---
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: all
      split: train
      args: all
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7
---

<!-- 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: 1.6085
- Accuracy: 0.7

## 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: 1e-05
- train_batch_size: 20
- eval_batch_size: 20
- 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.284         | 1.0   | 45   | 2.2715          | 0.28     |
| 2.2235        | 2.0   | 90   | 2.1789          | 0.47     |
| 2.0628        | 3.0   | 135  | 2.0368          | 0.63     |
| 1.9314        | 4.0   | 180  | 1.9068          | 0.66     |
| 1.8308        | 5.0   | 225  | 1.8077          | 0.66     |
| 1.7901        | 6.0   | 270  | 1.7276          | 0.7      |
| 1.7703        | 7.0   | 315  | 1.6747          | 0.69     |
| 1.7163        | 8.0   | 360  | 1.6382          | 0.69     |
| 1.6133        | 9.0   | 405  | 1.6154          | 0.7      |
| 1.6876        | 10.0  | 450  | 1.6085          | 0.7      |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3