---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ViTuned_buildings
  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. -->

# ViTuned_buildings

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: 0.0432
- Accuracy: 0.9931

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1985        | 0.33  | 100  | 1.1271          | 0.9726   |
| 0.4085        | 0.67  | 200  | 0.3959          | 0.9743   |
| 0.186         | 1.0   | 300  | 0.1963          | 0.9846   |
| 0.1066        | 1.34  | 400  | 0.2404          | 0.9417   |
| 0.1117        | 1.67  | 500  | 0.1423          | 0.9726   |
| 0.0923        | 2.01  | 600  | 0.1076          | 0.9794   |
| 0.0315        | 2.34  | 700  | 0.0656          | 0.9846   |
| 0.0263        | 2.68  | 800  | 0.0645          | 0.9880   |
| 0.0542        | 3.01  | 900  | 0.0458          | 0.9949   |
| 0.0203        | 3.34  | 1000 | 0.0444          | 0.9931   |
| 0.0189        | 3.68  | 1100 | 0.0432          | 0.9931   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2