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jialicheng/
unlearn-so_cifar10_swin-base_random_label_4_21

Name: unlearn-so_cifar10_swin-base_random_label_4_21
Availability: InStock

generated_from_trainer

microsoft/swin-base-patch4-window7-224

finetune

apache-2.0

endpoints_compatible

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21

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: 0.0961
Accuracy: 0.9808
Dt Accuracy: 0.9808
Df Accuracy: 0.819
Unlearn Overall Accuracy: 0.4377
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: 21
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	0.1312	0.9705	0.2286	0.2286	None
0.5613	2.0	782	0.1494	0.9625	0.2408	0.2408	None
0.4867	3.0	1173	0.1689	0.9565	0.2499	0.2499	None
0.4385	4.0	1564	0.1442	0.9745	0.2225	0.2225	None
0.4385	5.0	1955	0.1137	0.975	0.2219	0.2219	None
0.3925	6.0	2346	0.0980	0.972	0.2267	0.2267	None
0.3576	7.0	2737	0.1060	0.942	0.2725	0.2725	None
0.3235	8.0	3128	0.0995	0.9205	0.3040	0.3040	None
0.2834	9.0	3519	0.1076	0.8315	0.4224	0.4224	None
0.2834	10.0	3910	0.0961	0.819	0.4377	0.4377	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_random_label_4_21

21

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jialicheng/
unlearn-so_cifar10_swin-base_random_label_4_21