---
library_name: transformers
base_model: nateraw/vit-age-classifier
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: results
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9875
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# results

This model is a fine-tuned version of [nateraw/vit-age-classifier](https://huggingface.co/nateraw/vit-age-classifier) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0824
- Accuracy: 0.9875

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 100  | 1.5403          | 0.5375   |
| No log        | 2.0   | 200  | 0.7882          | 0.725    |
| No log        | 3.0   | 300  | 0.2481          | 0.9875   |
| No log        | 4.0   | 400  | 0.1088          | 0.9875   |
| 0.8658        | 5.0   | 500  | 0.0824          | 0.9875   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1