---
license: apache-2.0
base_model: dima806/music_genres_classification
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: music_genres_classification-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: 0.88
---

<!-- 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. -->

# music_genres_classification-finetuned-gtzan

This model is a fine-tuned version of [dima806/music_genres_classification](https://huggingface.co/dima806/music_genres_classification) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5964
- Accuracy: 0.88

## 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: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.12
- num_epochs: 12
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.8263        | 1.0   | 180  | 1.8672          | 0.53     |
| 1.5124        | 2.0   | 360  | 1.7102          | 0.45     |
| 1.0715        | 3.0   | 540  | 1.1957          | 0.69     |
| 1.0454        | 4.0   | 720  | 1.5712          | 0.68     |
| 0.3365        | 5.0   | 900  | 0.9891          | 0.81     |
| 0.3502        | 6.0   | 1080 | 1.2261          | 0.74     |
| 1.2326        | 7.0   | 1260 | 1.1571          | 0.77     |
| 0.5868        | 8.0   | 1440 | 0.7691          | 0.87     |
| 0.2718        | 9.0   | 1620 | 0.6720          | 0.88     |
| 0.1625        | 10.0  | 1800 | 0.3927          | 0.93     |
| 0.2519        | 11.0  | 1980 | 0.5140          | 0.91     |
| 0.0701        | 12.0  | 2160 | 0.5964          | 0.88     |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.2.1
- Datasets 2.17.1
- Tokenizers 0.15.2