---
license: apache-2.0
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: 0.84
---

<!-- 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: 0.5555
- Accuracy: 0.84

## 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

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 2.0326        | 1.0   | 113  | 0.45     | 1.8397          |
| 1.3293        | 2.0   | 226  | 0.64     | 1.2497          |
| 0.9968        | 3.0   | 339  | 0.75     | 0.9469          |
| 0.8413        | 4.0   | 452  | 0.76     | 0.8033          |
| 0.6769        | 5.0   | 565  | 0.8      | 0.6373          |
| 0.3725        | 6.0   | 678  | 0.6338   | 0.8             |
| 0.4498        | 7.0   | 791  | 0.5539   | 0.85            |
| 0.2232        | 8.0   | 904  | 0.5405   | 0.83            |
| 0.2456        | 9.0   | 1017 | 0.5259   | 0.85            |
| 0.1777        | 10.0  | 1130 | 0.5555   | 0.84            |


### Framework versions

- Transformers 4.31.0.dev0
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.12.1