---
license: bsd-3-clause
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ast_5-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_5-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: 1.2026
- Accuracy: 0.6547
- Sensitivity: 0.4720
- Specificity: 0.8181
- Score: 0.6451

## 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  |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:-----------:|:------:|
| 0.9246        | 1.0   | 258  | 0.9810          | 0.6076   | 0.5004      | 0.7035      | 0.6019 |
| 0.8279        | 2.0   | 517  | 0.8591          | 0.6478   | 0.3691      | 0.8970      | 0.6331 |
| 0.5969        | 3.0   | 776  | 0.9275          | 0.6446   | 0.5111      | 0.7639      | 0.6375 |
| 0.185         | 4.0   | 1035 | 1.2026          | 0.6547   | 0.4720      | 0.8181      | 0.6451 |
| 0.0305        | 4.99  | 1290 | 1.5138          | 0.6467   | 0.4873      | 0.7893      | 0.6383 |


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3