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jialicheng/
unlearn-so_cifar10_swin-base_bad_teaching_10_13

Name: unlearn-so_cifar10_swin-base_bad_teaching_10_13
Availability: InStock

generated_from_trainer

microsoft/swin-base-patch4-window7-224

finetune

apache-2.0

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13

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: 1.0933
Accuracy: 0.9722
Dt Accuracy: 0.9722
Df Accuracy: 0.9764
Unlearn Overall Accuracy: 0.2195
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: 13
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	79	1.7601	0.9478	0.2620	0.2620	None
No log	2.0	158	1.5560	0.9646	0.2373	0.2373	None
No log	3.0	237	1.9419	0.958	0.2473	0.2473	None
No log	4.0	316	1.6293	0.968	0.2322	0.2322	None
No log	5.0	395	1.8343	0.9564	0.2498	0.2498	None
No log	6.0	474	1.2374	0.977	0.2185	0.2185	None
0.0	7.0	553	1.1860	0.9804	0.2132	0.2132	None
0.0	8.0	632	1.2486	0.9744	0.2226	0.2226	None
0.0	9.0	711	1.2435	0.9748	0.2220	0.2220	None
0.0	10.0	790	1.0933	0.9764	0.2195	0.2195	None

Framework versions

Transformers 4.37.2
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.15.2

jialicheng/unlearn-so_cifar10_swin-base_bad_teaching_10_13

13

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jialicheng/
unlearn-so_cifar10_swin-base_bad_teaching_10_13