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jialicheng/
unlearn_cifar100_swin-base_salun_6_42

Name: unlearn_cifar100_swin-base_salun_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 cifar100 dataset. It achieves the following results on the evaluation set:

Loss: 0.4122
Accuracy: 0.8983
Dt Accuracy: 0.8983
Df Accuracy: 0.1827
Unlearn Overall Accuracy: 0.8922
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: 0.0002
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: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Overall Accuracy	Unlearn Overall Accuracy	Time
No log	1.0	391	0.4467	0.754	0.4033	0.4033	None
1.2106	2.0	782	0.4069	0.771	0.3831	0.3831	None
1.0503	3.0	1173	0.4355	0.7777	0.3738	0.3738	None
0.9645	4.0	1564	0.4543	0.762	0.3937	0.3937	None
0.9645	5.0	1955	0.4076	0.7477	0.4129	0.4129	None
0.8771	6.0	2346	0.4350	0.7047	0.4631	0.4631	None
0.7866	7.0	2737	0.4448	0.6643	0.5082	0.5082	None
0.7204	8.0	3128	0.4489	0.6137	0.5600	0.5600	None
0.6629	9.0	3519	0.4399	0.5727	0.6009	0.6009	None
0.6629	10.0	3910	0.4259	0.497	0.6689	0.6689	None
0.6048	11.0	4301	0.4372	0.439	0.7162	0.7162	None
0.5634	12.0	4692	0.4355	0.4067	0.7409	0.7409	None
0.5194	13.0	5083	0.4413	0.3437	0.7854	0.7854	None
0.5194	14.0	5474	0.4299	0.3327	0.7963	0.7963	None
0.4786	15.0	5865	0.4409	0.2567	0.8449	0.8449	None
0.4425	16.0	6256	0.4293	0.2327	0.8609	0.8609	None
0.4103	17.0	6647	0.4281	0.2177	0.8700	0.8700	None
0.3901	18.0	7038	0.4197	0.1933	0.8854	0.8854	None
0.3901	19.0	7429	0.4177	0.1897	0.8883	0.8883	None
0.3635	20.0	7820	0.4122	0.1827	0.8922	0.8922	None

Framework versions

Transformers 4.39.3
Pytorch 2.2.2+cu118
Datasets 2.18.0
Tokenizers 0.15.2

jialicheng/unlearn_cifar100_swin-base_salun_6_42

42

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jialicheng/
unlearn_cifar100_swin-base_salun_6_42