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jialicheng/
unlearn_cifar10_swin-base_salun_8_42

Name: unlearn_cifar10_swin-base_salun_8_42
Availability: InStock

generated_from_trainer

microsoft/swin-base-patch4-window7-224

finetune

apache-2.0

endpoints_compatible

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42

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: 0.1292
Accuracy: 0.9613
Dt Accuracy: 0.9613
Df Accuracy: 0.183
Unlearn Overall Accuracy: 0.9429
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: 42
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: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Overall Accuracy	Unlearn Overall Accuracy	Time
No log	1.0	391	0.1645	0.9247	0.2976	0.2976	None
0.5124	2.0	782	0.1573	0.912	0.3159	0.3159	None
0.475	3.0	1173	0.1458	0.9187	0.3062	0.3062	None
0.4633	4.0	1564	0.1423	0.9167	0.3093	0.3093	None
0.4633	5.0	1955	0.1317	0.8868	0.3508	0.3508	None
0.4346	6.0	2346	0.1369	0.868	0.3758	0.3758	None
0.4102	7.0	2737	0.1492	0.827	0.4273	0.4273	None
0.3817	8.0	3128	0.1626	0.7385	0.5280	0.5280	None
0.3512	9.0	3519	0.1587	0.6468	0.6183	0.6183	None
0.3512	10.0	3910	0.1697	0.545	0.7049	0.7049	None
0.3133	11.0	4301	0.1652	0.4525	0.7755	0.7755	None
0.2823	12.0	4692	0.1357	0.4288	0.7943	0.7943	None
0.2581	13.0	5083	0.1356	0.378	0.8283	0.8283	None
0.2581	14.0	5474	0.1346	0.294	0.8809	0.8809	None
0.2301	15.0	5865	0.1391	0.2805	0.8875	0.8875	None
0.2054	16.0	6256	0.1318	0.228	0.9178	0.9178	None
0.19	17.0	6647	0.1308	0.2265	0.9189	0.9189	None
0.1749	18.0	7038	0.1343	0.1968	0.9352	0.9352	None
0.1749	19.0	7429	0.1242	0.1943	0.9375	0.9375	None
0.1603	20.0	7820	0.1292	0.183	0.9429	0.9429	None

Framework versions

Transformers 4.48.0
Pytorch 2.2.2+cu118
Datasets 3.2.0
Tokenizers 0.21.0

jialicheng/unlearn_cifar10_swin-base_salun_8_42

42

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jialicheng/
unlearn_cifar10_swin-base_salun_8_42