---
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
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# 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: 0.7408
- 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5687        | 1.0   | 450  | 1.3520          | 0.58     |
| 0.0014        | 2.0   | 900  | 0.9949          | 0.7      |
| 0.2778        | 3.0   | 1350 | 0.7536          | 0.84     |
| 0.0042        | 4.0   | 1800 | 0.9976          | 0.86     |
| 0.0001        | 5.0   | 2250 | 0.7859          | 0.85     |
| 0.0002        | 6.0   | 2700 | 0.9659          | 0.86     |
| 0.0           | 7.0   | 3150 | 0.8016          | 0.88     |
| 0.0           | 8.0   | 3600 | 0.5691          | 0.88     |
| 0.0           | 9.0   | 4050 | 0.7230          | 0.88     |
| 0.0           | 10.0  | 4500 | 0.7408          | 0.88     |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3