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jialicheng/
unlearn-so_cifar10_swin-base_neggrad_2_21

Name: unlearn-so_cifar10_swin-base_neggrad_2_21
Availability: InStock

generated_from_trainer

microsoft/swin-base-patch4-window7-224

finetune

apache-2.0

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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: -46.0425
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: 5e-05
train_batch_size: 128
eval_batch_size: 256
seed: 21
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	8	-27.4264	0.1	None
No log	2.0	16	-39.3303	0.1	None
No log	3.0	24	-42.3581	0.1	None
No log	4.0	32	-43.3720	0.1	None
No log	5.0	40	-44.1224	0.1	None
No log	6.0	48	-44.6870	0.1	None
No log	7.0	56	-45.3080	0.1	None
No log	8.0	64	-45.5242	0.1	None
No log	9.0	72	-46.0305	0.1	None
No log	10.0	80	-46.0425	0.1	None

Framework versions

Transformers 4.37.2
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.15.2

jialicheng/unlearn-so_cifar10_swin-base_neggrad_2_21

21

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_21