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jialicheng/
unlearn-so_cifar10_swin-base_salun_8_100

Name: unlearn-so_cifar10_swin-base_salun_8_100
Availability: InStock

generated_from_trainer

microsoft/swin-base-patch4-window7-224

finetune

apache-2.0

endpoints_compatible

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100

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: 0.1468
Accuracy: 0.9713
Dt Accuracy: 0.9713
Df Accuracy: 0.7628
Unlearn Overall Accuracy: 0.5018
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: 100
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	0.1523	0.8908	0.3449	0.3449	None
0.6093	2.0	782	0.1887	0.8945	0.3399	0.3399	None
0.5511	3.0	1173	0.1500	0.9145	0.3123	0.3123	None
0.5084	4.0	1564	0.1658	0.9183	0.3070	0.3070	None
0.5084	5.0	1955	0.1557	0.9143	0.3127	0.3127	None
0.4709	6.0	2346	0.1486	0.9073	0.3226	0.3226	None
0.4335	7.0	2737	0.1504	0.889	0.3476	0.3476	None
0.3941	8.0	3128	0.1477	0.851	0.3977	0.3977	None
0.3617	9.0	3519	0.1308	0.8237	0.4317	0.4317	None
0.3617	10.0	3910	0.1468	0.7628	0.5018	0.5018	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_8_100

100

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jialicheng/
unlearn-so_cifar10_swin-base_salun_8_100