---
license: apache-2.0
base_model: bookbot/distil-ast-audioset
tags:
- generated_from_trainer
datasets:
- Nooon/Donate_a_cry
metrics:
- accuracy
model-index:
- name: distil-ast-audioset-finetuned-cry
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: DonateACry
      type: Nooon/Donate_a_cry
      config: train
      split: train
      args: train
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9347826086956522
---

<!-- 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-cry

This model is a fine-tuned version of [bookbot/distil-ast-audioset](https://huggingface.co/bookbot/distil-ast-audioset) on the DonateACry dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2731
- Accuracy: 0.9348

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.424         | 1.0   | 46   | 0.2375          | 0.9565   |
| 0.5755        | 2.0   | 92   | 0.3218          | 0.9565   |
| 0.5466        | 3.0   | 138  | 0.1731          | 0.9565   |
| 0.3545        | 4.0   | 184  | 0.2719          | 0.9348   |
| 0.0759        | 5.0   | 230  | 0.1582          | 0.9348   |
| 0.0178        | 6.0   | 276  | 0.2576          | 0.9130   |
| 0.0032        | 7.0   | 322  | 0.2695          | 0.9348   |
| 0.0014        | 8.0   | 368  | 0.2496          | 0.9348   |
| 0.0005        | 9.0   | 414  | 0.2639          | 0.9348   |
| 0.0004        | 10.0  | 460  | 0.2731          | 0.9348   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1