---
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-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-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: 0.3171
- 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: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.817         | 1.0   | 56   | 1.5314          | 0.83     |
| 1.3804        | 1.99  | 112  | 1.2976          | 0.73     |
| 1.1139        | 2.99  | 168  | 0.7886          | 0.9      |
| 0.8946        | 3.99  | 224  | 0.6678          | 0.89     |
| 0.7045        | 4.98  | 280  | 0.8158          | 0.82     |
| 0.7178        | 6.0   | 337  | 0.7588          | 0.83     |
| 0.6513        | 6.99  | 393  | 0.4012          | 0.93     |
| 0.548         | 7.99  | 449  | 0.3258          | 0.93     |
| 0.3329        | 8.99  | 505  | 0.3477          | 0.93     |
| 0.2874        | 9.97  | 560  | 0.3171          | 0.94     |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.2
- Datasets 2.18.0
- Tokenizers 0.15.2