---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-base-images
  results: []
---

<!-- 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. -->

# vit-base-images

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3465
- Accuracy: 0.905

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7334        | 0.4   | 100  | 0.6142          | 0.779    |
| 0.6032        | 0.8   | 200  | 0.5516          | 0.808    |
| 0.4725        | 1.2   | 300  | 0.4390          | 0.854    |
| 0.3638        | 1.6   | 400  | 0.4622          | 0.822    |
| 0.3279        | 2.0   | 500  | 0.3772          | 0.876    |
| 0.1337        | 2.4   | 600  | 0.4518          | 0.869    |
| 0.236         | 2.8   | 700  | 0.3766          | 0.878    |
| 0.0275        | 3.2   | 800  | 0.3518          | 0.891    |
| 0.0427        | 3.6   | 900  | 0.3709          | 0.896    |
| 0.0363        | 4.0   | 1000 | 0.3465          | 0.905    |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1