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MatanBT/
swin-tiny-patch4-window7-224-cifar10

Name: swin-tiny-patch4-window7-224-cifar10
Availability: InStock

generated_from_trainer

microsoft/swin-tiny-patch4-window7-224

finetune

apache-2.0

endpoints_compatible

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swin-tiny-patch4-window7-224-cifar10

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

Loss: 0.0995
Accuracy: 0.9803

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: 128
eval_batch_size: 64
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 0.1
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1430	1.2788	500	0.1258	0.9588
0.0699	2.5575	1000	0.1101	0.9676
0.0489	3.8363	1500	0.1001	0.9713
0.0234	5.1151	2000	0.1054	0.9734
0.0136	6.3939	2500	0.0970	0.98
0.0080	7.6726	3000	0.0995	0.9803
0.0059	8.9514	3500	0.1005	0.9799

Framework versions

Transformers 5.3.0
Pytorch 2.6.0+cu124
Datasets 4.8.3
Tokenizers 0.22.2

MatanBT/swin-tiny-patch4-window7-224-cifar10

swin-tiny-patch4-window7-224-cifar10

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

MatanBT/
swin-tiny-patch4-window7-224-cifar10