---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- HHD
- 3_class
- ViT
- generated_from_trainer
model-index:
- name: ViT_face
  results: []
---

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

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 face dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5240

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 38   | 0.9844          |
| No log        | 2.0   | 76   | 0.8261          |
| No log        | 3.0   | 114  | 0.6908          |
| No log        | 4.0   | 152  | 0.6297          |
| No log        | 5.0   | 190  | 0.5770          |
| No log        | 6.0   | 228  | 0.5463          |
| No log        | 7.0   | 266  | 0.5250          |
| No log        | 8.0   | 304  | 0.5263          |
| No log        | 9.0   | 342  | 0.5306          |
| No log        | 10.0  | 380  | 0.5240          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1