---
license: bsd-3-clause
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ast_binary_7-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_7-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: 0.7561
- Accuracy: 0.5764
- Sensitivity: 0.6185
- Specificity: 0.5450
- Score: 0.5818

## 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  |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:-----------:|:------:|
| 0.6321        | 1.0   | 259  | 0.7561          | 0.5764   | 0.6185      | 0.5450      | 0.5818 |
| 0.5672        | 2.0   | 518  | 0.8579          | 0.5626   | 0.6015      | 0.5336      | 0.5676 |
| 0.5443        | 3.0   | 777  | 1.0517          | 0.5074   | 0.8275      | 0.2687      | 0.5481 |
| 0.5075        | 4.0   | 1036 | 0.9977          | 0.5358   | 0.7638      | 0.3657      | 0.5647 |
| 0.4912        | 5.0   | 1295 | 1.2474          | 0.4969   | 0.8539      | 0.2307      | 0.5423 |
| 0.4331        | 6.0   | 1554 | 1.0732          | 0.5376   | 0.7077      | 0.4106      | 0.5592 |
| 0.4368        | 7.0   | 1813 | 1.0947          | 0.5405   | 0.7230      | 0.4043      | 0.5637 |


### Framework versions

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