---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-gtzan
  results: []
---

<!-- 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: 0.6711
- Accuracy: 0.82

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1962        | 1.0   | 113  | 2.2220          | 0.29     |
| 1.9431        | 2.0   | 226  | 1.8877          | 0.5      |
| 1.634         | 3.0   | 339  | 1.5106          | 0.63     |
| 1.3403        | 4.0   | 452  | 1.3191          | 0.66     |
| 1.1067        | 5.0   | 565  | 1.1082          | 0.68     |
| 1.0416        | 6.0   | 678  | 1.0664          | 0.72     |
| 0.7723        | 7.0   | 791  | 0.9729          | 0.77     |
| 0.8281        | 8.0   | 904  | 0.8799          | 0.78     |
| 0.6344        | 9.0   | 1017 | 0.8142          | 0.77     |
| 0.8819        | 10.0  | 1130 | 0.8719          | 0.73     |
| 0.4279        | 11.0  | 1243 | 0.8150          | 0.78     |
| 0.425         | 12.0  | 1356 | 0.7137          | 0.81     |
| 0.2749        | 13.0  | 1469 | 0.6987          | 0.8      |
| 0.2182        | 14.0  | 1582 | 0.6849          | 0.82     |
| 0.2128        | 15.0  | 1695 | 0.6918          | 0.82     |
| 0.1831        | 16.0  | 1808 | 0.6600          | 0.81     |
| 0.1517        | 17.0  | 1921 | 0.6571          | 0.82     |
| 0.2888        | 18.0  | 2034 | 0.6880          | 0.81     |
| 0.1605        | 19.0  | 2147 | 0.6874          | 0.82     |
| 0.1492        | 20.0  | 2260 | 0.6711          | 0.82     |


### Framework versions

- Transformers 4.29.2
- Pytorch 1.13.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3