---
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: distil-ast-audioset-finetuned-gtzan-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. -->

# distil-ast-audioset-finetuned-gtzan-finetuned-gtzan

This model is a fine-tuned version of [peterdamn/distil-ast-audioset-finetuned-gtzan](https://huggingface.co/peterdamn/distil-ast-audioset-finetuned-gtzan) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8269
- Accuracy: 0.84

## 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: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2642        | 1.0   | 225  | 1.0594          | 0.8      |
| 0.1655        | 2.0   | 450  | 0.9670          | 0.84     |
| 0.0009        | 3.0   | 675  | 0.9774          | 0.79     |
| 0.0093        | 4.0   | 900  | 0.9330          | 0.83     |
| 0.0           | 5.0   | 1125 | 0.8269          | 0.84     |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2