---
license: bsd-3-clause
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
base_model: MIT/ast-finetuned-audioset-10-10-0.4593
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: 0.4400
- Accuracy: 0.91

## 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: 8
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6505        | 1.0   | 113  | 0.6775          | 0.77     |
| 0.2847        | 2.0   | 226  | 0.6989          | 0.78     |
| 0.4559        | 3.0   | 339  | 0.5821          | 0.85     |
| 0.1643        | 4.0   | 452  | 0.6462          | 0.85     |
| 0.0083        | 5.0   | 565  | 0.6071          | 0.87     |
| 0.0281        | 6.0   | 678  | 0.5648          | 0.87     |
| 0.0001        | 7.0   | 791  | 0.4394          | 0.92     |
| 0.0002        | 8.0   | 904  | 0.4378          | 0.9      |
| 0.1345        | 9.0   | 1017 | 0.4299          | 0.9      |
| 0.0002        | 10.0  | 1130 | 0.4400          | 0.91     |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3