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jialicheng/
unlearn-so_cifar10_swin-base_bad_teaching_2_42

Name: unlearn-so_cifar10_swin-base_bad_teaching_2_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: 0.8179
Accuracy: 0.9607
Dt Accuracy: 0.9607
Df Accuracy: 0.949
Unlearn Overall Accuracy: 0.2613
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	16	0.6066	0.962	0.2414	0.2414	None
No log	2.0	32	1.1854	0.948	0.2620	0.2620	None
No log	3.0	48	1.0245	0.964	0.2382	0.2382	None
No log	4.0	64	0.9271	0.965	0.2369	0.2369	None
No log	5.0	80	0.9615	0.966	0.2353	0.2353	None
No log	6.0	96	0.6952	0.979	0.2153	0.2153	None
No log	7.0	112	0.7596	0.967	0.2340	0.2340	None
No log	8.0	128	0.7059	0.968	0.2325	0.2325	None
No log	9.0	144	0.8393	0.949	0.2613	0.2613	None
No log	10.0	160	0.8179	0.949	0.2613	0.2613	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_2_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_2_42