---
library_name: transformers
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-gtzan
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: GTZAN
      type: marsyas/gtzan
      config: default
      split: None
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.87
---

<!-- 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: 0.5071
- 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7065        | 1.0   | 113  | 1.5003          | 0.61     |
| 1.0785        | 2.0   | 226  | 1.0084          | 0.69     |
| 0.8457        | 3.0   | 339  | 0.7742          | 0.79     |
| 0.6696        | 4.0   | 452  | 0.6197          | 0.82     |
| 0.5859        | 5.0   | 565  | 0.5071          | 0.87     |
| 0.3813        | 6.0   | 678  | 0.5068          | 0.85     |
| 0.4032        | 7.0   | 791  | 0.4872          | 0.87     |
| 0.2352        | 8.0   | 904  | 0.5913          | 0.83     |
| 0.1345        | 9.0   | 1017 | 0.6382          | 0.84     |
| 0.1871        | 10.0  | 1130 | 0.5928          | 0.87     |
| 0.1533        | 11.0  | 1243 | 0.5992          | 0.86     |
| 0.108         | 12.0  | 1356 | 0.6503          | 0.83     |
| 0.0642        | 13.0  | 1469 | 0.6233          | 0.86     |
| 0.0419        | 14.0  | 1582 | 0.6289          | 0.86     |
| 0.0461        | 15.0  | 1695 | 0.6338          | 0.87     |


### Framework versions

- Transformers 4.54.1
- Pytorch 2.9.0.dev20250731+cu128
- Datasets 3.6.0
- Tokenizers 0.21.4