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jialicheng/
unlearn-so_cifar10_swin-base_salun_10_100

Name: unlearn-so_cifar10_swin-base_salun_10_100
Availability: InStock

generated_from_trainer

microsoft/swin-base-patch4-window7-224

finetune

apache-2.0

endpoints_compatible

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100

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

Loss: 0.1653
Accuracy: 0.9716
Dt Accuracy: 0.9716
Df Accuracy: 0.794
Unlearn Overall Accuracy: 0.4664
Unlearn Time: None

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: 0.0001
train_batch_size: 128
eval_batch_size: 256
seed: 100
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Overall Accuracy	Unlearn Overall Accuracy	Time
No log	1.0	391	0.2300	0.8654	0.3786	0.3786	None
0.659	2.0	782	0.1767	0.9116	0.3164	0.3164	None
0.5956	3.0	1173	0.1897	0.9056	0.3247	0.3247	None
0.5536	4.0	1564	0.1799	0.9152	0.3113	0.3113	None
0.5536	5.0	1955	0.1911	0.9178	0.3077	0.3077	None
0.513	6.0	2346	0.1492	0.9114	0.3168	0.3168	None
0.4783	7.0	2737	0.1692	0.8992	0.3338	0.3338	None
0.4402	8.0	3128	0.1768	0.8646	0.3799	0.3799	None
0.4021	9.0	3519	0.1457	0.8452	0.4051	0.4051	None
0.4021	10.0	3910	0.1653	0.794	0.4664	0.4664	None

Framework versions

Transformers 4.48.0
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.21.0

jialicheng/unlearn-so_cifar10_swin-base_salun_10_100

100

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jialicheng/
unlearn-so_cifar10_swin-base_salun_10_100