---
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: 0.9594
- Accuracy: 0.83

## 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: 8e-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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.874         | 1.0   | 113  | 1.8949          | 0.42     |
| 1.2872        | 2.0   | 226  | 1.3293          | 0.57     |
| 0.9764        | 3.0   | 339  | 0.9030          | 0.72     |
| 0.5805        | 4.0   | 452  | 0.6561          | 0.83     |
| 0.4618        | 5.0   | 565  | 0.5127          | 0.87     |
| 0.1487        | 6.0   | 678  | 0.7336          | 0.77     |
| 0.1542        | 7.0   | 791  | 0.5496          | 0.84     |
| 0.267         | 8.0   | 904  | 0.6534          | 0.85     |
| 0.037         | 9.0   | 1017 | 0.7327          | 0.85     |
| 0.0089        | 10.0  | 1130 | 1.1979          | 0.76     |
| 0.0436        | 11.0  | 1243 | 1.0857          | 0.82     |
| 0.003         | 12.0  | 1356 | 0.9266          | 0.84     |
| 0.0019        | 13.0  | 1469 | 0.9791          | 0.84     |
| 0.0017        | 14.0  | 1582 | 0.9259          | 0.84     |
| 0.0015        | 15.0  | 1695 | 0.9836          | 0.83     |
| 0.0014        | 16.0  | 1808 | 1.0018          | 0.83     |
| 0.0013        | 17.0  | 1921 | 0.9896          | 0.83     |
| 0.0012        | 18.0  | 2034 | 0.9836          | 0.84     |
| 0.0012        | 19.0  | 2147 | 0.9759          | 0.84     |
| 0.0011        | 20.0  | 2260 | 0.9594          | 0.83     |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3