---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: hurricane_model
  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. -->

# hurricane_model

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 jonathan-roberts1/Satellite-Images-of-Hurricane-Damage dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0224
- Model Preparation Time: 0.0051
- Accuracy: 0.9948

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Model Preparation Time | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:----------------------:|:--------:|
| 0.1118        | 0.3195 | 100  | 0.1486          | 0.0051                 | 0.9476   |
| 0.1112        | 0.6390 | 200  | 0.0701          | 0.0051                 | 0.9752   |
| 0.0694        | 0.9585 | 300  | 0.0608          | 0.0051                 | 0.9808   |
| 0.0048        | 1.2780 | 400  | 0.0917          | 0.0051                 | 0.9744   |
| 0.036         | 1.5974 | 500  | 0.0552          | 0.0051                 | 0.9836   |
| 0.0594        | 1.9169 | 600  | 0.0547          | 0.0051                 | 0.9808   |
| 0.0115        | 2.2364 | 700  | 0.0627          | 0.0051                 | 0.9844   |
| 0.0016        | 2.5559 | 800  | 0.0296          | 0.0051                 | 0.9936   |
| 0.004         | 2.8754 | 900  | 0.0325          | 0.0051                 | 0.9916   |
| 0.0009        | 3.1949 | 1000 | 0.0224          | 0.0051                 | 0.9948   |
| 0.0008        | 3.5144 | 1100 | 0.0270          | 0.0051                 | 0.9936   |
| 0.0008        | 3.8339 | 1200 | 0.0256          | 0.0051                 | 0.994    |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3