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jialicheng/
unlearn-so_cifar10_swin-base_salun_2_87

Name: unlearn-so_cifar10_swin-base_salun_2_87
Availability: InStock

generated_from_trainer

microsoft/swin-base-patch4-window7-224

finetune

apache-2.0

endpoints_compatible

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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: 0.0700
Accuracy: 0.9855
Dt Accuracy: 0.9855
Df Accuracy: 0.792
Unlearn Overall Accuracy: 0.4703
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: 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	0.1010	0.883	0.3556	0.3556	None
0.4207	2.0	782	0.1039	0.888	0.3485	0.3485	None
0.381	3.0	1173	0.0764	0.885	0.3531	0.3531	None
0.3375	4.0	1564	0.0868	0.894	0.3410	0.3410	None
0.3375	5.0	1955	0.0788	0.907	0.3231	0.3231	None
0.3031	6.0	2346	0.0782	0.903	0.3287	0.3287	None
0.2627	7.0	2737	0.0759	0.874	0.3682	0.3682	None
0.2383	8.0	3128	0.0795	0.843	0.4085	0.4085	None
0.2129	9.0	3519	0.0763	0.804	0.4561	0.4561	None
0.2129	10.0	3910	0.0700	0.792	0.4703	0.4703	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_salun_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_salun_2_87