
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# face_age_detection_base_v3_weighted

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0928
- Accuracy: 0.9691

## 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-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 6

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.1216        | 0.9968 | 157  | 0.1257          | 0.9567   |
| 0.1109        | 1.9952 | 314  | 0.1100          | 0.9637   |
| 0.0947        | 2.9937 | 471  | 0.1097          | 0.9640   |
| 0.0745        | 3.9984 | 629  | 0.0928          | 0.9679   |
| 0.0565        | 4.9968 | 786  | 0.0941          | 0.9668   |
| 0.0716        | 5.9889 | 942  | 0.0928          | 0.9691   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.3

minor adult