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jialicheng/
unlearn_cifar10_swin-base_neggrad_4_87

Name: unlearn_cifar10_swin-base_neggrad_4_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: -36.9124
Accuracy: 0.1
Dt Accuracy: 0.1
Df Accuracy: 0.1
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: 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	16	-0.0707	0.997	0.1867	0.1867	None
No log	2.0	32	-0.9802	0.9265	0.2921	0.2921	None
No log	3.0	48	-6.2972	0.5965	0	0	None
No log	4.0	64	-27.2808	0.1015	0	0	None
No log	5.0	80	-33.1146	0.1	0	0	None
No log	6.0	96	-35.5061	0.1	0	0	None
No log	7.0	112	-36.5854	0.1	0	0	None
No log	8.0	128	-36.9124	0.1	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_4_87

87

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jialicheng/
unlearn_cifar10_swin-base_neggrad_4_87