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jialicheng/
unlearn-so_cifar10_swin-base_bad_teaching_2_87

Name: unlearn-so_cifar10_swin-base_bad_teaching_2_87
Availability: InStock

generated_from_trainer

microsoft/swin-base-patch4-window7-224

finetune

apache-2.0

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87

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: 0.8609
Accuracy: 0.9619
Dt Accuracy: 0.9619
Df Accuracy: 0.959
Unlearn Overall Accuracy: 0.2462
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: 87
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	0.5547	0.962	0.2416	0.2416	None
No log	2.0	32	1.2324	0.941	0.2723	0.2723	None
No log	3.0	48	0.9226	0.963	0.2400	0.2400	None
No log	4.0	64	0.8922	0.965	0.2370	0.2370	None
No log	5.0	80	0.8288	0.969	0.2309	0.2309	None
No log	6.0	96	0.9246	0.972	0.2262	0.2262	None
No log	7.0	112	0.8645	0.964	0.2386	0.2386	None
No log	8.0	128	0.9277	0.961	0.2431	0.2431	None
No log	9.0	144	0.8539	0.958	0.2477	0.2477	None
No log	10.0	160	0.8609	0.959	0.2462	0.2462	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_87

87

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_87