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# genderage_convnext

This model is a fine-tuned version of [facebook/convnext-base-224](https://huggingface.co/facebook/convnext-base-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3896

## 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: 1e-05
- train_batch_size: 11
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.5114        | 0.89  | 100  | 0.4998          |
| 0.425         | 1.79  | 200  | 0.4246          |
| 0.4124        | 2.68  | 300  | 0.4100          |
| 0.4034        | 3.57  | 400  | 0.4037          |
| 0.3938        | 4.46  | 500  | 0.3992          |
| 0.4021        | 5.36  | 600  | 0.3952          |
| 0.3843        | 6.25  | 700  | 0.3918          |
| 0.3804        | 7.14  | 800  | 0.3896          |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "model-index": [{"name": "genderage_convnext", "results": []}]}
transformers pytorch convnext image-classification generated_from_trainer dataset:imagefolder license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #convnext #image-classification #generated_from_trainer #dataset-imagefolder #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

genderage\_convnext
===================


This model is a fine-tuned version of facebook/convnext-base-224 on the imagefolder dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3896


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: 1e-05
* train\_batch\_size: 11
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 8
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.25.1
* Pytorch 1.13.1+cu117
* Datasets 2.8.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 11
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 8
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.25.1
* Pytorch 1.13.1+cu117
* Datasets 2.8.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #convnext #image-classification #generated_from_trainer #dataset-imagefolder #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 11
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 8
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.25.1
* Pytorch 1.13.1+cu117
* Datasets 2.8.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #convnext #image-classification #generated_from_trainer #dataset-imagefolder #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 11
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 8
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.25.1
* Pytorch 1.13.1+cu117
* Datasets 2.8.0
* Tokenizers 0.13.2