---
license: bsd-3-clause
base_model: MIT/ast-finetuned-audioset-10-10-0.4593
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: ast-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: 0.93
---

<!-- 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-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: 0.4436
- Accuracy: 0.93

## 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: 4
- eval_batch_size: 4
- 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0001        | 1.0   | 225  | 0.5546          | 0.89     |
| 1.204         | 2.0   | 450  | 0.9484          | 0.81     |
| 0.4719        | 3.0   | 675  | 0.7417          | 0.85     |
| 0.0132        | 4.0   | 900  | 0.7101          | 0.9      |
| 0.0527        | 5.0   | 1125 | 0.8170          | 0.86     |
| 0.0           | 6.0   | 1350 | 0.6406          | 0.93     |
| 0.3099        | 7.0   | 1575 | 0.8426          | 0.84     |
| 0.0           | 8.0   | 1800 | 0.9173          | 0.89     |
| 0.0           | 9.0   | 2025 | 0.7142          | 0.9      |
| 0.0602        | 10.0  | 2250 | 0.4718          | 0.92     |
| 0.0003        | 11.0  | 2475 | 0.9860          | 0.9      |
| 0.0001        | 12.0  | 2700 | 0.5918          | 0.91     |
| 0.0           | 13.0  | 2925 | 0.4886          | 0.92     |
| 0.0           | 14.0  | 3150 | 0.4562          | 0.93     |
| 0.0           | 15.0  | 3375 | 0.4360          | 0.94     |
| 0.0           | 16.0  | 3600 | 0.4433          | 0.94     |
| 0.0           | 17.0  | 3825 | 0.4454          | 0.94     |
| 0.0           | 18.0  | 4050 | 0.4454          | 0.94     |
| 0.0           | 19.0  | 4275 | 0.4434          | 0.93     |
| 0.0           | 20.0  | 4500 | 0.4436          | 0.93     |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.2
- Tokenizers 0.13.3