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# genderage2

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2771

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.3737        | 0.89  | 100  | 0.3702          |
| 0.3208        | 1.79  | 200  | 0.3308          |
| 0.2681        | 2.68  | 300  | 0.2977          |
| 0.2334        | 3.57  | 400  | 0.2875          |
| 0.2093        | 4.46  | 500  | 0.2840          |
| 0.1989        | 5.36  | 600  | 0.2798          |
| 0.1801        | 6.25  | 700  | 0.2785          |
| 0.1707        | 7.14  | 800  | 0.2771          |


### Framework versions

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

female male age0to5 age6to10 age11to15 age16to25 age26to35 age36to49 age50to69 age70to99