You can deploy this model and start earning money today!

jialicheng/
unlearn_cifar10_swin-base_salun_4_87

Name: unlearn_cifar10_swin-base_salun_4_87
Availability: InStock

generated_from_trainer

microsoft/swin-base-patch4-window7-224

finetune

apache-2.0

endpoints_compatible

Views

No views yet

87

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: 0.0825
Accuracy: 0.9792
Dt Accuracy: 0.9792
Df Accuracy: 0.179
Unlearn Overall Accuracy: 0.9534
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: 87
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	0.1058	0.9205	0.3039	0.3039	None
0.3974	2.0	782	0.0935	0.9235	0.2997	0.2997	None
0.3726	3.0	1173	0.1171	0.9205	0.3038	0.3038	None
0.3518	4.0	1564	0.1017	0.913	0.3147	0.3147	None
0.3518	5.0	1955	0.0879	0.896	0.3383	0.3383	None
0.3365	6.0	2346	0.1100	0.851	0.3978	0.3978	None
0.3064	7.0	2737	0.1047	0.789	0.4733	0.4733	None
0.2941	8.0	3128	0.1327	0.689	0.5793	0.5793	None
0.2625	9.0	3519	0.0937	0.657	0.6117	0.6117	None
0.2625	10.0	3910	0.0939	0.5315	0.7217	0.7217	None
0.2401	11.0	4301	0.0946	0.4795	0.7620	0.7620	None
0.2143	12.0	4692	0.0991	0.427	0.7992	0.7992	None
0.1997	13.0	5083	0.0944	0.3575	0.8468	0.8468	None
0.1997	14.0	5474	0.0922	0.3065	0.8791	0.8791	None
0.1831	15.0	5865	0.0972	0.2725	0.8991	0.8991	None
0.1624	16.0	6256	0.0931	0.2455	0.9149	0.9149	None
0.151	17.0	6647	0.0913	0.21	0.9353	0.9353	None
0.1402	18.0	7038	0.0905	0.1845	0.9495	0.9495	None
0.1402	19.0	7429	0.0830	0.18	0.9527	0.9527	None
0.1312	20.0	7820	0.0825	0.179	0.9534	0.9534	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_87

87

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jialicheng/
unlearn_cifar10_swin-base_salun_4_87