---
license: bsd-3-clause
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ast_binary_6-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_binary_6-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: 0.6811
- Accuracy: 0.6
- Sensitivity: 0.6593
- Specificity: 0.5558
- Score: 0.6075

## 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: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Sensitivity | Specificity | Score  |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:-----------:|:------:|
| 0.6592        | 1.0   | 259  | 0.6811          | 0.6      | 0.6593      | 0.5558      | 0.6075 |
| 0.5766        | 2.0   | 518  | 0.7937          | 0.5779   | 0.5939      | 0.5659      | 0.5799 |
| 0.5117        | 3.0   | 777  | 1.0242          | 0.5267   | 0.8139      | 0.3124      | 0.5632 |
| 0.5407        | 4.0   | 1036 | 0.9152          | 0.5445   | 0.8088      | 0.3473      | 0.5781 |
| 0.4504        | 5.0   | 1295 | 0.9963          | 0.5401   | 0.7596      | 0.3764      | 0.5680 |
| 0.4304        | 6.0   | 1554 | 0.9598          | 0.5579   | 0.6814      | 0.4658      | 0.5736 |
| 0.4132        | 7.0   | 1813 | 0.9771          | 0.5506   | 0.6950      | 0.4430      | 0.5690 |


### Framework versions

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