---
base_model: yus988/pingpong-music_genres_classification-finetuned
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: pingpong-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: 0.94
---

<!-- 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. -->

# pingpong-music_genres_classification-finetuned-gtzan

This model is a fine-tuned version of [yus988/pingpong-music_genres_classification-finetuned](https://huggingface.co/yus988/pingpong-music_genres_classification-finetuned) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2967
- Accuracy: 0.94

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4316        | 1.0   | 112  | 1.2668          | 0.75     |
| 1.7743        | 1.99  | 224  | 1.0659          | 0.64     |
| 0.9712        | 3.0   | 337  | 0.5958          | 0.84     |
| 1.2043        | 4.0   | 449  | 0.6563          | 0.86     |
| 0.5506        | 4.99  | 561  | 0.3875          | 0.9      |
| 0.5882        | 6.0   | 674  | 0.4775          | 0.9      |
| 0.3522        | 6.98  | 784  | 0.2967          | 0.94     |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0