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# ast-finetuned-audioset-10-10-0.4593_ft_env_aug_0-2

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: 0.6899
- Accuracy: 0.9643
- Precision: 0.9694
- Recall: 0.9643
- F1: 0.9631

## 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: 2e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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 | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 2.0165        | 1.0   | 28   | 1.6252          | 0.4643   | 0.5373    | 0.4643 | 0.4711 |
| 1.3702        | 2.0   | 56   | 1.0553          | 0.8571   | 0.8929    | 0.8571 | 0.8536 |
| 0.8861        | 3.0   | 84   | 0.6899          | 0.9643   | 0.9694    | 0.9643 | 0.9631 |
| 0.5655        | 4.0   | 112  | 0.4766          | 0.9643   | 0.9694    | 0.9643 | 0.9631 |
| 0.4232        | 5.0   | 140  | 0.3403          | 0.9643   | 0.9694    | 0.9643 | 0.9631 |
| 0.3148        | 6.0   | 168  | 0.2679          | 0.9643   | 0.9694    | 0.9643 | 0.9631 |
| 0.2335        | 7.0   | 196  | 0.2239          | 0.9643   | 0.9694    | 0.9643 | 0.9631 |
| 0.176         | 8.0   | 224  | 0.1979          | 0.9643   | 0.9694    | 0.9643 | 0.9631 |
| 0.1624        | 9.0   | 252  | 0.1824          | 0.9643   | 0.9694    | 0.9643 | 0.9631 |
| 0.1466        | 10.0  | 280  | 0.1781          | 0.9643   | 0.9694    | 0.9643 | 0.9631 |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0
- Datasets 2.10.1
- Tokenizers 0.11.0

{"license": "bsd-3-clause", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "precision", "recall", "f1"], "model-index": [{"name": "ast-finetuned-audioset-10-10-0.4593_ft_env_aug_0-2", "results": []}]}
transformers pytorch audio-spectrogram-transformer audio-classification generated_from_trainer license:bsd-3-clause endpoints_compatible region:us
TAGS
#transformers #pytorch #audio-spectrogram-transformer #audio-classification #generated_from_trainer #license-bsd-3-clause #endpoints_compatible #region-us 

ast-finetuned-audioset-10-10-0.4593\_ft\_env\_aug\_0-2
======================================================


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: 0.6899
* Accuracy: 0.9643
* Precision: 0.9694
* Recall: 0.9643
* F1: 0.9631


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: 2e-06
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 8
* 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 4.27.4
* Pytorch 2.0.0
* Datasets 2.10.1
* Tokenizers 0.11.0



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-06
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 8
* 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 4.27.4
* Pytorch 2.0.0
* Datasets 2.10.1
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #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: 2e-06
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 8
* 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 4.27.4
* Pytorch 2.0.0
* Datasets 2.10.1
* Tokenizers 0.11.0