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jialicheng/
unlearn-so_cifar10_swin-base_bad_teaching_2_21

Name: unlearn-so_cifar10_swin-base_bad_teaching_2_21
Availability: InStock

generated_from_trainer

microsoft/swin-base-patch4-window7-224

finetune

apache-2.0

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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: 0.9412
Accuracy: 0.955
Dt Accuracy: 0.955
Df Accuracy: 0.936
Unlearn Overall Accuracy: 0.2803
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
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	16	0.6313	0.963	0.2399	0.2399	None
No log	2.0	32	0.8377	0.951	0.2580	0.2580	None
No log	3.0	48	0.8592	0.962	0.2414	0.2414	None
No log	4.0	64	1.2518	0.943	0.2697	0.2697	None
No log	5.0	80	1.0190	0.954	0.2535	0.2535	None
No log	6.0	96	1.0689	0.944	0.2685	0.2685	None
No log	7.0	112	0.9776	0.951	0.2582	0.2582	None
No log	8.0	128	0.9352	0.941	0.2731	0.2731	None
No log	9.0	144	0.9614	0.938	0.2774	0.2774	None
No log	10.0	160	0.9412	0.936	0.2803	0.2803	None

Framework versions

Transformers 4.37.2
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.15.2

jialicheng/unlearn-so_cifar10_swin-base_bad_teaching_2_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_bad_teaching_2_21