---
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: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8
---

<!-- 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: 0.6141
- Accuracy: 0.8

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 14

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1976        | 0.99  | 56   | 2.1232          | 0.36     |
| 1.5738        | 2.0   | 113  | 1.4564          | 0.68     |
| 1.2321        | 2.99  | 169  | 1.1535          | 0.74     |
| 0.9847        | 4.0   | 226  | 0.9799          | 0.74     |
| 0.8254        | 4.99  | 282  | 0.8700          | 0.78     |
| 0.6017        | 6.0   | 339  | 0.8466          | 0.74     |
| 0.631         | 6.99  | 395  | 0.6828          | 0.8      |
| 0.4887        | 8.0   | 452  | 0.6360          | 0.81     |
| 0.3798        | 8.99  | 508  | 0.6158          | 0.82     |
| 0.2427        | 10.0  | 565  | 0.6163          | 0.78     |
| 0.2077        | 10.99 | 621  | 0.6197          | 0.8      |
| 0.1506        | 12.0  | 678  | 0.5992          | 0.8      |
| 0.1467        | 12.99 | 734  | 0.6003          | 0.8      |
| 0.1967        | 13.88 | 784  | 0.6141          | 0.8      |


### Framework versions

- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3