---
license: bsd-3-clause
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ast_18-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_18-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: 1.0867
- Accuracy: 0.5757
- Sensitivity: 0.1164
- Specificity: 0.9183
- Score: 0.5173

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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  |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:-----------:|:------:|
| 1.5436        | 0.98  | 32   | 1.4656          | 0.1684   | 0.3127      | 0.0608      | 0.1867 |
| 1.2922        | 2.0   | 65   | 1.2055          | 0.4530   | 0.1121      | 0.7072      | 0.4097 |
| 1.2213        | 2.98  | 97   | 1.1364          | 0.5387   | 0.0450      | 0.9068      | 0.4759 |
| 1.149         | 4.0   | 130  | 1.1176          | 0.5543   | 0.0731      | 0.9132      | 0.4931 |
| 1.1558        | 4.98  | 162  | 1.1035          | 0.5630   | 0.0705      | 0.9303      | 0.5004 |
| 1.1363        | 6.0   | 195  | 1.1006          | 0.5655   | 0.1020      | 0.9113      | 0.5066 |
| 1.1138        | 6.98  | 227  | 1.0938          | 0.5699   | 0.1121      | 0.9113      | 0.5117 |
| 1.0807        | 8.0   | 260  | 1.0897          | 0.5742   | 0.1147      | 0.9170      | 0.5158 |
| 1.1071        | 8.98  | 292  | 1.0867          | 0.5757   | 0.1138      | 0.9202      | 0.5170 |
| 1.1017        | 9.85  | 320  | 1.0867          | 0.5757   | 0.1164      | 0.9183      | 0.5173 |


### Framework versions

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