---
license: bsd-3-clause
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ast_21-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_21-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: 2.5318
- Accuracy: 0.6797
- Sensitivity: 0.5322
- Specificity: 0.8118
- Score: 0.6720

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Sensitivity | Specificity | Score  |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:-----------:|:------:|
| 0.8802        | 1.0   | 345  | 0.9189          | 0.6355   | 0.3236      | 0.9148      | 0.6192 |
| 0.8729        | 2.0   | 690  | 0.8915          | 0.6283   | 0.5138      | 0.7308      | 0.6223 |
| 0.6646        | 3.0   | 1035 | 0.9005          | 0.6551   | 0.6043      | 0.7005      | 0.6524 |
| 0.3145        | 4.0   | 1380 | 1.1884          | 0.6572   | 0.4018      | 0.8860      | 0.6439 |
| 0.2176        | 5.0   | 1725 | 1.4167          | 0.6623   | 0.5828      | 0.7335      | 0.6582 |
| 0.1556        | 6.0   | 2070 | 1.9695          | 0.6732   | 0.5061      | 0.8228      | 0.6645 |
| 0.0144        | 7.0   | 2415 | 2.3115          | 0.6761   | 0.5506      | 0.7885      | 0.6695 |
| 0.0001        | 8.0   | 2760 | 2.4443          | 0.6746   | 0.5291      | 0.8049      | 0.6670 |
| 0.0001        | 9.0   | 3105 | 2.5163          | 0.6775   | 0.5291      | 0.8104      | 0.6698 |
| 0.0001        | 10.0  | 3450 | 2.5318          | 0.6797   | 0.5322      | 0.8118      | 0.6720 |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3