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jialicheng/
unlearn_cifar10_swin-base_bad_teaching_6_42

Name: unlearn_cifar10_swin-base_bad_teaching_6_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 cifar10 dataset. It achieves the following results on the evaluation set:

Loss: 0.4094
Accuracy: 0.9819
Dt Accuracy: 0.9819
Df Accuracy: 0.9853
Unlearn Overall Accuracy: 0.2055
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: 0.0001
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	Overall Accuracy	Unlearn Overall Accuracy	Time
No log	1.0	47	0.3000	0.9917	0.1953	0.1953	None
No log	2.0	94	0.4181	0.9897	0.1985	0.1985	None
No log	3.0	141	0.4695	0.9843	0.2070	0.2070	None
No log	4.0	188	0.4164	0.9887	0.2001	0.2001	None
No log	5.0	235	0.4460	0.9887	0.2002	0.2002	None
No log	6.0	282	0.4185	0.9857	0.2050	0.2050	None
No log	7.0	329	0.4680	0.9847	0.2065	0.2065	None
No log	8.0	376	0.4696	0.983	0.2092	0.2092	None
No log	9.0	423	0.4176	0.987	0.2028	0.2028	None
No log	10.0	470	0.4094	0.9853	0.2055	0.2055	None

Framework versions

Transformers 4.37.2
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.15.2

jialicheng/unlearn_cifar10_swin-base_bad_teaching_6_42

42

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jialicheng/
unlearn_cifar10_swin-base_bad_teaching_6_42