---
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: 1.2425
- 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: 0.0005
- train_batch_size: 8
- eval_batch_size: 12
- 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2069        | 1.0   | 113  | 1.3361          | 0.5      |
| 1.5776        | 2.0   | 226  | 1.4992          | 0.43     |
| 1.2343        | 3.0   | 339  | 1.2779          | 0.48     |
| 0.8813        | 4.0   | 452  | 1.2418          | 0.62     |
| 0.8836        | 5.0   | 565  | 0.9679          | 0.71     |
| 0.7827        | 6.0   | 678  | 0.9275          | 0.7      |
| 0.4979        | 7.0   | 791  | 1.2511          | 0.69     |
| 0.466         | 8.0   | 904  | 1.0917          | 0.73     |
| 0.6358        | 9.0   | 1017 | 0.7578          | 0.81     |
| 0.5371        | 10.0  | 1130 | 1.2664          | 0.72     |
| 0.0353        | 11.0  | 1243 | 1.2281          | 0.77     |
| 0.0159        | 12.0  | 1356 | 1.5949          | 0.73     |
| 0.0011        | 13.0  | 1469 | 1.0783          | 0.85     |
| 0.0007        | 14.0  | 1582 | 1.3324          | 0.82     |
| 0.0007        | 15.0  | 1695 | 1.2425          | 0.84     |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3