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jialicheng/
unlearn-so_cifar10_swin-base_random_label_8_21

Name: unlearn-so_cifar10_swin-base_random_label_8_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: 0.1464
Accuracy: 0.9747
Dt Accuracy: 0.9747
Df Accuracy: 0.7853
Unlearn Overall Accuracy: 0.4769
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	0.2017	0.973	0.2246	0.2246	None
0.6698	2.0	782	0.1854	0.9762	0.2196	0.2196	None
0.6002	3.0	1173	0.1599	0.9785	0.2163	0.2163	None
0.5443	4.0	1564	0.1837	0.9778	0.2174	0.2174	None
0.5443	5.0	1955	0.1724	0.9768	0.2190	0.2190	None
0.5022	6.0	2346	0.1409	0.9685	0.2322	0.2322	None
0.4602	7.0	2737	0.1560	0.9495	0.2613	0.2613	None
0.4172	8.0	3128	0.1779	0.864	0.3807	0.3807	None
0.3783	9.0	3519	0.1588	0.8117	0.4458	0.4458	None
0.3783	10.0	3910	0.1464	0.7853	0.4769	0.4769	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_8_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_8_21