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jialicheng/
unlearn-so_cifar100_swin-base_neggrad_4_42

Name: unlearn-so_cifar100_swin-base_neggrad_4_42
Availability: InStock

generated_from_trainer

microsoft/swin-base-patch4-window7-224

finetune

apache-2.0

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42

This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224 on the cifar100 dataset. It achieves the following results on the evaluation set:

Loss: -49.0808
Accuracy: 0.01
Dt Accuracy: 0.01
Df Accuracy: 0.01
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: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Time
No log	1.0	16	-38.3303	0.01	None
No log	2.0	32	-43.1898	0.01	None
No log	3.0	48	-44.5752	0.01	None
No log	4.0	64	-45.7123	0.01	None
No log	5.0	80	-46.6978	0.01	None
No log	6.0	96	-47.5299	0.01	None
-40.4033	7.0	112	-48.1956	0.01	None
-40.4033	8.0	128	-48.6682	0.01	None
-40.4033	9.0	144	-48.9784	0.01	None
-40.4033	10.0	160	-49.0808	0.01	None

Framework versions

Transformers 4.39.3
Pytorch 2.2.2+cu118
Datasets 2.19.0
Tokenizers 0.15.2

jialicheng/unlearn-so_cifar100_swin-base_neggrad_4_42

42

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jialicheng/
unlearn-so_cifar100_swin-base_neggrad_4_42