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jialicheng/
unlearn-so_cifar10_swin-base_bad_teaching_6_13

Name: unlearn-so_cifar10_swin-base_bad_teaching_6_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: 0.9863
Accuracy: 0.9665
Dt Accuracy: 0.9665
Df Accuracy: 0.9643
Unlearn Overall Accuracy: 0.2382
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	47	1.2474	0.9643	0.2375	0.2375	None
No log	2.0	94	1.1489	0.9593	0.2454	0.2454	None
No log	3.0	141	1.3052	0.966	0.2353	0.2353	None
No log	4.0	188	1.3526	0.963	0.2398	0.2398	None
No log	5.0	235	1.4689	0.9653	0.2363	0.2363	None
No log	6.0	282	1.0760	0.9743	0.2226	0.2226	None
No log	7.0	329	0.9787	0.976	0.2201	0.2201	None
No log	8.0	376	0.9946	0.9653	0.2367	0.2367	None
No log	9.0	423	0.9774	0.9643	0.2382	0.2382	None
No log	10.0	470	0.9863	0.9643	0.2382	0.2382	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_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_6_13