---
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: 0.6363636363636364
---

<!-- 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: 1.8592
- Accuracy: 0.6364

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9595        | 1.0   | 11   | 1.6120          | 0.0909   |
| 1.3053        | 2.0   | 22   | 1.3677          | 0.2727   |
| 0.7604        | 3.0   | 33   | 1.9563          | 0.1818   |
| 0.4351        | 4.0   | 44   | 1.3875          | 0.5455   |
| 0.316         | 5.0   | 55   | 1.7235          | 0.5455   |
| 0.0949        | 6.0   | 66   | 1.5362          | 0.6364   |
| 0.0355        | 7.0   | 77   | 1.8020          | 0.5455   |
| 0.0156        | 8.0   | 88   | 1.8320          | 0.6364   |
| 0.0102        | 9.0   | 99   | 1.9028          | 0.6364   |
| 0.0061        | 10.0  | 110  | 1.8592          | 0.6364   |


### Framework versions

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