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jialicheng/
unlearn-so_cifar10_swin-base_neggrad_2_87

Name: unlearn-so_cifar10_swin-base_neggrad_2_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: -3.4281
Accuracy: 0.7266
Dt Accuracy: 0.7266
Df Accuracy: 0.763
Unlearn Overall Accuracy: 0.4622
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-06
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: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Overall Accuracy	Unlearn Overall Accuracy	Time
No log	1.0	8	-0.0537	0.998	0.1851	0.1851	None
No log	2.0	16	-0.0948	0.992	0.1948	0.1948	None
No log	3.0	24	-0.2552	0.972	0.2262	0.2262	None
No log	4.0	32	-0.6476	0.944	0.2675	0.2675	None
No log	5.0	40	-1.3391	0.89	0.3393	0.3393	None
No log	6.0	48	-2.2371	0.818	0.4199	0.4199	None
No log	7.0	56	-3.0575	0.783	0.4478	0.4478	None
No log	8.0	64	-3.4281	0.763	0.4622	0.4622	None

Framework versions

Transformers 4.48.0
Pytorch 2.2.2+cu118
Datasets 3.2.0
Tokenizers 0.21.0

jialicheng/unlearn-so_cifar10_swin-base_neggrad_2_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_neggrad_2_87