---
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-gtzan
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: audiofolder
      type: audiofolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.0
---

<!-- 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 audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 5.7174
- Accuracy: 0.0

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 5.6861        | 1.0   | 61   | 5.7174          | 0.0      |
| 5.573         | 2.0   | 122  | 5.7429          | 0.0      |
| 5.4992        | 3.0   | 183  | 5.7735          | 0.0      |
| 5.3129        | 4.0   | 244  | 5.7965          | 0.0      |
| 5.3243        | 5.0   | 305  | 5.8150          | 0.0      |
| 5.2456        | 6.0   | 366  | 5.7999          | 0.0      |
| 4.8339        | 7.0   | 427  | 5.8090          | 0.0      |
| 5.0512        | 8.0   | 488  | 5.8288          | 0.0      |
| 4.7789        | 9.0   | 549  | 5.8143          | 0.0      |
| 5.1463        | 10.0  | 610  | 5.8238          | 0.0      |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0