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jialicheng/
unlearn-so_cifar10_swin-base_bad_teaching_6_42

Name: unlearn-so_cifar10_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 cifar10 dataset. It achieves the following results on the evaluation set:

Loss: 0.7511
Accuracy: 0.9745
Dt Accuracy: 0.9745
Df Accuracy: 0.9767
Unlearn Overall Accuracy: 0.2192
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: 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	47	1.5112	0.9437	0.2685	0.2685	None
No log	2.0	94	0.9308	0.9687	0.2313	0.2313	None
No log	3.0	141	1.2615	0.9563	0.2499	0.2499	None
No log	4.0	188	1.2645	0.9697	0.2297	0.2297	None
No log	5.0	235	0.9540	0.9753	0.2211	0.2211	None
No log	6.0	282	1.3100	0.968	0.2324	0.2324	None
No log	7.0	329	0.9073	0.9737	0.2238	0.2238	None
No log	8.0	376	0.7619	0.98	0.2139	0.2139	None
No log	9.0	423	0.8607	0.9733	0.2244	0.2244	None
No log	10.0	470	0.7511	0.9767	0.2192	0.2192	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_6_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_bad_teaching_6_42