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jialicheng/
unlearn_cifar100_swin-base_bad_teaching_6_42

Name: unlearn_cifar100_swin-base_bad_teaching_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: 37.3071
Accuracy: 0.1768
Dt Accuracy: 0.1768
Df Accuracy: 0.1223
Unlearn Overall Accuracy: 0
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	Time
No log	1.0	47	1.5751	0.71	None
No log	2.0	94	3.0157	0.5943	None
No log	3.0	141	4.5211	0.475	None
No log	4.0	188	5.4633	0.4523	None
No log	5.0	235	7.3936	0.39	None
No log	6.0	282	9.1390	0.3477	None
No log	7.0	329	11.9795	0.2747	None
No log	8.0	376	11.1489	0.2913	None
No log	9.0	423	12.7584	0.273	None
No log	10.0	470	15.1925	0.246	None
0.0	11.0	517	17.5846	0.2153	None
0.0	12.0	564	21.0736	0.1893	None
0.0	13.0	611	21.0434	0.188	None
0.0	14.0	658	26.1360	0.171	None
0.0	15.0	705	24.8298	0.1597	None
0.0	16.0	752	28.5803	0.1507	None
0.0	17.0	799	37.3501	0.1237	None
0.0	18.0	846	38.3154	0.1207	None
0.0	19.0	893	35.8127	0.126	None
0.0	20.0	940	37.3071	0.1223	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_bad_teaching_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_bad_teaching_6_42