---
license: bsd-3-clause
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: ast-finetuned-audioset-10-10-0.4593-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. -->

# ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan

This model is a fine-tuned version of [MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6230
- 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: 2
- eval_batch_size: 2
- 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1198        | 1.0   | 450  | 1.8429          | 0.47     |
| 0.0005        | 2.0   | 900  | 1.6282          | 0.71     |
| 0.3129        | 3.0   | 1350 | 1.0553          | 0.73     |
| 0.0225        | 4.0   | 1800 | 0.9422          | 0.82     |
| 0.0025        | 5.0   | 2250 | 0.6008          | 0.85     |
| 0.0           | 6.0   | 2700 | 0.7194          | 0.86     |
| 0.0           | 7.0   | 3150 | 0.6268          | 0.89     |
| 0.0           | 8.0   | 3600 | 0.6372          | 0.89     |
| 0.0           | 9.0   | 4050 | 0.6167          | 0.89     |
| 0.0           | 10.0  | 4500 | 0.6230          | 0.89     |


### Framework versions

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