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---
license: bsd-3-clause
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ast_13-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_13-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: 1.0981
- Accuracy: 0.5811
- Sensitivity: 0.0484
- Specificity: 0.9785
- Score: 0.5134
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:-----------:|:------:|
| 1.0311 | 1.0 | 259 | 1.0981 | 0.5811 | 0.0484 | 0.9785 | 0.5134 |
| 1.1378 | 2.0 | 518 | 1.0778 | 0.5800 | 0.1427 | 0.9062 | 0.5245 |
| 1.0184 | 3.0 | 777 | 1.0696 | 0.5779 | 0.1495 | 0.8973 | 0.5234 |
| 1.0743 | 4.0 | 1036 | 1.0705 | 0.5757 | 0.1946 | 0.8599 | 0.5273 |
| 0.9974 | 5.0 | 1295 | 1.0692 | 0.5789 | 0.1963 | 0.8644 | 0.5303 |
### Framework versions
- Transformers 4.29.2
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3