This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the cifar10 dataset. It achieves the following results on the evaluation set:

Loss: 0.1681
Accuracy: 0.9414

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.7686	1.0	351	0.2945	0.902
0.5339	2.0	703	0.1910	0.9336
0.4822	2.99	1053	0.1681	0.9414

Framework versions

Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.0
Tokenizers 0.13.3

2022happy/swin-tiny-patch4-window7-224-pruned-0.1-Ln-finetuned-eurosat

swin-tiny-patch4-window7-224-pruned-0.1-Ln-finetuned-eurosat

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

2022happy/
swin-tiny-patch4-window7-224-pruned-0.1-Ln-finetuned-eurosat