---
library_name: transformers
license: apache-2.0
base_model: bookbot/distil-ast-audioset
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: distil-ast-audioset-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: 0.88
---

<!-- 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

This model is a fine-tuned version of [bookbot/distil-ast-audioset](https://huggingface.co/bookbot/distil-ast-audioset) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3707
- 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.7768        | 0.9912 | 28   | 0.4780          | 0.85     |
| 0.4124        | 1.9823 | 56   | 0.4763          | 0.87     |
| 0.2095        | 2.9735 | 84   | 0.4231          | 0.89     |
| 0.0874        | 4.0    | 113  | 0.4250          | 0.87     |
| 0.0406        | 4.9912 | 141  | 0.4068          | 0.87     |
| 0.0205        | 5.9823 | 169  | 0.3918          | 0.88     |
| 0.0082        | 6.9735 | 197  | 0.3604          | 0.89     |
| 0.0082        | 8.0    | 226  | 0.3804          | 0.89     |
| 0.0059        | 8.9912 | 254  | 0.3821          | 0.87     |
| 0.004         | 9.9115 | 280  | 0.3707          | 0.88     |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1
- Datasets 3.0.0
- Tokenizers 0.19.1