---
library_name: transformers
license: bsd-3-clause
base_model: MIT/ast-finetuned-audioset-10-10-0.4593
tags:
- generated_from_trainer
datasets:
- kim2024military
metrics:
- accuracy
model-index:
- name: ast-finetuned-audioset-10-10-0.4593-finetuned-MAD
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: MAD
      type: kim2024military
      config: default
      split: test
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9344262295081968
---

<!-- 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-MAD

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 MAD dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0444
- Accuracy: 0.9344

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2166        | 1.0   | 402  | 0.5008          | 0.8959   |
| 0.4771        | 2.0   | 804  | 0.7085          | 0.9257   |
| 0.1525        | 3.0   | 1206 | 0.9449          | 0.9373   |
| 0.1688        | 4.0   | 1608 | 1.1073          | 0.9219   |
| 0.1975        | 5.0   | 2010 | 1.2495          | 0.9209   |
| 0.0           | 6.0   | 2412 | 1.0608          | 0.9306   |
| 0.0           | 7.0   | 2814 | 1.0338          | 0.9344   |
| 0.0           | 8.0   | 3216 | 1.0192          | 0.9373   |
| 0.0           | 9.0   | 3618 | 1.0345          | 0.9344   |
| 0.0           | 10.0  | 4020 | 1.0444          | 0.9344   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3