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# image_age_classification

This model is a fine-tuned version of [nateraw/vit-age-classifier](https://huggingface.co/nateraw/vit-age-classifier) on the fair_face dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9464
- Accuracy: 0.601

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9107        | 1.0   | 125  | 0.9360          | 0.6065   |
| 0.7945        | 2.0   | 250  | 0.9545          | 0.588    |
| 1.0256        | 3.0   | 375  | 1.0144          | 0.586    |
| 0.7354        | 4.0   | 500  | 0.9726          | 0.594    |
| 0.6979        | 5.0   | 625  | 0.9735          | 0.5995   |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 1.12.1+cu116
- Datasets 2.14.5
- Tokenizers 0.12.1

0-2 3-9 10-19 20-29 30-39 40-49 50-59 60-69 more than 70