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jialicheng/
unlearn_cifar10_swin-base_neggrad_2_42

Name: unlearn_cifar10_swin-base_neggrad_2_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: -12.6327
Accuracy: 0.2966
Dt Accuracy: 0.2966
Df Accuracy: 0.322
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: 1e-05
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: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Overall Accuracy	Unlearn Overall Accuracy	Time
No log	1.0	8	-0.0514	0.999	0.1834	0.1834	None
No log	2.0	16	-0.0687	0.996	0.1883	0.1883	None
No log	3.0	24	-0.1412	0.985	0.2059	0.2059	None
No log	4.0	32	-0.5672	0.936	0.2790	0.2790	None
No log	5.0	40	-2.1561	0.795	0.4424	0.4424	None
No log	6.0	48	-6.1028	0.573	0	0	None
No log	7.0	56	-10.6847	0.38	0	0	None
No log	8.0	64	-12.6327	0.322	0	0	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_neggrad_2_42

42

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jialicheng/
unlearn_cifar10_swin-base_neggrad_2_42