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jialicheng/
unlearn-so_cifar10_swin-base_random_label_6_21

Name: unlearn-so_cifar10_swin-base_random_label_6_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: 0.1227
Accuracy: 0.9787
Dt Accuracy: 0.9787
Df Accuracy: 0.8317
Unlearn Overall Accuracy: 0.4220
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	0.2027	0.967	0.2339	0.2339	None
0.6194	2.0	782	0.1540	0.967	0.2341	0.2341	None
0.5472	3.0	1173	0.1622	0.9697	0.2300	0.2300	None
0.4983	4.0	1564	0.1490	0.974	0.2234	0.2234	None
0.4983	5.0	1955	0.1327	0.975	0.2219	0.2219	None
0.4508	6.0	2346	0.1261	0.9753	0.2214	0.2214	None
0.4119	7.0	2737	0.1350	0.9533	0.2554	0.2554	None
0.38	8.0	3128	0.1432	0.9167	0.3093	0.3093	None
0.3386	9.0	3519	0.1245	0.874	0.3679	0.3679	None
0.3386	10.0	3910	0.1227	0.8317	0.4220	0.4220	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_6_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_6_21