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jialicheng/
unlearn_cifar10_swin-base_salun_4_42

Name: unlearn_cifar10_swin-base_salun_4_42
Availability: InStock

generated_from_trainer

microsoft/swin-base-patch4-window7-224

finetune

apache-2.0

endpoints_compatible

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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: 0.0800
Accuracy: 0.9797
Dt Accuracy: 0.9797
Df Accuracy: 0.191
Unlearn Overall Accuracy: 0.9472
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: 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: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Overall Accuracy	Unlearn Overall Accuracy	Time
No log	1.0	391	0.0973	0.9295	0.2910	0.2910	None
0.4008	2.0	782	0.0962	0.915	0.3118	0.3118	None
0.3695	3.0	1173	0.1002	0.9085	0.3210	0.3210	None
0.3552	4.0	1564	0.1136	0.909	0.3201	0.3201	None
0.3552	5.0	1955	0.1013	0.882	0.3572	0.3572	None
0.332	6.0	2346	0.0930	0.849	0.4005	0.4005	None
0.3073	7.0	2737	0.1020	0.811	0.4475	0.4475	None
0.2803	8.0	3128	0.1116	0.716	0.5530	0.5530	None
0.2645	9.0	3519	0.1008	0.6385	0.6287	0.6287	None
0.2645	10.0	3910	0.1065	0.5315	0.7205	0.7205	None
0.2368	11.0	4301	0.0951	0.4855	0.7567	0.7567	None
0.217	12.0	4692	0.1006	0.4065	0.8137	0.8137	None
0.1984	13.0	5083	0.0944	0.3885	0.8266	0.8266	None
0.1984	14.0	5474	0.0856	0.29	0.8897	0.8897	None
0.1775	15.0	5865	0.0937	0.257	0.9078	0.9078	None
0.1683	16.0	6256	0.0837	0.233	0.9230	0.9230	None
0.1481	17.0	6647	0.0900	0.234	0.9221	0.9221	None
0.1419	18.0	7038	0.0839	0.198	0.9426	0.9426	None
0.1419	19.0	7429	0.0804	0.197	0.9439	0.9439	None
0.1308	20.0	7820	0.0800	0.191	0.9472	0.9472	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_salun_4_42

42

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jialicheng/
unlearn_cifar10_swin-base_salun_4_42