---
license: apache-2.0
base_model: bookbot/distil-ast-audioset
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: distil-ast-audioset-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: 0.89
---

<!-- 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. -->

# distil-ast-audioset-finetuned-gtzan

This model is a fine-tuned version of [bookbot/distil-ast-audioset](https://huggingface.co/bookbot/distil-ast-audioset) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4548
- Accuracy: 0.89

## 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: 20
- eval_batch_size: 20
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 80
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.9887        | 0.9778 | 11   | 0.9550          | 0.79     |
| 0.8046        | 1.9556 | 22   | 0.6496          | 0.79     |
| 0.517         | 2.9333 | 33   | 0.5969          | 0.8      |
| 0.3425        | 4.0    | 45   | 0.4936          | 0.87     |
| 0.1616        | 4.9778 | 56   | 0.5090          | 0.88     |
| 0.1274        | 5.9556 | 67   | 0.4367          | 0.88     |
| 0.071         | 6.9333 | 78   | 0.4128          | 0.88     |
| 0.026         | 8.0    | 90   | 0.4548          | 0.89     |
| 0.0185        | 8.9778 | 101  | 0.3586          | 0.88     |
| 0.0089        | 9.7778 | 110  | 0.3642          | 0.88     |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1