This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.0271
Accuracy: 0.9967

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0898	1.0	327	0.0707	0.9757
0.0221	2.0	654	0.0278	0.9920
0.06	3.0	981	0.0345	0.9913
0.0094	4.0	1309	0.0300	0.9947
0.0004	5.0	1636	0.0398	0.9942
0.0035	6.0	1963	0.0136	0.9975
0.0246	7.0	2290	0.0339	0.9940
0.0012	8.0	2618	0.0316	0.9958
0.0	9.0	2945	0.0302	0.9964
0.0	10.0	3272	0.0201	0.9973
0.0003	11.0	3599	0.0222	0.9955
0.0	12.0	3927	0.0218	0.9962
0.0001	13.0	4254	0.0293	0.9962
0.0002	14.0	4581	0.0272	0.9962
0.0	14.99	4905	0.0271	0.9967

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.15.0
Tokenizers 0.15.0

andrecastro/swin-tiny-patch4-window7-224-finetuned-eurosat

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

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

andrecastro/
swin-tiny-patch4-window7-224-finetuned-eurosat