          | 0.89     |


### Framework versions

- Transformers 4.29.0
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2