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# ast_20-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: 2.3414
- Accuracy: 0.6942
- Sensitivity: 0.5361
- Specificity: 0.8354
- Score: 0.6857

## 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  |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:-----------:|:------:|
| 0.895         | 1.0   | 345  | 0.9921          | 0.6029   | 0.2458      | 0.9218      | 0.5838 |
| 0.8244        | 2.0   | 690  | 0.8522          | 0.6717   | 0.4147      | 0.9012      | 0.6580 |
| 0.7002        | 3.0   | 1035 | 0.8378          | 0.6775   | 0.5346      | 0.8052      | 0.6699 |
| 0.415         | 4.0   | 1380 | 1.0645          | 0.6674   | 0.5392      | 0.7819      | 0.6605 |
| 0.19          | 5.0   | 1725 | 1.3827          | 0.6732   | 0.5207      | 0.8093      | 0.6650 |
| 0.0465        | 6.0   | 2070 | 1.7785          | 0.6754   | 0.5346      | 0.8011      | 0.6678 |
| 0.0078        | 7.0   | 2415 | 2.0612          | 0.6819   | 0.6252      | 0.7325      | 0.6789 |
| 0.0003        | 8.0   | 2760 | 2.2956          | 0.6971   | 0.5376      | 0.8395      | 0.6886 |
| 0.0001        | 9.0   | 3105 | 2.3499          | 0.6942   | 0.5192      | 0.8505      | 0.6848 |
| 0.0001        | 10.0  | 3450 | 2.3414          | 0.6942   | 0.5361      | 0.8354      | 0.6857 |


### Framework versions

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

{"license": "bsd-3-clause", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "ast_20-finetuned-ICBHI", "results": []}]}
transformers pytorch tensorboard audio-spectrogram-transformer audio-classification generated_from_trainer license:bsd-3-clause endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #audio-spectrogram-transformer #audio-classification #generated_from_trainer #license-bsd-3-clause #endpoints_compatible #region-us 

ast\_20-finetuned-ICBHI
=======================


This model is a fine-tuned version of MIT/ast-finetuned-audioset-10-10-0.4593 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 2.3414
* Accuracy: 0.6942
* Sensitivity: 0.5361
* Specificity: 0.8354
* Score: 0.6857


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



### Framework versions


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



### 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 ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #audio-spectrogram-transformer #audio-classification #generated_from_trainer #license-bsd-3-clause #endpoints_compatible #region-us 
 ### 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 ### Framework versions


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