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jialicheng/
unlearn-cl_cifar10_swin-base_random_label_6_87

Name: unlearn-cl_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: 0.0832
Accuracy: 0.9754
Dt Accuracy: 0.9754
Df Accuracy: 0.0737
Unlearn Overall Accuracy: 0
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: 5e-05
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	0.0885	0.9967	0.1872	0.1872	None
0.3702	2.0	782	0.0881	0.9943	0.1911	0.1911	None
0.3423	3.0	1173	0.0975	0.9867	0.2035	0.2035	None
0.3301	4.0	1564	0.0890	0.9727	0.2258	0.2258	None
0.3301	5.0	1955	0.0870	0.9257	0.2967	0.2967	None
0.3151	6.0	2346	0.1058	0.8323	0.4216	0.4216	None
0.295	7.0	2737	0.1012	0.7513	0.5160	0.5160	None
0.2844	8.0	3128	0.1253	0.583	0.6772	0.6772	None
0.2615	9.0	3519	0.1059	0.5467	0.7085	0.7085	None
0.2615	10.0	3910	0.1099	0.4437	0.7869	0.7869	None
0.2375	11.0	4301	0.1069	0.3547	0.8475	0.8475	None
0.2235	12.0	4692	0.1077	0.277	0.8940	0.8940	None
0.2072	13.0	5083	0.0996	0.223	0.9260	0.9260	None
0.2072	14.0	5474	0.1007	0.16	0.9602	0.9602	None
0.1912	15.0	5865	0.1043	0.1207	0.9790	0.9790	None
0.1803	16.0	6256	0.0928	0.1127	0.9847	0.9847	None
0.1671	17.0	6647	0.0957	0.1013	0.9897	0.9897	None
0.1581	18.0	7038	0.0886	0.0807	0.9813	0.9813	None
0.1581	19.0	7429	0.0869	0.0663	0	0	None
0.1524	20.0	7820	0.0832	0.0737	0	0	None

Framework versions

Transformers 4.48.0
Pytorch 2.2.2+cu118
Datasets 3.2.0
Tokenizers 0.21.0

jialicheng/unlearn-cl_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-cl_cifar10_swin-base_random_label_6_87