---
license: bsd-3-clause
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ast_13-finetuned-ICBHI
  results: []
---

<!-- 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_13-finetuned-ICBHI

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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0981
- Accuracy: 0.5811
- Sensitivity: 0.0484
- Specificity: 0.9785
- Score: 0.5134

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Sensitivity | Specificity | Score  |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:-----------:|:------:|
| 1.0311        | 1.0   | 259  | 1.0981          | 0.5811   | 0.0484      | 0.9785      | 0.5134 |
| 1.1378        | 2.0   | 518  | 1.0778          | 0.5800   | 0.1427      | 0.9062      | 0.5245 |
| 1.0184        | 3.0   | 777  | 1.0696          | 0.5779   | 0.1495      | 0.8973      | 0.5234 |
| 1.0743        | 4.0   | 1036 | 1.0705          | 0.5757   | 0.1946      | 0.8599      | 0.5273 |
| 0.9974        | 5.0   | 1295 | 1.0692          | 0.5789   | 0.1963      | 0.8644      | 0.5303 |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3