---
base_model: wetdog/TUT-urban-acoustic-scenes-2018-development
tags:
- audio-classification
- generated_from_trainer
datasets:
- acoustic-scenes
metrics:
- accuracy
model-index:
- name: ast-finetuned-audioset-10-10-0.4593-TUT-acoustic-scenes
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: TUT-urban-acoustic-scenes-2018-development
      type: acoustic-scenes
      args: 'split: train'
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.52
---

<!-- 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-TUT-acoustic-scenes

This model is a fine-tuned version of [wetdog/TUT-urban-acoustic-scenes-2018-development](https://huggingface.co/wetdog/TUT-urban-acoustic-scenes-2018-development) on the TUT-urban-acoustic-scenes-2018-development dataset.
It achieves the following results on the evaluation set:
- Loss: 4.4942
- Accuracy: 0.52

## 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: 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
- training_steps: 4000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.212         | 0.12  | 500  | 2.5780          | 0.375    |
| 0.5031        | 1.12  | 1000 | 3.6818          | 0.435    |
| 0.2583        | 2.12  | 1500 | 3.8194          | 0.465    |
| 0.0828        | 3.12  | 2000 | 4.3022          | 0.455    |
| 0.0367        | 4.12  | 2500 | 4.6687          | 0.45     |
| 0.0054        | 5.12  | 3000 | 4.8838          | 0.465    |
| 0.0014        | 6.12  | 3500 | 4.6808          | 0.495    |
| 0.0029        | 7.12  | 4000 | 4.4942          | 0.52     |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3