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---
license: apache-2.0
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: 0.9341978866474544
---
<!-- 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: 0.1507
- Accuracy: 0.9342
## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 12
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2891 | 1.0 | 146 | 0.2322 | 0.9068 |
| 0.2609 | 2.0 | 292 | 0.1710 | 0.9227 |
| 0.2417 | 3.0 | 438 | 0.1830 | 0.9251 |
| 0.2406 | 4.0 | 584 | 0.1809 | 0.9198 |
| 0.2113 | 5.0 | 730 | 0.1631 | 0.9289 |
| 0.1812 | 6.0 | 876 | 0.1561 | 0.9308 |
| 0.2082 | 7.0 | 1022 | 0.1507 | 0.9342 |
| 0.1922 | 8.0 | 1168 | 0.1611 | 0.9294 |
| 0.1715 | 9.0 | 1314 | 0.1536 | 0.9308 |
| 0.1675 | 10.0 | 1460 | 0.1609 | 0.9289 |
| 0.194 | 11.0 | 1606 | 0.1499 | 0.9337 |
| 0.1706 | 12.0 | 1752 | 0.1514 | 0.9323 |
### Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1
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