---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swinv2-large-patch4-window12to16-192to256-22kto1k-ft-finetuned-eurosat-50
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: Augmented-Final
      split: train
      args: Augmented-Final
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9722507708119219
---

<!-- 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. -->

# swinv2-large-patch4-window12to16-192to256-22kto1k-ft-finetuned-eurosat-50

This model is a fine-tuned version of [microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft](https://huggingface.co/microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0966
- Accuracy: 0.9723

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.5
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9035        | 1.0   | 61   | 1.8946          | 0.2713   |
| 1.4731        | 2.0   | 122  | 1.2931          | 0.5560   |
| 0.9549        | 3.0   | 183  | 0.7530          | 0.6999   |
| 0.7375        | 4.0   | 244  | 0.4989          | 0.8129   |
| 0.615         | 5.0   | 305  | 0.3545          | 0.8746   |
| 0.4751        | 6.0   | 366  | 0.2399          | 0.9168   |
| 0.3778        | 7.0   | 427  | 0.1628          | 0.9558   |
| 0.3054        | 8.0   | 488  | 0.1202          | 0.9620   |
| 0.2787        | 9.0   | 549  | 0.0988          | 0.9733   |
| 0.253         | 10.0  | 610  | 0.0966          | 0.9723   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3