You can deploy this model and start earning money today!

jialicheng/
unlearn_cifar100_swin-base_salun_2_42

Name: unlearn_cifar100_swin-base_salun_2_42
Availability: InStock

generated_from_trainer

microsoft/swin-base-patch4-window7-224

finetune

apache-2.0

Views

No views yet

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: 0.3695
Accuracy: 0.9121
Dt Accuracy: 0.9121
Df Accuracy: 0.195
Unlearn Overall Accuracy: 0.8907
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	0.4430	0.741	0.4185	0.4185	None
1.0495	2.0	782	0.4270	0.766	0.3883	0.3883	None
0.914	3.0	1173	0.4064	0.745	0.4150	0.4150	None
0.8334	4.0	1564	0.3782	0.749	0.4109	0.4109	None
0.8334	5.0	1955	0.4124	0.707	0.4604	0.4604	None
0.7526	6.0	2346	0.3898	0.705	0.4635	0.4635	None
0.6826	7.0	2737	0.3798	0.676	0.4969	0.4969	None
0.6152	8.0	3128	0.3997	0.617	0.5586	0.5586	None
0.565	9.0	3519	0.3915	0.6	0.5760	0.5760	None
0.565	10.0	3910	0.3787	0.506	0.6637	0.6637	None
0.5155	11.0	4301	0.4009	0.447	0.7124	0.7124	None
0.4893	12.0	4692	0.3895	0.406	0.7456	0.7456	None
0.4481	13.0	5083	0.3987	0.4	0.7498	0.7498	None
0.4481	14.0	5474	0.4049	0.317	0.8097	0.8097	None
0.4164	15.0	5865	0.3994	0.289	0.8289	0.8289	None
0.3905	16.0	6256	0.3802	0.241	0.8610	0.8610	None
0.3575	17.0	6647	0.3812	0.223	0.8721	0.8721	None
0.3358	18.0	7038	0.3804	0.22	0.8751	0.8751	None
0.3358	19.0	7429	0.3765	0.189	0.8939	0.8939	None
0.3223	20.0	7820	0.3695	0.195	0.8907	0.8907	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_2_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_2_42