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jialicheng/
unlearn-so_cifar10_swin-base_salun_8_42

Name: unlearn-so_cifar10_swin-base_salun_8_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: 0.1320
Accuracy: 0.9758
Dt Accuracy: 0.9758
Df Accuracy: 0.779
Unlearn Overall Accuracy: 0.4842
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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Overall Accuracy	Unlearn Overall Accuracy	Time
No log	1.0	391	0.1700	0.8975	0.3356	0.3356	None
0.6062	2.0	782	0.1826	0.8945	0.3395	0.3395	None
0.5503	3.0	1173	0.1456	0.9093	0.3196	0.3196	None
0.5062	4.0	1564	0.1641	0.9067	0.3230	0.3230	None
0.5062	5.0	1955	0.1459	0.9115	0.3167	0.3167	None
0.4715	6.0	2346	0.1405	0.9095	0.3196	0.3196	None
0.4282	7.0	2737	0.1342	0.8942	0.3406	0.3406	None
0.3896	8.0	3128	0.1408	0.8468	0.4030	0.4030	None
0.3554	9.0	3519	0.1282	0.8107	0.4474	0.4474	None
0.3554	10.0	3910	0.1320	0.779	0.4842	0.4842	None

Framework versions

Transformers 4.48.0
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.21.0

jialicheng/unlearn-so_cifar10_swin-base_salun_8_42

42

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jialicheng/
unlearn-so_cifar10_swin-base_salun_8_42