---
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-eurosat
  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: 0.0
---

<!-- 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. -->

# swin-tiny-patch4-window7-224-finetuned-eurosat

This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co./microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 5.5031
- Accuracy: 0.0

## 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: 256
- eval_batch_size: 256
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 1024
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 1    | 0.6744          | 1.0      |
| No log        | 2.0   | 2    | 0.7507          | 0.0      |
| No log        | 3.0   | 3    | 0.9175          | 0.0      |
| No log        | 4.0   | 4    | 1.1669          | 0.0      |
| No log        | 5.0   | 5    | 1.4443          | 0.0      |
| No log        | 6.0   | 6    | 1.7218          | 0.0      |
| No log        | 7.0   | 7    | 2.0269          | 0.0      |
| No log        | 8.0   | 8    | 2.3374          | 0.0      |
| No log        | 9.0   | 9    | 2.6657          | 0.0      |
| 0.0781        | 10.0  | 10   | 2.9900          | 0.0      |
| 0.0781        | 11.0  | 11   | 3.2990          | 0.0      |
| 0.0781        | 12.0  | 12   | 3.5921          | 0.0      |
| 0.0781        | 13.0  | 13   | 3.8577          | 0.0      |
| 0.0781        | 14.0  | 14   | 4.1048          | 0.0      |
| 0.0781        | 15.0  | 15   | 4.3232          | 0.0      |
| 0.0781        | 16.0  | 16   | 4.5163          | 0.0      |
| 0.0781        | 17.0  | 17   | 4.6854          | 0.0      |
| 0.0781        | 18.0  | 18   | 4.8332          | 0.0      |
| 0.0781        | 19.0  | 19   | 4.9602          | 0.0      |
| 0.0003        | 20.0  | 20   | 5.0735          | 0.0      |
| 0.0003        | 21.0  | 21   | 5.1691          | 0.0      |
| 0.0003        | 22.0  | 22   | 5.2486          | 0.0      |
| 0.0003        | 23.0  | 23   | 5.3151          | 0.0      |
| 0.0003        | 24.0  | 24   | 5.3696          | 0.0      |
| 0.0003        | 25.0  | 25   | 5.4131          | 0.0      |
| 0.0003        | 26.0  | 26   | 5.4466          | 0.0      |
| 0.0003        | 27.0  | 27   | 5.4711          | 0.0      |
| 0.0003        | 28.0  | 28   | 5.4879          | 0.0      |
| 0.0003        | 29.0  | 29   | 5.4983          | 0.0      |
| 0.0           | 30.0  | 30   | 5.5031          | 0.0      |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3