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---
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
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