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

Loss: nan
Accuracy: 0.3896

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: 64
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.91	5	nan	0.3896
0.0	2.0	11	nan	0.3896
0.0	2.73	15	nan	0.3896

Framework versions

Transformers 4.36.0
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.15.0

21nao3/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

21nao3/
swin-tiny-patch4-window7-224-finetuned-eurosat