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jialicheng/
unlearn_cifar10_swin-base_salun_10_87

Name: unlearn_cifar10_swin-base_salun_10_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: 0.1437
Accuracy: 0.9564
Dt Accuracy: 0.9564
Df Accuracy: 0.1894
Unlearn Overall Accuracy: 0.9372
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: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Overall Accuracy	Unlearn Overall Accuracy	Time
No log	1.0	391	0.1611	0.9218	0.3020	0.3020	None
0.5636	2.0	782	0.1624	0.9232	0.3001	0.3001	None
0.5188	3.0	1173	0.1547	0.9176	0.3081	0.3081	None
0.5058	4.0	1564	0.1797	0.9084	0.3211	0.3211	None
0.5058	5.0	1955	0.1411	0.9154	0.3113	0.3113	None
0.4821	6.0	2346	0.1596	0.8608	0.3849	0.3849	None
0.449	7.0	2737	0.1637	0.7924	0.4679	0.4679	None
0.42	8.0	3128	0.1620	0.74	0.5259	0.5259	None
0.3848	9.0	3519	0.1713	0.6352	0.6282	0.6282	None
0.3848	10.0	3910	0.1673	0.5684	0.6857	0.6857	None
0.3435	11.0	4301	0.1622	0.4858	0.7508	0.7508	None
0.3106	12.0	4692	0.1708	0.408	0.8033	0.8033	None
0.2816	13.0	5083	0.1924	0.312	0.8612	0.8612	None
0.2816	14.0	5474	0.1941	0.2802	0.8793	0.8793	None
0.2517	15.0	5865	0.1644	0.2678	0.8915	0.8915	None
0.2246	16.0	6256	0.1660	0.2418	0.9057	0.9057	None
0.2104	17.0	6647	0.1567	0.2164	0.9207	0.9207	None
0.1924	18.0	7038	0.1550	0.1978	0.9317	0.9317	None
0.1924	19.0	7429	0.1509	0.1802	0.9415	0.9415	None
0.1785	20.0	7820	0.1437	0.1894	0.9372	0.9372	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_10_87

87

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jialicheng/
unlearn_cifar10_swin-base_salun_10_87