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# swin-tiny-patch4-window7-224-finetuned-ai-not

This model is a fine-tuned version of [lukee/swin-tiny-patch4-window7-224-finetuned-ai-not](https://huggingface.co/lukee/swin-tiny-patch4-window7-224-finetuned-ai-not) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0827
- Accuracy: 0.9796
- F1: 0.9794
- Log Loss: 0.7049

## 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: 5e-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 | F1     | Log Loss |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|
| 0.1026        | 1.0   | 131  | 0.0761          | 0.9715   | 0.9713 | 0.9831   |
| 0.1111        | 2.0   | 262  | 0.1050          | 0.9597   | 0.9591 | 1.3912   |
| 0.0736        | 3.0   | 393  | 0.0736          | 0.9748   | 0.9745 | 0.8718   |
| 0.0708        | 4.0   | 524  | 0.0888          | 0.9694   | 0.9690 | 1.0573   |
| 0.0439        | 5.0   | 655  | 0.0998          | 0.9683   | 0.9679 | 1.0944   |
| 0.0514        | 6.0   | 786  | 0.0854          | 0.9705   | 0.9701 | 1.0202   |
| 0.0361        | 7.0   | 917  | 0.0737          | 0.9780   | 0.9778 | 0.7605   |
| 0.0256        | 8.0   | 1048 | 0.0764          | 0.9801   | 0.9799 | 0.6863   |
| 0.0375        | 9.0   | 1179 | 0.0740          | 0.9785   | 0.9783 | 0.7420   |
| 0.0257        | 10.0  | 1310 | 0.0827          | 0.9796   | 0.9794 | 0.7049   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "swin-tiny-patch4-window7-224-finetuned-ai-not", "results": []}]}
transformers pytorch tensorboard swin image-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #swin #image-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

swin-tiny-patch4-window7-224-finetuned-ai-not
=============================================


This model is a fine-tuned version of lukee/swin-tiny-patch4-window7-224-finetuned-ai-not on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0827
* Accuracy: 0.9796
* F1: 0.9794
* Log Loss: 0.7049


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: 5e-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



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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 ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #swin #image-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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 ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #swin #image-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2