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jialicheng/
unlearn-so_cifar10_swin-base_random_label_6_87

Name: unlearn-so_cifar10_swin-base_random_label_6_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: 0.1207
Accuracy: 0.9769
Dt Accuracy: 0.9769
Df Accuracy: 0.7893
Unlearn Overall Accuracy: 0.4725
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	0.1615	0.9623	0.2412	0.2412	None
0.6135	2.0	782	0.1615	0.9743	0.2227	0.2227	None
0.546	3.0	1173	0.1423	0.9773	0.2181	0.2181	None
0.4974	4.0	1564	0.1341	0.98	0.2140	0.2140	None
0.4974	5.0	1955	0.1264	0.978	0.2171	0.2171	None
0.4556	6.0	2346	0.1434	0.9633	0.2400	0.2400	None
0.4085	7.0	2737	0.1187	0.9597	0.2458	0.2458	None
0.3774	8.0	3128	0.1326	0.895	0.3396	0.3396	None
0.3322	9.0	3519	0.1177	0.8307	0.4233	0.4233	None
0.3322	10.0	3910	0.1207	0.7893	0.4725	0.4725	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_6_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_random_label_6_87